Fractal Wave MarkerFractal Wave Marker is an indicator that processes relative extremes of fluctuating prices within 2 periodical aspects. The special labeling system detects and visually marks multi-scale turning points, letting you visualize fractal echoes within unfolding cycles dynamically.
What This Indicator Does
Identifies major and minor swing highs/lows based on adjustable period.
Uses Phi in power exponent to compute a higher-degree swing filter.
Labels of higher degree appear only after confirmed base swings — no phantom levels, no hindsight bias. What you see is what the market has validated.
Swing points unfold in a structured, alternating rhythm . No two consecutive pivots share the same hierarchical degree!
Inspired by the Fractal Market Hypothesis, this script visualizes the principle that market behavior repeats across time scales, revealing structured narrative of "random walk". This inherent sequencing ensures fractal consistency across timeframes. "Fractal echoes" demonstrate how smaller price swings can proportionally mirror larger ones in both structure and timing, allowing traders to anticipate movements by recursive patterns. Cycle Transitions highlight critical inflection points where minor pivots flip polarity such as a series of lower highs progress into higher highs—signaling the birth of a new macro trend. A dense dense clusters of swing points can indicate Liquidity Zones, acting as footprints of institutional accumulation or distribution where price action validates supply and demand imbalances.
Visualization of nested cycles within macro trend anchors - a main feature specifically designed for the chartists who prioritize working with complex wave oscillations their analysis.
Pesquisar nos scripts por "supply and demand"
Nef33-Volume Footprint ApproximationDescription of the "Volume Footprint Approximation" Indicator
Purpose
The "Volume Footprint Approximation" indicator is a tool designed to assist traders in analyzing market volume dynamics and anticipating potential trend changes in price. It is inspired by the concept of a volume footprint chart, which visualizes the distribution of trading volume across different price levels. However, since TradingView does not provide detailed intrabar data for all users, this indicator approximates the behavior of a footprint chart by using available volume and price data (open, close, volume) to classify volume as buy or sell, calculate volume delta, detect imbalances, and generate trend change signals.
The indicator is particularly useful for identifying areas of high buying or selling activity, imbalances between supply and demand, delta divergences, and potential reversal points in the market. It provides specific signals for bullish and bearish trend changes, making it suitable for traders looking to trade reversals or confirm trends.
How It Works
The indicator uses volume and price data from each candlestick to perform the following calculations:
Volume Classification:
Classifies the volume of each candlestick as "buy" or "sell" based on price movement:
If the closing price is higher than the opening price (close > open), the volume is classified as "buy."
If the closing price is lower than the opening price (close < open), the volume is classified as "sell."
If the closing price equals the opening price (close == open), it compares with the previous close to determine the direction:
If the current close is higher than the previous close, it is classified as "buy."
If the current close is lower than the previous close, it is classified as "sell."
If the current close equals the previous close, the classification from the previous bar is used.
Delta Calculation:
Calculates the volume delta as the difference between buy volume and sell volume (buyVolume - sellVolume).
A positive delta indicates more buy volume; a negative delta indicates more sell volume.
Imbalance Detection:
Identifies imbalances between buy and sell volume:
A buy imbalance occurs when buy volume exceeds sell volume by a defined percentage (default is 300%).
A sell imbalance occurs when sell volume exceeds buy volume by the same percentage.
Delta Divergence Detection:
Positive Delta Divergence: Occurs when the price is falling (for at least 2 bars) but the delta is increasing or becomes positive, indicating that buyers are entering despite the price decline.
Negative Delta Divergence: Occurs when the price is rising (for at least 2 bars) but the delta is decreasing or becomes negative, indicating that sellers are entering despite the price increase.
Trend Change Signals:
Bullish Signal (trendChangeBullish): Generated when the following conditions are met:
There is a positive delta divergence.
The delta has moved from a negative value (e.g., -500) to a positive value (e.g., +200) over the last 3 bars.
There is a buy imbalance.
The price is near a historical support level (approximated as the lowest low of the last 50 bars).
Bearish Signal (trendChangeBearish): Generated when the following conditions are met:
There is a negative delta divergence.
The delta has moved from a positive value (e.g., +500) to a negative value (e.g., -200) over the last 3 bars.
There is a sell imbalance.
The price is near a historical resistance level (approximated as the highest high of the last 50 bars).
Visual Elements
The indicator is displayed in a separate panel below the price chart (overlay=false) and includes the following elements:
Volume Histograms:
Buy Volume: Represented by a green histogram. Shows the volume classified as "buy."
Sell Volume: Represented by a red histogram. Shows the volume classified as "sell."
Note: The histograms overlap, and the last plotted histogram (red) takes visual precedence, meaning the sell volume may cover the buy volume if it is larger.
Delta Line:
Delta Volume: Represented by a blue line. Shows the difference between buy and sell volume.
A line above zero indicates more buy volume; a line below zero indicates more sell volume.
A dashed gray horizontal line marks the zero level for easier interpretation.
Imbalance Backgrounds:
Buy Imbalance: Light green background when buy volume exceeds sell volume by the defined percentage.
Sell Imbalance: Light red background when sell volume exceeds buy volume by the defined percentage.
Divergence Backgrounds:
Positive Delta Divergence: Lime green background when a positive delta divergence is detected.
Negative Delta Divergence: Fuchsia background when a negative delta divergence is detected.
Trend Change Signals:
Bullish Signal: Green label with the text "Bullish Trend Change" when the conditions for a bullish trend change are met.
Bearish Signal: Red label with the text "Bearish Trend Change" when the conditions for a bearish trend change are met.
Information Labels:
Below each bar, a label displays:
Total Vol: The total volume of the bar.
Delta: The delta volume value.
Alerts
The indicator generates the following alerts:
Positive Delta Divergence: "Positive Delta Divergence Detected! Price is falling, but delta is increasing."
Negative Delta Divergence: "Negative Delta Divergence Detected! Price is rising, but delta is decreasing."
Bullish Trend Change Signal: "Bullish Trend Change Signal! Positive Delta Divergence, Delta Rise, Buy Imbalance, and Near Support."
Bearish Trend Change Signal: "Bearish Trend Change Signal! Negative Delta Divergence, Delta Drop, Sell Imbalance, and Near Resistance."
These alerts can be configured in TradingView to receive real-time notifications.
Adjustable Parameters
The indicator allows customization of the following parameters:
Imbalance Threshold (%): The percentage required to detect an imbalance between buy and sell volume (default is 300%).
Lookback Period for Divergence: Number of bars to look back for detecting price and delta trends (default is 2 bars).
Support/Resistance Lookback Period: Number of bars to look back for identifying historical support and resistance levels (default is 50 bars).
Delta High Threshold (Bearish): Minimum delta value 2 bars ago for the bearish signal (default is +500).
Delta Low Threshold (Bearish): Maximum delta value in the current bar for the bearish signal (default is -200).
Delta Low Threshold (Bullish): Maximum delta value 2 bars ago for the bullish signal (default is -500).
Delta High Threshold (Bullish): Minimum delta value in the current bar for the bullish signal (default is +200).
Practical Use
The indicator is useful for the following purposes:
Identifying Trend Changes:
The trend change signals (trendChangeBullish and trendChangeBearish) indicate potential price reversals. For example, a bullish signal near a support level may be an opportunity to enter a long position.
Detecting Divergences:
Delta divergences (positive and negative) can anticipate trend changes by showing a disagreement between price movement and underlying buying/selling pressure.
Finding Key Levels:
Imbalances (green and red backgrounds) often coincide with support and resistance levels, helping to identify areas where the market might react.
Confirming Trends:
A consistently positive delta in an uptrend or a negative delta in a downtrend can confirm the strength of the trend.
Identifying Failed Auctions:
Although not detected automatically, you can manually identify failed auctions by observing a price move to new highs/lows with decreasing volume in the direction of the move.
Limitations
Intrabar Data: It does not use detailed intrabar data, making it less precise than a native footprint chart.
Approximations: Volume classification and support/resistance detection are approximations, which may lead to false signals.
Volume Dependency: It requires reliable volume data, so it may be less effective on assets with inaccurate volume data (e.g., some forex pairs).
False Signals: Divergences and imbalances do not always indicate a trend change, especially in strongly trending markets.
Recommendations
Combine with Other Indicators: Use tools like RSI, MACD, support/resistance levels, or candlestick patterns to confirm signals.
Trade on Higher Timeframes: Signals are more reliable on higher timeframes like 1-hour or 4-hour charts.
Perform Backtesting: Evaluate the indicator's accuracy on historical data to adjust parameters and improve effectiveness.
Adjust Parameters: Modify thresholds (e.g., imbalanceThreshold or supportResistanceLookback) based on the asset and timeframe you are trading.
Conclusion
The "Volume Footprint Approximation" indicator is a powerful tool for analyzing volume dynamics and anticipating price trend changes. By classifying volume, calculating delta, detecting imbalances and divergences, and generating trend change signals, it provides traders with valuable insights into market buying and selling pressure. While it has limitations due to the lack of intrabar data, it can be highly effective when used in combination with other technical analysis tools and on assets with reliable volume data.
Fib BB on VWMA*ATRThis TradingView Pine Script is designed to plot Fibonacci Bollinger Bands on a Volume Weighted Moving Average (VWMA) using the Average True Range (ATR). The script takes a higher timeframe (HTF) approach, allowing traders to analyze price action and volatility from a broader market perspective.
🔹 How It Works
Higher Timeframe Data Integration
Users can select a specific timeframe to calculate the VWMA and ATR.
This allows for a more macro perspective, avoiding the noise of lower timeframes.
Volume Weighted Moving Average (VWMA)
Unlike the Simple Moving Average (SMA), VWMA gives higher weight to price movements with larger volume.
Calculation Formula:
𝑉𝑊𝑀𝐴=∑(𝐶𝑙𝑜𝑠𝑒×𝑉𝑜𝑙𝑢𝑚𝑒) / ∑𝑉𝑜𝑙𝑢𝑚𝑒
Since VWMA accounts for volume, it is more reactive to price zones with high buying or selling activity, making it useful for identifying liquidity zones.
ATR-Based Fibonacci Bollinger Bands
The Average True Range (ATR) is used to measure market volatility.
Instead of standard deviation-based Bollinger Bands, Fibonacci multipliers (2.618, 3.0, 3.414) are applied to ATR.
These bands adjust dynamically with market volatility.
🔹 Key Findings from Exploration
Through testing and analysis, this indicator seems to effectively detect supply and demand zones, particularly at the Fibonacci levels of 2.618 to 3.414.
Price frequently reacts at these bands, indicating that they capture key liquidity zones.
Potential Order Block Detection:
The ends of the Fibonacci Bollinger Bands (especially at 2.618, 3.0, and 3.414) tend to align with order blocks—areas where institutional traders previously accumulated or distributed positions.
This is particularly useful for order flow traders who focus on unfilled institutional orders.
🔹 How to Use This Indicator?
Identifying Order Blocks
When price reaches the upper or lower bands, check if there was a strong reaction (rejection or consolidation).
If price rapidly moves away from a band, that level might be an order block.
Spotting Liquidity Pools
VWMA’s nature enhances liquidity detection since it emphasizes high-volume price action.
If a price level repeatedly touches the band without breaking through, it suggests institutional orders may be absorbing liquidity there.
Trend Confirmation
If VWMA is trending upwards and price keeps rejecting the lower bands, it confirms a strong bullish trend.
Conversely, constant rejection from the upper bands suggests a bearish market.
This script is designed for open-source publication and offers traders a refined approach to detecting order blocks and liquidity zones using Fibonacci-based volatility bands.
📌 한글 설명 (상세 설명)
이 트레이딩뷰 파인스크립트는 거래량 가중 이동평균(VWMA)과 평균 실제 범위(ATR)를 활용하여 피보나치 볼린저 밴드를 표시하는 지표입니다.
또한, 고차 타임프레임(HTF) 데이터를 활용하여 시장의 큰 흐름을 분석할 수 있도록 설계되었습니다.
🔹 지표 작동 방식
고차 타임프레임(HTF) 데이터 적용
사용자가 원하는 타임프레임을 선택하여 VWMA와 ATR을 계산할 수 있습니다.
이를 통해 더 큰 시장 흐름을 분석할 수 있으며, 저타임프레임의 노이즈를 줄일 수 있습니다.
거래량 가중 이동평균(VWMA) 적용
VWMA는 단순 이동평균(SMA)보다 거래량이 많은 가격 움직임에 더 큰 가중치를 부여합니다.
계산 공식:
𝑉𝑊𝑀𝐴=∑(𝐶𝑙𝑜𝑠𝑒×𝑉𝑜𝑙𝑢𝑚𝑒) / ∑𝑉𝑜𝑙𝑢𝑚𝑒
거래량이 많이 발생한 가격 구간을 강조하는 특성이 있어, 시장의 유동성 구간을 더 정확히 포착할 수 있습니다.
ATR 기반 피보나치 볼린저 밴드 생성
ATR(Average True Range)를 활용하여 변동성을 측정합니다.
기존의 표준편차 기반 볼린저 밴드 대신, 피보나치 계수(2.618, 3.0, 3.414)를 ATR에 곱하여 밴드를 생성합니다.
이 밴드는 시장 변동성에 따라 유동적으로 조정됩니다.
🔹 탐구 결과: 매물대 및 오더블록 감지
테스트를 통해 Fibonacci 2.618 ~ 3.414 구간에서 매물대 및 오더블록을 포착하는 경향이 있음을 확인했습니다.
가격이 피보나치 밴드(특히 2.618, 3.0, 3.414)에 닿을 때 반응하는 경우가 많음
VWMA의 특성을 통해 오더블록을 감지할 가능성이 높음
🔹 오더블록(Order Block) 감지 원리
Fibonacci 밴드 끄트머리(2.618 ~ 3.414)에서 가격이 강하게 반응
이 영역에서 가격이 강하게 튀어 오르거나(매수 압력) 급락하는(매도 압력) 경우,
→ 기관들이 포지션을 청산하거나 추가 매집하는 구간일 가능성이 큼.
과거에 대량 주문이 체결된 가격 구간(= 오더블록)일 수 있음.
VWMA를 통한 유동성 감지
VWMA는 거래량이 집중된 가격을 기준으로 이동하기 때문에, 기관 주문이 많이 들어온 가격대를 강조하는 특징이 있음.
따라서 VWMA와 피보나치 밴드가 만나는 지점은 유동성이 높은 핵심 구간이 될 가능성이 큼.
매물대 및 청산 구간 분석
가격이 밴드에 도달했을 때 강한 반등이 나오는지를 확인 → 오더블록 가능성
가격이 밴드를 여러 번 테스트하면서 돌파하지 못한다면, 해당 지점은 강한 매물대일 가능성
🔹 활용 방법
✅ 오더블록 감지:
가격이 밴드(2.618~3.414)에 닿고 강하게 튕긴다면, 오더블록 가능성
해당 지점에서 거래량 증가 및 강한 반등 발생 시 매수 고려
✅ 유동성 풀 확인:
VWMA와 피보나치 밴드가 만나는 구간에서 반복적으로 거래량이 터진다면, 해당 지점은 기관 유동성 구간일 가능성
✅ 추세 확인:
VWMA가 상승하고 가격이 밴드 하단(지지선)에서 튕긴다면 강한 상승 추세
VWMA가 하락하고 가격이 밴드 상단(저항선)에서 거부당하면 하락 추세 지속
VSA Volume + Fibonacci (Volunacci)Overview
This indicator combines Volume Spread Analysis (VSA) with Fibonacci levels to identify key price zones based on volume behavior. It helps traders determine potential support and resistance levels influenced by volume strength.
How It Works
Volume Calculation
The indicator calculates volume levels based on the selected timeframe.
It identifies high volume spikes and low volume dips, which are critical for detecting supply and demand shifts.
It uses a simple moving average (SMA) of volume to smooth fluctuations.
Fibonacci Levels Integration
When a high-volume event is detected, the indicator records the highest high and lowest low of that candle.
It then plots Fibonacci retracement and extension levels to highlight potential price reaction zones.
Negative Fibonacci levels are included to identify possible deep retracements.
Visual Features
The indicator adapts to both light and dark themes for better visibility.
Fibonacci lines are color-coded based on key retracement and extension levels.
A table displaying key Fibonacci levels and their corresponding prices is provided for quick reference.
Why Is This Indicator Useful?
It helps traders spot accumulation and distribution phases by analyzing volume at key price points.
The combination of VSA and Fibonacci allows traders to confirm trend strength and identify potential reversal points.
Works well for trend-following strategies, scalping, and breakout trading.
How to Use This Indicator?
Use it to confirm breakouts or reversals at Fibonacci levels when volume supports the move.
Watch for high-volume spikes near key Fibonacci zones—these can signal strong trend continuation or reversal.
Use the displayed Fibonacci table to quickly assess price reaction levels.
Credits
This script was inspired by the Hidden Gap’s VSA Volume indicator by HPotter and has been enhanced by integrating Fibonacci-based analysis.
Rally Base Drop SND Pivots [LuxAlgo]The Rally Base Drop SND Pivots indicator uses "Rally", "Base", and "Drop" Candles to determine pivot points at which supply and demand (SND) levels are drawn.
🔶 USAGE
Rally, Base, and Drop (RBD) candles create a formula for seeing market structure through a fixed methodology. We are able to use this concept to point out pivot areas where Rallies and Drops directly meet.
The RBD SND Pivots are similar to traditionally identified "fractal" pivot points, with one key difference.
RBD SND Pivots detect a specific number of Rally and Drop candles directly back-to-back, requiring one side of the pivot to contain entirely green candles and the other to be entirely red candles or vice versa.
Since these pivot levels are based on Rally, Base, and Drop candles, the method directly implements rigid logic to further structure a trading system when utilizing these pivot levels with traditional SND concepts.
Furthermore, by implementing this logic when looking for pivots, a significant portion of potential noise is naturally filtered out.
🔶 DETAILS
In typical SND systems, the term "Base" is used for multiple meanings.
In this indicator, the base is a product of a pivot being formed. Once a Pivot is identified, the "Base" is marked as the first Rally or Drop of the second half of the pivot formation.
Once the pivot is identified, the high or low of the base candle is used to measure the pivot level.
🔶 SETTINGS
Length: Sets the number of Rally and Drop Candles that the script will require to identify pivots.
Ex. "3" = 3 Rally followed by 3 Drop
Historical Lookback: Hides historic levels based on a bar # Lookback from the current bar.
When set to 0, all Levels will display. (0 by default)
Liquidity Depth [AlgoAlpha]OVERVIEW
This script visualizes market liquidity by identifying key price levels where significant volume has transacted. It highlights zones of high buying and selling interest, helping traders understand where liquidity is accumulating and how price may respond to these areas. By dynamically tracking volume at highs and lows, the script builds a real-time liquidity profile, making it a powerful tool for identifying potential support and resistance levels.
CONCEPTS
Liquidity depth analysis helps traders determine how price interacts with supply and demand at different levels. The script processes historical volume data to distinguish between high-liquidity and low-liquidity zones. It assigns transparency levels to plotted lines , ensuring that more relevant liquidity areas stand out visually. The script adds a profile to show the depth of liquidity (derived from historical volume data) for levels above and below the current price
FEATURES
Liquidity Levels: Tracks liquidity levels based on volume concentration at price high and lows.
Volume-Based Transparency: More significant liquidity levels are displayed with higher visibility, showing their significance.
Interpolation: interpolates the bullish and bearish liquidity depth at a user defined range away from the price, helping in comparing the liquidity amounts between bullish and bearish.
Depth Profile: Allows traders to visualize depth of liquidity in a more quantitative and clearer way than the liquidity levels/list]
USAGE
This indicator is best used to track liquidity levels and potential price reaction areas. Traders can adjust the Liquidity Lookback setting to analyze past liquidity levels over different historical periods. The Profile Resolution setting controls the granularity of liquidity depth visualization, with higher values providing more detail. The script can be applied across different timeframes, from intraday scalping to swing trading analysis. The plotted liquidity zones provide traders with insights into where price may encounter strong support, resistance, or potential liquidity-driven reversals.
2:30 [LuciTech]this is a technical analysis tool designed to highlight key price levels and patterns during a specific trading window, based on UK time (Europe/London). It overlays visual elements on the chart, including a 12 PM reference line, Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL) levels, a highlighted 2:30 PM candle, and Engulfing Fair Value Gaps (FVGs). This indicator is intended for traders who focus on intraday price action and liquidity zones.
Features
The 12 PM Line displays a vertical line at 12:00 PM (UK time) to mark the start of the session. It’s customizable, allowing you to enable or disable it and adjust its color.
BSL/SSL Lines track the highest high (BSL) and lowest low (SSL) from 12:00 PM to 2:00 PM (UK time). These lines extend horizontally until 3:30 PM, after which they remain static at their last recorded levels. You can customize them by enabling or disabling visibility, adjusting colors, choosing a line style (solid, dashed, or dotted), and setting the width.
The 2:30 PM Candle highlights the candle at 2:30 PM (UK time) with a distinct color. It’s customizable, with options to enable or disable it and change its color.
Engulfing FVG (Fair Value Gap) identifies bullish and bearish engulfing patterns with a gap from the prior candle’s range. It draws a shaded box over the FVG area, and you can customize it by enabling or disabling it and adjusting the box color.
How It Works
The indicator operates within a session starting at 12:00 PM (UK time). BSL/SSL levels update between 12:00 PM and 2:00 PM, with lines extending until 3:30 PM. After 3:30 PM, these lines freeze.
BSL/SSL lines show the highest price (BSL) and lowest price (SSL) reached during the 12:00 PM to 2:00 PM window. After 3:30 PM, they remain static, marking the final range boundaries.
The 2:30 PM candle emphasizes a key timestamp, often of interest to intraday traders.
Engulfing FVGs detect significant price gaps created by engulfing candles, which may indicate potential reversal or continuation zones.
Settings
12 PM Line Settings let you toggle visibility and set the line color.
BSL/SSL Line Settings allow you to toggle visibility, set BSL and SSL colors, choose a line style (Solid, Dashed, Dotted), and adjust width (1-4).
2:30 Candle Settings let you toggle visibility and set the candle color.
Engulfing FVG Settings allow you to toggle visibility and set the box color.
Interpretation
The 12 PM Line serves as a reference for the session start.
BSL/SSL Lines may act as potential support or resistance zones or highlight liquidity areas. After 3:30 PM, they remain static, showing the session’s final range.
The 2:30 PM Candle can be monitored for price action signals, such as reversals or breakouts.
Engulfing FVGs shaded areas may indicate imbalances in supply and demand, useful for identifying trade opportunities or stop-loss placement.
Notes
The timezone is set to Europe/London (UK time). Ensure your chart’s timezone aligns for accurate results.
This indicator is best used on intraday timeframes, such as 1-minute or 5-minute charts.
It provides visual aids for analysis and does not generate buy or sell signals on its own.
Window Seasonality IndicatorThis is a time window seasonal returns indicator. That is, it will provide the mean returns for a given time window based on a given number of lookbacks set by the user. The script finds matching time windows, e.g., 1st week of March going back 5 years or 9:00-10:00 window of every day going 50 days, and then calculates an average return for that window close price with respect to the close price in the immediately preceding time window, e.g. last week of February or 8:00-9:00 close price, respectively.
There are 4 input options:
1) Historical Periods to Average: Set the number of matching historical windows with which to calculate an average price. The max is 730 lookback windows. Note: for monthly or weekly windows, setting too large a number will cause the script to error out.
2) Use Open Price: calculates the seasonal returns using the open price rather than close price.
3) Show Bands: select from 1 Gaussian standard deviation or a nonparamateric ranked confidence interval. As a rough heuristic, the Gaussian band requires at least 30 lookback periods, and the ranked confidence interval requires 50 or more.
4) Upper Percentile: set the upper cutoff for ranked confidence interval.
5) Lower Percentile: set the lower cutoff for ranked confidence interval.
Please be aware, this indicator does not use rigorous statistical methodology and does not imply predictive power. You'll notice the range bands are very wide. Do not trade solely based on this indicator! Certain time windows, such as weekly and monthly, will make more sense applied to commodities, where annual cycles play a role in its supply and demand dynamics. Hourly windows are more useful in looking at equities markets. I like to look at equities with 1-hr windows to see if there is some pattern to overnight behavior or for market open and close.
Naive Bayes Candlestick Pattern Classifier v1.1 BETAAn intermezzo on why i made this script publication..
A : Candlestick Pattern took hours to backtest, why not using Machine Learning techniques?
B : Machine Learning, no that's gonna be really heavy bro!
A : Not really, because we use Naive Bayes.
B : The simplest, yet powerful machine learning algorithm to separate (a.k.a classify) multivariate data.
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Hello, everyone!
After deep research in extracting meaningful information from the market, I ended up building this powerful machine learning indicator based on the evolution of Bayesian Statistics. This indicator not only leverages the simplicity of Naive Bayes but also extends its application to candlestick pattern analysis, making it an invaluable tool for traders who are looking to enhance their technical analysis without spending countless hours manually backtesting each pattern on each market!.
What most interesting part is actually after learning all of likely useless methods like fibonacci, supply and demand, volume profile, etc. We always ended up back to basic like support and resistance and candlestick patterns, but with a slight twist on strategy algorithm design and statistical approach. Thus, the only reason why i made this, because i exactly know that you guys will ended up in this position as time goes by.
The essence of this indicator lies in its ability to automate the recognition and statistical evaluation of various candlestick patterns. Traditionally, traders have relied on visual inspection and manual backtesting to determine the effectiveness of patterns like Bullish Engulfing, Bearish Engulfing, Harami variations, Hammer formations, and even more complex multi-candle patterns such as Three White Soldiers, Three Black Crows, Dark Cloud Cover, and Piercing Pattern. However, these conventional methods are both time-consuming and prone to subjective bias.
To address these challenges, I employed Naive Bayes—a probabilistic classifier that, despite its simplicity, offers robust performance in various domains. Naive Bayes assumes that each feature is independent of the others given the class label, which, although a strong assumption, works remarkably well in practice, especially when the dataset is large like market data and the feature space is high-dimensional. In our case, each candlestick pattern acts as a feature that can be statistically evaluated based on its historical performance. The indicator calculates a probability that a given pattern will lead to a price reversal, by comparing the pattern’s close price to the highest or lowest price achieved in a lookahead window.
One of the standout features of this script is its flexibility. Each candlestick pattern is not only coded into the system but also comes with individual toggles to enable or disable them based on your trading strategy. This means you can choose to focus on single-candle patterns like Bullish Engulfing or more complex multi-candle formations such as Three White Soldiers, without modifying the core code. The built-in customization options allow you to adjust colors and labels for each pattern, giving you the freedom to tailor the visual output to your preference. This level of customization ensures that the indicator integrates seamlessly into your existing TradingView setup.
Moreover, the indicator isn’t just about pattern recognition—it also incorporates outcome-based learning. Every time a pattern is detected, it looks ahead a predefined number of bars to evaluate if the expected reversal actually materialized. This outcome is then stored in arrays, and over time, the script dynamically calculates the probability of success for each pattern. These probabilities are presented in a real-time updating table on your chart, which shows not only the percentage probability but also the count of historical occurrences. With this information at your fingertips, you can quickly gauge the reliability of each pattern in your chosen market and timeframe.
Another significant advantage of this approach is its speed and efficiency. While more complex machine learning models like neural networks might require heavy computational resources and longer training times, the Naive Bayes classifier in this script is lightweight, instantaneous and can be updated on the fly with each new bar. This real-time capability is essential for modern traders who need to make quick decisions in fast-paced markets.
Furthermore, by automating the process of backtesting, the indicator frees up your time to focus on other aspects of trading strategy development. Instead of manually analyzing hundreds or even thousands of candles, you can rely on the statistical power of Naive Bayes to provide you with insights on which patterns are most likely to result in profitable moves. This not only enhances your efficiency but also helps to eliminate the cognitive biases that often plague manual analysis.
In summary, this indicator represents a fusion of traditional candlestick analysis with modern machine learning techniques. It harnesses the simplicity and effectiveness of Naive Bayes to deliver a dynamic, real-time evaluation of various candlestick patterns. Whether you are a seasoned trader looking to refine your technical analysis or a beginner eager to understand market dynamics, this tool offers a powerful, customizable, and efficient solution. Welcome to a new era where advanced statistical methods meet practical trading insights—happy trading and may your patterns always be in your favor!
Note : On this current released beta version, you must manually adjust reversal percentage move based on each market. Further updates may include automated best range detection and probability.
Order Blocks with Volume Heatmap & Clusters - VK TradingOrder Blocks with Volume Heatmap & Clusters - VK Trading
This script is designed to identify and highlight Order Blocks, a key concept in institutional trading, and combines it with powerful tools like volume heatmaps and accumulation clusters for enhanced market analysis. Suitable for traders of all experience levels, this script provides a clear and customizable visualization to help identify significant market zones effectively.
What Does This Script Do?
Order Block Identification: Highlights bullish and bearish order blocks directly on the chart, making it easier to spot key supply and demand zones.
Volume Heatmap: A dynamic heatmap adjusts colors based on relative volume, allowing you to quickly identify areas of heightened activity.
Institutional Accumulation Clusters: Zones of potential institutional accumulation are calculated using a combination of ATR (Average True Range), standardized volume, and RSI (Relative Strength Index).
Automatic Clearing: Invalidated order blocks are automatically removed, ensuring your charts remain clean and focused.
Key Features
Customizable Sensitivity: Adjust the script’s sensitivity to tailor order block detection to different market conditions and strategies.
Advanced Volume Display Options: Toggle volume visibility on or off. Customize the position, size, and color of volume labels for better integration with your chart's design.
Dynamic Heatmap Intensity: Fine-tune the heatmap’s intensity and color to highlight areas of interest based on trading volume.
Dual Order Block Detection: Uses two independent detection settings to analyze the market from multiple perspectives.
Visual Alerts: Automatically draws key level lines based on detected order blocks for better clarity.
User Benefits:
Clear Market Analysis: Helps pinpoint institutional activity and key levels with minimal effort.
Increased Efficiency: Automates plotting and analysis, allowing you to focus on decision-making.
Versatile Compatibility: Complements strategies like Smart Money Concepts, Wyckoff, and Price Action approaches.
Disclaimer
This script is intended as an analytical and educational tool. It does not guarantee specific outcomes or eliminate trading risks. Use this tool at your own discretion and always practice proper risk management.
Rolling Angled Volume Profile [Trendoscope®]🎲 Volume Profile Indicators
🎯Traditional Volume Profile
Volume profile indicators visually represent the distribution of volume across price levels. These indicators typically operate on horizontal price levels, making them effective in identifying supply and demand zones in ranging markets. However, they are less useful in trending markets where price movements follow a slope.
🎯The Need for Angled Volume Profiles
Just as support and resistance levels differ from trendlines, volume profile indicators require an equivalent method to account for volume distribution along a sloped trajectory. This would enable more accurate volume analysis in trending markets.
We identified the need of Angled Volume profile and have already published few indicators that implements the concept.
Angled Volume Profile calculates volume distribution along a slope. Users interact with the indicator by selecting the starting point, after which the volume profile is calculated for the selected trajectory.
Volume Forks is another tool that extends angled volume profile analysis, aligning volume profiles along the trajectory of pitchforks.
🎲 Rolling Volume Profile Indicator
The Rolling Volume Profile offers a new approach to angled volume profile calculations, addressing some limitations of earlier implementations:
🎯 Rolling Calculation
The volume profile is calculated for the last N bars of the instrument
The slope of the profile lines is determined by the closing prices of the starting and ending bars
Profiles are drawn in the direction of price movement between the start and end bars.
🎯 Dynamic Updates
As new bars are added, the calculations are updated, and the profile is redrawn based on the latest data.
This dynamic behavior earns it the name "Rolling Volume Profile."
🎯 Advantages Over Earlier Versions
Unlimited Profile Lines : Unlike previous implementations limited to 500 profile lines, this indicator uses polyline objects, overcoming the restriction.
Live Updates : Previous angled volume profile tools lacked real-time updates when new bars appeared. This limitation is resolved in the Rolling Volume Profile Indicator.
The Rolling Volume Profile provides an efficient and scalable solution for analyzing volume in trending markets.
🎯 Indicator Settings
Simple settings include few customisable options
Up Gap Strategy with DelayThis strategy, titled “Up Gap Strategy with Delay,” is based on identifying up gaps in the price action of an asset. A gap is defined as the percentage difference between the current bar’s open price and the previous bar’s close price. The strategy triggers a long position if the gap exceeds a user-defined threshold and includes a delay period before entering the position. After entering, the position is held for a set number of periods before being closed.
Key Features:
1. Gap Threshold: The strategy defines an up gap when the gap size exceeds a specified threshold (in percentage terms). The gap threshold is an input parameter that allows customization based on the user’s preference.
2. Delay Period: After the gap occurs, the strategy waits for a delay period before initiating a long position. This delay can help mitigate any short-term volatility that might occur immediately after the gap.
3. Holding Period: Once the position is entered, it is held for a user-defined number of periods (holdingPeriods). This is to capture the potential post-gap trend continuation, as gaps often indicate strong directional momentum.
4. Gap Plotting: The strategy visually plots up gaps on the chart by placing a green label beneath the bar where the gap condition is met. Additionally, the background color turns green to highlight up-gap occurrences.
5. Exit Condition: The position is exited after the defined holding period. The strategy ensures that the position is closed after this time, regardless of whether the price is in profit or loss.
Scientific Background:
The gap theory has been widely studied in financial literature and is based on the premise that gaps in price often represent areas of significant support or resistance. According to research by Kaufman (2002), gaps in price action can be indicators of future price direction, particularly when they occur after a period of consolidation or a trend reversal. Moreover, Gaps and their Implications in Technical Analysis (Murphy, 1999) highlights that gaps can reflect imbalances between supply and demand, leading to high momentum and potential price continuation or reversal.
In trading strategies, utilizing gaps with specific conditions, such as delay and holding periods, can enhance the ability to capture significant price moves. The strategy’s delay period helps avoid potential market noise immediately after the gap, while the holding period seeks to capitalize on the price continuation that often follows gap formation.
This methodology aligns with momentum-based strategies, which rely on the persistence of trends in financial markets. Several studies, including Jegadeesh & Titman (1993), have documented the existence of momentum effects in stock prices, where past price movements can be predictive of future returns.
Conclusion:
This strategy incorporates gap detection and momentum principles, supported by empirical research in technical analysis, to attempt to capitalize on price movements following significant gaps. By waiting for a delay period and holding the position for a specified time, it aims to mitigate the risk associated with early volatility while maximizing the potential for sustained price moves.
Order Blocks - VK TradingOrder Blocks - VK Trading
This script in Pine Script identifies and highlights Order Blocks, key tools in institutional trading. Designed for traders of all levels, it provides clear and customizable visualization, helping you anticipate market movements with greater accuracy.
Key Features:
Order Block Visualization: Highlights relevant bullish and bearish zones directly on the chart.
Customizable Settings: Adjust sensitivity, colors, and other parameters to suit your analysis needs.
Dual Block Detection: Uses two independent settings to cover different market perspectives.
Visual Alerts: Automatic line drawing for key levels.
Automatic Clearing: Dynamic clearing of already invalidated blocks.
User Benefits:
Clear Visual Analysis: Identifies key supply and demand points used by institutions.
Improved Trading Decisions: Anticipate entry and exit zones more accurately.
Time Saver: Automates level plotting, allowing you to focus on strategy and execution.
Strategy Adaptability: Compatible with Smart Money, Wyckoff, and Price Action approaches.
Disclaimer:
This script is an educational and analytical tool. It does not guarantee specific results or eliminate trading risk. Trading in the financial markets involves significant risks; use this script at your own risk.
Structure Pilot Vision [Wang Indicators]Built and refined with Dave Teaches, the HTF Vision Pro supercharges the trader, providing them with the tools to approach price with a layered analysis.
Providing the trader the instruments to put on the spotlight significant zones to anticipate price deliveries
HTF CANDLE VISION
Displays up to 3 series of HTF Candles
Shows candlesticks from a higher time frame (e.g., daily, 4-hour, weekly) on a lower time frame chart (e.g., 1-hour, 15-minute). This allows traders to simultaneously observe both short-term and long-term market dynamics.
Customizable Time Frames: Users can select any higher time frame to overlay on the current chart. Common time frames include daily, weekly, and monthly candles, but other custom time frames can also be used.
Color Coding: The HTF candles are color-coded for easy differentiation from the lower time frame candles. Users can customize colors to suit their preferences.
Open, High, Low, Close (OHLC) Representation: The indicator displays the full candlestick pattern for the chosen HTF, including the open, high, low, and close values. This helps traders easily identify key price levels and trends.
Settings :
Number of candles
Space between the chart and the HTF candles
Space between candles sets
Size : from Tiny (2x regular candle size) to Large (x8 regular candle size)
Space between candles
Colors of candles, borders and wicks
Incorporating a Higher Time Frame (HTF) candle into your Lower Time Frame (LTF) chart can be immensely beneficial for traders looking to enhance their analysis and decision-making process.
Use Cases for HTF Candles on LTF Charts:
Trend Confirmation:
Use Case: A trader might be looking at a 15-minute chart (LTF) but wants to confirm if the short-term trends align with the daily trend (HTF). Plotting a daily candle on the 15-minute chart helps visualize whether the short-term movements are part of a broader, longer-term trend.
Support and Resistance Identification:
Use Case: By plotting a weekly candle on a daily chart, traders can quickly identify levels that have acted as significant support or resistance in the past on the higher time frame, which might not be as visible or influential on the daily chart alone.
Entry and Exit Points Enhancement:
Use Case: When preparing to enter a trade based on a 1-hour chart, overlaying a 4-hour candle can provide insights into potential reversal points or continuation patterns that are more significant on the higher time frame, thus refining entry and exit strategies.
Volatility and Breakout Analysis:
Use Case: Seeing how a single HTF candle (like a monthly candle on a weekly chart) closes can give traders an idea of the market's volatility or the strength behind breakouts. A long wick on the HTF candle might suggest a rejected breakout or a potential reversal.
Risk Management:
Use Case: Using an HTF candle can help set more informed stop-loss levels. For instance, if a trader uses a 4-hour candle on a 1-hour chart, they might place their stop-loss just beyond the low of the HTF candle, assuming this represents a significant level of support or resistance.
Contextual Trading Decisions:
Use Case: For scalpers or day traders, understanding where the current price action sits within the context of a higher timeframe can lead to better decision-making. For instance, trading within an HTF consolidation range might suggest less aggressive moves, while being near the top or bottom of such a range might indicate potential for larger movements.
Market Sentiment Analysis:
Use Case: The color (red for bearish, green for bullish) and size of the HTF candle can give a quick visual cue of the market sentiment over that period, helping traders assess whether they are going with or against the broader market flow.
Swing Trading:
Use Case: Swing traders might plot a weekly candle on a daily chart to align their trades with the direction of the weekly trend, ensuring they're not fighting the broader market momentum.
Educational and Visual Reference:
Use Case: For educational purposes, having an HTF candle overlay can serve as a visual reminder for students or new traders about how price movements on different time frames can influence each other, aiding in teaching concepts like "the trend is your friend."
Wang use cases :
The way it is intended to be used is as follow
If you trade the 1 min chart and have a set of 5 min HTF candles plotted on your charts it could be used as follow :
As long as the 5 min keep providing close below the last 5 min candle if you're short you're safe ... if the 5 min candle stop closing below the last ones and start giving up-close you should consider closing your trade
Another use of HTF Candle is to find fractals responsible (up or down internal mouv before the breakout that creates a new zone). This fractal acts as supply and demand zone responsible for maintening the trend or for a reversal.
See examples below :
These fractals are interesting zones because they often cause the price to react, so following a flip in the fractal, you can take a short in bearish zones and a long in bullish zones. Fractals are easier to detect thanks to the HTF candles function, and allow you to enter positions with greater confidence. They can be used in the same way as the 70%, 50% and 30% interest zones, or they can be used simultaneously.
Use with zones :
▫️ VERTICAL BARS VISION ▫️
The vertical bars provide a view of market fractality: on a low time frame chart, they show the size of a candle in a higher time frame, and thus give a better understanding of the price fractality essential to the strategy we use.
Example :
For your information, when you modify data in the vertical bars or HTF candles parameters, the two are synchronized automatically.
The Vertical HTF Candle Closures Indicator is a simple yet effective tool that helps traders visually track the closing times of higher time frame (HTF) candles (such as 4H, 1H, 15M) on a lower time frame chart (e.g., 1-minute).
This feature plots vertical lines on the chart at the exact closure time of each selected HTF, allowing traders to quickly recognize key moments when the HTF candles close, or better yet when we trade above / below the last one and reverse ''sweepy sweepy'' .
Its more like a vertical and more micro visualisation than the HTF Candles.
Wang usage :
its a great tool to be able to reverse engineer what's in a HTFcandle precisely its a good combination with HTF candle projections to train the eyes of the traders about Whats is inside a candle that formed on the higher time frame
Limitation & know issues :
The chart may become cluttered with too many lines if multiple time frames are selected. Adjusting the line style or disabling certain time frames can help reduce visual noise.
On low time frame (<30s), some bar may notshow exactly on time (e.g : in 10sec timeframe, the 15min bar can be displayed at 01:15:10 instead of 01:15:00).
Because of the data provider and the interpreter of Trading View, if there is not data for a candle, Trading view just "skip" the candle. Sometime, those skip are on the candle that goes to 15min, 1 hour or 4 hour. As this is a Trading View issue. There is pretty much nothing we can do.
Some users may experience vertical bars at 1am, 5am, 9am ... instead of 0am, 4am, 8am ... That is because of the difference between the Timezone set on the chart and the timezone of the market they trade. Vertical bar will always refer to the symbol displayed
ImbalancesThis Pine Script is a trading indicator designed to identify imbalances in the market, specifically on candlestick charts. An imbalance refers to situations where there is a significant difference between buyers and sellers, which can create gaps or areas of inefficiency in the price. These imbalances often act as zones where price may return to "fill" or correct these inefficiencies.
1. Identifying Imbalances
The script analyzes candlestick patterns to detect imbalances based on the relationship between the highs, lows, and closes of consecutive candles. Specifically, it looks for:
Top Imbalances (Bearish): Areas where selling pressure has dominated, causing inefficiencies in the price. These are represented by patterns like multiple consecutive bearish candles or bearish gaps.
Bottom Imbalances (Bullish): Areas where buying pressure has dominated, leading to bullish gaps or inefficiencies.
When an imbalance is detected, the script highlights the area using visual boxes on the chart.
2. Visual Representation
The indicator uses colored boxes to show imbalances directly on the chart:
Top (Bearish) Imbalances: Highlighted using shades of red.
Bottom (Bullish) Imbalances: Highlighted using shades of green.
The boxes are further categorized into three states based on their level of mitigation:
Unmitigated: The imbalance has not been "filled" by price yet.
Partially Mitigated: Price has entered the imbalance zone but not completely filled it.
Fully Mitigated: Price has completely filled the imbalance zone.
3. Mitigation Logic
The concept of mitigation refers to the price revisiting an imbalance zone to correct the inefficiency:
If price fully or partially revisits an imbalance zone, the box's color changes to indicate the mitigation level (e.g., from unmitigated to partially/fully mitigated).
Fully mitigated boxes may be removed or recolored, depending on user preferences.
4. User Customization
The script provides several inputs to customize its behavior:
Enable or disable top and bottom imbalance detection.
Color settings: Users can define different colors for unmitigated, partially mitigated, and fully mitigated imbalances.
Mitigation display options: Users can choose whether to show fully mitigated imbalances on the chart or remove them.
5. Key Calculations
Imbalance Size: The size of the imbalance is calculated as the price difference between a candle's high and low across the relevant pattern.
Pattern Detection: The script checks for specific candlestick patterns (e.g., three consecutive bearish candles) to identify potential imbalances.
6. Practical Use Case
This indicator is useful for traders who:
Rely on supply and demand zones for their trading strategies.
Look for areas where price is likely to return (retesting unmitigated imbalances can signal potential trade setups).
Want to visually track market inefficiencies over time.
In Summary
The "Imbalances" indicator highlights and tracks price inefficiencies on candlestick charts. It marks zones where buying or selling pressure was dominant, and it dynamically updates these zones based on price action to indicate their mitigation status. This tool is particularly helpful for traders who use price action and market structure in their strategies.
Enhanced London Session SMC SetupEnhanced London Session SMC Setup Indicator
This Pine Script-based indicator is designed for traders focusing on the London trading session, leveraging smart money concepts (SMC) to identify potential trading opportunities in the GBP/USD currency pair. The script uses multiple techniques such as Order Block Detection, Imbalance (Fair Value Gap) Analysis, Change of Character (CHoCH) detection, and Fibonacci retracement levels to aid in market structure analysis, providing a well-rounded approach to trade setups.
Features:
London Session Highlight:
The indicator visually marks the London trading session (from 08:00 AM to 04:00 PM UTC) on the chart using a blue background, signaling when the high-volume, high-impulse moves tend to occur, helping traders focus their analysis on this key session.
Order Block Detection:
Identifies significant impulse moves that may form order blocks (supply and demand zones). Order blocks are areas where institutions have executed large orders, often leading to price reversals or continuation. The indicator plots the high and low of these order blocks, providing key levels to monitor for potential entries.
Imbalance (Fair Value Gap) Detection:
Detects and highlights price imbalances or fair value gaps (FVG) where the market has moved too quickly, creating a gap in price action. These areas are often revisited by price, offering potential trade opportunities. The upper and lower bounds of the imbalance are visually marked for easy reference.
Change of Character (CHoCH) Detection:
This feature identifies potential trend reversals by detecting significant changes in market character. When the price action shifts from bullish to bearish or vice versa, a CHoCH signal is triggered, and the corresponding level is marked on the chart. This can help traders catch trend reversals at key levels.
Fibonacci Retracement Levels:
The script calculates and plots the key Fibonacci retracement levels (0.618 and 0.786 by default) based on the highest and lowest points over a user-defined swing lookback period. These levels are commonly used by traders to identify potential pullback zones where price may reverse or find support/resistance.
Directional Bias Based on Market Structure:
The indicator provides a market structure analysis by comparing the current highs and lows to the previous periods' highs and lows. This helps in identifying whether the market is in a bullish or bearish state, providing a clear directional bias for trade setups.
Alerts:
The indicator comes with built-in alert conditions to notify the trader when an order block, imbalance, CHoCH, or other significant price action event is detected, ensuring timely action can be taken.
Ideal Usage:
Timeframe: Suitable for intraday trading, particularly focusing on the London session (08:00 AM to 04:00 PM UTC).
Currency Pair: Specifically designed for GBP/USD but can be adapted to other pairs with similar market behavior.
Trading Strategy: Best used in conjunction with a price action strategy, focusing on the key levels identified (order blocks, FVG, CHoCH) and using Fibonacci retracement levels for precision entries.
Target Audience: Ideal for traders who follow smart money concepts (SMC) and are looking for a structured approach to identify high-probability setups during the London session.
ICT Open Range Gap & 1st FVG (fadi)In his 2024 mentorship program, ICT detailed how price action interacts with Open Range Gaps and the initial 1-minute Fair Value Gap following the market open at 9:30 AM.
What is an Open Range Gap?
An Open Range Gap occurs when the market opens at 9:30 AM at a higher or lower level compared to the previous day's close at 4:14 PM, primarily relevant in futures trading. According to ICT, there is a statistical probability of 70% that the price action will close 50% or more of the Open Range Gap within the first 30 minutes of trading (9:30 AM to 10:00 AM).
What is the First 1-Minute Fair Value Gap?
ICT places significant emphasis on the first 1-minute Fair Value Gap (FVG) that forms after the market opens at 9:30 AM. The FVG must occur at 9:31 AM or later to be considered valid. This gap often presents key opportunities for traders, as it represents a temporary imbalance between supply and demand that the market seeks to correct.
Understanding and leveraging these patterns can enhance trading strategies by offering insights into potential price movements shortly after market open.
ICT Open Range Gap & 1st FVG
This indicator is engineered to identify and highlight the Open Range Gaps and the first 1-minute Fair Value Gap. Furthermore, it functions across multiple timeframes, from seconds to hours, catering to various trading preferences. This flexibility is particularly beneficial for traders who favor higher timeframes or wish to observe these patterns' application at broader intervals.
Settings
The Open Range Gap indicator offers flexible display settings. It identifies the quadrants and provides optional color coding to distinguish them. Additionally, it tracks the "fill" level to visualize how far the price action has progressed into the gap, enhancing traders' ability to monitor and analyze price movements effectively. By default, the Open Range Gap will stop extending at 10:00 AM; however, there is an option to continue extending until the end of the trading day.
The 1st Fair Value Gap (FVG) can be viewed on any timeframe the indicator is active on, offering various styling options to match each trader's preferences. While the 1st FVG is particularly relevant to the day it is created, previous 1st FVGs within the same week may provide additional value. This indicator allows traders to extend Monday's 1st FVG, marking the first FVG of the week, or to extend all 1st FVGs throughout the week.
Smart Money Setup 07 [TradingFinder] Liquidity Hunts & Minor OB🔵 Introduction
The Smart Money Concept relies on analyzing market structure, tracking liquidity flows, and identifying order blocks. Research indicates that traders who apply these methods can improve their accuracy in predicting market movements by up to 30%.
These elements allow traders to understand the behavior of market makers, including banks and large financial institutions, which have the ability to influence price movements and shape major market trends. By recognizing how these entities operate, traders can align their strategies with Smart Money actions and better anticipate shifts in the market.
Smart Money typically enters the market at points of high liquidity where trading opportunities are more attractive. By following these liquidity flows, professional traders can position themselves at market reversal points, leading to profitable trades.
The Smart Money Setup 07 indicator has been specifically designed to detect these complex patterns. Using advanced algorithms, this indicator automatically identifies both bullish and bearish trading setups, assisting traders in discovering hidden market opportunities.
As a powerful technical analysis tool, the Smart Money Setup indicator helps predict the actions of major market participants and highlights optimal entry and exit points. Essentially, this tool enables traders to act like institutional investors and market makers, making the most of price fluctuations in their favor.
Ultimately, the Smart Money Setup 07 indicator transforms complex technical analysis into a simple and practical tool. By detecting order blocks and liquidity zones, this tool helps traders execute their strategies with greater precision, leading to more informed and successful trading decisions.
🟣 Bullish Setup
🟣 Bearish Setup
🔵 How to Use
One of the key strengths of the Smart Money Setup 07 indicator is its ability to accurately identify order blocks and analyze liquidity flows. Order blocks represent areas where large buy or sell orders are placed by Smart Money investors, which often indicate key reversal points in the market. Traders can use these order blocks to pinpoint potential entry and exit opportunities.
The Smart Money Setup indicator detects and visually displays these order blocks on the chart, helping traders identify the best zones to enter or exit trades. Since these zones are frequently used by large institutional investors, following these blocks allows traders to capitalize on price fluctuations and trade with confidence.
🟣 Bullish Smart Money Setup
A Bullish Smart Money Setup forms when the market creates Higher Lows and Higher Highs. In this situation, the indicator analyzes pivot points, liquidity flows, and order blocks to identify buy opportunities. Liquidity points in these setups indicate areas where Smart Money is likely to enter long positions.
In the bullish setup image, multiple Higher Lows and Higher Highs are formed. The green zone represents a Bullish Order Block, signaling traders to enter a long trade. The Smart Money Setup indicator displays a green arrow, indicating a high-probability upward price movement from this liquidity zone.
🟣 Bearish Smart Money Setup
A Bearish Smart Money Setup occurs when the market structure shows Lower Highs and Lower Lows, indicating weakness in price. The indicator identifies these patterns and highlights potential sell opportunities. Liquidity points in this setup mark areas where Smart Money enters sell positions.
In the bearish setup image, a Lower High is followed by a Lower Low, with the red liquidity zone acting as a Bearish Order Block. The Smart Money Setup indicator shows a red arrow, signaling a likely downward move, offering traders an opportunity to enter short positions.
🔵 Settings
Pivot Period : This setting determines how many candles are needed to form a pivot point. A default value of 2 is optimal for quickly identifying key pivot points in price action.
Order Block Validity Period : This parameter defines the lifespan of an order block. Traders can adjust how long each order block remains valid. For instance, setting it to 500 means that an order block will be valid for 500 bars after its formation.
Mitigation Level OB : This setting allows traders to select whether order blocks should be based on the "Proximal," "50% OB," or "Distal" levels, helping traders manage risk more effectively.
Order Block Refinement : Traders can refine the order blocks with precision. The indicator offers two refinement modes: Defensive and Aggressive. The Defensive mode identifies safer order blocks, while the Aggressive mode targets higher-risk blocks with the potential for larger reversals.
🔵 Conclusion
The Smart Money Setup 07 indicator is a powerful tool for identifying key Smart Money movements in the market. It provides traders with essential insights for making informed trading decisions, particularly when combined with technical analysis and liquidity flow analysis. This indicator allows traders to accurately pinpoint entry and exit points, helping them maximize profits and minimize risk.
By offering a range of customizable settings, the Smart Money Setup indicator adapts to different trading styles and strategies. Furthermore, its ability to detect order blocks and identify supply and demand zones makes it an indispensable tool for any trader looking to enhance their strategy.
In conclusion, the Smart Money Setup 07 is a crucial tool for traders aiming to optimize their trading performance. By utilizing the concepts of Smart Money in technical analysis, traders can make more precise decisions and take advantage of market fluctuations.
Advanced Multi-Seasonality StrategyThe Multi-Seasonality Strategy is a trading system based on seasonal market patterns. Seasonality refers to recurring market trends driven by predictable calendar-based events. These patterns emerge due to economic cycles, corporate activities (e.g., earnings reports), and investor behavior around specific times of the year. Studies have shown that such effects can influence asset prices over defined periods, leading to opportunities for traders who exploit these patterns (Hirshleifer, 2001; Bouman & Jacobsen, 2002).
How the Strategy Works:
The strategy allows the user to define four distinct periods within a calendar year. For each period, the trader selects:
Entry Date (Month and Day): The date to enter the trade.
Holding Period: The number of trading days to remain in the trade after the entry.
Trade Direction: Whether to take a long or short position during that period.
The system is designed with flexibility, enabling the user to activate or deactivate each of the four periods. The idea is to take advantage of seasonal patterns, such as buying during historically strong periods and selling during weaker ones. A well-known example is the "Sell in May and Go Away" phenomenon, which suggests that stock returns are higher from November to April and weaker from May to October (Bouman & Jacobsen, 2002).
Seasonality in Financial Markets:
Seasonal effects have been documented across different asset classes and markets:
Equities: Stock markets tend to exhibit higher returns during certain months, such as the "January effect," where prices rise after year-end tax-loss selling (Haugen & Lakonishok, 1987).
Commodities: Agricultural commodities often follow seasonal planting and harvesting cycles, which impact supply and demand patterns (Fama & French, 1987).
Forex: Currency pairs may show strength or weakness during specific quarters based on macroeconomic factors, such as fiscal year-end flows or central bank policy decisions.
Scientific Basis:
Research shows that market anomalies like seasonality are linked to behavioral biases and institutional practices. For example, investors may respond to tax incentives at the end of the year, and companies may engage in window dressing (Haugen & Lakonishok, 1987). Additionally, macroeconomic factors, such as monetary policy shifts and holiday trading volumes, can also contribute to predictable seasonal trends (Bouman & Jacobsen, 2002).
Risks of Seasonal Trading:
While the strategy seeks to exploit predictable patterns, there are inherent risks:
Market Changes: Seasonal effects observed in the past may weaken or disappear as market conditions evolve. Increased algorithmic trading, globalization, and policy changes can reduce the reliability of historical patterns (Lo, 2004).
Overfitting: One of the risks in seasonal trading is overfitting the strategy to historical data. A pattern that worked in the past may not necessarily work in the future, especially if it was based on random chance or external factors that no longer apply (Sullivan, Timmermann, & White, 1999).
Liquidity and Volatility: Trading during specific periods may expose the trader to low liquidity, especially around holidays or earnings seasons, leading to slippage and larger-than-expected price swings.
Economic and Geopolitical Shocks: External events such as pandemics, wars, or political instability can disrupt seasonal patterns, leading to unexpected market behavior.
Conclusion:
The Multi-Seasonality Strategy capitalizes on the predictable nature of certain calendar-based patterns in financial markets. By entering and exiting trades based on well-established seasonal effects, traders can potentially capture short-term profits. However, caution is necessary, as market dynamics can change, and seasonal patterns are not guaranteed to persist. Rigorous backtesting, combined with risk management practices, is essential to successfully implementing this strategy.
References:
Bouman, S., & Jacobsen, B. (2002). The Halloween Indicator, "Sell in May and Go Away": Another Puzzle. American Economic Review, 92(5), 1618-1635.
Fama, E. F., & French, K. R. (1987). Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage. Journal of Business, 60(1), 55-73.
Haugen, R. A., & Lakonishok, J. (1987). The Incredible January Effect: The Stock Market's Unsolved Mystery. Dow Jones-Irwin.
Hirshleifer, D. (2001). Investor Psychology and Asset Pricing. Journal of Finance, 56(4), 1533-1597.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Sullivan, R., Timmermann, A., & White, H. (1999). Data-Snooping, Technical Trading Rule Performance, and the Bootstrap. Journal of Finance, 54(5), 1647-1691.
This strategy harnesses the power of seasonality but requires careful consideration of the risks and potential changes in market behavior over time.
Freak VolumeFreak Volume is a technical indicator designed to identify bars with exceptionally high trading volume. It operates by calculating the mean volume over a specified period and determines high volume thresholds using both multiples of the mean and standard deviations from this mean.
High Volume Identification:
Standard Deviation Threshold: Bars with volume exceeding a specified number of standard deviations above the mean are highlighted within the indicator and on the corresponding candlesticks on the chart.
Mean Multiple Threshold: Bars with volume exceeding a multiple of the average volume are also highlighted. This highlighting is secondary to the standard deviation threshold, meaning standard deviation-based highlights take precedence.
Price Range Plotting: The indicator offers an option to display the price range of high volume candles, which may serve as potential supply and demand zones or support and resistance levels.
Freak Volume assists traders in visually identifying significant volume spikes that could indicate important market activity or potential turning points by providing multiple methods of high volume detection.
Iceberg Trade Revealer [CHE]Unveiling Iceberg Trades: A Deep Dive into Low Volatility Market Phases
Introduction
In the dynamic world of trading, hidden forces often influence market movements in ways that aren't immediately apparent. One such force is the phenomenon of iceberg trades—large orders that are concealed to prevent significant market impact. This presentation explores the concept of iceberg trades, explains why they are typically hidden during periods of low volatility, and introduces an indicator designed to reveal these elusive trades.
Agenda
1. Understanding Iceberg Trades
- Definition and Purpose
- Impact on Market Dynamics
2. The Low Volatility Concealment
- Why Low Volatility Phases?
- Strategies Behind Hiding Large Orders
3. Introducing the Iceberg Trade Revealer Indicator
- How the Indicator Works
- Key Components and Calculations
4. Demonstration and Use Cases
- Interpreting the Indicator Signals
- Practical Trading Applications
5. Conclusion
- Summarizing the Insights
- Q&A Session
1. Understanding Iceberg Trades
Definition and Purpose
- Iceberg Trades are large single orders divided into smaller lots to disguise the total order quantity.
- Traders use iceberg orders to minimize market impact and avoid unfavorable price movements.
Impact on Market Dynamics
- Concealed Volume: Iceberg orders hide true supply and demand levels.
- Price Stability: They prevent sudden spikes or drops by releasing orders gradually.
- Market Sentiment: Their presence can influence perceptions of market strength or weakness.
2. The Low Volatility Concealment
Why Low Volatility Phases?
- Less Market Attention: Low volatility periods attract fewer traders, making it easier to conceal large orders.
- Reduced Slippage: Prices are more stable, reducing the risk of executing orders at unfavorable prices.
- Strategic Advantage: Large players can accumulate or distribute positions without tipping off the market.
Strategies Behind Hiding Large Orders
- Order Splitting: Breaking down large orders into smaller pieces.
- Time Slicing: Executing orders over an extended period.
- Algorithmic Trading: Using sophisticated algorithms to optimize order execution.
3. Introducing the Iceberg Trade Revealer Indicator
How the Indicator Works
- Core Thesis: Iceberg trades can be detected by analyzing periods of unusually low volatility.
- Volatility Analysis: Uses the Average True Range (ATR) and Bollinger Bands to identify low volatility phases.
- Signal Generation: Marks periods where iceberg trades are likely occurring.
Key Components and Calculations
1. Average True Range (ATR)
- Measures market volatility over a specified period.
- Lower ATR values indicate less price movement.
2. Bollinger Bands
- Creates a volatility envelope around the ATR.
- Bands tighten during low volatility and widen during high volatility.
3. Timeframe Adjustments
- Utilizes multiple timeframes to enhance signal accuracy.
- Options for auto, multiplier, or manual timeframe selection.
4. Signal Conditions
- Iceberg Trade Detection: ATR falls below the lower Bollinger Band.
- Revealed Volatility: ATR rises above the upper Bollinger Band, indicating potential market moves after iceberg trades.
4. Demonstration and Use Cases
Interpreting the Indicator Signals
- Iceberg Trade Zones: Highlighted areas where large hidden orders are likely.
- Revealed Volatility Zones: Areas indicating the market's response to the execution of iceberg trades.
Practical Trading Applications
- Entry and Exit Points: Use signals to time trades alongside institutional activity.
- Risk Management: Adjust strategies during detected low volatility phases.
- Market Analysis: Gain insights into underlying market mechanics.
5. Conclusion
Summarizing the Insights
- Iceberg Trades play a significant role in market movements, especially when concealed during low volatility phases.
- The Iceberg Trade Revealer Indicator provides a tool to uncover these hidden activities, offering traders a strategic edge.
- Understanding and utilizing this indicator can enhance trading decisions by aligning them with the actions of major market players.
Best regards Chervolino ( Volker )
Q&A Session
- Questions and Discussions: Open the floor for any queries or further explanations.
Thank You!
By delving into the hidden aspects of market activity, traders can better navigate the complexities of financial markets. The Iceberg Trade Revealer Indicator serves as a bridge between observable market data and the concealed strategies of large institutions.
References
- Average True Range (ATR): A technical analysis indicator that measures market volatility.
- Bollinger Bands: A volatility indicator that creates a band of three lines which are plotted in relation to a security's price.
- Iceberg Orders: Large orders divided into smaller lots to hide the actual order quantity.
Note: Always consider multiple factors when making trading decisions. Indicators provide tools, but they do not guarantee results.
Educational Content Disclaimer:
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Bitcoin CME-Spot Z-Spread - Strategy [presentTrading]This time is a swing trading strategy! It measures the sentiment of the Bitcoin market through the spread of CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. By applying Bollinger Bands to the spread, the strategy seeks to capture mean-reversion opportunities when prices deviate significantly from their historical norms
█ Introduction and How it is Different
The Bitcoin CME-Spot Bollinger Bands Strategy is designed to capture mean-reversion opportunities by exploiting the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. The strategy uses Bollinger Bands to detect when the spread between these two correlated assets has deviated significantly from its historical norm, signaling potential overbought or oversold conditions.
What sets this strategy apart is its focus on spread trading between futures and spot markets rather than price-based indicators. By applying Bollinger Bands to the spread rather than individual prices, the strategy identifies price inefficiencies across markets, allowing traders to take advantage of the natural reversion to the mean that often occurs in these correlated assets.
BTCUSD 8hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy relies on Bollinger Bands to assess the volatility and relative deviation of the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. Bollinger Bands consist of a moving average and two standard deviation bands, which help measure how much the spread deviates from its historical mean.
🔶 Spread Calculation:
The spread is calculated by subtracting the Bitfinex spot price from the CME Bitcoin futures price:
Spread = CME Price - Bitfinex Price
This spread represents the difference between the futures and spot markets, which may widen or narrow based on supply and demand dynamics in each market. By analyzing the spread, the strategy can detect when prices are too far apart (potentially overbought or oversold), indicating a trading opportunity.
🔶 Bollinger Bands Calculation:
The Bollinger Bands for the spread are calculated using a simple moving average (SMA) and the standard deviation of the spread over a defined period.
1. Moving Average (SMA):
The simple moving average of the spread (mu_S) over a specified period P is calculated as:
mu_S = (1/P) * sum(S_i from i=1 to P)
Where S_i represents the spread at time i, and P is the lookback period (default is 200 bars). The moving average provides a baseline for the normal spread behavior.
2. Standard Deviation:
The standard deviation (sigma_S) of the spread is calculated to measure the volatility of the spread:
sigma_S = sqrt((1/P) * sum((S_i - mu_S)^2 from i=1 to P))
3. Upper and Lower Bollinger Bands:
The upper and lower Bollinger Bands are derived by adding and subtracting a multiple of the standard deviation from the moving average. The number of standard deviations is determined by a user-defined parameter k (default is 2.618).
- Upper Band:
Upper Band = mu_S + (k * sigma_S)
- Lower Band:
Lower Band = mu_S - (k * sigma_S)
These bands provide a dynamic range within which the spread typically fluctuates. When the spread moves outside of these bands, it is considered overbought or oversold, potentially offering trading opportunities.
Local view
🔶 Entry Conditions:
- Long Entry: A long position is triggered when the spread crosses below the lower Bollinger Band, indicating that the spread has become oversold and is likely to revert upward.
Spread < Lower Band
- Short Entry: A short position is triggered when the spread crosses above the upper Bollinger Band, indicating that the spread has become overbought and is likely to revert downward.
Spread > Upper Band
🔶 Risk Management and Profit-Taking:
The strategy incorporates multi-step take profits to lock in gains as the trade moves in favor. The position is gradually reduced at predefined profit levels, reducing risk while allowing part of the trade to continue running if the price keeps moving favorably.
Additionally, the strategy uses a hold period exit mechanism. If the trade does not hit any of the take-profit levels within a certain number of bars, the position is closed automatically to avoid excessive exposure to market risks.
█ Trade Direction
The trade direction is based on deviations of the spread from its historical norm:
- Long Trade: The strategy enters a long position when the spread crosses below the lower Bollinger Band, signaling an oversold condition where the spread is expected to narrow.
- Short Trade: The strategy enters a short position when the spread crosses above the upper Bollinger Band, signaling an overbought condition where the spread is expected to widen.
These entries rely on the assumption of mean reversion, where extreme deviations from the average spread are likely to revert over time.
█ Usage
The Bitcoin CME-Spot Bollinger Bands Strategy is ideal for traders looking to capitalize on price inefficiencies between Bitcoin futures and spot markets. It’s especially useful in volatile markets where large deviations between futures and spot prices occur.
- Market Conditions: This strategy is most effective in correlated markets, like CME futures and spot Bitcoin. Traders can adjust the Bollinger Bands period and standard deviation multiplier to suit different volatility regimes.
- Backtesting: Before deployment, backtesting the strategy across different market conditions and timeframes is recommended to ensure robustness. Adjust the take-profit steps and hold periods to reflect the trader’s risk tolerance and market behavior.
█ Default Settings
The default settings provide a balanced approach to spread trading using Bollinger Bands but can be adjusted depending on market conditions or personal trading preferences.
🔶 Bollinger Bands Period (200 bars):
This defines the number of bars used to calculate the moving average and standard deviation for the Bollinger Bands. A longer period smooths out short-term fluctuations and focuses on larger, more significant trends. Adjusting the period affects the responsiveness of the strategy:
- Shorter periods (e.g., 100 bars): Makes the strategy more reactive to short-term market fluctuations, potentially generating more signals but increasing the risk of false positives.
- Longer periods (e.g., 300 bars): Focuses on longer-term trends, reducing the frequency of trades and focusing only on significant deviations.
🔶 Standard Deviation Multiplier (2.618):
The multiplier controls how wide the Bollinger Bands are around the moving average. By default, the bands are set at 2.618 standard deviations away from the average, ensuring that only significant deviations trigger trades.
- Higher multipliers (e.g., 3.0): Require a more extreme deviation to trigger trades, reducing trade frequency but potentially increasing the accuracy of signals.
- Lower multipliers (e.g., 2.0): Make the bands narrower, increasing the number of trade signals but potentially decreasing their reliability.
🔶 Take-Profit Levels:
The strategy has four take-profit levels to gradually lock in profits:
- Level 1 (3%): 25% of the position is closed at a 3% profit.
- Level 2 (8%): 20% of the position is closed at an 8% profit.
- Level 3 (14%): 15% of the position is closed at a 14% profit.
- Level 4 (21%): 10% of the position is closed at a 21% profit.
Adjusting these take-profit levels affects how quickly profits are realized:
- Lower take-profit levels: Capture gains more quickly, reducing risk but potentially cutting off larger profits.
- Higher take-profit levels: Let trades run longer, aiming for bigger gains but increasing the risk of price reversals before profits are locked in.
🔶 Hold Days (20 bars):
The strategy automatically closes the position after 20 bars if none of the take-profit levels are hit. This feature prevents trades from being held indefinitely, especially if market conditions are stagnant. Adjusting this:
- Shorter hold periods: Reduce the duration of exposure, minimizing risks from market changes but potentially closing trades too early.
- Longer hold periods: Allow trades to stay open longer, increasing the chance for mean reversion but also increasing exposure to unfavorable market conditions.
By understanding how these default settings affect the strategy’s performance, traders can optimize the Bitcoin CME-Spot Bollinger Bands Strategy to their preferences, adapting it to different market environments and risk tolerances.
FVG Price & Volume Graph [LuxAlgo]The FVG Price & Volume Graph tool plot recently detected fair value gaps relative to the volume traded within their area during their formation. This allows us to effectively visualize significant fair value gaps caused by high liquidity.
The indicator also returns levels from the fair value gaps areas average with the highest associated volume.
Do note that the indicator can consider the chart's visible range when being computed, which will recalculate the indicator when the chart's visible range changes.
🔶 USAGE
Fair Value Gaps (FVG) are core price action concepts occurring when the disparity between supply and demand is significant. Price has a tendency to come back to those areas and mitigating them, that is filling them.
The provided tools allow for effective visualization of both FVG's area's height as well as the volume originating from their creation, which is defined by the total traded volume located within the FVG during its creation. FVG's with more associated volume are displayed to the rightmost of the chart.
Users can determine the amount of most recent FVG's to display from the "Display Amount" setting. Disabling the "Consider Mitigation" setting will return mitigated FVGs in the plot, which can be useful to know where most FVGs were located.
We can use the area average of the FVGs with the most associated volume as potential support/resistance levels. Users can extend more FVG's averages by increasing the "Highest Volume Averages" setting.
🔹 Visualizing Volume/Price Relationships of FVG's
A linear regression is fit between FVG's areas average and their associated volume, with this linear regression helping us see where FVG's with specific volume might be located in the future based on existing FVG's.
Note that FVG's do not tend to exhibit linear relationships with their associated volume, the provided linear regression can give a general sense of tendency, but nothing necessarily accurate.
🔶 DETAILS
🔹 Intrabar Data TF
Given a formation of three candles causing an FVG, the volume traded within that FVG area is obtained by looking at the lower timeframe intrabar candles located within the intermediary candle of the formation. The volume of the intrabar candles located within the FVG areas is added up to obtain the associated volume of the FVG.
Using a lower "Intrabar Data TF" allows obtaining more precise volume results, at the cost of computation time and data availability (if there is a high difference between the "Intrabar Data TF" and the chart TF then less FVG can have their associated volume calculated due to Tradingview limitations).
🔹 Display
Users have access to multiple graphical settings affecting how the indicator is displayed.
The "Graph Resolution" setting determines the length of the X axis, with higher values returning more precise results on the location of FVGs over the X axis. Users can also control the number of labels displayed on the X-axis using the numerical input to the right of "Show X-Axis Labels".
Additionally, users can color FVG areas using a gradient relative to the size of the area, or the volume associated with the FVG.
🔶 SETTINGS
Display Amount: Amount of most recent FVGs to display.
Highest Volume Averages: Amount of FVG averages levels with the highest volume to display and extend.
Consider Mitigation: Only display unmitigated FVGs.
Filter FVGs Outside Visible Range: Only display FVGs areas that are located within the user chart visible range.
Intrabar Data TF: Timeframe used to obtain intrabar data. Should be lower than the user chart timeframe.
