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.
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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.
Gabriel's Andean Oscillator📈 Gabriel's Andean Oscillator — Enhanced Trend-Momentum Hybrid
Gabriel's Andean Oscillator is a sophisticated trend-momentum indicator inspired by Alex Grover’s original Andean Oscillator concept. This enhanced version integrates multiple envelope types, smoothing options, and the ability to track volatility from both open/close and high/low dynamics—making it more responsive, adaptable, and visually intuitive.
🔍 What It Does
This oscillator measures bullish and bearish "energy" by calculating variance envelopes around price. Instead of traditional momentum formulas, it builds two exponential variance envelopes—one capturing the downside (bullish potential) and the other capturing the upside (bearish pressure). The result is a smoothed oscillator that reflects internal market tension and potential breakouts.
⚙️ Key Features
📐 Envelope Types:
Choose between:
"Regular" – Uses single EMA-based smoothing on open/close variance. Ideal for shorter timeframes.
"Double Smoothed" – Adds an extra layer of smoothing for noise reduction. Ideal for longer timeframes.
📊 Bullish & Bearish Components:
Bull = Measures potential upside using price lows (or open/close).
Bear = Measures downside pressure using highs (or open/close).
These can optionally be derived from high/low or open/close for flexible interpretation.
📏 Signal Line:
A customizable EMA of the dominant component to confirm momentum direction.
📉 Break Zone Area Plot:
An optional filled area showing when bull > bear or vice versa, useful for detecting expansion/contraction phases.
🟢 High/Low Overlay Option (Use Highs and Lows?):
Visualize secondary components derived from high/low prices to compare against the open/close dynamics and highlight volatility asymmetry.
🧠 How to Use It
Trend Confirmation:
When bull > bear and rising above signal → bullish bias.
When bear > bull and rising above signal → bearish bias.
Breakout Potential:
Watch the Break area plot (√(bull - bear)) for rapid expansion, signaling volatility bursts or directional moves.
High/Low Envelope Divergence:
Enabling the high/low comparison reveals hidden strength or weakness not visible in open/close alone.
🛠 Customizable Inputs
Envelope Type: Regular vs. Double Smoothed
EMA Envelope Lengths: For both regular and smoothed logic
Signal Length: Controls EMA smoothing for the signal
Use Highs and Lows?: Toggles second set of envelopes; the original doesn't include highs and lows.
Plot Breaks: Enables the filled “break” zone area, the squared difference between Open and Close.
🧪 Based On:
Andean Oscillator - Alpaca Markets
Licensed under CC BY-NC-SA 4.0
Developed by Gabriel, based on the work of Alex Grover
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.
LevelUp^ AlphaLevelUp 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
The Strat [LuxAlgo]The Strat indicator is a full toolkit regarding most of the concepts within "The Strat" methodology with features such as candle numbering, pivot machine gun (PMG) highlighting, custom combo highlighting, and various statistics included.
Alerts are also included for the detection of specific candle numbers, custom combos, and PMGs.
🔶 SETTINGS
Show Numbers on Chart: Shows candle numbering on the chart.
Style Candles: Style candles based on the detected number. Only effective on non-line charts and if the script is brought to the front.
🔹 Custom Combo Search
Combo: User defined combo to be searched by the script. Combos can be composed of any series of numbers including (1, 2, -2, 3), e.g : 2-21. No spaces or other characters should be used.
🔹 Pivot Machine Gun
Show Labels: Highlight detected PMGs with a label.
Min Sequence Length: Minimum sequence length of consecutive higher lows/lower highs required to detect a PMG.
Min Breaks: Minimum amount of broken previous highs/lows required to detect a PMG.
Show Levels: Show levels of the broken highs/lows.
🔹 Pivot Combos
Pivot Lookback: Lookback period used for detecting pivot points.
Right Bars Scan: Number of bars scanned to the right side of a detected pivot.
Left Bars Scan: Number of bars scanned to the left side of a detected pivot.
🔹 Dashboard
Show Dashboard: Displays statistics dashboard on chart.
Numbers Counter: Displays the numbers counter section on the dashboard.
Pivot Combos: Displays pivots combo section on the dashboard.
%: Display the percentage of detected pivot combos on the dashboard instead of absolute numbers.
Pivot Combos Rows: Number of rows displayed by the "Pivots Combo" dashboard section.
Show MTF: Showa MTF candle numbering on the dashboard.
Location: Location of the dashboard on the chart.
Size: Size of the displayed dashboard.
🔶 USAGE
This script allows users with an understanding of The Strat to quickly highlight elements such as candle numbers, pivot machine guns, and custom combos. The usage for these concepts is given in the sub-sections below.
🔹 Candle Numbers
The Strat assigns a number to individual candles, this number is determined by the current candle position relative to the precedent candle, these include:
Number 1 - Inside bar, occurs when the previous candle range engulfs the current one.
Number 2 Up - Upside Directional Bar, occurs when the current price high breaks the previous high while the current low is lower than the previous high.
Number 2 Down - Downside Directional Bar, occurs when the current price low breaks the previous low while the current high is higher than the previous low.
Number 3 - Outside bar, occurs when the current candle range engulfs the previous one.
The script can highlight the number of a candle by using labels but can also style candles by depending on the candle number. Inside bars (1) only have their candle wick highlighted, directional bars (2) (-2) only have their candle body highlighted. Outside bars have their candle range highlighted.
Note that downside directional bars are highlighted with the number -2.
Users can see the total amount of times a specific candle number is detected on the historical data on the dashboard available within the settings, as well as the number of times a candle number is detected relative to the total amount of detected candle numbers expressed as a percentage.
It is also possible to see the current candle numbers returned by multiple timeframes on the dashboard.
🔹 Searching For Custom Combos
Combos are made of a sequence of two or more candle numbers. These combos can highlight multiple reversals/continuation scenarios. Various common combos are documented by The Strat community.
This script allows users to search for custom combos by entering them on the Combo user setting field.
When a user combo is found, it is highlighted on the chart as a box highlighting the combo range.
🔹 Pivot Combos
It can be of interest to a user to display the combo associated with a pivot high/low. This script will highlight the location of pivot points on the chart and display its associated combo by default. These are based on the Pivot Combo lookback and not displayed in real-time.
Users can see on the dashboard the combos associated with a pivot high/low, these are ranked by frequency.
🔹 Pivot Machine Gun (PMG)
Pivot Machine Guns (PMG)s describe the scenario where a single price variation breaks the value of multiple past successive higher lows/lower highs. This can highlight a self-exciting behavior, where even more past successive higher lows/lower highs get broken.
Users can select the minimum sequence length of successive higher lows/lower highs required for a PMG to be detected, as well the amount of these successive higher lows/lower highs that must be broken.
Previous Day/Week High & Low + 50% w/ Alerts| by Octopu$
📈 Previous Day/Week High & Low + 50% w/ Alerts| by Octopu$
This Indicator includes Previous Day High and Low Levels and 50% (Half of High & Low)
As well as Previous Week High and Low Levels ((Half of High & Low))
And also Pre-Market Session High and Low.
All of them with Built-in alerts.
Can be used in any timeframe with any ticker.
(Using SPY 5m just as an example:)
www.tradingview.com
SPY
Features:
• D High: Green Top Line
• D Low: Red Bottom Line
• D 50%: White 50% Line
• Week High and Low: Blue Top and Bottom Lines
• Pre-Market and Afterhours Session: Gray Lines
• Labels for Identification
Options:
• Toggle on/off for Day High, Low and 50%
• Toggle on/off for DWeek High, Low and 50%
• Toggle on/off for PM and AH Sessions
• Show/Hide the Labels with names
• Show/Hide the Lines themselves
• Fully Customizable Style and Color
Alerts:
• Triggers for Day (above or below level)
• Triggers for Week (above or below level)
Notes:
v1.0
Release of the Indicator
Changes and updates can come in the future for additional functionalities or per requests.
Did you like it? Shoot me a message! I'd appreciate if you dropped by to say thanks.
- Octopu$
🐙
50% Retracement - Support & ResistanceRetracement refers to price reversal after reaching a recent high or low, finding an area of support or resistance, and then continuing in the direction of the bigger picture trend. The concept of 50% retracement is based on the work of W.D. Gann.
Gann was born in 1878 in Texas. Over his trading career, it's been stated he was one of the most successful traders who ever lived. With that said, there is no irrefutable proof he made great fortunes in the market. However, it's a fact that his trading ideas and principles are still in use today, many years after his death in 1955.
Gann believed there was a natural order that exists for everything in the universe, including the stock market. He theorized that price movements occurred in a manner that can be pre-determined based on historical precedent and the influence of mathematical equations and relationships. The end result was predictable movement of prices between areas of support and resistance.
The idea of 50% retracement is best explained in this quote from Gann:
"After an initial, sustained price move, either up or down, prices retrace to 50% of their initial move."
What's important here is the idea that retracement applies in both directions. When price is heading up, it may be approaching an area of resistance. When price is declining, it may be heading towards an area of support.
Continuation of the Trend
The primary reason we are interested to gauge levels of retracement is that once a retracement is complete, there is often a continuation of the previous trend. For example, if moving from a recent low to a new high, if price retraces 50%, at that point we look for a bounce and a continuation of the upward trend.
Retracement to Area of Support
When moving a recent low to a recent high, one can anticipate a price to move down 50% of the original move up.
For example, if a stock climbed from $50 to $100, a 50% retracement of the move from low to high would result in a price of $75. We now look for this $75 price area to be an area of support.
Retracement to Area of Resistance
Retracement is also applicable in the other direction. If price moves from a recent high to a new low and starts moving back up, look for price to regain 50% of the original move down. This retracement is often an area of resistance.
For example, if the recent high was $100 and price bounced off a low of $50, look for resistance near $75.
Additional Retracements - 33% and 66%
Gann also focused on other incremental retracements that he calculated based on various geometric angles believed to balance price and time. What I've found most helpful is to keep things simple and focus on no more than three retracements, 33% 50% and 66%.
Direction of Retracement
When moving from a recent low to a new high, the retracement will be downward. If multiple retracement percentages are shown, they will be smallest to largest going from the top to bottom.
When moving from a recent high to a new low, the retracement will be upward. If multiple retracement percentages are shown, they will be smallest to largest going from the bottom to top.
Retracement Versus Reversal
As described above, retracement refers to retracing a move back down towards a recent low after hitting a new high, or moving back up from a recent low towards a previous high.
The difference between a retracement and reversal is that the latter breaks the uptrend as shown in the chart that follows:
■ With retracements, the upward trendline acted as support of the upward trend.
■ With a reversal, the upward trendline was broken and the price continued to move down.
Additional Retracement Examples
Features
■ Choose up to three retracement levels: 33%, 50% and 66%.
■ Configure price and line color at each retracement level.
■ Show/hide retracements on intraday, daily, weekly and monthly.
■ Set preferred lookback count for Marked Highs/Lows.
■ Show Marked Highs/Lows as price or symbols.
■ Show lines of support and/or resistance.
EP/SL and ratio calculationExplanation of the indicator
The first question is - what is shown here at all. Generally, the indicator calculates order prices depending on the data found in the chart. The order is based on the lowest low (for a long) of the bounce and the high of the last candle. For a short it is based on the highest high and on the low of the last candle. There is no value for you, if you don’t do swing trading using trend lines on your chart.
All values shown are no financial advise - you are responsible for all your trades.
The indicator looks for the lowest low of the last days. How many days back to be searched can be configured in the settings. The lowest low is marked with the flag - the date and price is displayed there.
The high of the last candle is read out and based on this the entry price is calculated. On the green line are the EP percentages with which is calculated, the entry price and also the high of the last candle displayed.
On the line there is a green (or red) triangle, which indicates the trading direction. More about the direction can be found below in the settings.
Based on the lowest low (or in case of short the highest high) the stop loss is calculated. Also here the percentage and the price is given.
The lines labeled R1 to R5 are the prices of the respective ratios. The lines are 40 time units long (in the standard setting) and thus one can read off the ratio, which the trade would reach after approx. 8 weeks, over the trend lines and their intersection point at the end of the ratio lines.
The orange line marks the point at which we would be 10% above the entry price (or below the entry price for a short).
In general, the calculations are equivalent for short, the marker of the highest high is displayed.
The capital and the number of shares to be traded are not publicly displayed on the chart. The complete calculation is visible when you move the mouse over the text of the entry price.
In this small pop-up window you can see with which capital the calculation was done. The capital should be updated daily in the settings. Furthermore, you can see how many shares can be traded with this capital, taking into account the 1% portfolio risk. It is again the entry price and a proposal for a stop limit price (percentages also configurable) displayed. The price for the 3 ratio (take profit) and also the price for the stop loss can be read here. So actually everything that is necessary for the creation of the order.
Settings
The indicator now has a lot of settings and options. I have also built-in indicators such as EMA and JMA to have all the indicators necessary for me - with the free TV. Some things can also be changed under "Style", but I don't want to go into the things under "Style" here, just the basic settings.
Settings of the main indicator
With the checkmark at "Main Indicator" all lines etc. can be switched off without the other indicators (EMA, JMA) disappearing.
Capital:
Here you can set your daily capital (from paper trading or from the real money deposit). This is used to calculate the number of shares.
Search last bounce in last x candles:
Here you can influence how many candles the tool should look into the past to search for the lowest (long) or highest (short) candle. Default is 10, but sometimes shorter or longer periods make sense. It is also possible to tune a bit here and e.g. with "0" make the calculation of the SL based on the low/high of the last candle. Which low (long) or high (short) is taken, is always evident with the above described flag.
go back x candles for calculation:
If the calculation is not to be made on the basis of the last candle, but e.g. the one before last, this can be adjusted here. Everything is adapted with, thus e.g. also the Stochastic of this time is used for the direction. One can go back in time and reconstruct the calculation at that time.
EP percent:
Specifying how far the EP should be from the high (long)/low (short) of the last candle.
EP limit percent:
Specify how far the EP limit should be from the EP.
SL percent:
Specifying how far the SL should be from the lowest low (long)/highest high (short).
direction mode:
here is set in which way the indicator should be directed long or short. The stochastic used here has the settings 8-5-5. k is the blue line and d is the red line of this stochastic.
Stoch k>d = long automatic, blue line above the red line for long calculation
Stoch k<50% = long automatic, blue line below 50% for long calculation
long no automatic, always long calculation
short no automatic, always short calculation
ignore last candle if market is open:
Normally one calculates at closed market, thus on the finished candles. If you want to calculate with an open market or if you want to make sure that the indicator is not constantly running back and forth after the market has opened, you can automatically ignore the last candle (i.e. calculate on the second to last candle) if the market is open. If the market is closed, the last candle is always taken. If turned off, the last candle is always taken even if the market is open.
use close price for EP (instead of high/low):
You can adjust the EP calculation here to take the close price instead of the high/low of the last candle. This is not the usual strategy, but if there are long wicks/luns and you are quite sure with the trading direction, this can improve the ratio significantly.
Ratio lines length (bars):
The length of the lines. You can change here for 3M/6M trades to 80 time units.
Text color:
Color of the text (default is gray, this is kind of useful for white and black background).
Line color R-lines:
Color of the ratio lines (default is gray)
10% color:
Color of the 10% line (default orange)
Additional indicators settings
EMAs:
Here you can switch on/off all EMA lines
xx EMA Length:
Configuration of the individual EMA lines to be displayed. At 0 the line is switched off, colors are configured at the style.
JMA:
Here you can additionally display the JMA. Also its colors can be configured at Style.
JMA length:
JMA length, default 20, phase is fixed at 50 and power is fixed at 2.
Rabbit HoleHow deep is the Rabbit hole? Interesting experiment that finds the RISING HIGHS and FALLING LOWS and place the difference between the highs and lows into separate arrays.
== Calculations ==
In case current high is higher than previous high, we calculate the value by subtracting the current highest high with the previous High (lowest high) into array A,
same method for the lows just in Array B.
Since we subtract highs and lows it means velocity is taken into consideration with the plotting.
After adding a new value we remove the oldest value if the array is bigger than the Look back length. This is done for both lows and highs array.
Afterwards we sum up the lows and highs array (separately) and plot them separately, We can also smooth them a bit with Moving averages like HMA, JMA, KAMA and more.
== RULES ==
When High Lines crosses the Low Line we get a GREEN tunnel.
When Low Lines crosses the High line we get the RED tunnel.
The Greenish the stronger the up trend.
The Redish the stronger the downtrend.
== NOTES ==
Bars are not colored by default.
Better for higher time frames, 1 hour and above.
Enjoy and like if you like!
Follow up for new scripts: www.tradingview.com
TradeChartist Fib Master™TradeChartist Fib Master is a versatile Fibonacci Support and Resistance indicator that can be used to plot Automatic Levels and Fibonacci Levels based on a variety of ways from the settings, including Auto Fibs plot by connecting to an external indicator.
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What does ™TradeChartist Fib Master do?
Plots Automatic Levels without the need for user input
Plots 3 types of Fibonacci Levels
════ 1. Auto-Fibs (by connecting to an external indicator - Oscillatory or non-Oscillatory)
════ 2. Fibs based on Lookback (Lookback type - Candles or Days)
════ 3. Fibs based on Price Input
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Detailed description of ™TradeChartist Fib Master features
╔══ Automatic Levels Generator ══╗
Enabling Plot Automatic Levels plots support and resistance levels automatically without any input from the user other than preferred levels plot from the indicator settings namely,
Plot Local Levels for Lower TF - Plots all important Support/Resistance levels for mostly smaller time frames (can be used for up to 1hr in most cases). Recommended for Scalping/Swing Trading mostly dependent on volatility.
Plot Local Levels for Higher TF - Plots all important Support/Resistance levels inferred from mostly time frames - Short to Mid term outlook.
Plot Extended Levels for Higher TF - Plots all important Support/Resistance levels inferred from very higher time frames - Mid to Long term outlook.
Use Trading View Data Window to make effective use of the levels.
Tip: Add a duplicate Fib Master indicator to chart, use Automatic Levels Generator and increase transparency of Fib colours to 100. This helps view the levels on Data Window while having the Fib plots on chart.
Note: Uncheck Plot Automatic Levels to enable Fibonacci plots from Fibonacci Levels Generator
╔══ Fibonacci Levels Generator ══╗
════ 1. Auto-Fibs ════
Almost any indicator plot or Signal (Oscillatory or non-Oscillatory) can be connected to Fib Master to generate automatic fib levels. This is done by automatically detecting the price trend based on the connected indicator, its corresponding highest high and lowest low prices of each trend.
Also, Fib Master plots Bull (default - green) and Bear (default - red) Zones background including the signal candle (default - orange), where the trend changes based on the connected indicator Signal. This helps detect the effectiveness of the connected indicator Signal too, as too many unproductive signals from the connected indicator will create numerous Bull and Bear Zones (which also will render the Auto-Fibs ineffective).
To connect an external indicator Signal, just choose the corresponding Signal plot from the Plug Indicator Here dropdown from settings and choose whether the connected signal is Oscillatory (for Oscillators like RSI, CCI, MACD, Trend Identifier signals from more complex indicators like ™TradeChartist Bollinger Bands and Donchian Channels Pro etc.) or non-Oscillatory (for plots like Moving Averages, Super Trend, Ichimoku plots like Kijun Sen etc.)
If the connected Signal is Oscillatory, enter the filter levels. Default is 0 for both fields as most Oscillators have 0 as their mean reversal zone. For Oscillators like RSI, 60/40, 50/50, 55/45 etc. can be used.
Note: Please test the performance and effectiveness of Auto-Fibs of connected Signal first before using it for trades.
════ 2. Fibs based on Lookback ════
Lookback type - Candles
Determines the High and Low price of the user input number of Candles back (100 default) and plots Fibonacci Levels based on the calculated High and Low for the number of candles in the past from the current candle. The levels stay intact on any time frame as long as no new Highs or Lows are formed.
Lookback type - Days
Determines the High and Low price of the user input number of Days back (100 default) and plots Fibonacci Levels based on the calculated High and Low for the number of days in the past from the day of the current bar. The levels stay intact on any time frame as long as no new Highs or Lows are formed.
════ 3. Fibs based on Price Input ════
Plots Fibonacci Levels based on the user specified High and Low Price in the settings input fields. The levels stay intact on any time frame irrespective of new Highs or Lows being formed. Manual Price Input will enable the trader to keep the Levels intact and visually see the higher Fibonacci Retracement levels, when the price crosses beyond 100% retracement. On the other two lookback types, the Fibonacci levels are displayed only upto 100% retracement.
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Note: Show Auto-Fibs from current High/Low
When this option is chosen from indicator settings, the Auto-fib levels are drawn from the highest high of the trending price direction to lowest low of last trend for uptrend or vice-versa for downtrend.
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Extra Features
The Fibonacci levels can also be reversed by enabling Reverse Fibonacci Levels option from the settings.
0.886 and 1.113 Fib levels can be plotted on chart by enabling Show 0.886 and 1.113 Fibs from settings, as these are important levels for harmonic pattern traders.
Fib Line and Label Style including Color, transparency, size etc. can be changed from settings based on user preference.
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Example Charts
XAU-USD Gold Daily chart using Automatic Levels Generator with Zones identified when connected to external indicator
BTC-USDT Daily chart using Automatic Levels Generator
SPX 1hr chart using Automatic Levels Generator
ETH-USDT 1hr chart using AutoFibs generated by connecting Fib Master to RSI with 60/40 Filter levels
XAG-USD (Silver) 1hr chart using Fibonacci Levels based on lookback
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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This is not a free to use indicator. Get in touch with me (PM me directly if you would like trial access to test the indicator)
Premium Scripts - Trial access and Information
Trial access offered on all Premium scripts.
PM me directly to request trial access to the scripts or for more information.
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Master Pivots (CPR)This helps in monitoring the support and resistance of the current day and plan for tomorrow's support and resistance. The formula for creating the indicator is as below.
Pivot Point (P) = (High + Low + Close)/3
Support 1 (S1) = (P x 2) - High
Support 2 (S2) = P - (High - Low)
Resistance 1 (R1) = (P x 2) - Low
Resistance 2 (R2) = P + (High - Low)
Floor Pivots are one of the classic pivot ranges and helps us in trading based on pivot values. This indicator that I have built is also capable of predicting tomorrow's support and resistance up to 3 levels i.e. R1, R2, R3 and S1, S2 and S3. This is the only indicator available in trading view which does the same. Thats the only reason of making a separate indicator.
In this indicator we have also added some symbols to identify the reversal patterns based on candle. This is best if used in 15 min candle. This plots engulfing pattern, shooting star, hammer and bullish and bearish reversals.
Please use it and provide feedback for changes. If i would change anything it would be available automatically anyway.
I have not added Fibonacci Pivots as its generally available in many sites out of box. How ever if you want to code you can use the below formula.
Pivot Point (P) = (High + Low + Close)/3
Support 1 (S1) = P - {.382 * (High - Low)}
Support 2 (S2) = P - {.618 * (High - Low)}
Support 3 (S3) = P - {1 * (High - Low)}
Resistance 1 (R1) = P + {.382 * (High - Low)}
Resistance 2 (R2) = P + {.618 * (High - Low)}
Resistance 3 (R3) = P + {1 * (High - Low)}
RTH Standard Deviation+RTH Standard Deviation+ Indicator
Overview
The RTH Standard Deviation+ (RTH SD+) indicator is a versatile tool designed for traders to visualize key price levels based on the Regular Trading Hours (RTH) session.
It calculates and displays the high, low, equilibrium (midpoint), and standard deviation-based levels derived from the RTH session's price range.
This indicator is ideal for day traders and swing traders looking to identify potential support, resistance, and breakout zones.
Features
Customizable Session Window: Define the RTH session based on your preferred time window and timezone.
Key Price Levels: Displays high, low, equilibrium, 25%/75% quartile levels, and standard deviation levels (±0.5, ±1.0, ±1.33, ±1.66, ±2.0, and optional extended levels up to ±4.0).
Visual Elements: Includes horizontal lines, labels, boxes, and vertical lines to highlight key levels and session boundaries.
Flexible Styling: Customize line styles, colors, thicknesses, and visibility for all elements.
Extended Levels: Optional display of additional standard deviation levels (±2.25, ±2.33, ±2.5, ±2.66, ±2.75, ±3.0, ±3.25, ±3.33, ±3.5, ±3.66, ±3.75, ±4.0).
Deviation Boxes: Visualize specific standard deviation ranges (±0.1, ±1.33/1.66, ±2.33/2.66, ±3.33/3.66) with customizable colors.
Inputs
Session Window: Set the RTH session time (default: 06:00–09:00).
Timezone: Select the appropriate timezone (default: UTC-4).
Label Offset: Adjust the horizontal offset for price level labels (default: 5 bars).
Line Offset: Set the length of horizontal lines extending from the session end (default: 20 bars).
Show SD Levels: Toggle visibility of standard deviation lines (±0.5, ±1.0, ±1.33, ±1.66, ±2.0).
Show SD Labels: Enable or disable labels for standard deviation levels.
Show SD Boxes: Display shaded boxes for specific standard deviation ranges (e.g., ±1.33/1.66).
Show ±0.1 Dev Boxes: Highlight smaller deviation ranges (±0.1) with boxes.
Vertical Line: Toggle a vertical line at the session end, with customizable color, style, and thickness.
High/Low, Equilibrium, 25%/75%, ±0.1 Dev, ±1.33/1.66: Toggle visibility and customize colors, styles, and thicknesses for these levels.
Extended Levels: Enable additional standard deviation levels (e.g., ±2.25, ±2.5, etc.) for advanced analysis.
How It Works
Session Tracking: The indicator identifies the user-defined RTH session based on the specified time window and timezone.
It tracks the high, low, and equilibrium (midpoint) of the session's price action.
Price Range Calculation: At the session's end, the indicator calculates the price range (high - low) and uses it to compute standard deviation levels relative to the high, low, or equilibrium.
Level Visualization:
High/Low Lines: Display the session's high and low prices as horizontal lines, extended beyond the session end.
Equilibrium Line: Shows the midpoint of the session range.
Quartile Lines: Plots 25% and 75% levels within the session range.
Standard Deviation Lines: Displays levels at ±0.5, ±1.0, ±1.33, ±1.66, and ±2.0 standard deviations, with optional extended levels up to ±4.0.
Deviation Boxes: Shaded boxes highlight specific ranges (e.g., ±1.33/1.66) for quick reference.
±0.1 Deviation Lines/Boxes: Optional smaller deviation levels for precise analysis.
Dynamic Updates: During the session, high and low lines update in real-time. At session end, all levels are finalized and extended forward for post-session analysis.
Clearing Mechanism: When a new session begins, previous drawings are cleared to avoid clutter.
Usage
Add to Chart: Apply the indicator to your TradingView chart via the Pine Editor or Indicator menu.
Configure Settings:
Adjust the session window and timezone to match your market (e.g., 09:30–16:00 UTC-4 for US equities RTH).
Customize visibility, colors, styles, and thicknesses to suit your chart preferences.
Enable extended levels for deeper analysis or disable them for simplicity.
Interpret Levels:
High/Low: Act as potential support/resistance or breakout levels.
Equilibrium: Represents the session's midpoint, often a pivot point.
25%/75% Quartiles: Indicate intermediate levels within the session range.
Standard Deviation Levels: Highlight statistically significant price zones for potential reversals or breakouts.
Boxes: Emphasize key zones for quick visual reference.
Trading Application: Use levels to identify entry/exit points, set stop-losses, or gauge market volatility.
For example, ±1.0 standard deviation levels often act as strong support/resistance, while ±2.0 levels may indicate overextension.
Notes
Ensure the session window aligns with the market’s trading hours for accurate calculations.
The indicator is designed for intraday and post-session analysis but can be adapted for other timeframes.
Use in conjunction with other technical analysis tools for comprehensive decision-making.
Extended levels (±2.25 and beyond) are disabled by default to reduce chart clutter but can be enabled for specific strategies.
TradingView House Rules Compliance
This indicator contains no copyrighted material and adheres to TradingView’s Pine Script guidelines.
This indicator was approved and created with @TIMELESS1_
