Weekly Opening Range and Previous Data for FuturesThis indicator will not predict future price action.
This indicator is a time based range tool. These types of tools are great to use when there is not any historical data to look back on (as in all time highs/lows). The user can use this indicator to measure distributions, use deviations of the range to identify support/resistance levels, and see how historical price action influences current price action. This indicator is unique because it uses the price range from the open of the futures market on Sunday 18:00 America/New York to the open of the Bond Market 8:00 America/New York as the range for all calculations.
This indicator collects the multiple points of data from each day of the week, and gives the user many options on how to use the data that is collected. The amount of data collected is based on the time frame of the chart (best used on a 15 minute chart), but is limited to 30 minute charts.
Data Collected:
Opening Range for the week
High of Each Day
Low of Each Day
Close of Each Day
Initially the range is plotted on the chart as a box, when the Bond market opens the high/low/mid is plotted, as well as the current week open and previous week close.
How the data is used.
Intraday: Monday does not have a previous day to pull data on, so all data for Monday is intraday data. When a new high is made, the indicator will search all previous data in the lookback period for the current day , find all highs that are within a set variance (determined by the user), and plot the corresponding lows from the matching days. It will do the same for new lows that are made, with corresponding historical highs. All of these levels are plotted on the chart, as well as the Average High, Average Low. If price moves beyond either Average, the Average of all days that distributed higher than the Average is plotted on the chart as Min/Max Average.
Previous Day Data: Tuesday - Friday. After the close of the day, the user has the option to choose either the High, Low, or Close of that day to find previous data that matches within a variance determined by the user; or an option to find the n closest matches (up to 20). That data is then matched to the corresponding next day data and plotted on the chart as a box. Example: Monday closes at +1 Deviation (Dev) of the Weekly Opening Range (WOR). The user sets the variance at 0.5 (0.5 Dev of the WOR), the indicator will search the lookback period for all Mondays that closed between 1.25 Dev and 0.75 Dev of the WOR. The matching Mondays will then be matched to their corresponding Tuesdays and the data for the High and Low from those Tuesdays will be placed on the chart as a box overlaying the current Tuesday. Each match is numbered so that corresponding Highs and Lows of each historical day can be identified. The same can be done for either the High or Low of the Previous Day.
The indicator has a table that can be shown.
Data shown in table:
Current Extension of the WOR
Maximum Extension of the WOR
Average WOR in %
Current WOR in %
Average Range for the day in % based on data set
Current Range for the day in %
Number of days in the data set
Number of Previous Day Matches
Variance for previous day data
Number of Intraday High Matches
Number of Intraday Low Matches
Variance for Intraday Matches
The table as well as all lines and boxes have the option of being shown or not, as well as have their settings customized to fit the users chart layout.
As with any indicator, do not let the data shown change your trading model. Past performance is not indicative to future performance.
Pesquisar nos scripts por "high low"
UVR Crypto TrendINDICATOR OVERVIEW: UVR CRYPTO TREND
The UVR Crypto Trend indicator is a custom-built tool designed specifically for cryptocurrency markets, utilizing advanced volatility, momentum, and trend-following techniques. It aims to identify trend reversals and provide buy and sell signals by analyzing multiple factors, such as price volatility(UVR), RSI (Relative Strength Index), CMF (Chaikin Money Flow), and EMA (Exponential Moving Average). The indicator is optimized for CRYPTO MARKETS only.
KEY FEATURES AND HOW IT WORKS
Volatility Analysis with UVR
The UVR (Ultimate Volatility Rate) is a proprietary calculation that measures market volatility by comparing significant price extremes and smoothing the data over time.
Purpose: UVR aims to reduce noise in low-volatility environments and highlight significant movements during higher-volatility periods. While it strives to improve filtering in low-volatility conditions, it does not guarantee perfect performance, making it a balanced and adaptable tool for dynamic markets like cryptocurrency.
HOW UVR (ULTIMATE VOLATILITY RATE) IS CALCULATED
UVR is calculated using a method that ensures precise measurement of market volatility by comparing price extremes across consecutive candles:
Volatility Components:
Two values are calculated to represent potential price fluctuations:
The absolute difference between the current candle's high and the previous candle's low:
Volatility Component 1=∣High−Low ∣
The absolute difference between the previous candle's high and the current candle's low:
Volatility Component 2=∣High −Low∣
Volatility Ratio:
The larger of the two components is selected as the Volatility Ratio, ensuring UVR captures the most significant movement:
Volatility Ratio=max(Volatility Component 1,Volatility Component 2)
Smoothing with SMMA:
To stabilize the volatility calculation, the Volatility Ratio is smoothed using a Smoothed Moving Average (SMMA) over a user-defined period (e.g., 14 candles):
UVR=(UVR(Previous)×(Period−1)+Volatility Ratio)/Period
This calculation ensures UVR adapts dynamically to market conditions, focusing on significant price movements while filtering out noise.
RSI FOR MOMENTUM DETECTION
RSI (Relative Strength Index) identifies overbought and oversold conditions.
Trend Confirmation at the 50 Level
RSI values crossing above 50 signal the potential start of an upward trend.
RSI values crossing below 50 indicate the potential start of a downward trend.
Key Reversals at Extreme Levels
RSI detects trend reversals at overbought (>70) and oversold (<30) levels.
For example:
Overbought Trend Reversal: RSI >70 followed by bearish price action signals a potential downtrend.
Oversold Trend Reversal: RSI <30 with bullish confirmation signals a potential uptrend.
Rare Extreme RSI Readings
Extreme levels, such as RSI <12 (oversold) or RSI >88 (overbought), are used to identify rare yet powerful reversals.
---HOW IT DIFFERS FROM OTHER INDICATORS---
Using UVR High and Low Values
The Ultimate Volatility Rate (UVR) focuses on analyzing the high and low price ranges of the market to measure volatility.
Unlike traditional trend indicators that rely primarily on momentum or moving average crossovers, UVR leverages price extremes to better identify trend reversals.
This approach ensures fewer false signals during low-volatility phases and more accurate trend detection during high-volatility conditions.
UVR as the Core Component
The indicator is fundamentally built around UVR as the primary filter, while supporting tools like RSI (momentum detection), CMF (volume confirmation), and EMA (trend validation) complement its functionality.
By integrating these additional components, the indicator provides a multidimensional analysis rather than relying solely on a single approach.
Dynamic Adaptation to Volatility
UVR dynamically adjusts to market conditions, striving to improve filtering in low-volatility phases. While not flawless, this approach minimizes false signals and adapts more effectively to varying levels of market activity.
Trend Clouds for Visual Guidance
UVR-based dynamic clouds visually mark high and low price areas, highlighting potential consolidation or retracement zones.
These clouds serve as guides for setting stop-loss or take-profit levels, offering clear risk management strategies.
BUY AND SELL SIGNAL LOGIC
BUY CONDITIONS
Momentum-Based Buy-Entry
RSI >50, CMF >0, and the close price is above EMA50.
The price difference between open and close exceeds a threshold based on UVR.
Oversold Reversal
RSI <30 and CMF >0 with a strong bullish candle (close > open and UVR-based sensitivity filter).
Breakout Confirmation
The price breaks above a previously identified resistance, with conditions for RSI and CMF supporting the breakout.
Reversal from Oversold RSI Extreme
RSI <12 on the previous candle with a strong rebound on the current candle with UVR confirmation filter.
SELL CONDITIONS
Momentum-Based Sell-Entry
RSI <50, CMF <0, and the close price is below EMA50.
The price difference between open and close exceeds the UVR threshold.
Overbought Reversal
RSI >70 with bearish price action (open > close and UVR-based sensitivity filter).
Breakdown Confirmation
The price breaks below a previously identified support, with RSI and CMF supporting the breakdown.
Reversal from Overbought RSI Extreme
RSI >88 on the previous candle with a bearish confirmation on the current candle with UVR confirmation filter.
BUY AND SELL SIGNALS VISUALIZATION
The UVR Crypto Trend Indicator visually represents buy and sell conditions using dynamic plots, making it easier for traders to interpret and act on the signals. Below is an explanation of the visual representation:
Buy Signals and Visualization
Signal Trigger:
A buy signal is generated when one of the defined Buy Conditions is met (e.g., RSI >50, CMF >0, price above EMA50).
Visual Representation:
A blue upward arrow appears at the candle where the buy condition is triggered.
A blue cloud forms above the price candles, representing the strength of the bullish trend. The cloud dynamically adapts to market volatility, using the UVR calculation to mark support zones or consolidation levels.
Purpose of the Blue Cloud:
It acts as a visual guide for price movements and stay horizontal when the trend is not moving up
Sell Signals and Visualization
Signal Trigger:
A sell signal is generated when one of the defined Sell Conditions is met (e.g., RSI <50, CMF <0, price below EMA50).
Visual Representation:
A red downward arrow appears at the candle where the sell condition is triggered.
A red cloud forms below the price candles, representing the strength of the bearish trend. Like the blue cloud, it uses the UVR calculation to dynamically mark resistance zones or potential retracement levels.
Purpose of the Red Cloud:
It acts as a visual guide for price movements and stay horizontal when the trend is not moving down.
CONCLUSION
The UVR Crypto Trend indicator provides a powerful tool for trend reversal detection by combining volatility analysis, momentum confirmation, and trend-following techniques. Its unique use of the Ultimate Volatility Rate (UVR) as a core element, supported by proven indicators like RSI, CMF, and EMA, ensures reliable and actionable signals tailored for the crypto market's dynamic nature. By leveraging UVR’s high and low price range analysis, it achieves a level of precision that traditional indicators lack, making it a high-performing system for cryptocurrency traders.
Trading Sessions with Highs and LowsTrading Sessions with Highs and Lows is designed to visually highlight specific trading sessions on the chart, providing traders with key insights into market behavior during these time periods. Here’s a detailed explanation of how the indicator works:
Key Features
1. Session Boxes:
• The indicator plots colored boxes on the chart to represent the price range of defined trading sessions.
• Each box spans the session’s start and end times and encapsulates the high and low prices during that period.
• Two trading sessions are defined by default:
• USA Trading Session: 9:30 AM - 4:00 PM (New York Time).
• UK Trading Session: 8:00 AM - 4:30 PM (London Time).
2. Session Labels:
• The name of the session (e.g., “USA” or “UK”) is displayed above the session box for clear identification.
3. High and Low Markers:
• Markers are added to the chart at the session’s high and low points:
• High Marker: A green label indicating the session high.
• Low Marker: A red label indicating the session low.
4. Dynamic Reset:
• After the session ends, the session high and low values are reset to na to prepare for the next trading day.
5. Customizable Background Colors:
• Each session’s box has a distinct, semi-transparent background color for better visual separation.
How It Works
1. Core Functionality:
• A function, plot_box, takes the session name, start time, end time, and background color as input.
• It calculates whether the current time is within the session.
• During the session:
• It tracks the session’s highest and lowest prices.
• It identifies the bars where the high and low occurred.
• At the session’s end:
• It plots a box on the chart covering the session’s time and price range.
• Labels are created for the session name and its high/low points.
2. Session Timing:
• Timestamps for the USA and UK trading sessions are calculated using the timestamp function with respective time zones.
3. Visual Elements:
• The box.new function draws the session boxes on the chart.
• The label.new function creates session name and high/low labels.
Usage
• Overlay Mode: The indicator is applied directly on the price chart (overlay=true), making it easy to visualize session-specific price behavior.
• Trading Strategy:
• Identify session-specific support and resistance levels.
• Observe price action trends during key trading periods.
• Align trading decisions with session dynamics.
Customization
While the indicator is preset for the USA and UK trading sessions, it can be easily modified:
1. Add/Remove Sessions: Define additional sessions by providing their start and end times.
2. Change Colors: Update the background_color in the plot_box calls to use different colors for sessions.
3. Adjust Time Zones: Replace the current time zones with others relevant to your trading style.
Visualization Example
• USA Session:
• Time: 9:30 AM - 4:00 PM (New York Time).
• Box Color: Semi-transparent orange.
• UK Session:
• Time: 8:00 AM - 4:30 PM (London Time).
• Box Color: Semi-transparent green.
Why Use This Indicator?
1. Market Awareness: Easily spot price behavior during high-liquidity trading periods.
2. Trend Analysis: Analyze how sessions overlap or affect each other.
3. Session Boundaries: Use session high/low levels as dynamic support and resistance zones.
This indicator is an essential tool for intraday and swing traders who want to align their strategies with key market timings.
Structure Pilot - Z&Z [Wang Indicators]Structure Pilot Zone & Zil is a complete suite of structure driven features that's build around pattern that can be visible around any timeframe.
Built in collaboration with Dave Teaches,
All these tools were shaped and combined together as the only toolkit Structure & DTFX traders want to have !
▫️ Structures & Zones ▫️
Zones are drawn when a break of structure (new high or low being created) or a market reversal happens.
It will highlight the last valid down move before a new high for bullish zones and the last valid up move before a new low for bearish zones.
These zones are used to analyze the market trend and to make entries into the market trend once the price retraces into these zones.
For example, with the latest bullish zones drawn in green for LTF zones and in blue for HTF zones, when the price retraces into this zone, there is a strong probability that the price will turn around to provide a buying opportunity all the way to the top of the zone or even higher.
These buying opportunities generally occur at specific retracement levels in the 30%, 50% and 70% zones, automatically represented by broken lines in the zones when they are created.
Example with bullish zones :
The aim with these zones is to find places on the chart where it's best to buy or sell, in order to take the biggest possible move while minimizing your risk.
Indeed, if the price is rising and a bullish zone has been created, I don't want to buy on the highs, preferring to wait for a retracement in my bullish zone to buy lower and reduce my risk, as the invalidation of the current trend will be found below the last protected low under the bullish zone drawn in blue for the HTF and in green for the LTF. Conversely, if the price is falling and a bearish zone has been created, I don't want to sell at the bottom. I'd rather wait for a retracement in the bearish zone to sell higher and reduce my risk, as the invalidation of the current trend will this time be above the last protected high above the bearish zone drawn in orange for the HTF and red for the LTF.
Example with bearish zones :
When it comes to market structure, it's good to know that zones recur within the same trend at a frequency of between 3 and 6 before there's a trend reversal.
So, after a certain number of successive zones, you can expect a reversal or the last protected high or low to be breached. The indicator automatically counts the number of successive zones, so you can keep track of the market and avoid surprises.
The zones are generated through the structure length. It can be increased to display larger (and more important) zones.
As we recommend keeping the default value (20) for new traders, experienced traders will find some success with other settings depending on their strategies.
Structure Pilot also provides auto HTF Zones, which is particularly useful to have a macro vision of the market.
Settings:
Swing types: Bullish only, Bearish only, both, or none
Structure length
Swing count: useful when it comes to tracking Trend strenght in any given time frame
Show Zones: Display boxes with 30%, 50%, and 70% fibs
Show HTF Zones: Display HTF zones with the same retracement configuration as the regular zones
Show 30%, 50% and 70%: Enable/disable these options to show or hide the corresponding fibs.
Box visibility, Line width & Line style: Style configuration for the zone
All settings can be activated or deactivated in the indicator parameters to suit individual needs and preferences.
30% Level : This is often considered a shallow retracement. If prices pull back to this level after an uptrend and flip in a lower timeframe, traders might view it as a strong sign of continued bullish momentum. Conversely, after a downtrend, this level could act as a temporary resistance where sellers might re-enter after a flip in a lower timeframe.
50% Level : This level is seen as a balance point or midpoint in the price move. A retracement to 50% can indicate a strong trend change or continuation.
70% Level : A retracement this deep can signal that the market might be losing steam or that the previous trend could be weakening. If the price bounces off this level, it might suggest that the trend is still in control but needed a more significant correction before moving further in its original direction.
We as structure traders prefer to take entry out of The 50% or when price retrace past it
there will be something at the level i'm looking for price to reverse from either some specific candles or imbalances.
Advanced traders might combine these levels with other tools or chart patterns that we bundle in this indicator.
▫️ ZIL ▫️
The ZIL Indicator is designed to automate the process of identifying key structural levels in the market and applying Fibonacci retracements when a significant price break occurs.
The indicator detects when a market structure (high or low) is broken and a candle closes below the previous low or above the previous high, indicating a potential trend shift or continuation.
• Tracks the break of structural lows or highs and waits for a confirmation candle that closes above or bellow the candle that set the new low.
Automated Fibonacci Retracement:
• Once the structure break is confirmed, the indicator automatically plots a Fibonacci retracement between:
• The high of the last bullish move (before the new low is set) or the low of the last bearish move (before the new high is set)
• The newly formed low after the structure break or the newly formed high after the structure break
Fibonacci levels plotted with colors :
• -0.27 : Dark red - Stop loss
• 0 : white - The new high/low - Potential entry
• 0.3, Orange 0.5, Light green 0.7: Green : Levels - Partial and take profit zones
• 1.15 pale blue - for your runner
We may long the retracement when the price is comming from a bearish zone using the ZIL to manage
Example :
Multi-Timeframe Support:
• Using the option "HTF ZIL" will display ZIL on higher timeframe (corresponding to the HTF Zones) on your charts to help traders find structural breaks and Fibonacci setups in both short-term and long-term markets.
HTF ZIL is really usefull to manage trades if the regular ZIL target get ran through
Wang use case :
HTF zill level are used when the small zill get ran through
▫️ Opening Range Tracker ▫️
The Opening Range Tracker is designed to help traders identify and track the opening range of a specified time period, specifically starting with the 144-minute candle between 8:24 AM and 10:48 AM. (default value) The indicator highlights this range and automatically plots key levels (30%, 50%, 70%) to provide potential strong reaction areas for trading. The time period for the opening range is fully customizable, allowing users to adjust it according to their strategy.
Opening range should be seen and used as a classic zone. If we trade above or below it price tend to come back into it and bounce of of the One or multiple level...
classic 30/50/70.
• Customizable Opening Range: Adapt the indicator to any market or session by changing the opening range time window.
• Precise Levels for Trading: The 30%, 50%, and 70% levels provide key zones where price may react, helping traders define entries, exits, or stop loss placements.
• Visual Clarity: The range box and levels make it easy to see the important price areas during the opening range and the rest of the trading session. If we range a lot in the opening range, we may range for the rest of the day. We should keep that in mind to avoid taking wrong decisions.
its basically a large zone that's we have seen often time price rejects from the level in it
Daily Reset: Each trading day resets the opening range, giving traders fresh data and new opportunities to capitalize on market movements.
Structure Pilot is built for beginner and experienced. It provides the tools to the traders that want to learn, understand, and trade efficiently within the principles of structure trading.
BOS TRADER [v 1.0] [Influxum]The name of the tool, BOS Trader, comes from the abbreviation BOS, which stands for Break Of Structure. In simple terms, this tool identifies situations where a change in market structure occurs after liquidity has been grabbed. Following the structural change, it looks for a point where the balance between buyers and sellers will be tested, potentially continuing the price movement in the direction of the structural break.
The goal of this tool is to identify areas where a trader can look for potential entry opportunities based on their entry rules and filters. In our own research, we found that while this tool is not a standalone strategy, it provides a statistical advantage that stems from the nature of the market itself. If you expect the market to reverse at a certain price level against a short-term, medium-term, or long-term trend, that reversal must logically begin with a change in structure – i.e., its break. BOS Trader then highlights the zone where you can expect a strong reaction from traders speculating on the continuation of price in the direction of the break.
Another important piece of the puzzle is the concept of liquidity. Liquidity grabs are generally considered by traders to be events that can trigger market direction changes. That's why BOS Trader is complemented with multiple ways to identify liquidity in the market from a Price Action perspective. We have explored the liquidity concept in depth in our other tools – the Liquidity Tool and Liquidity Strategy Tester – so we won’t go into too much detail on liquidity settings here.
🟪 Pivots
Liquidity can be found beyond pivot extremes – the highest candles in a series of candles. The pivot liquidity setting specifies how many candles must be before and after the pivot candle with a lower high for a pivot high or a higher low for a pivot low. A pivot high is the local highest point of the last 31 candles (15 before the pivot candle, the pivot candle itself, and 15 after). Another option is to set the time period in which the pivot extreme must occur. For example, you can differentiate between pivot highs of the Asian or London session.
🟪 % Percent Change
This setting is based on the well-known Zig Zag indicator and confirms swing highs or swing lows when there is a certain percentage change in price. This helps filter out noise that can occur when the market consolidates and randomly creates pivot highs or lows that aren’t significant.
🟪 Session High/Low
Many popular strategies are based on liquidity defined as the price range of a specific trading session. This doesn't have to be London, Asia, or New York sessions, but could be, for instance, the first hour of the New York session, and so on.
🟪 Day High/Low, Week High/Low, Month High/Low
As the name suggests, liquidity is often defined by the high/low of the previous day, week, or month. These price levels are watched by many market participants, and it's reasonable to expect reactions at these levels. That’s why we included this option in the BOS tool.
Tip for Traders
To avoid common issues with setting the correct session time, we have added the BG option to the tool – the ability to display a background for the configured trading session. This makes it easy to verify that your trading session is set correctly in relation to your time zone.
Delete grabbed liquidity
If a liquidity level is breached by price, it becomes invalid. For those who prefer to keep their charts clean and uncluttered, there is an option to delete grabbed liquidity. This way, only untraded, valid liquidity lines will be visible on the chart.
Bars after liquidity grab
A liquidity grab should be a significant event that triggers a reaction from market participants. To ensure this is a real response to liquidity rather than random market behavior, we added a time test to the BOS tool. A structural break must occur within a specified time after the liquidity grab. You can define this time in the tool as the number of bars after which the structural break is still considered valid following the liquidity grab.
🟪 AOI (Area of Interest) Settings
Initially, it's important to note that there are two main options for setting the behavior of the AOI. The first option is to fix its duration by the number of bars – Duration, and the second is to keep the AOI valid until it is traded through – Extended.
Duration
Since we expect a quick reaction to the liquidity grab, we also expect a fast pullback to the AOI and a swift response of traders. Our research has shown that the strongest reactions typically occur within a maximum of 15 bars from the formation of the AOI (fractally across timeframes). Therefore, this value is set as the default. However, we recommend considering not just the speed of the reaction but also its intensity. After the set number of bars, the AOI stops extending further.
Extended
We have noticed that price has a tendency to return to the AOI even after a longer period and react again. For this reason, we included the option in the BOS tool to extend the AOI into the future, with the ability to freely adjust the Max AOI Length.
🟪 AOI Size Mode
There are two options for setting the size of the AOI. Either it can be calculated as a percentage of the swing size (% of swing) in which the structural break occurred (the default setting is 30%), or you can set a different concept for the AOI size. For example, the well-known Optimal Trade Entry model. Custom values can be set in the FIBO Levels option, where you can define either preferred Fibonacci values or values based on your own criteria.
🟪 Trading Session (signals + alerts + visibility)
The main goal of our tools is to make it easier for traders to identify patterns and opportunities in the market and allow them to be alerted to their occurrence. The time for AOI plotting after a liquidity grab is combined into a single Trading Session function. This controls both the AOI plotting and when the tool will send alerts. All of this is aimed at helping traders avoid spending the entire day in front of their monitors, waiting for trading opportunities. Here, too, you can use the BG feature to plot a background on the chart showing the current session.
🟪 Trading within session range
We found that some traders have difficulty navigating the many AOIs plotted during times when the market consolidates and creates numerous false breakouts. Therefore, we included an option in the BOS tool to track only structural changes at the price extremes of the current day and trading session. The tool will not plot structural changes for internal liquidity grabs (within the session range), but only for external liquidity grabs (highest highs and lowest lows of the session or liquidity from previous days).
Visuals
The BOS tool is, of course, supplemented with the option to customize the appearance of all its components according to your preferences.
Enhanced MACD Swing Analysis增強版 MACD 擺動分析
概述
增強版 MACD 擺動分析是一個適用於 TradingView 的技術指標，它通過額外的視覺工具增強了傳統的 MACD（移動平均收斂背離），以幫助識別擺動高點和低點。該指標旨在幫助交易者可視化動能的變化，並更準確地確定市場進出位置。它提供基於可自定義閾值的動態顏色變化直方圖，並直接在圖表上繪製擺動高/低點的線條，方便分析。
功能
MACD 計算：該腳本包括傳統的 MACD 計算，並且允許調整快速長度、慢速長度和信號平滑參數。
擺動高/低點檢測：根據用戶定義的回看週期，自動檢測擺動高點和低點，並在圖表右上角顯示這些數值。
動態顏色變化直方圖：根據 MACD 比率動態改變直方圖的顏色，使交易者可以輕鬆識別不同的動能強度。顏色可以自定義，正負動能都有多種色調。
擺動高/低點線條：繪製線條以視覺化顯示擺動高點和低點，並向右延伸這些線條，以便更好地視覺指引。
參數
快速長度 (MACD Fast Length)：計算快速移動平均的週期數。預設值為 12。
慢速長度 (MACD Slow Length)：計算慢速移動平均的週期數。預設值為 26。
信號平滑 (MACD Signal Smoothing)：平滑 MACD 信號線的週期數。預設值為 9。
擺動回看範圍 (Swing Lookback Range)：回看多少根 K 線以檢測擺動高點和低點。預設值為 25。
顏色變化比率 (Color Change Ratios)：逗號分隔的比率，用於定義直方圖顏色變化的閾值。這些閾值允許用戶自定義何時基於 MACD 比率改變直方圖的顏色強度。提供了默認值。
工作原理
MACD 計算：該腳本使用用戶定義的快速和慢速長度，以及信號線平滑來計算 MACD。
直方圖顏色變化：根據 MACD 線和信號線之間的差值，計算比率以確定直方圖顏色的強度。顏色根據用戶指定的閾值進行變化，以視覺化顯示動能的變化。
擺動高/低點檢測：腳本回看一定數量的 K 線來檢測擺動高點和低點，並在圖表上繪製向右延伸的線條，方便識別。
使用方法
添加到圖表：將指標應用到您的 TradingView 圖表上，以更清晰地可視化 MACD 動能。
調整參數：根據您的交易風格自定義參數。您可以調整 MACD 長度、擺動回看範圍和顏色變化閾值。
解讀信號：使用顏色編碼的直方圖來判斷動能的強弱和方向。擺動高/低點線條有助於識別潛在的市場反轉或進出場位置。
實際應用
動能分析：使用顏色變化直方圖來評估趨勢的強度。顏色越亮表示動能越強，顏色越暗表示趨勢減弱。
擺動識別：擺動高/低點線條便於識別價格可能反轉的支撐和阻力區域。
進出場信號：當直方圖顏色強度變化時，這可能是動能轉變的早期信號，提供潛在的買入或賣出機會。
自定義
該指標高度可自定義，允許交易者修改 MACD 參數、擺動回看範圍和顏色變化閾值。這種靈活性使其適合於不同的交易風格，無論是日內交易者、擺動交易者，還是長期投資者。
Enhanced MACD Swing Analysis
Overview
The Enhanced MACD Swing Analysis script is a technical indicator for TradingView that enhances the traditional MACD (Moving Average Convergence Divergence) with additional visual tools to identify swing highs and swing lows. This indicator is designed to help traders visualize momentum shifts and determine market entry/exit points with greater accuracy. It provides dynamic color-changing histograms based on customizable thresholds and draws swing high/low lines directly on the chart for easy analysis.
Features
MACD Calculation: The script includes the traditional MACD calculation, with adjustable parameters for fast length, slow length, and signal smoothing.
Swing High/Low Detection: Automatically detects swing highs and lows based on a user-defined lookback period and displays the values in the top-right corner of the chart.
Dynamic Color-Changing Histogram: The histogram colors change dynamically based on the MACD ratio, allowing traders to easily identify different levels of momentum. The colors are customizable, with a variety of shades for both positive and negative momentum.
Swing High/Low Lines: Draws lines to visually indicate swing highs and lows, extending these lines to the right for better visual guidance.
Parameters
快速長度 (MACD Fast Length): The number of periods for the fast moving average. Default is 12.
慢速長度 (MACD Slow Length): The number of periods for the slow moving average. Default is 26.
信號平滑 (MACD Signal Smoothing): The number of periods for smoothing the MACD signal line. Default is 9.
擺動回看範圍 (Swing Lookback Range): The number of bars to look back for detecting swing highs and lows. Default is 25.
顏色變化比率 (Color Change Ratios): Comma-separated values for defining the ratios at which histogram colors change. These thresholds allow users to customize when the histogram changes its color intensity based on the MACD ratio. Default values are provided.
How It Works
MACD Calculation: The script calculates the MACD using the user-defined fast and slow lengths, along with a signal line for smoothing.
Histogram Color Change: Based on the difference between the MACD line and the signal line, a ratio is calculated to determine the intensity of the histogram's color. The color changes depending on user-specified thresholds to visually indicate shifts in momentum.
Swing High/Low Detection: The script looks back over a specified number of bars to detect swing highs and lows, which are then plotted on the chart using lines that extend to the right for easier identification.
How to Use
Add to Chart: Apply the indicator to your TradingView chart to visualize MACD momentum with enhanced clarity.
Adjust Parameters: Customize the parameters to suit your trading style. You can adjust the MACD lengths, swing lookback range, and color change thresholds as needed.
Interpret the Signals: Use the color-coded histogram to gauge momentum strength and direction. The swing high/low lines help identify key levels for potential market reversals or entry/exit points.
Practical Applications
Momentum Analysis: Use the color-changing histogram to assess the strength of a trend. Brighter colors indicate stronger momentum, while darker colors suggest weakening trends.
Swing Identification: The swing high and low lines make it easy to identify support and resistance areas where price may reverse.
Entry and Exit Signals: When the histogram color intensity changes, it could be an early indication of a shift in momentum, providing potential buy or sell opportunities.
Customization
This indicator is highly customizable, allowing traders to modify the MACD parameters, swing lookback range, and color change thresholds. This flexibility makes it suitable for different trading styles, whether you're a day trader, swing trader, or long-term investor.
Time and Price Lines and Zones (fadi)
Draw a red line starting from the open at 9:30
Show dotted lines between 11 and 12 and shade it
Mark the ORB high and low from 9:30 to 10:00 and extend it in orange and shade it
In trading, time and price are two crucial elements that help traders make decisions about buying and selling assets like stocks, commodities, or currencies. Forex or futures traders may prefer to trade during the Asia, London, and New York sessions to increase the probability of price moves. Additionally, traders often focus on key levels on the chart to frame their trades.
The Time and Price Lines and Zones indicator allows traders to set an unlimited number of time- and price-based levels on a chart, with full control over how they are displayed. Traders can simply type in their desired settings, and the indicator will interpret the instructions and plot the levels on the chart.
However, as it is a scripted tool, there are some limitations, and traders should keep their inputs relatively straightforward.
How It Works
In the settings, you type in the time and price levels you'd like to see, along with the timeframes for display. Each new line will render a line, a set of lines, or a price zone within a specific time interval. You can specify starting and ending times, price levels such as highs and lows, and details like color, line style, and thickness.
The following are some settings you can use:
Time
Always required, formatted as 0 to 23 for hours (with 0 representing midnight) and 0 to 59 for minutes. You can specify just a start time or both start and end times to "box" a period.
Examples:
1 ( for 1:00 AM)
13 (for 1:00 PM)
13:50 (for 1:50 PM)
Price
Optional. If no price level is provided, the indicator will treat it as an open time window and draw vertical lines at the specified time intervals.
Color
The indicator recognizes the 17 built-in colors from TradingView ( www.tradingview.com ). You also have the option to override or create your own colors to match your color schema under settings. Silver (light gray) is the default if none is specified.
Line Style
There are three available line styles:
Solid (default)
Dashed
Dotted
Line Thickness
Line thickness can also be controlled with the following options:
Thin (default)
Medium
Thick
Fill or No Fill
When specifying two price levels, or two time periods, you can choose to keep the area between them empty or fill it with a semitransparent color. You can set this by specifying "shade," "shaded," "fill," or "filled."
Extend or Not
There are times, such as with the Open Range Breakout (ORB), where you may want to extend the zone without tracking additional price level changes. You can indicate this by specifying whether you want to extend it or not.
Additional Indicator Settings
Ignore lines that start with a defined character to instruct the indicator to ignore the line. For example, if you want to hide a line without deleting it, add # in front of it (default is #).
Hide Above Will hide all lines and zones above a defined timeframe.
Show Next Area Hours in Advance This will plot lines in advance to the right of the current price action, helping traders recognize upcoming points of interest.
Show Last X Days This controls the clutter on the screen by limiting the display to the most recent X number of days.
Fill Transparency The percentage of transparency applied to the background when a fill is specified.
Examples:
12 to 13 gray area shaded with dotted lines
Will result in two vertical lines, one at 12 noon and one at 1 PM, with the area between them shaded gray and a dotted line style.
0:00 vertical line red solid
Adds one vertical red line at midnight.
By specifying the open, high, low, and/or close price components, the indicator will interpret this as an instruction to draw a horizontal line at the specified price level. If two or more price levels are provided, each will be tracked accordingly.
Draw a red line starting from 0 open
Draws a line starting from midnight open until the end of the trading day.
Track high and low starting from 9:30 in a dashed green medium line
Tracks the day’s high and low, adjusting as new highs and lows are drawn in a dashed thicker green line from 9:30 AM until the end of trading hours.
# Asia
20 to 0 green high to low filled
# London
2:00 to 5 blue low and high filled
#New York
8:30 to 11:30 orange zone shaded orange between the high and low dotted
Adds three ICT Kill Zones for Asia, London, and New York based on their respective high and low.
8:30 to 11:30 orange zone shaded orange open close dotted
Will add a second New York zone overlapping the high and low zone.
#Draw Open Range Breakout (ORB)
9:30 to 10:00 purple extended zone
Extends the zone from 9:30 to 10:00 AM with a purple extended zone.
Equal Highs and Lows {Reh's and Rel's }# Equal Highs and Lows {Reh's and Rel's} Indicator
## Overview
The "Equal Highs and Lows {Reh's and Rel's}" indicator is designed to identify and mark equal highs and lows on a price chart. It detects both exact and relative equal levels, draws lines connecting these levels, and optionally labels them. This tool can help traders identify potential support and resistance zones based on historical price levels.
## Key Features
1. **Exact and Relative Equality**: Detects both precise price matches and relative equality within a specified threshold.
2. **Customizable Appearance**: Allows users to adjust colors, line styles, and widths.
3. **Dynamic Line Management**: Automatically extends or removes lines based on ongoing price action.
4. **Labeling System**: Optional labels to identify types of equal levels (e.g., "Equal High", "REH/Equal High").
5. **Flexible Settings**: Adjustable parameters for lookback periods, maximum bars apart, and relative equality thresholds.
## User Inputs
### Appearance
- `lineColorHigh`: Color for lines marking equal highs (default: red)
- `lineColorLow`: Color for lines marking equal lows (default: green)
- `lineWidth`: Thickness of the lines (range: 1-5, default: 1)
- `lineStyle`: Style of the lines (options: Solid, Dash, Dotted)
- `showLabels`: Toggle to show or hide labels for equal highs and lows
### Settings
- `lookbackLength`: Number of bars to look back for finding equal highs and lows (default: 200)
- `maxBarsApart`: Maximum number of bars apart for equal highs/lows to be considered (range: 2-10, default: 5)
### Relative Equality
- `considerRelativeEquals`: Enable detection of relative equal highs and lows
- `thresholdIndex`: Maximum tick difference for relative equality in index instruments (range: 1-10, default: 2)
- `thresholdStocks`: Maximum tick difference for relative equality in stock instruments (range: 5-200, step: 5, default: 10)
## How It Works
The indicator scans historical price data to identify equal or relatively equal highs and lows. It draws lines connecting these levels and updates them as new price data comes in. Lines are extended if the level holds and removed if the price breaks through. The tool adapts to different market conditions by allowing adjustments to the equality thresholds for various instrument types.
## Practical Use
Traders can use this indicator to:
- Identify potential support and resistance levels
- Spot areas where price might react based on historical turning points
- Enhance their understanding of price structure and repetitive patterns
## Disclaimer
This indicator is provided as a tool to assist in identifying potential price levels of interest. It is not financial advice. Users should not rely solely on this or any single indicator for trading decisions. Always conduct thorough analysis, consider multiple factors, and be aware that past price behavior does not guarantee future results. All trading involves risk.
ZigZag ProHello Traders!
TRN ZigZag Pro is an indicator which identifies, and highlights pivot points (swings) and prints useful information about the swings in the chart (e.g. length, duration, ...). The indicator uses an extremely precise swing algorithm to detect the most important pivot points. Compared to other swing or zig-zag indicators TRN ZigZag Pro works in real-time, does not need a look-a-head to find swings and is not repainting. Moreover, equal (double) highs and lows are detected and displayed. The TRN ZigZag Pro helps traders to visualize pure price action and supports the trader to identify key turning points or trends.
The indicator comes with the following features:
Precise real-time swing detection without repainting
Equal/double high and low detection
Displaying of swing labels, values and information
Customizable settings as well as look and feel
It's important to note that the TRN ZigZag Pro is a visual tool and does not provide specific buy or sell signals. It serves as a guide for traders to analyze market structure in depth and make well-informed trading decisions based on their trading strategy and additional technical analysis.
Getting an edge with the TRN ZigZag Pro
The indicator clearly displays up trends, defined as a sequence of higher highs (HH) and higher lows (HL), with green labels and down trends, defined as a sequence of lower lows (LL) and lower highs (LH), with red labels. Equal highs/double tops (DT) and equal lows/ double bottoms (DB) are highlighted in gold.
In addition, the labels show a full stack of valuable information about the swings to maximize your accuracy.
Length
Length percentage in relation to the last swing length
Duration
Label (e.g. HH, LL...)
Use cases for swing detection
Trend Identification
By connecting the swing highs and lows, traders can identify and analyze the prevailing trend in the market. An uptrend is characterized by higher swing highs and lows, while a downtrend is characterized by lower highs and lower lows. The indicator helps traders visually to assess the strength and continuity of the trend.
Support And Resistance Levels
The swing highs and lows can act as support and resistance levels. Swing highs may act as resistance levels where selling pressure increases, while swing lows may act as support levels where buying pressure increases. Traders often pay attention to these levels as potential areas for trade entries, exits, or placing stop-loss orders.
Pattern Recognition
The swings identified by the indicator can help traders recognize chart patterns, such as equal high/lows, consolidations, wedges, triangles or more complex patterns like Gartley or Head and Shoulders. These patterns can provide insights into potential trend continuation or reversal.
Trade Entry and Exit
Traders may use TRN ZigZag Pro to determine potential trade entry and exit points. For example, in an uptrend, traders may look for opportunities to enter long positions near swing lows or on pullbacks to support levels. Conversely, in a downtrend, traders may consider short positions near swing highs or on retracements to resistance levels.
Conclusion
While signals from TRN ZigZag Pro can be informative, it is important to recognize that their reliability may vary. Various external factors can impact market prices, and it is essential to consider your risk tolerance and investment goals when executing trades.
Risk Disclaimer
The content, tools, scripts, articles, and educational resources offered by TRN Trading are intended solely for informational and educational purposes. Remember, past performance does not ensure future outcomes.
Mxwll Price Action Suite [Mxwll]Introducing the Mxwll Price Action Suite!
The Mxwll Price Action Suite is an all-in-one analysis indicator incorporating elements of SMC and also ideas extending beyond the trading methodology!
Features
Internal structures
External structures
Customizable Sensitivities
BoS/CHoCH
Order Blocks
HH/LH/LL/LH Areas
Rolling TF highs/lows
Rolling Volume Comparisons
Auto Fibs
And more!
The image above shows the indicator's market structure identification capabilities. Internal BoS and CHoCH structures in addition to overarching market structures are available with customizable sensitivities.
The image above shows the indicator identifying order blocks! Additionally, HH/LH/LL/LH areas are also identified.
The image above shows a rolling area of interest. These areas can be compared to supply/demand zones, where traders might consider a bargain long/short/sell area.
The indicator displays a rolling 4hr high/low and 1D high/low, alongside auto fibonacci levels with a customizable sensitivity.
Finally, the Mxwll Price Action Suite shows relevant session information.
Table information
Current Session
Countdown to session close
Next Session
Countdown to next session open
Rolling 4-Hr volume intensity
Rolling 24-Hr volume intensity
Introducing the Mxwll SMC Suite!
The Mxwll SMC Suite is an all-in-one analysis indicator incorporating elements of SMC and also ideas extending beyond the trading methodology!
Features
Internal structures
External structures
Customizable Sensitivities
BoS/CHoCH
Order Blocks
HH/LH/LL/LH Areas
Rolling TF highs/lows
Rolling Volume Comparisons
Auto Fibs
And more!
The image above shows the indicator's market structure identification capabilities. Internal BoS and CHoCH structures in addition to overarching market structures are available with customizable sensitivities.
The image above shows the indicator identifying order blocks! Additionally, HH/LH/LL/LH areas are also identified.
The image above shows a rolling area of interest. These areas can be compared to supply/demand zones, where traders might consider a bargain long/short/sell area.
The indicator displays a rolling 4hr high/low and 1D high/low, alongside auto fibonacci levels with a customizable sensitivity.
Finally, the Mxwll Price Action Suite shows relevant session information.
Table information
Current Session
Countdown to session close
Next Session
Countdown to next session open
Rolling 4-Hr volume intensity
Rolling 24-Hr volume intensity
Expanded Features of Mxwll Price Action Suite
Internal and External Structures
Internal Structures: These elements refer to the price formations and patterns that occur within a smaller scope or a specific trading session. The suite can detect intricate details like minor support/resistance levels or short-term trend reversals.
External Structures: These involve larger, more significant market patterns and trends spanning multiple sessions or time frames. This capability helps traders understand overarching market directions.
Customizable Sensitivities
Adjusting sensitivity settings allows users to tailor the indicator's responsiveness to market changes. Higher sensitivity can catch smaller fluctuations, while lower sensitivity might focus on more significant, reliable market moves.
Break of Structure (BoS) and Change of Character (CHoCH)
BoS: This feature identifies points where the price breaks a significant structure, potentially indicating a new trend or a trend reversal.
CHoCH: Detects subtle shifts in the market's behavior, which could suggest the early stages of a trend change before they become apparent to the broader market.
Order Blocks and Market Phases
Order Blocks: These are essentially price levels or zones where significant trading activities previously occurred, likely pointing to the positions of smart money.
HH/LH/LL/LH Areas: Identifying Higher Highs (HH), Lower Highs (LH), Lower Lows (LL), and Lower Highs (LH) helps in understanding the trend and market structure, aiding in predictive analysis.
Rolling Timeframe Highs/Lows and Volume Comparisons
Tracks highs and lows over specified rolling periods, providing dynamic support and resistance levels.
Compares volume data across different timeframes to assess the strength or weakness of the current price movements.
Auto Fibonacci Levels
Automatically calculates and plots Fibonacci retracement levels, a popular tool among traders to identify potential reversal points based on past movements.
Session Data and Volume Intensity
Session Information: Displays current and upcoming trading sessions along with countdown timers, which is crucial for day traders and those trading on session overlaps.
Volume Intensity: Measures and compares the volume within the last 4 hours and 24 hours to gauge market activity and potential breakout/breakdown movements.
Visualizations and Practical Use
Dynamic Visuals: The suite provides dynamic visual aids, such as real-time updating of high/low markers and Fibonacci levels, which adjust as new data comes in. This feature is critical in fast-paced markets.
Strategic Entry/Exit Points: By identifying order blocks and using Fibonacci levels, traders can pinpoint strategic entry and exit points, maximizing potential returns.
Risk Management: Enhanced features like session countdowns and volume intensity help in better risk management by providing traders with more data on market sentiment and potential volatility.
Fib Pivot Points HLThis TradingView indicator allows users to select a specific timeframe (TF) and then analyzes the high, low, and closing prices from the past period within that TF to calculate a central pivot point. The pivot point is determined using the formula (High + Close + Low) / 3, providing a key level around which the market is expected to pivot or change direction.
In addition to the central pivot point, the indicator enhances its utility by incorporating Fibonacci levels. These levels are calculated based on the range from the low to the high of the selected timeframe. For instance, a Fibonacci level like R0.38 would be calculated by adding 38% of the high-low range to the pivot point, giving traders potential resistance levels above the pivot.
Key features of this indicator include:
Timeframe Selection: Users can choose their desired timeframe, such as weekly, daily, etc., for analysis.
Pivot Point Calculation: The indicator calculates the pivot point based on the previous period's high, low, and closing prices within the selected timeframe.
Fibonacci Levels: Adds Fibonacci retracement levels to the pivot point, offering traders additional layers of potential support and resistance based on the natural Fibonacci sequence.
This indicator is particularly useful for traders looking to identify potential turning points in the market and key levels of support and resistance based on historical price action and the Fibonacci sequence, which is widely regarded for its ability to predict market movements.
Example:
Suppose you're analyzing the EUR/USD currency pair using this indicator with a weekly timeframe setting. The previous week's price action showed a high of 1.2100, a low of 1.1900, and the week closed at 1.2000.
Using the formula ( High + Close + Low ) / 3 (High+Close+Low)/3, the pivot point would be calculated as ( 1.2100 + 1.2000 + 1.1900 ) / 3 = 1.2000. Thus, the central pivot point for the current week is at 1.2000.
The range from the low to the high is 1.2100 − 1.1900 = 0.0200 1.2100−1.1900=0.0200.
To calculate a specific Fibonacci level, such as R0.38, you would add 38% of the high-low range to the pivot point: 1.2000 + ( 0.0200 ∗ 0.38 ) = 1.2076 1.2000+(0.0200∗0.38)=1.2076. Thus, the R0.38 Fibonacci resistance level is at 1.2076.
Similarly, you can calculate other Fibonacci levels such as S0.38 (Support level at 38% retracement) by subtracting 38% of the high-low range from the pivot point.
Traders can use the pivot point as a reference for the market's directional bias: prices above the pivot point suggest bullish sentiment, while prices below indicate bearish sentiment. The Fibonacci levels act as potential stepping stones for price movements, offering strategic points for entry, exit, or placing stop-loss orders.
Alpha Edge - Intraday [LevelUp]LevelUp Alpha is a collection of tools designed in collaboration with Brian Shannon, CMT, creator of the anchored VWAP (AVWAP) and the author of two best-selling books on technical analysis. This indicator is focused on tools and techniques that Brian uses in both his analysis and trading.
LevelUp Alpha Goals
One primary goal of LevelUp Alpha was to create an indicator with tools and visuals that mimic Brian's preferred chart layouts. For example, the default lengths/colors for AVWAP, 5-day moving average and vertical lines where moving averages begin, are all aligned with Brian's approach to technical analysis. Through this educational process, one can learn how to effectively use AVWAP and other intraday tools to properly manage trades and adhere to sound risk management principles. At any point, the indicator can be customized to match one's preferred layout, colors and trading style.
Trend Alignment - Multiple Timeframe Analysis
As trend followers, we look for stocks in an established uptrend. This starts with reviewing stocks on weekly and/or daily charts. From there, we focus on lower timeframes using intraday charts, with the objective to verify alignment between the timeframes.
Important Note: The majority of tools in LevelUp Alpha are for lower timeframes (intraday) analysis as this is where potential trade setups, entries and exits (stops) are often determined.
Key Features:
▪ AVWAP auto-anchored on 1-day, 2-day, week-to-date and month-to-date (for intraday charts).
▪ AVWAP works with any exchange around the globe, respecting trading days, hours and holidays.
▪ AVWAP works with the TradingView Replay feature, facilitating historical and post-mortem analysis.
▪ 5-day moving average auto-calculated based on the chart timeframe.
▪ 5-day moving average auto-adjusts the minutes in the trading day for crypto and futures.
▪ View up to three daily moving averages on intraday charts, including optional price data.
▪ Anticipate moving average direction based on vertical lines placed at the first bar for each moving average.
▪ Pivot points, aka floor trader pivots or support/resistance levels (R1/S1, R2/S2, etc).
▪ Highlight current and prior day highs/lows with line and price data as these are areas of potential support and resistance.
▪ Table of stats for AVWAP, current and prior day highs/lows, and pivot point price levels, helpful for entries, exits and stops.
▪ Custom alerts for all AVWAPs and pivot points.
AVWAP
The Volume Weighted Average Price (VWAP) is the cumulative average price a stock traded for one day. AVWAP is the same as the VWAP with the exception that the start point (the anchor) is configurable based on a trader's preference, not simply the start of the trading day. From the anchor point forward, on each bar, AVWAP is calculated based on the cumulative volume and average price.
The AVWAP shows the relationship between price and volume over any time period based on the anchor point. At a glance we can see who is in control, the buyers (bulls) or the sellers (bears).
AVWAP Concepts:
▪ When a stock is above an advancing AVWAP, buyers are in control for that timeframe, as the average price is increasing.
▪ When prices are below a declining AVWAP, sellers are in control for that timeframe, as the average price is declining.
▪ When prices oscillate above and below the AVWAP it indicates indecision for that timeframe.
What's unique about AVWAP in this indicator is that it is auto-anchored on 1-day, 2-day, week-to-date and month-to-date. In addition, LevelUp Alpha supports any exchange around the globe, respecting trading days, hours and holidays. You can also use the TradingView replay feature with this indicator, a powerful tool for historical and post-mortem analysis.
AVWAP Auto-Anchor: 1-day, 2-day, week-to-date and month-to-date
AVWAP and TradingView Replay: Review Historical Data and Past Trades
Saudi Exchange (Tadāwul): Trading Days, Sunday to Thursday, 10:00am to 3:00pm
Auto-Anchor: Detects Trading Days
London Stock Exchange (LSE): Trading Days, Monday to Friday, 8:00am to 4:30pm
Auto-Anchor: Detects U.K. Bank Holiday
5-Day Moving Average
When using AVWAP, we look for stocks where the trend of the 50-SMA is higher. We follow this by reviewing lower timeframes (intraday charts) to see if the price action is setting up for a low risk trade by verifying the shorter timeframes align with the longer. As we look at various timeframes, we need to make sure the moving average is consistent across the timeframes, which is done via the 5-day moving average as explained by Brian:
"If you want to see a five DAY moving average on a chart with 10 minute candles, you have to consider how many 10 minute periods of trading there are in the trading day. The US equities markets are open from 9:30- 4:00 each day, which is 6.5 hours per trading day. In each hour of trading, there are 6-10 minute periods, so during the regular session for equities, the market is open for 390 minutes or 39-10 minute periods per day. If we are to get a five day moving average, we would take the 39-10 minute periods the market is open each day and then multiply that by five days. 39 x 5 = 195. So a 5 DAY moving average is represented by a 195 PERIOD moving average when looking at a 10 minute timeframe."
In LevelUp Alpha, the default value for the minutes per day is 390, the number of minutes in one trading day in the U.S. This value can be changed to match any exchange. For example, if trading the India National Stock Exchange (NSE), which is open from 9:30am to 3:30pm, the minutes per day would be set to 375.
As trend followers, our goal is to find stocks where the 5-day moving average is trending up.
5-Day Moving Average Trending Up
When viewing charts of crypto or futures, the minutes per trading day will be auto-adjusted as follows:
• Crypto: 1440 minutes per day based on 24 hrs per day.
• Futures: 1380 minutes per day based on 23 hrs per day - S&P 500 E-mini Futures (ES1!) & NASDAQ 100 E-mini Futures (NS1!)
Important Note: Based on the math as described above using the minutes in the trading day, there will be chart timeframes where the 5-day moving average is not shown. If you have the 5-day moving average enabled from within the indicator Settings, yet the 5-day line is not visible, try changing to another timeframe.
Moving Averages
There are three configurable daily moving averages, including the option to use simple or exponential calculations. These daily moving averages can be viewed on intraday charts as they can often act as areas of support or resistance. There is also an option to smooth the daily moving average when they are shown on an intraday chart.
Daily 10-SMA on Intraday Chart - Acting as Support
Auto-smoothing feature is off.
Daily 20-SMA on Intraday Chart - Acting as Support
Auto-smoothing feature is on.
Vertical Lines - Anticipating Direction
By placing vertical lines at the starting bar where a moving average calculation begins, one can anticipate the direction of the moving average by viewing the trend of the bars that will fall off the moving average as new bars are added. This can be helpful to gauge if the trend will continue in its current trajectory or begin to move in a different direction.
Intraday Chart
Daily Chart
S&P 500 E-mini Futures (ES1!)
Crypto
Pivot Points
Pivot points are intraday price levels that may act as areas of support or resistance. These pivot points were initially created by floor traders operating within the trading pits of the equity futures exchange in Chicago.
The calculations for determining these pivots are based on the prior days high, low and close:
Pivot (P) = (prevHigh + prevLow + prevClose) / 3
Resistance R1 = (2 * P) - prevLow
Support S1 = (2 * P) - prevHigh
Resistance R2 = P + (prevHigh - prevLow)
Support S2 = P - (prevHigh - prevLow)
Resistance R3 = prevHigh + (2 * (pivot - prevLow))
Support S3 = prevLow - (2 * (prevHigh - pivot))
R1 Acting as Resistance
S2 Acting as Support
Prior Day High and Low
With LevelUp Alpha you can show horizontal lines at both the prior day high and low values. This makes it easy to visualize the prior day's trading range in anticipation of potential areas of support or resistance. These area can also be potential points for entering, exiting or profit taking.
Current Day High and Low
In a similar manner to prior day high and low values, you can also view the current day high and low. Notice in the chart below that you can easily see inside days and watch the price action in real-time.
Tables for AVWAP and Pivot Stats
To make it easy to quickly determine potential entries, exits and stops, as well as areas of support or resistance, key values can be shown in a table. The table contents are configurable, with options to include: AVWAP, current day and prior day highs/lows as well as pivot points.
AVWAP Color Coded & Pivot Points
Current Day High/Low and Prior Day High Low
Custom Alerts
There are alert options for all AVWAP values as well as resistance levels R1, R2 and support levels S1 and S2.
Acknowledgements
Many thanks to Brian Shannon for sharing his expertise on technical analysis and risk management, as well as providing feedback and suggestions on the indicator.
[KVA] Kamvia Directional MovementKamvia Directional Movement (KDM) Indicator is an analytical tool designed to identify potential buying and selling opportunities in the market. It highlights the phases of price depletion which typically align with price highs and lows, offering a nuanced understanding of market dynamics.
Efficient at pinpointing trend breakdowns and excelling in the identification of intra-day entry and exit points, the Kamvia Directional Movement Indicator is a valuable asset for traders aiming to optimize their market strategies.
The KDM not only takes into account the traditional high and low price points within its analysis but also introduces an innovative approach by incorporating the concepts of body high and body low. This nuanced analysis offers a deeper insight into market momentum and potential shifts in market dynamics.
High and Low Analysis : The indicator examines the price highs and lows to gauge the overall market volatility and potential turning points. By analyzing these extremities, traders can get a sense of market strength and possible shifts in trend direction. The high points indicate periods of maximum buying interest, potentially signaling overbought conditions, while the low points reflect selling interest, hinting at oversold conditions.
Body High and Body Low Analysis : Unique to the KDM Indicator is the emphasis on the body of the candlestick, which is the range between the open and close prices. This analysis offers a more refined view of market sentiment by focusing on the actual trading range experienced within the period. The body high (the upper end of the candlestick body) and body low (the lower end of the candlestick body) provide insights into the buying and selling pressure during the trading session, beyond mere price extremities.
The indicator is calibrated on a scale from 0 to 100, making interpretation intuitive and straightforward. A reading above 70 is considered to be in the overbought region, suggesting that the market might be experiencing a heightened level of buying activity that could lead to a potential pullback or reversal. Conversely, a reading below 30 falls into the oversold region, indicating a possible exhaustion in selling pressure and a potential for market reversal or bounce back.
This scale and the detailed analysis of both price and body dynamics equip traders with a comprehensive tool for assessing market conditions. The distinction between high/low and body high/body low analysis enriches the indicator's capability to provide more targeted insights into market behavior, enabling traders to make more nuanced decisions based on a broader spectrum of information. By identifying the duration and extent to which these conditions persist, traders can better interpret the market's momentum and align their strategies with the prevailing trend or prepare for an impending reversal.
KDM Strategy
The strategy focuses on spotting price reversals within a confirmed trend. While the indicator features regions indicating overbought and oversold conditions, these signals alone are not sufficient predictors of a market reversal.
The terms "overbought" and "oversold" describe scenarios where prices reach levels that are unusually high or low within a specified look-back period. Entering these zones often indicates a continuation of the trend rather than a reversal.
A "strongly overbought" condition signals buying pressure, whereas a "strongly oversold" condition indicates selling pressure. The key to leveraging these conditions lies in analyzing the duration for which the market remains in either state. This duration can provide critical insights into whether the market is trending or ranging.
Extended periods in extreme overbought territories confirm an uptrend, while prolonged presence in slight overbought zones (above 50 but below 70, for example) suggests a more moderate uptrend. Conventionally, levels above 70 signal extreme overbought conditions, and those below 30 indicate extreme oversold conditions.
Traders are advised to exercise caution when the oscillator stays within these extreme areas. Ideally, the strategy involves capitalizing on temporary price drops within an overall uptrend or on temporary price spikes within an overall downtrend.
Identifying trading opportunities with the KDM Indicator involves looking for the indicator to exit these extreme overbought or oversold regions, signaling potential reversals or continuations in the market's direction. This approach helps traders make informed decisions by considering the broader market trend alongside short-term price movements.
Forex Kill Zones - SMC IndicatorsWhat are Kill Zones?
Kill Zones are specific Time Windows of opportunity during the Session that have the potential for the highest volatility and where looking for trading opportunities is ideal.
The Forex Kill Zone Indicator is specifically designed for the Forex Market. What differentiates this script from other Kill Zones scripts is that this script is based on NY Midnight as the basis for the start of the day.
This is not the usual below-average Kill Zone indicator because this indicator does not only show the 3 main Kill Zones or Sessions, but it also offers extra Kill Zones that are called "Asian Range (AR)", "Central Bank Dealing Range (CBDR)", and "FLOUT".
Another key differentiator of this indicator's functionality is that it shows the highs and lows of each Kill zone allowing SMC traders to monitor Time-Based Liquidity above the highs and lows of each trading session.
Another added benefit of this indicator is the Standard Deviations features for the AR, CBDR, and FLOUT that we added. The Standard Deviations act as key levels where there is a high probability of price reacting when in confluence with 1H or higher key levels (PD Arrays). The Standard Deviations are not pivot levels but are ranges above and below the Kill Zones that rely on TIME and PRICE in their calculations.
Finally, we have also incorporated a Notification function to remind the trader of the start of the trading Kill Zones to not miss out on potential trade opportunities.
Key Functionalities
1) Universal Time Reference:
Every day starts at 00:00 NY Midnight, irrespective of the trader's local time, Instead of the Standard GMT Midnight. This allows all Kill Zones to be in line with the New York start of the day at Midnight, as thought by ICT.
Weekend Highlighter
This feature highlights time from Sunday Market Open at 5 PM NY Time to 00:00 NY Midnight.
It's useful for identifying the non-trading or the low volatility periods when trading should be avoided.
Features Breakdown
Lookback Period
Defaulted to 60 trading days, aligning with “IPDA Data Ranges”, which is ideal for backtesting.
Adjustable for trading, and it's recommended to keep it at 20 trading days to focus on most recent data only.
24-hour Daily Intervals
The 24-hour intervals are not the same as the usual daily candle. Instead, the start of each trading day is anchored to the 00:00 NY Midnight.
Highlights "Days of the Week" labels, "Weekend" Trading Time, and the daily high-low ranges based on the start of trading day mark being at 00:00 NY Midnight.
London Kill Zone (Green)
Starts from 01:00 NY Time to 05:00 NY Time.
London closes at 12:00 NY Time.
Highlight the high and low of the London Kill Zone to Identify Time-Based Liquidity above and below the London Kill Zone Range.
Marks the London Close Session to mark the end of London End of the trading day, where volatility drops.
Highlights the time when there is the highest volatility during the London Session Kill Zone.
New York Kill Zone (Blue)
Starts from 07:00 NY time to 10:00 NY Time.
Marks The CME Open at 08:30 (the opening of the Bond Market).
Highlight the high and low of the New York Kill Zone to Identify Time-Based Liquidity above and below the NY Kill Zone Range.
Highlights the time when there is the highest volatility during the New York Session.
The Central Bank Dealing Range or "CBDR" (Orange)
Starts From 14:00 NY Time to 20:00 NY Time.
Highlight the high and low of the CBDR Kill Zone to Identify Time-Based Liquidity above and below the CBDR Kill Zone Range.
Also, there is an added ability to add the CBDR Standard Deviations above and below the CBDR.
Can also extend the CBDR Standard Deviations key levels until the end of the next day's London Kill Zone.
What are the CBDR Standard Deviations?
The Standard Deviations are extensions of the CBDR above and below the CBDR original range. It takes the high and low of the range and adds the range above and below the original range by x times.
The CCBDR Standard Deviations are NOT pivot levels. They are used as points of reference where we could expect the price to react when in confluence with higher timeframe reference points.
The idea behind them is that if the price is Bearish, the price could rally to +1 CBDR Standard Deviation below dropping lower. As shown in the image below on Thursday, the two vertical lines before the start of Thursday mark the CBDR Kill Zone, then the price rallied to +1 CBDR SDv and then dropped.
Asian Range "AR" Kill Zone
Starts from 20:00 NY Time to 00:00 NY Time.
Highlight the high and low of the AR Kill Zone to Identify Time-Based Liquidity above and below the AR Kill Zone Range.
Also, there is an added ability to add the AR Standard Deviations above and below the AR.
This KillZone should be primarily used when CBDR exceeds 40 pips.
Similar to the CBDR, the AR Standard Deviations also can be used as points of reference where we could expect the price to react when in confluence with higher timeframe reference points.
The AR Standard Deviations can also be extended until the end of the next day's London Kill Zone.
FLOUT Range
It Combines AR and CBDR, spanning from 14:00 NY Time to 00:00 NY Time.
The FLOUT should only be used when both AR and CBDR have small ranges of less than 10 pips combined.
Highlight the high and low of the FLOUT Kill Zone to Identify Time-Based Liquidity above and below the FLOUT Kill Zone Range.
The FLOUT Standard Deviations also can be used as points of reference where we could expect the price to react when in confluence with higher timeframe reference points.
The Flout Standard Deviations can be extended until the end of the next day London Kill Zone.
Bonus Features
Daily & Weekly Open Price Levels
The Open Price levels draw a horizontal line from the start of the trading day at 00:00 NY midnight, and it extends it towards the end of the trading day.
This is useful for understanding where the price is relative to the daily candle.
When Bullish, the trader should look for setups at or below the daily or weekly open price.
When Bearish, the trader should look for setups at or above the daily or weekly open price.
Whether to choose the Daily or Weekly open price depends on the trader's trading style. If the trader is day trading or scaling, then it's more appropriate to choose the Daily Open Price.
However, Day Traders can also use the Weekly candle to align with the Weekly Candle's expected range direction.
On the other hand, if the trader is a Swing Trader and wants to capitalise on the weekly candle's trend, then it's more appropriate to choose the Weekly Open Price.
However, Swing Traders can also use the Daily Open Price when looking to take a trade to time better entries with a high risk-to-reward ratio.
Notifications
The trader can also receive alerts as a reminder at the start of the desired session to not miss out on the start of the trading session.
Fake BreakoutThis indicator detect fake breakout on previous day high/low and option previous swing high and low
Rule Detect Fake Breakout On Previous Day High/Low Or Swing high low Fake Breakout -
1) Detect previous day high/low or swing high/low
2)
A) If price revisit on previous day high/swing high look for upside breakout after input
number of candle (1-5) price came back to previous high and breakout happen downside
it show sell because its fake breakout of previous day high or swing high
B) If price revisit on previous day low/swing low look for downside breakout after input
number of candle (1-5) price came back to previous low and breakout upside of previous
day low it show Buy because its fake breakout of previous day low or swing low
Disclaimer -Traders can use this script as a starting point for further customization or as a reference for developing their own trading strategies. It's important to note that past performance is not indicative of future results, and thorough testing and validation are recommended before deploying any trading strategy.
BTC Halving [YinYangAlgorithms]This Indicator not only estimates what it thinks may be the PRICE for the Start, High and Low of the Halving, but likewise estimates WHEN the Start, High and Low of Halving may be. It then creates Trend Lines based on these predictions so that you may get an evaluation towards if the Price is currently Overbought or Oversold. These Trend Lines may be very useful for seeing the Slope in which the Price may move if it is to reach the estimated Price by the estimated Date. By evaluating the Prices location based on these Trend Lines we may determine if the Price is currently Overbought or Oversold.
These Trend Lines likewise may help identify locations of Support and Resistance. If the Price is much higher than its current Trend Line it is Overbought. There is a chance it will Consolidate back to the Trend Line or it may even correct with a dump all the way back to it; the opposite is true if it is much lower than its current Trend Line.
Trend Lines and Estimates are not all that is featured within this Indicator however. There are also Price Zones which may help identify if the price is currently:
Very Overbought (Red)
Slightly Overbought (Orange)
Neutral (Yellow)
Slightly Oversold (Teal)
Very Oversold (Green)
These zones may help give you an idea of how the price is currently fairing and its potential for movement. Likewise, it may help define where Support and Resistance may be found.
The trend line estimates are done with an algorithm created to evaluate the difference between price and % change that has occurred between the Start, High and Low of all the halvings over how many days between each data type. This may allow us to make an educated estimate towards what Price and Date the Start, High and Low will occur at.
Our Zones are created by evaluating the current Market Cap and circulating supply vs Max Supply of BTC. This may help give us an evaluation of what Price may be considered to be Overbought and Oversold; and likewise may help with estimations of where there may be Support and Resistance based on these Zones.
Tutorial:
In the example above we’re displaying the Halving Start Trend Line, our Information Tables and our Estimated Halving Vertical Marker. This Trend Line may help to display not only the trajectory and slope the Price needs to take to reach the Estimated Halving Price by the Estimated Halving Date; but it may also help to show if the price is Overvalued or Undervalued based on its position above or below this Trend Line.
Based on the Trajectory of the Estimated High Upward Trend Line (Green Line) in the photo above and from the ‘High Date’ estimated in the Information tables; we may attempt to estimate the location the ATH of this Bull Market will create and the price slope it may follow in doing so. This Trajectory may be very useful for understanding the price action that may occur for it to reach the High estimated Price by the High estimated Date.
We currently allow for two different types of zones within our Settings, one called ‘Fast’ displayed in the example above; and the other called ‘Slow’ displayed in the example below.
Our Fast Zone aims to move the Zone Levels Faster in an attempt to move with volatility and parabolic movement. This may help to keep the Very Overbought (Red) and Very OverSold (Green) Levels more accurate by attempting to keep the price within them. By doing so, we may aim to keep all of the Slightly Overbought, Slightly Oversold and Neutral Levels more accurate as well.
The Levels within these zones are defined by the Bright (less transparent) Lines. Whereas the Darker (more transparent) lines represent the Basis Lines between two different levels. These Basis lines may likewise act as a Support and Resistance Location too, but generally hold less weight than the actual Levels themselves.
What you may see is that during the Bull Market, the price is within the very Overbought Zones and even touches again the Very Overbought Level a few times. Likewise, during the Bear Market, the price is within the very Oversold Zones and even slightly drops below the Very Oversold Level. This may be expected and likewise may help to give estimates at potential for growth and decay within the Price based on which condition the Market is within.
Slow Zones move a little slower than Fast Zones, however they may still be accurate. Likewise, it is up to you to decide which Zone works better for your specific Trading Style; however, by default, the Zone type is set to Fast.
If you refer to both the Fast and Slow examples above, you may notice in the Fast the Price is only slightly above the ‘Slightly Oversold’ (Teal) line. Also, In the Fast, the Price where the ‘Very Overbought’ Level is 100k. This is one of the many reasons we’ve opted for ‘Fast’ as the default, and it is because it allows more room for movement; and in our opinion, potentially accuracy as well.
If you refer to the Slow example, you’ll see that the price is currently facing the Neutral Level as a Resistance location. However, if you refer to the price residing at the Slows ‘Very Overbought’ Level, it is only 81.5k, compared to the 100k of Fast.
The BTC Halving is a major event that takes place roughly every 4 years. It historically has a major impact on the market, and some may even say it signifies the Start, or close to start of the Bull Market. Therefore, since historically there may be cycles that BTC and potentially crypto itself follows, we’ve developed this Indicator in hopes that it may solve one of the biggest questions traders face. What Date will the Start, High and Low of the Halving occur and also at what Price.
Hopefully this Tutorial has given you some guidance as to how this Indicator may be used to help identify some of these key levels; including the slope at which the price may have to move if it is to reach its projection Price by its projected Date.
Settings:
1. Show Prediction Trend Lines:
- Options:
All
Start + High
Start + Low
High + Low
Start
High
Low
None
- Description:
Prediction Trend Lines may be an important way to see the Slope the Price needs to take to reach the Predicted Price by the Predicted Date. This may be useful for identifying if the Price is currently Overbought or Oversold.
2. Zone Type:
- Options:
Fast
Slow
- Description:
Zone types change the way the Zones expand.
3. Show Zones:
- Options:
All
Zones
Basis
None
- Description:
Zones are a way of seeing Overbought and Oversold Price locations based on Market Cap and Circulating Supply vs Max Supply.
4. Vertical Markers:
- Options:
All
Line
Label
None
- Description:
Vertical Markers display where the Halving has occurred with a Vertical Line and Label.
5. Show Tables:
Tables may be useful for seeing the Price and Date for when the Start, High and Low of the Halving may occur.
6. Fill Zones:
Filling in Zones may help to identify which Zone the Price is currently in.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
ICT Playbook by dokterfuseFEATURES
- New York daily ranges high to low
- 08-12 UTC-5 Time Window Highlighted
- New York day of week divider
- Weekly high/low + EQ
- TGIF
- Monday & Thursday range extended
- Weekly open
- Midnight open
- Previous daily range percentiles (fib)
- 5 ADR
PURPOSE INDICATOR & UNIQUENESS
The concepts used in this indicator are widely variated from teachings by 'The Inner Circle Trader' the purpose of this indicator is to give the 'ICT community' the
resourse to automate the visualization of the daily ranges in New York Time. The highs and lows from 00:00 - 00:00 [New York Time) will be horizontally plotted along
with vertical daily dividers. The indicator solves the struggle of having Tradingview's editor's 'normal' daily highs and lows which opens at 05.00 PM New York Time.
The indicator has flexible settings, so you can enable/disable whatever feature you'd like to have displayed. There is no other indicator which will give you the
daily range in New York Time. The previous daily range percentiles in new york time are the 25%, 50%, and 75% levels measured from the previous daily range
high and low , they are extended to the current day, this to measure whether price is in a premium or discount, and to converge it with PD Array's.
This feature alone, is nowhere to be seen... The concept of dividing daily ranges starting from 00.00 New York Time brought by ICT, can open a whole new world to
reading price action. This indicator enables it to plot these levels out automatically, without worrying about the 'normal daily open' at 05.00 PM New York Time.
The other features in the indicator such as TGIF, Weekly Range, 5ADR, Midnight Open, and more are mainly build to give you an intraweek perspective about
the behaviour of price action during specific times and 'time' levels, such as the opening price at midnight or the previous daily equilibrium .
TIMEFRAME & MARKETS
Since this indicator is made with the purpose of giving you an intra-week perspective, the author of this script would advice you to use anything in between
the '15m-1h' timeframe. The indicator is made mainly for Forex Pairs, however feel free to use it on other markets too.
WHAT IS NOT THE PURPOSE OF THIS INDICATOR
As the name tells you 'ICT Playbook'; it's a playbook of concepts by ICT for you to 'play around' with, so for study and educational purposes. This indicator IS NOT
a trading system, or a signal provider. Nor is it a roadmap of what's happening to the markets... Without a background in ICT his lectures, you won't have any idea
what kind of value this indicator provides. You will only understand this indicator if you are an intermediate ICT student.
FEATURES INSTRUCTION
1. New York Daily Ranges: This feature will plot 2 horizontal lines each day starting from 00.00 , 1 placed at the low and 1 placed at the high.
It will also plot vertical dividers in between. The line color and style are adjustable in the settings.
2. Time Window: This feature will plot a colored and transparent background to highlight the 08:00-12:00 New York Time window, which is often a time window
where a lot of volume enters the market. The 8.30-9.30 is extra highlighted, cause of the news embargo's and equities open will often bring 'Manipulation'.
3. New York Day of Week Divider: Will plot the names of the days above the chart
4. Weekly high/low + EQ: This feature will plot the current low and high of the week. Also, it will plot the EQ, which stands for the 'Equilibrium' of the weekly range
.
5. TGIF: 'Thank God It's Friday'; a concept of ICT where if we had consecutive up-days/down-days it will plot the 20%-30% of the weekly range .
6. Monday + Thursday Range Extended: ICT explained algorithmic principles coupled to these days. For example: "In a bullish week we can use Monday's high as support".
7. Weekly Open: Opening price of the weekly candle.
8. Midnight Open: Opening price of New York Midnight / True Day Open.
9. Previous Daily Range Percentiles: 25%, 50%, and 75% levels extended of the previous daily range .
10. ADR: 'Average Daily Range', the average range of 5 daily candles, the current daily range, and the previous daily range plotted in a table.
AUTHOR
This script is created by dokterfuse for the ICT community to make their tradingview experience easier. I'd like to give credits to ICT for his concepts used in this script.
TERMS & CONDITIONS
The indicator is only created for educational purposes, the script does not take any responsibility for the user's decisions in the markets. When using the tool,
you're agreeing to the 'Terms & Conditions'.
FUTURE UPDATES & BUGS
The script will be maintained and updated after the public release. Bugs and Ideas can be suggested in the comments.
Price based concepts / quantifytools- Overview
Price based concepts incorporates a collection of multiple price action based concepts. Main component of the script is market structure, on top of which liquidity sweeps and deviations are built on, leaving imbalances the only standalone concept included. Each concept can be enabled/disabled separately for creating a selection of indications that one deems relevant for their purposes. Price based concepts are quantified using metrics that measure their expected behavior, such as historical likelihood of supportive price action for given market structure state and volume traded at liquidity sweeps. The concepts principally work on any chart, whether that is equities, currencies, cryptocurrencies or commodities, charts with volume data or no volume data. Essentially any asset that can be considered an ordinary speculative asset. The concepts also work on any timeframe, from second charts to monthly charts. None of the indications are repainted.
Market structure
Market structure is an analysis of support/resistance levels (pivots) and their position relative to each other. Market structure is considered to be bullish on a series of higher highs/higher lows and bearish on a series of lower highs/lower lows. Market structure shifts from bullish to bearish and vice versa on a break of the most recent pivot high/low, indicating weak ability to defend a key level from the dominating side. Supportive market structure typically provides lengthier and sustained trending environment, making it an ideal point of confluence for establishing directional bias for trades.
Liquidity sweeps
Liquidity sweeps are formed when price exceeds a pivot level that served as a provable level of demand once and is expected to display demand again when revisited. A simple way to look at liquidity sweeps is re-tests of untapped support/resistance levels.
Deviations
Deviations are formed when price exceeds a reference level (market structure shift level/liquidity sweep level) and shortly closes back in, leaving participating breakout traders in an awkward position. On further adverse movement, stuck breakout traders are forced to cover their underwater positions, creating ideal conditions for a lengthier reversal.
Imbalances
Imbalances, also known as fair value gaps or single prints, depict areas of inefficient and one sided transacting. Given inclination for markets to trade efficiently, price is naturally attracted to areas that lack proper participation, making imbalances ideal targets for entries or exits.
Key takeaways
- Price based concepts consists of market structure, liquidity sweeps, deviations and imbalances.
- Market structure shifts from bullish to bearish and vice versa on a break of the most recent pivot high/low, indicating weak ability to defend a key level from the dominating side.
- Supportive market structure tends to provide lengthier and sustained movement for the dominating side, making it an ideal foundation for establishing directional bias for trades.
- Liquidity sweeps are formed when price exceeds an untapped support/resistance level that served as a provable level of demand in the past, likely to show demand again when revisited.
- Deviations are formed when price exceeds a key level and shortly closes back in, leaving breakout traders in an awkward position. Further adverse movement compels trapped participants to cover their positions, creating ideal conditions for a reversal.
- Imbalances depict areas of inefficient and one sided transacting where price is naturally attracted to, making them ideal targets for entries or exits.
- Price based concepts are quantified using metrics that measure expected behavior, such as historical likelihood of supportive structure and volume traded at liquidity sweeps.
- For practical guide with practical examples, see last section.
Accessing script 🔑
See "Author's instructions" section, found at bottom of the script page.
Disclaimer
Price based concepts are not buy/sell signals, a standalone trading strategy or financial advice. They also do not substitute knowing how to trade. Example charts and ideas shown for use cases are textbook examples under ideal conditions, not guaranteed to repeat as they are presented. Price based concepts notify when a set of conditions are in place from a purely technical standpoint. Price based concepts should be viewed as one tool providing one kind of evidence, to be used in conjunction with other means of analysis.
Price based concepts are backtested using metrics that reasonably depict their expected behaviour, such as historical likelihood of supportive price movement on each market structure state. The metrics are not intended to be elaborate and perfect, but to serve as a general barometer for feedback created by the indications. Backtesting is done first and foremost to exclude scenarios where the concepts clearly don't work or work suboptimally, in which case they can't be considered as valid evidence. Even when the metrics indicate historical reactions of good quality, price impact can and inevitably does deviate from the expected. Past results do not guarantee future performance.
- Example charts
Chart #1 : BTCUSDT
Chart #2 : EURUSD
Chart #3 : ES futures
Chart #4 : NG futures
Chart #5 : Custom timeframes
- Concepts
Market structure
Knowing when price has truly pivoted is much harder than it might seem at first. In this script, pivots are determined using a custom formula based on volatility adjusted average price, a fundamentally different approach to the widely used highest/lowest price within X amount of bars. The script calculates average price within set period and adjusts it to volatility. Using this formula, the script determines when price has turned significantly enough and aggressively enough to constitute a relevant pivot, resulting in high accuracy while ruling out subjective decision making completely. Users can adjust length of market structure basis and sensitivity of volatility adjustment to achieve desired magnitude of pivots, reflected on the average swing metrics. Note that structure pivots are backpainted. Typical confirmation time for a pivot is within 2-3 bars after peak in price.
Market structure shifts
Generally speaking, traders consider market structure to have shifted when most recent structure high/low gets taken out, flipping underlying bias from one side over to the other (e.g. from bullish structure favoring upside to bearish structure favoring downside). However, there are many ways to approach the concept and the most popular method might not always be the best one. Users can determine their own market structure shift rules by choosing source (close, high, low, ohlc4 etc.) for determining structure shift. Users can also choose additional rules for structure shift, such as two consecutive closes above/below pivot to qualify as a valid shift.
Liquidity sweeps
Users can set maximum amount of bars liquidity levels are considered relevant from the moment of confirmed pivot. By default liquidity levels are monitored for 250 bars and then discarded. Level of tolerance can be set to anything between 100 and 1000 bars. For each liquidity sweep, relative volume (volume relative to volume moving average) is stored and added to average calculations for keeping track of typical depth of liquidity found at sweeps.
Deviations
Users can set a maximum amount of bars price has to spend above/below reference level to consider a deviation to be in place. By default set to 6 bars.
Imbalances
Users can set a desired fill point for imbalances using the following options: 100%, 75%, 50%, 25%. Users can also opt for excluding insignificant imbalances to attain better relevance in indications.
- Backtesting
Built-in backtesting is based on metrics that are considered to reasonably quantify expected behaviour of the main concept, market structure. Structure feedback is monitored using two metrics, supportive structure and structure period gain. Rest of the metrics provided are informational in nature, such as average swing and average relative volume traded at liquidity sweeps. Main purpose of the metrics is to form a general barometer for monitoring whether or not the concepts can be viewed as valid evidence. When the concepts are clearly not working optimally, one should adjust expectations accordingly or take action to improve performance. To make any valid conclusions of performance, sample size should also be significant enough to eliminate randomness effectively. If sample size on any individual chart is insufficient, one should view feedback scores on multiple correlating and comparable charts to make up for the loss.
For more elaborate backtesting, price based concepts can be used in any other script that has a source input, including fully mechanic strategies utilizing Tradingview's native backtester. Each concept and their indications (e.g. higher low on a bearish structure, lower high on a bullish structure, market structure shift up, imbalance filled etc.) can be utilized separately and used as a component in a backtesting script of your choice.
Structure feedback
Structure feedback is monitored using two metrics, likelihood of supportive price movement following a market structure shift and average structure period gain. If either of the two employed tests indicate failed reactions beyond a tolerable level, one should take action to improve feedback by adjusting the settings. If feedback metrics after adjusting the settings are still insufficient, the concepts are working suboptimally for the given chart and cannot be regarded as valid technical evidence as they are.
Metric #1 : Supportive structure
Each structure pivot is benchmarked against its respective structure shift level. Feedback is considered successful if structure pivot takes place above market structure shift level (in the case of bullish structure) or below market structure shift level (in the case of bearish structure). Structure feedback constitutes as one test indicating how often a market structure state results in price movement that can be considered supportive.
Metric #2 : Structure period gain
Each structure period is expected to present favorable appreciation, measured from one market structure shift level to another. E.g. bullish structure period gain is measured from market structure shift up level to market structure shift down level that ends the bullish structure period. Bearish structure is measured in a vice versa manner, from market structure shift down level to market structure shift up level that ends the bearish structure period. Feedback is considered successful if average structure period gain is supportive for a given structure (positive for bullish structure, negative for bearish structure).
Additional metrics
On top of structure feedback metrics, percentage gain for each swing (distance between a pivot to previous pivot) is recorded and stored to average calculations. Average swing calculations shed light on typical pivot magnitude for better understanding changes made in market structure settings. Average relative volume traded at liquidity sweep on the other hand gives a clue of depth of liquidity typically found on a sweeps.
Feedback scores
When market structure (basis for most concepts) is working optimally, quality threshold for both feedback metrics are met. By default, threshold for supportive structure is set to 66%, indicating valid feedback on 2/3 of backtesting periods on average. On top, average structure period gain needs to be positive (for bullish structures) and negative (for bearish structure) to qualify as valid feedback. When both tests are passed, a tick indicating valid feedback will appear next to feedback scores, otherwise an exclamation mark indicating suboptimal performance on either or both. If both or either test fail, market structure parameters need to be optimized for better performance or one needs to adjust expectations accordingly.
Verifying backtest calculations
Backtest metrics can be toggled on via input menu, separately for bullish and bearish structure. When toggled on, both cumulative and average counters used in backtesting will appear on "Data Window" tab. Calculation states are shown at a point in time where cursor is hovered. E.g. when hovering cursor on 4th of January 2021, backtest calculations as they were during this date will be shown.
- Alerts
Available alerts are the following.
- HH/HL/LH/LL/EQL/EQH on a bullish/bearish structure
- Bullish/bearish market structure shift
- Bullish/bearish imbalance created
- Bullish/bearish imbalance filled
- Bullish/bearish liquidity sweep
- Bullish/bearish deviation
- Visuals
Each concept can be enabled/disabled separately for creating a selection indications that one deems relevant for their purposes. On top, each concept has a stealth visual option for more discreet visuals.
Unfilled imbalances and untapped liquidity levels can be extended forward to better gauge key areas of interest.
Liquidity sweeps have an intensity option, using color and width to visualize volume traded at sweep.
Market structure states and market structure shifts can be visualized as chart color.
Metric table can be offsetted horizontally or vertically from any four corners of the chart, allowing space for tables from other scripts.
Table sizes, label sizes and colors are fully customizable via input menu.
- Practical guide
The basic idea behind market structure is that a side (bulls or bears) have shown significant weakness on a failed attempt to defend a key level (most recent pivot high/low). In the same way, a side has shown significant strength on a successful attempt to break through a key level. This successful break through a key level often leads to sustained lengthier movement for the side that provably has the upper hand, making it an ideal tool for establishing directional bias.
Multi-timeframe view of market structure provides crucial guidance for analyzing market structure states on any individual timeframe. If higher timeframe market structure is bullish, it doesn't make sense to expect contradicting lower timeframe market structure to provide significant adverse movement, but rather a normal correction within a long term trend. In the same way, if lower timeframe market structure is in agreement with higher timeframe market structure, one can expect a reliable trending environment to ensue as multiple points of confluence are in place.
Bullish structure can be considered constructive on a series of higher highs and higher lows, indicating strong interest from bulls to sustain an uptrend. Vice versa is true for bearish structure, a series of lower highs and lower lows can be considered constructive. When structure does not indicate strong interest to maintain a supportive trend (lower highs on bullish structure, higher lows on bearish structure), a structure shift and a turn in trend might be nearing.
Market structure shifts are of great interest for breakout traders who position for continuation. Structure shifts can indeed be fertile ground for executing a breakout trade, but breakouts can easily turn into fakeouts that leave participants in an awkward position. When price moves further away from the underwater participants, potential for snowball effect of covering positions and driving price further away is elevated.
Liquidity sweeps as a concept is based on the premise that pivoting price is evidence of meaningful depth of liquidity found at/around pivot. If liquidity existed at a pivot once, it is likely to exist there in the future as well. When price grinds against liquidity, it is on a path of resistance rather than path of least resistance. Pivots are also attractive placements for traders to set stop-losses, which act as fuel for price to move to the opposite direction when swept and triggered.
Behind tightly formed pivots are potentially many stop-loss orders lulled in the comfort of having many layers of levels protecting their position. Compression that leaves such clusters of unswept liquidity rarely goes unvisited.
As markets strive for efficient and proper transacting most of the time, imbalances serve as points in price where price is naturally attracted to. However, imbalances too are contextual and sometimes one sided trading is rewarded with follow through, rather than with a fill. Identifying market regimes give further clue into what to expect from imbalances. In a ranging environment, one can expect imbalances to fill relatively quick, making them ideal targets for entries and exits.
On a strongly trending environment on the other hand imbalances tend to stick for a much longer time. In such environments continuation can be expected with no fills or only partial fills. Signs of demand preventing fill attempts serve as additional clues for imminent continuation.
4H RangeThis script visualizes certain key values based on a 4-hour timeframe of the selected market on the chart. These values include the High, Mid, and Low price levels during each 4-hour period.
These levels can be helpful to identify inside range price action, chop, and consolidation. They can sometimes act as pivots and can be a great reference for potential entries and exits if price continues to hold the same range.
Here's a step-by-step overview of what this indicator does:
1. Inputs: At the beginning of the script, users are allowed to customize some inputs:
Choose the color of lines and labels.
Decide whether to show labels on the chart.
Choose the size of labels ("tiny", "small", "normal", or "large").
Choose whether to display price values in labels.
Set the number of bars to offset the labels to the right.
Set a threshold for the number of ticks that triggers a new calculation of high, mid, and low values.
* Tick settings may need to be increased on equity charts as one tick is usually equal to one cent.
For example, if you want to clear the range when there is a close one point/one dollar above or below the range high/low then on ES
that would be 4 ticks but one whole point on AAPL would be 100 ticks. 100 ticks on an equity chart may or may not be ideal due to
different % change of 100 ticks might be too excessive depending on the price per share.
So be aware that user preferred thresholds can vary greatly depending on which chart you're using.
2. Retrieving Price Data: The script retrieves the high, low, and closing price for every 4-hour period for the current market.
The script also calculates the mid-price of each 4-hour period (the average of the high and low prices).
3. Line Drawing: At the start of the script (first run), it draws three lines (high, mid, and low) at the levels corresponding to the high,
mid, and low prices. Users can also change transparency settings on historical lines to view them. Default setting for historical lines
is for them to be hidden.
4. Updating Lines and Labels: For each subsequent 4-hour period, the script checks whether the close price of the period has gone
beyond a certain threshold (set by user input) above the previous high or below the previous low. If it has, the script deletes the
previous lines and labels, draws new lines at the new high, mid, and low levels, and creates new labels (if the user has opted to
show labels).
5. Displaying Values in the Data Window: In addition to the visual representation on the chart, the script also plots the high, mid, and
low prices. These plotted values appear in the Data Window of TradingView, allowing users to see the exact price levels even when
they're not directly labeled on the chart.
6. Updating Lines and Labels Position: At the end of each period, the script moves the lines and labels (if they're shown) to the right,
keeping them aligned with the current period.
Please note: This script operates based on a 4-hour timeframe, regardless of the timeframe selected on the chart. If a shorter timeframe is selected on the chart, the lines and labels will appear to extend across multiple bars because they represent 4-hour price levels. If a longer timeframe is selected, the lines and labels may not accurately represent high, mid, and low levels within that longer timeframe.
DB Support Resistance Levels + Smart Higher Highs and Lower LowsDB Support Resistance Levels + Smart Higher Highs and Lower Lows
The indicator plots historic lines for high, low and close prices shown in settings as "base levels". Users can control the lookback period that is plotted along with an optional multiplier. Traders will notice that the price bounces off these historic base levels. The base levels are shown as light gray by default (customizable in the settings). Users may choose to display base levels by a combination of historic high, low and close values.
On top of the historic base levels, the indicator display higher high and lower low levels from the current bar high/low. Higher highs are shown by default in pink and lower lows by default in yellow. The user can adjust the lookback period for displaying higher highs and the optional multiplier. Only historic values higher than the current bar high are displayed filtering out (by highlighting) the remaining levels for the current bar. Users may choose to use a combination of historic open, low and close values for displaying higher highs. The user can adjust the lookback period for displaying lower lows and the optional multiplier. Only historic values lower than the current bar low are displayed filtering out (by highlighting) the remaining levels for the current bar. Users may choose to use a combination of historic open, low and close values for displaying lower low.
The indicator includes two optional filters for filtering out higher highs and lower lows to focus (highlight) the most relevant levels. The filters include KC and a simple price multiplier filter. The latter is enabled by default and recommended.
The indicator aims to provide two things; first a simple plot of historic base levels and second as the price moves to highlight the most relevant levels for the current price action. While the indicator works on all timeframes, it was tested with the weekly. Please keep in mind adjusting the timeframe may require the lookback settings to be adjusted to ensure the bars are within range.
How should I use this indicator?
Traders may use this indicator to gain a visual reference of support and resistance levels from higher periods of time with the most likely levels highlighted in pink and yellow. Replaying the indicator gives a visual show of levels in action and just how very often price action bounces from these highlighted levels.
Additional Notes
This indicator does increase the max total lines allowed which may impact performance depending on device specs. No alerts or signals for now. Perhaps coming soon...
Ticker Correlation Reference IndicatorHello,
I am super excited to be releasing this Ticker Correlation assessment indicator. This is a big one so let us get right into it!
Inspiration:
The inspiration for this indicator came from a similar indicator by Balipour called the Correlation with P-Value and Confidence Interval. It’s a great indicator, you should check it out!
I used it quite a lot when looking for correlations; however, there were some limitations to this indicator’s functionality that I wanted. So I decided to make my own indicator that had the functionality I wanted. I have been using this for some time but decided to actual spruce it up a bit and make it user friendly so that I could share it publically. So let me get into what this indicator does and, most importantly, the expanded functionality of this indicator.
What it does:
This indicator determines the correlation between 2 separate tickers. The user selects the two tickers they wish to compare and it performs a correlation assessment over a defaulted 14 period length and displays the results. However, the indicator takes this much further. The complete functionality of this indicator includes the following:
1. Assesses the correlation of all 4 ticker variables (Open, High, Low and Close) over a user defined period of time (defaulted to 14);
2. Converts both tickers to a Z-Score in order to standardize the data and provide a side by side comparison;
3. Displays areas of high and low correlation between all 4 variables;
4. Looks back over the consistency of the relationship (is correlation consistent among the two tickers or infrequent?);
5. Displays the variance in the correlation (there may be a statistically significant relationship, but if there is a high variance, it means the relationship is unstable);
6. Permits manual conversion between prices; and
7. Determines the degree of statistical significance (be it stable, unstable or non-existent).
I will discuss each of these functions below.
Function 1: Assesses the correlation of all 4 variables.
The only other indicator that does this only determines the correlation of the close price. However, correlation between all 4 variables varies. The correlation between open prices, high prices, low prices and close prices varies in statistically significant ways. As such, this indicator plots the correlation of all 4 ticker variables and displays each correlation.
Assessing this matters because sometimes a stock may not have the same magnitude in highs and lows as another stock (one stock may be more bullish, i.e. attain higher highs in comparison to another stock). Close price is helpful but does not pain the full picture. As such, the indicator displays the correlation relationship between all 4 variables (image below):
Function 2: Converts both tickers to Z-Score
Z-Score is a way of standardizing data. It simply measures how far a stock is trading in relation to its mean. As such, it is a way to express both tickers on a level playing field. Z-Score was also chosen because the Z-Score Values (0 – 4) also provide an appropriate scale to plot correlation lines (which range from 0 to 1).
The primary ticker (Ticker 1) is plotted in blue, the secondary comparison ticker (Ticker 2) is plotted in a colour changing format (which will be discussed below). See the image below:
Function 3: Displays areas of high and low correlation
While Ticker 1 is plotted in a static blue, Ticker 2 (the comparison ticker) is plotted in a dynamic, colour changing format. It will display areas of high correlation (i.e. areas with a P value greater than or equal to 0.9 or less than and equal to -0.9) in green, areas of moderate correlation in white. Areas of low correlation (between 0.4 and 0 or -0.4 and 0) are in red. (see image below):
Function 4: Checks consistency of relationship
While at the time of assessing a stock there very well maybe a high correlation, whether that correlation is consistent or not is the question. The indicator employs the use of the SMA function to plot the average correlation over a defined period of time. If the correlation is consistently high, the SMA should be within an area of statistical significance (over 0.5 or under -0.5). If the relationship is inconsistent, the SMA will read a lower value than the actual correlation.
You can see an example of this when you compare ETH to Tezos in the image below:
You can see that the correlation between ETH and Tezo’s on the high level seems to be inconsistent. While the current correlation is significant, the SMA is showing that the average correlation between the highs is actually less than 0.5.
The indicator also tells the user narratively the degree of consistency in the statistical relationship. This will be discussed later.
Function 5: Displays the variance
When it comes to correlation, variance is important. Variance simply means the distance between the highest and lowest value. The indicator assess the variance. A high degree of variance (i.e. a number surpassing 0.5 or greater) generally means the consistency and stability of the relationship is in issue. If there is a high variance, it means that the two tickers, while seemingly significantly correlated, tend to deviate from each other quite extensively.
The indicator will tell the user the variance in the narrative bar at the bottom of the chart (see image below):
Function 6: Permits manual conversion of price
One thing that I frequently want and like to do is convert prices between tickers. If I am looking at SPX and I want to calculate a price on SPY, I want to be able to do that quickly. This indicator permits you to do that by employing a regression based formula to convert Ticker 1 to Ticker 2.
The user can actually input which variable they would like to convert, whether they want to convert Ticker 1 Close to Ticker 2 Close, or Ticker 1 High to Ticker 2 High, or low or open.
To do this, open the settings and click “Permit Manual Conversion”. This will then take the current Ticker 1 Close price and convert it to Ticker 2 based on the regression calculations.
If you want to know what a specific price on Ticker 1 is on Ticker 2, simply click the “Allow Manual Price Input” variable and type in the price of Ticker 1 you want to know on Ticker 2. It will perform the calculation for you and will also list the standard error of the calculation.
Below is an example of calculating a SPY price using SPX data:
Above, the indicator was asked to convert an SPX price of 4,100 to a SPY price. The result was 408.83 with a standard error of 4.31, meaning we can expect 4,100 to fall within 408.83 +/- 4.31 on SPY.
Function 7: Determines the degree of statistical significance
The indicator will provide the user with a narrative output of the degree of statistical significance. The indicator looks beyond simply what the correlation is at the time of the assessment. It uses the SMA and the highest and lowest function to make an assessment of the stability of the statistical relationship and then indicates this to the user. Below is an example of IWM compared to SPY:
You will see, the indicator indicates that, while there is a statistically significant positive relationship, the relationship is somewhat unstable and inconsistent. Not only does it tell you this, but it indicates the degree of inconsistencies by listing the variance and the range of the inconsistencies.
And below is SPY to DIA:
SPY to BTCUSD:
And finally SPY to USDCAD Currency:
Other functions:
The indicator will also plot the raw or smoothed correlation result for the Open, High, Low or Close price. The default is to close price and smoothed. Smoothed just means it is displaying the SMA over the raw correlation score. Unsmoothing it will show you the raw correlation score.
The user also has the ability to toggle on and off the correlation table and the narrative table so that they can just review the chart (the side by side comparison of the 2 tickers).
Customizability
All of the functions are customizable for the most part. The user can determine the length of lookback, etc. The default parameters for all are 14. The only thing not customizable is the assessment used for determining the stability of a statistical relationship (set at 100 candle lookback) and the regression analysis used to convert price (10 candle lookback).
User Notes and important application tips:
#1: If using the manual calculation function to convert price, it is recommended to use this on the hourly or daily chart.
#2: Leaving pre-market data on can cause some errors. It is recommended to use the indicator with regular market hours enabled and extended market hours disabled.
#3: No ticker is off limits. You can compare anything against anything! Have fun with it and experiment!
Non-Indicator Specific Discussions:
Why does correlation between stocks mater?
This can matter for a number of reasons. For investors, it is good to diversify your portfolio and have a good array of stocks that operate somewhat independently of each other. This will allow you to see how your investments compare to each other and the degree of the relationship.
Another function may be getting exposure to more expensive tickers. I am guilty of trading IWM to gain exposure to SPY at a reduced cost basis :-).
What is a statistically significant correlation?
The rule of thumb is anything 0.5 or greater is considered statistically significant. The ideal setup is 0.9 or more as the effect is almost identical. That said, a lot of factors play into statistical significance. For example, the consistency and variance are 2 important factors most do not consider when ascertaining significance. Perhaps IWM and SPY are significantly correlated today, but is that a reliable relationship and can that be counted on as a rule?
These are things that should be considered when trading one ticker against another and these are things that I have attempted to address with this indicator!
Final notes:
I know I usually do tutorial videos. I have not done one here, but I will. Check back later for this.
I hope you enjoy the indicator and please feel free to share your thoughts and suggestions!
Safe trades all!
Liquidity prints / quantifytools- Overview
Liquidity prints detect points in price where buyers or sellers are being effectively absorbed, indicative of price being on a path of resistance. In other words, the prints detect points in price where hard way is likely in current motion and easy way in the opposite. Prints with ideal attributes such as prints into extended trends or into a deviation are marked separately as print confluence. Prints with important or multiple confluence factors give further color into potential strength and duration of print influence. Liquidity prints are detected using an universally applicable method based on price action (OHLC). The prints principally work on any chart, whether that is equities, currencies, cryptocurrencies or commodities, charts with volume data or no volume data. Essentially any asset that can be considered an ordinary speculative asset. The prints also work on any timeframe, from second charts to monthly charts. Liquidity prints are activated real-time after a confirmed bar close, meaning they are not repainted and can be interacted with once a confirmation is in place.
Liquidity prints are based on the premise that price acts a certain way when sufficient liquidity is found, in other words when price shows exhaustion of some sort. A simple example of such price action are wicks, attempted moves that were rejected within the same time period where move was initiated. This type of price action typically takes place when price is close to or at meaningful amount of bids in an order book. There's no guarantee the stacked orders can't be just cleared and moved through, but at face value it does not make sense to expect price moving the hard way. When sufficient amount of characteristics in price action are hinting proximate liquidity, a print is activated. As a barometer for print feedback quality, short term impact on price rate of change and likelihood of print lows/highs being revisited during backtesting period are tracked for each print. Peak increase/decrease during backtesting period is also recorded and added to average calculations. Liquidity prints can also be backtested using any script that has a source input, including mechanic strategies utilizing Tradingview's native backtester.
Key takeaways
Liquidity prints are activated when price is showing signs of grind against path of greater resistance, leaving path of least resistance to the opposite direction.
Liquidity prints with ideal attributes are marked separately as print confluence, giving further color into print strength and duration of influence.
Liquidity prints are backtested using price rate of change, print invalidation mark and peak magnitude metrics.
Liquidity prints can be backtested and utilized in any other Tradingview script, including mechanic strategies utilizing Tradingview's native backtester.
Liquidity prints are detected using price action based methodology. They principally work on any chart or timeframe, including charts with no volume data.
Liquidity prints are activated real-time after a confirmed bar close and are not repainted.
For practical guide with practical examples, see last section.
Accessing script 🔑
See "Author's instructions" section, found at bottom of the script page.
Disclaimer
Liquidity prints are not buy/sell signals, a standalone trading strategy or financial advice. They also do not substitute knowing how to trade. Example charts and ideas shown for use cases are textbook examples under ideal conditions, not guaranteed to repeat as they are presented. Liquidity prints notify when a set of conditions (various reversal patterns, overextended price etc.) are in place from a purely technical standpoint. Liquidity prints should be viewed as one tool providing one kind of evidence, to be used in conjunction with other means of analysis.
Liquidity print quality is backtested using metrics that reasonably depict their expected behaviour, such as historical likelihood of price slowing down or turning shortly after a print. Print quality metrics are not intended to be elaborate and perfect, but to serve as a general barometer for print feedback. Backtesting is done first and foremost to exclude scenarios where prints clearly don't work or work suboptimally, in which case they can't be considered as valid evidence. Even when print metrics indicate historical reactions of good quality, price impact can and inevitably does deviate from the expected. Past results do not guarantee future performance.
- Example charts
Chart #1: BTCUSDT
Chart #2: DXY
Chart #3: NQ futures
Chart #4: Crude oil futures
Chart #5: Custom timeframes
- Print confluence
Attributes that make prints ideal in one way or another are marked separately as print confluence, giving clue into potential strength and duration of print influence. Prints with important or multiple confluence factors can be considered as heavier and more reliable evidence of price being on a path of resistance. Users can choose which confluence to show/hide (by default all) and set a minimum amount of confluence for confluence text to activate (by default 1).
Confluence type #1: Trend extensions
Price trending for abnormally long time doesn't happen too often and requires effort to sustain. Prints taking place at extended trends often have a longer duration influence, indicating a potential larger scale topping/bottoming process being close. Trend extension confluence is indicated using a numbered label, equal to amount of bars price has been in a trending state.
Confluence type #2: Consecutive prints
Prints that take place consecutively imply heavier resistance ahead, as required conditions trigger multiple times within a short period. Consecutive prints tend to lead to more clean, aggressive and heavier magnitude reactions relative to prints with no confluence. Consecutive print confluence is indicated using a numbered label with an x in front, equal to amount of prints that have taken place consecutively.
Confluence type #3: Deviations
When price closes above/below prior print highs/lows and closes right back in with a print, odds are some market participants are stuck in an awkward position. When market participants are stuck, potential for a snowball effect of covering underwater positions is higher, driving price further away. Prints into deviations act similarly to consecutive prints, elevating potential for more aggressive reactions relative to prints with no confluence. Deviation confluence is indicated using a label with a curve symbol.
- Backtesting
Built-in backtesting is based on metrics that are considered to reasonably quantify expected behaviour of prints. Main purpose of the metrics is to form a general barometer for monitoring whether or not prints can be viewed as valid evidence. When prints are clearly not working optimally, one should adjust expectations accordingly or take action to improve print performance. To make any valid conclusions of print performance, sample size should also be significant enough to eliminate randomness effectively. If sample size on any individual chart is insufficient, one should view feedback scores on multiple correlating and comparable charts to make up for the loss.
For more elaborate backtesting, prints can be used in any other script that has a source input, including fully mechanic strategies utilizing Tradingview's native backtester. Print plots are created separately for regular prints and prints with each type of confluence.
Print feedback
Print feedback is monitored for 3 bars following a print. Feedback is considered to be 100% successful when all 3/3 bars show a supportive reaction. When 2/3 bars are supportive, feedback rate is 66%, 1/3 bars = 33% and 0/3 = 0%. After print backtesting period is finished, performance of given print is added to average calculations.
Metric #1 : Rate of change
Rate of change used for backtesting is based on OHLC4 average (open + high + low + close / 4) with a length of 3. Rate of change trending up is considered valid feedback for bullish liquidity prints, trending down for bearish liquidity prints. Note that trending rate of change does not always correlate with trending price, but sometimes simply means current trend in price is slowing down.
Metric #2 : Invalidation mark
Print invalidation marks are set at print low/high with a little bit of "wiggle room". Wiggle room applied is always 1/10th of print bar range. E.g. for a bullish print with bar range of 2%, invalidation mark is set to 0.20% below print low. For most prints this is practically at print low/high, but in the case of prints with high volatility a more noticeable excess is given, due to the expectation of greater adverse reaction without necessarily meaning invalidation. A low being above invalidation mark is considered valid feedback for bullish prints and a high being below invalidation mark for bearish prints.
Metric #3 : Peak increase/decrease
Unlike prior two metrics, peak increase/decrease is not feedback the same way, but rather an assisting factor to be viewed with feedback scores. Peak increase/decrease is measured from print close to highest high/lowest low during backtesting period and added to average calculations
Feedback scores
When liquidity prints are working optimally, quality threshold for both feedback metrics are met. By default, threshold is set to 66%, indicating valid feedback on 2/3 of backtesting periods on average. When threshold is met, a tick will appear next to feedback scores, otherwise an exclamation mark indicating suboptimal performance on either or both.
By default, the prints are filtered as little as possible, idea behind being that it is better to have more poor prints filtered with discretion/mechanically afterwards than potentially filtering too much from the get go. Sometimes filtering is insufficient, leading to failed reactions beyond a tolerable level. When this is the case, print sensitivity can be adjusted via input menu, separately for bullish and bearish prints. Print filter sensitivity ranges from 1 to 5, by default set to 1. Lower sensitivity sets looser criteria for print activation, higher sensitivity sets stricter criteria. For most charts and timeframes default sensitivity works just fine, but when this is not the case, filters can be tweaked in search of better settings. If feedback score threshold is met, it's better to keep filter sensitivity intact and use discretion, which is much more nuanced and capable than any mechanical process. If feedback scores are still insufficient after tweaking, depending on the severity of lack, prints should be vetted extra carefully using other means of analysis or simply avoided.
Verifying backtest calculations
Backtest metrics can be toggled on via input menu, separately for bullish and bearish prints. When toggled on, both cumulative and average counters used in print backtesting will appear on "Data Window" tab. Calculation states are shown at a point in time where cursor is hovered. E.g. when hovering cursor on 4th of January 2021, backtest calculations as they were during this date will be shown. Backtest calculations are updated after backtest period of a print has finished (3 bars). Assisting backtest visuals are also plotted on chart to ease inspection.
- Alerts
Available alerts are the following.
- Bullish/bearish liquidity print
- Bullish/bearish liquidity print with specified print confluence
- Bullish/bearish liquidity print with set minimum print confluence amount exceeded
- Visuals
Visual impact of prints can be managed by adjusting width and length via input menu. Length of prints is available in 3 modes (1-3 from shortest to longest) and width in 10 modes (1-10 from narrowest to widest).
Print confluence text can be embedded inside print nodes, eliminating visuals outside the chart.
Metric table is available in two themes, Classic and Stealth.
Metric table can be offsetted horizontally or vertically from any four corners of the chart, allowing space for tables from other scripts.
Table sizes, label sizes and colors are fully customizable via input menu.
-Practical guide
Key in maximizing success with prints is knowing when they are likely reliable and when not. In general, the more volatile and ranging the market regime, the better liquidity prints will work. Any type of volatile spike in price, parabola or a clean range is where liquidity prints provide optimal feedback. On the other hand low volatility and trending environments are suboptimal and tend to provide more mute/lagged or completely failed feedback. Anomalies such as market wide crashes are also environments where prints can't be expected to work reliably.
Being aware of events on multiple timeframes is crucial for establishing bias for any individual timeframe. Not often it makes sense to go against higher timeframe moves on lower timeframes and this principle of timeframe hierarchy also applies to prints. In other words, higher timeframe prints dictate likelihood of successful prints on lower timeframes. If hard way on a weekly chart is up, same likely applies to daily chart during weekly print influence time. In such scenarios, it's best to not swim in upstream and avoid contradicting lower timeframe prints, at least until clear evidence suggesting otherwise has developed.
Points in price where it anyway makes sense to favor one side over the other are key points of confluence for prints as well. Prints into clean range highs/lows with clean taps can be valuable for optimal entry timing. This is especially true if simultaneously previous pivot gets taken out, increasing odds of liquidity indicated by a print being swept stop-losses.
Prints that don't match underlying bias (e.g. bullish prints at range high, bearish prints at range low) should be avoided until clear evidence has developed favoring them, such as a convincing break through a level followed by a re-test.
Prints that are immediately rejected aggressively are more likely prints that end up failing. Next bar following a print closing below print lows/above print highs is a strong hint of print failure. To consider print still valid in such cases, there should be quick and clear defending of print lows/highs. Failed prints are an inevitable bummer, but never useless. Failed prints are ideal for future reference, as liquidity still likely exists there. Re-tests into these levels often provide sensible entries.
Stacked confluence doesn't come too often and is worth paying special attention to, as multiple benefitting factors are in place simultaneously.
From a more zoomed out perspective, any larger zone with multiple prints taking place inside are potential topping/bottoming processes taking place, also worth paying attention to.
GKD-B Stepped Baseline [Loxx]Giga Kaleidoscope GKD-B Stepped Baseline is a Baseline module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-B Stepped Baseline
This is a special implementation of GKD-B Baseline in that it allows the user to filter the selected moving average using the various types of volatility listed below. This additional filter allows the trader to identify longer trends that may be more confucive to a slow and steady trading style.
GKD Stepped Baseline includes 64 different moving averages:
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Ehlers Optimal Tracking Filter - EOTF
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Ehlers Optimal Tracking Filter - EOTF
The Elher's Optimum Tracking Filter quickly adjusts rapid shifts in the price and yet is relatively smooth when the price has a sideways action. The operation of this filter is similar to Kaufman’s Adaptive Moving
Average
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Kalman Filter
Kalman filter is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies. This means that the filter was originally designed to work with noisy data. Also, it is able to work with incomplete data. Another advantage is that it is designed for and applied in dynamic systems; our price chart belongs to such systems. This version is true to the original design of the trade-ready Kalman Filter where velocity is the triggering mechanism.
Kalman Filter is a more accurate smoothing/prediction algorithm than the moving average because it is adaptive: it accounts for estimation errors and tries to adjust its predictions from the information it learned in the previous stage. Theoretically, Kalman Filter consists of measurement and transition components.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and its smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
One More Moving Average (OMA)
The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
Volatility Goldie Locks Zone
This volatility filter is the standard first pass filter that is used for all NNFX systems despite the additional volatility/volume filter used in step 5. For this filter, price must fall into a range of maximum and minimum values calculated using multiples of volatility. Unlike the standard NNFX systems, this version of volatility filtering is separated from the core Baseline and uses it's own moving average with Loxx's Exotic Source Types. The green and red dots at the top of the chart denote whether a candle qualifies for a either or long or short respectively. The green and red triangles at the bottom of the chart denote whether the trigger has crossed up or down and qualifies inside the Goldie Locks zone. White coloring of the Goldie Locks Zone mean line is where volatility is too low to trade.
Volatility Types Included
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility .
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility . That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator consists of using the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e. it assumes that the underlying asset follows a GBM process with zero drift. Therefore the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis we usually use it to measure the level of current volatility .
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA , we can call it EMA deviation. And added to that, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, I used a manual recreation of the quantile function in Pine Script. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is widely used indicator in many occasions for technical analysis . It is calculated as the RMA of true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation ( SD ). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
For Pine Coders, this is equivalent of using ta.dev()
Additional features will be added in future releases.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average as shown on the chart above
Volatility/Volume: Hurst Exponent
Confirmation 1: Fisher Transform
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Outputs
Chained or Standalone: GKD-BT or GKC-V
Stack 1: GKD-C Continuation indicator
Stack 2: GKD-C Continuation indicator
