[PX] Level & TrendlinesThe indicator identifies the intermediate fractal pattern, where neighboring fractals are either higher or lower. It plots horizontal level and trendlines based on those fractals and comes with a variety of settings.
If you are looking for someone to develop your on indicator or trading strategy, don't hesitate to get in touch with me here on TradingView or below.
Contact:
www.pascal-simon.de
info@pascal-simon.de
Komut dosyalarını "Fractal" için ara
Rally Base Drop SND Pivots Strategy [LuxAlgo X PineIndicators]This strategy is based on the Rally Base Drop (RBD) SND Pivots indicator developed by LuxAlgo. Full credit for the concept and original indicator goes to LuxAlgo.
The Rally Base Drop SND Pivots Strategy is a non-repainting supply and demand trading system that detects pivot points based on Rally, Base, and Drop (RBD) candles. This strategy automatically identifies key market structure levels, allowing traders to:
Identify pivot-based supply and demand (SND) zones.
Use fixed criteria for trend continuation or reversals.
Filter out market noise by requiring structured price formations.
Enter trades based on breakouts of key SND pivot levels.
How the Rally Base Drop SND Pivots Strategy Works
1. Pivot Point Detection Using RBD Candles
The strategy follows a rigid market structure methodology, where pivots are detected only when:
A Rally (R) consists of multiple consecutive bullish candles.
A Drop (D) consists of multiple consecutive bearish candles.
A Base (B) is identified as a transition between Rallies and Drops, acting as a pivot point.
The pivot level is confirmed when the formation is complete.
Unlike traditional fractal-based pivots, RBD Pivots enforce stricter structural rules, ensuring that each pivot:
Has a well-defined bullish or bearish price movement.
Reduces false signals caused by single-bar fluctuations.
Provides clear supply and demand levels based on structured price movements.
These pivot levels are drawn on the chart using color-coded boxes:
Green zones represent bullish pivot levels (Rally Base formations).
Red zones represent bearish pivot levels (Drop Base formations).
Once a pivot is confirmed, the high or low of the base candle is used as the reference level for future trades.
2. Trade Entry Conditions
The strategy allows traders to select from three trading modes:
Long Only – Only takes long trades when bullish pivot breakouts occur.
Short Only – Only takes short trades when bearish pivot breakouts occur.
Long & Short – Trades in both directions based on pivot breakouts.
Trade entry signals are triggered when price breaks through a confirmed pivot level:
Long Entry:
A bullish pivot level is formed.
Price breaks above the bullish pivot level.
The strategy enters a long position.
Short Entry:
A bearish pivot level is formed.
Price breaks below the bearish pivot level.
The strategy enters a short position.
The strategy includes an optional mode to reverse long and short conditions, allowing traders to experiment with contrarian entries.
3. Exit Conditions Using ATR-Based Risk Management
This strategy uses the Average True Range (ATR) to calculate dynamic stop-loss and take-profit levels:
Stop-Loss (SL): Placed 1 ATR below entry for long trades and 1 ATR above entry for short trades.
Take-Profit (TP): Set using a Risk-Reward Ratio (RR) multiplier (default = 6x ATR).
When a trade is opened:
The entry price is recorded.
ATR is calculated at the time of entry to determine stop-loss and take-profit levels.
Trades exit automatically when either SL or TP is reached.
If reverse conditions mode is enabled, stop-loss and take-profit placements are flipped.
Visualization & Dynamic Support/Resistance Levels
1. Pivot Boxes for Market Structure
Each pivot is marked with a colored box:
Green boxes indicate bullish demand zones.
Red boxes indicate bearish supply zones.
These boxes remain on the chart to act as dynamic support and resistance levels, helping traders identify key price reaction zones.
2. Horizontal Entry, Stop-Loss, and Take-Profit Lines
When a trade is active, the strategy plots:
White line → Entry price.
Red line → Stop-loss level.
Green line → Take-profit level.
Labels display the exact entry, SL, and TP values, updating dynamically as price moves.
Customization Options
This strategy offers multiple adjustable settings to optimize performance for different market conditions:
Trade Mode Selection → Choose between Long Only, Short Only, or Long & Short.
Pivot Length → Defines the number of required Rally & Drop candles for a pivot.
ATR Exit Multiplier → Adjusts stop-loss distance based on ATR.
Risk-Reward Ratio (RR) → Modifies take-profit level relative to risk.
Historical Lookback → Limits how far back pivot zones are displayed.
Color Settings → Customize pivot box colors for bullish and bearish setups.
Considerations & Limitations
Pivot Breakouts Do Not Guarantee Reversals. Some pivot breaks may lead to continuation moves instead of trend reversals.
Not Optimized for Low Volatility Conditions. This strategy works best in trending markets with strong momentum.
ATR-Based Stop-Loss & Take-Profit May Require Optimization. Different assets may require different ATR multipliers and RR settings.
Market Noise May Still Influence Pivots. While this method filters some noise, fake breakouts can still occur.
Conclusion
The Rally Base Drop SND Pivots Strategy is a non-repainting supply and demand system that combines:
Pivot-based market structure analysis (using Rally, Base, and Drop candles).
Breakout-based trade entries at confirmed SND levels.
ATR-based dynamic risk management for stop-loss and take-profit calculation.
This strategy helps traders:
Identify high-probability supply and demand levels.
Trade based on structured market pivots.
Use a systematic approach to price action analysis.
Automatically manage risk with ATR-based exits.
The strict pivot detection rules and built-in breakout validation make this strategy ideal for traders looking to:
Trade based on market structure.
Use defined support & resistance levels.
Reduce noise compared to traditional fractals.
Implement a structured supply & demand trading model.
This strategy is fully customizable, allowing traders to adjust parameters to fit their market and trading style.
Full credit for the original concept and indicator goes to LuxAlgo.
MMXM ICT [TradingFinder] Market Maker Model PO3 CHoCH/CSID + FVG🔵 Introduction
The MMXM Smart Money Reversal leverages key metrics such as SMT Divergence, Liquidity Sweep, HTF PD Array, Market Structure Shift (MSS) or (ChoCh), CISD, and Fair Value Gap (FVG) to identify critical turning points in the market. Designed for traders aiming to analyze the behavior of major market participants, this setup pinpoints strategic areas for making informed trading decisions.
The document introduces the MMXM model, a trading strategy that identifies market maker activity to predict price movements. The model operates across five distinct stages: original consolidation, price run, smart money reversal, accumulation/distribution, and completion. This systematic approach allows traders to differentiate between buyside and sellside curves, offering a structured framework for interpreting price action.
Market makers play a pivotal role in facilitating these movements by bridging liquidity gaps. They continuously quote bid (buy) and ask (sell) prices for assets, ensuring smooth trading conditions.
By maintaining liquidity, market makers prevent scenarios where buyers are left without sellers and vice versa, making their activity a cornerstone of the MMXM strategy.
SMT Divergence serves as the first signal of a potential trend reversal, arising from discrepancies between the movements of related assets or indices. This divergence is detected when two or more highly correlated assets or indices move in opposite directions, signaling a likely shift in market trends.
Liquidity Sweep occurs when the market targets liquidity in specific zones through false price movements. This process allows major market participants to execute their orders efficiently by collecting the necessary liquidity to enter or exit positions.
The HTF PD Array refers to premium and discount zones on higher timeframes. These zones highlight price levels where the market is in a premium (ideal for selling) or discount (ideal for buying). These areas are identified based on higher timeframe market behavior and guide traders toward lucrative opportunities.
Market Structure Shift (MSS), also referred to as ChoCh, indicates a change in market structure, often marked by breaking key support or resistance levels. This shift confirms the directional movement of the market, signaling the start of a new trend.
CISD (Change in State of Delivery) reflects a transition in price delivery mechanisms. Typically occurring after MSS, CISD confirms the continuation of price movement in the new direction.
Fair Value Gap (FVG) represents zones where price imbalance exists between buyers and sellers. These gaps often act as price targets for filling, offering traders opportunities for entry or exit.
By combining all these metrics, the Smart Money Reversal provides a comprehensive tool for analyzing market behavior and identifying key trading opportunities. It enables traders to anticipate the actions of major players and align their strategies accordingly.
MMBM :
MMSM :
🔵 How to Use
The Smart Money Reversal operates in two primary states: MMBM (Market Maker Buy Model) and MMSM (Market Maker Sell Model). Each state highlights critical structural changes in market trends, focusing on liquidity behavior and price reactions at key levels to offer precise and effective trading opportunities.
The MMXM model expands on this by identifying five distinct stages of market behavior: original consolidation, price run, smart money reversal, accumulation/distribution, and completion. These stages provide traders with a detailed roadmap for interpreting price action and anticipating market maker activity.
🟣 Market Maker Buy Model
In the MMBM state, the market transitions from a bearish trend to a bullish trend. Initially, SMT Divergence between related assets or indices reveals weaknesses in the bearish trend. Subsequently, a Liquidity Sweep collects liquidity from lower levels through false breakouts.
After this, the price reacts to discount zones identified in the HTF PD Array, where major market participants often execute buy orders. The market confirms the bullish trend with a Market Structure Shift (MSS) and a change in price delivery state (CISD). During this phase, an FVG emerges as a key trading opportunity. Traders can open long positions upon a pullback to this FVG zone, capitalizing on the bullish continuation.
🟣 Market Maker Sell Model
In the MMSM state, the market shifts from a bullish trend to a bearish trend. Here, SMT Divergence highlights weaknesses in the bullish trend. A Liquidity Sweep then gathers liquidity from higher levels.
The price reacts to premium zones identified in the HTF PD Array, where major sellers enter the market and reverse the price direction. A Market Structure Shift (MSS) and a change in delivery state (CISD) confirm the bearish trend. The FVG then acts as a target for the price. Traders can initiate short positions upon a pullback to this FVG zone, profiting from the bearish continuation.
Market makers actively bridge liquidity gaps throughout these stages, quoting continuous bid and ask prices for assets. This ensures that trades are executed seamlessly, even during periods of low market participation, and supports the structured progression of the MMXM model.
The price’s reaction to FVG zones in both states provides traders with opportunities to reduce risk and enhance precision. These pullbacks to FVG zones not only represent optimal entry points but also create avenues for maximizing returns with minimal risk.
🔵 Settings
Higher TimeFrame PD Array : Selects the timeframe for identifying premium/discount arrays on higher timeframes.
PD Array Period : Specifies the number of candles for identifying key swing points.
ATR Coefficient Threshold : Defines the threshold for acceptable volatility based on ATR.
Max Swing Back Method : Choose between analyzing all swings ("All") or a fixed number ("Custom").
Max Swing Back : Sets the maximum number of candles to consider for swing analysis (if "Custom" is selected).
Second Symbol for SMT : Specifies the second asset or index for detecting SMT divergence.
SMT Fractal Periods : Sets the number of candles required to identify SMT fractals.
FVG Validity Period : Defines the validity duration for FVG zones.
MSS Validity Period : Sets the validity duration for MSS zones.
FVG Filter : Activates filtering for FVG zones based on width.
FVG Filter Type : Selects the filtering level from "Very Aggressive" to "Very Defensive."
Mitigation Level FVG : Determines the level within the FVG zone (proximal, 50%, or distal) that price reacts to.
Demand FVG : Enables the display of demand FVG zones.
Supply FVG : Enables the display of supply FVG zones.
Zone Colors : Allows customization of colors for demand and supply FVG zones.
Bottom Line & Label : Enables or disables the SMT divergence line and label from the bottom.
Top Line & Label : Enables or disables the SMT divergence line and label from the top.
Show All HTF Levels : Displays all premium/discount levels on higher timeframes.
High/Low Levels : Activates the display of high/low levels.
Color Options : Customizes the colors for high/low lines and labels.
Show All MSS Levels : Enables display of all MSS zones.
High/Low MSS Levels : Activates the display of high/low MSS levels.
Color Options : Customizes the colors for MSS lines and labels.
🔵 Conclusion
The Smart Money Reversal model represents one of the most advanced tools for technical analysis, enabling traders to identify critical market turning points. By leveraging metrics such as SMT Divergence, Liquidity Sweep, HTF PD Array, MSS, CISD, and FVG, traders can predict future price movements with precision.
The price’s interaction with key zones such as PD Array and FVG, combined with pullbacks to imbalance areas, offers exceptional opportunities with favorable risk-to-reward ratios. This approach empowers traders to analyze the behavior of major market participants and adopt professional strategies for entry and exit.
By employing this analytical framework, traders can reduce errors, make more informed decisions, and capitalize on profitable opportunities. The Smart Money Reversal focuses on liquidity behavior and structural changes, making it an indispensable tool for financial market success.
Time Based 3 Candle Model CRT FrameworkThe 3 Candle Model Overview:
The 3 Candle Model serves as a sophisticated framework for traders to navigate the complexities of financial markets, particularly within futures and forex trading. This guide not only elaborates on the model's key features but also emphasizes its originality and practical usefulness in the TradingView community. The core principle of the 3 Candle Model revolves around understanding how candle patterns can represent significant price ranges, offering valuable insights into potential market movements. By integrating the model with other critical trading concepts such as the Power of Three (PO3), Open-High-Low-Close (OHLC), and Turtle Soup setups, traders can enhance their ability to identify high-probability trades and achieve better trading outcomes.
Indicator includes:
3 Customizable Timeframe choices to fractally frame 3 candle models for precision
Live Timers for each timeframe to always be aware of the models timing
Parent Candle tracking on every preffered timeframe until new models parent candle is printed
Key Features of the 3 Candle Model
The 3 Candle Model primarily utilizes a three-candle structure, where the first candle establishes a price range, the second candle may act as a confirmation (often termed a "turtle soup"), and the third candle provides the breakout or continuation. This structure is pivotal in determining entry and exit points for trades, ensuring that each trading decision is backed by solid price action analysis.
OHLC Principle:
The Open-High-Low-Close (OHLC) concept is integral to the 3 Candle Model, allowing traders to analyze price action more effectively. Understanding the relationship between these four price points helps traders gauge market sentiment and potential reversals. By incorporating OHLC into the model, traders can develop a deeper understanding of market structure and its implications for future price movements.
Delivery States:
The 3 Candle Model emphasizes the importance of delivery states, which refer to the market's phase during specific time frames. Recognizing these states aids traders in determining the appropriate conditions for entering trades, particularly when combined with the power of three and candle range patterns. This understanding is crucial for positioning trades in alignment with market momentum.
High Probability Setups:
By aligning the 3 Candle Model with inside bar setups, traders can optimize their strategies for high-probability outcomes. This approach capitalizes on the inherent fractal nature of price movements, where previous patterns repeat at different scales. The combination of the model and inside bar setups enhances the trader's toolkit, allowing for more strategic trade placements.
Turtle Soup Formation:
The 3 Candle Model intricately connects with the Turtle Soup concept, which focuses on false breakouts. Identifying these formations at critical levels enhances the trader's ability to anticipate reversals or continuation patterns. The timing of these setups, particularly during specified times like 3:00 AM, 6:00 AM, 9:00 AM, and 1:00 PM, is crucial for maximizing trade success.
Using the 3 Candle Model in Trading
Integration with PO3:
The Power of Three (PO3) is a fundamental aspect of the 3 Candle Model that emphasizes the significance of three distinct stages of price delivery. Traders can leverage this principle by observing the initial range, confirming patterns, and executing trades during the third phase, leading to higher risk-to-reward ratios. This three-stage approach enhances a trader's ability to make informed decisions based on market behavior.
Targeting Midpoints:
Successful application of the 3 Candle Model involves targeting the midpoints of identified ranges. This practice not only provides strategic entry points but also enhances the probability of reaching desired profit levels. By targeting these midpoints, traders can refine their exit strategies and manage risk more effectively.
Aligning with Market Timing:
Timing is everything in trading. By synchronizing the 3 Candle Model setups with the aforementioned key timeframes, traders can better position themselves to exploit market dynamics. This alignment also facilitates the identification of high-quality trades that exhibit strong potential for profitability.
Prioritizing A+ Setups:
By focusing on the 3 Candle Model and its associated concepts, traders can prioritize A+ setups that exhibit a strong alignment of factors. This methodical approach enhances the quality of trades taken, leading to improved overall performance. By cultivating a strategy centered on high-probability setups, traders can maximize their return on investment.
Ensuring Originality and Usefulness
To meet the TradingView community guidelines, it is essential that this script is both original and useful. The 3 Candle Model, in its essence, is designed to provide traders with a unique perspective on market movements, free from generic or rehashed strategies. This tool integrates unique interpretations of the three-candle model and the associated strategies that are distinctly articulated and innovative.
Practical Applications: there are many practical applications of the 3 Candle Model in various trading contexts. This model in conjunction with other strategies to cultivate high-probability trade setups that can enhance performance across diverse market conditions.
Educational Value: This script is crafted with educational value in mind, providing insights that extend beyond mere trading signals. It encourages users to develop a deeper understanding of market mechanics and the interplay between price action, time, and trader psychology.
Conclusion
The 3 Candle Model provides a comprehensive framework for traders to enhance their trading strategies in the futures and forex markets. By understanding and applying the principles of this model alongside the Power of Three, OHLC concepts, and Turtle Soup formations, traders can significantly improve their ability to identify high-probability trades. The emphasis on timing, delivery states, and alignment of ranges ensures that traders are well-equipped to navigate the complexities of market movements, ultimately leading to more consistent and rewarding trading outcomes.
As trading involves risk, it is essential for traders to utilize these principles judiciously and maintain a disciplined approach to their trading strategies. By adhering to the TradingView community guidelines and emphasizing originality, usefulness, and detailed descriptions, this 3 Candle Model script stands as a valuable resource for traders seeking to refine their skills and achieve greater success in the financial markets.
Through this detailed exploration of the 3 Candle Model, traders will not only learn to recognize and exploit key patterns in price action but also appreciate the interconnectedness of various trading strategies that can significantly enhance their performance and profitability.
Support-Resistance breakoutStrategy based on longing resistance breakout and shorting support breakout.
It defines highs and lows using fractal with 2 bars for confirming high/lows. So it has 2 bars lag.
It calculates the difference between sma with defined length (21 by default) of highs and of lows and uses it as alt SR level. This idea I took from synapticEx's indicator Nebula-Advanced-Dynamic-Support-Resistance.
Position enter is the breakout of SR, defined by fractals.
Position exit is: bar change in opposite to position direction > difference is sma of highs and of lows.
Guerrilla AdvancedThis indicator was designed with people without Pro License in mind (Including many of my close friends).
Basically, you will get a combo of few different tools in one box, with ability to turn them on and off with a single check mark, also, you have total control over the input numbers that was used in calculations if you so want to, for example, sometimes when i see a massive bullish up trend, i reduce the short rally from 12 to 8 even 6 to get faster signal for selling the trend.
So, what will you get in this pack?
1- Ichimoko. Yes, you heard it right, although we have it in the default tools but hey, it will use one indicator slot and if you don't have a pro license, you will use that slot
2- Rally. This is an old yet very powerful system for getting buy or sell signals, basically, you get two lines and for making the life easier i draw a cloud between them. when the trend passes above the cloud and it was bellow it in past, right after the very first candle that gets above the cloud you can put the buy order, and vice versa, the moment a candle body enters the cloud, if you want an aggressive signal, you can sell, if not, you may want to wait to see if the candles drop bellow the cloud or not then decide.
3- Resistance Support Cloud. Most of us always heard about resistance and support "lines" but many of us don't know that, in each trend, the trend line itself is a resistance or support line, and when you are going in a bullish or bearish tunnel, the floor and roof of tunnels are again resistance and supports, using this part of the tool, just like rally, you get a cloud that shows you the resistance / support "zone"
4- William Fractals. To be honest, I got this part of the code from another source available around. Why? looking at those fractal indicators, you can easily eyeball the trend line or existence of a tunnel.
5- Different EMA lines. If you are one of those people that use EMA lines for their trading, have fun with them, there are few different standard ones and even a custom one that you can put your desired number for it.
Swiss Knife [MERT]Introduction
The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format.
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Key Features
Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes.
Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection.
Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score.
Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart.
Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots.
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Explanation of Each Indicator
Moving Average Convergence Divergence (MACD)
- Purpose : Measures the relationship between two moving averages of price.
- Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum.
Awesome Oscillator (AO)
- Purpose : Gauges market momentum by comparing recent market movements to historic ones.
- Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum.
Parabolic SAR (SAR)
- Purpose : Identifies potential reversal points in price direction.
- Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend.
SuperTrend
- Purpose : Determines the prevailing market trend.
- Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line.
Detrended Price Oscillator (DPO)
- Purpose : Removes trend from price to identify cycles.
- Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below.
Relative Strength Index (RSI)
- Purpose : Measures the speed and change of price movements.
- Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum.
Stochastic Oscillator
- Purpose : Compares a particular closing price to a range of its prices over a certain period.
- Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions.
Bollinger Bands (BB)
- Purpose : Measures market volatility and provides relative price levels.
- Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness.
Ichimoku Cloud
- Purpose : Provides support and resistance levels, trend direction, and momentum.
- Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud.
Chande Momentum Oscillator (CMO)
- Purpose : Measures momentum on both up and down days.
- Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum.
Donchian Channels
- Purpose : Identifies volatility and potential breakouts.
- Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout.
Average Directional Index (ADX)
- Purpose : Measures the strength of a trend.
- Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend.
Volume Momentum Indicators (VolMom, CumVolMom, POCMom)
- Purpose : Analyze volume to assess buying and selling pressure.
- Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum.
Fractals
- Purpose : Identify potential reversal points in the market.
- Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend.
Divergence Detection
- Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line).
- Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal.
- Note : This functionality utilizes the library from Divergence Indicator .
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Coloring Scheme
Background Color
- Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes.
- Interpretation :
- Green Shades : Indicate bullish market sentiment.
- Red Shades : Indicate bearish market sentiment.
- Intensity : The strength of the color corresponds to the strength of the sentiment score.
Sentiment Table
- Purpose : Displays the status of each indicator across different timeframes.
- Interpretation :
- Green Cell : The indicator suggests a bullish signal.
- Red Cell : The indicator suggests a bearish signal.
- Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe.
Exponential Moving Averages (EMAs)
- Purpose : Provide dynamic support and resistance levels.
- Colors :
- EMA 10 : Lime
- EMA 20 : Yellow
- EMA 50 : Orange
- EMA 100 : Red
- EMA 200 : Purple
Trendlines
- Purpose : Visual representation of support and resistance levels based on pivot points.
- Interpretation :
- Upward Trendlines : Colored green , indicating support levels.
- Downward Trendlines : Colored red , indicating resistance levels.
- Note : Trendlines are drawn using the library from Simple Trendlines .
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Utility of Market Sentiment
The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by:
Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend.
Identifying Reversals : Divergences and fractals can signal potential turning points.
Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades.
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Divergences
Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal.
- Bullish Divergence : Price makes a lower low, but the indicator makes a higher low.
- Bearish Divergence : Price makes a higher high, but the indicator makes a lower high.
The indicator detects divergences for:
RSI
MACD
Stochastic Oscillator
On-Balance Volume (OBV)
Money Flow Index (MFI)
Accumulation/Distribution Line (A/D Line)
By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly.
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Trendlines
Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points:
- Upward Trendlines (Support) : Connect higher lows, indicating an uptrend.
- Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend.
These trendlines help traders visualize the trend direction and potential breakout or reversal points.
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Super Trend Reversals (ST Reversal)
The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders:
Engage Early : Enter the market as reversal momentum builds up.
Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes.
By capturing these reversal points, traders can enhance their trading performance.
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Conclusion
The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions.
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Citations
- Divergence Detection Library : Divergence Indicator by DevLucem
- Trendline Drawing Library : Simple Trendlines by HoanGhetti
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Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions.
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ka66: Swing/Pivot Point LinesThis indicator draws swing-highs and swing-lows, also called pivot highs and lows.
A swing high is a bar which has a higher-high than its surrounding bars (to the left and the right).
A swing low is a bar which has a lower-low than its surrounding bars (to the left and the right).
A common example of a pivot is Bill Williams' Fractal, which specifies that the centre bar must have a higher high than 2 bars to its left, and 2 bars to its right for a swing high, taking into account 5 bars at a time. Similarly, for a swing low, the centre bar must have a lower low than the 2 bars to its left and right.
This indicator allows configurable adjacent bars as input. Entering 2, means it essentially picks out a Williams Fractal. But you can select 1 (say for higher timeframes), using one 1 bar to the left and right of the centre bar.
The indicator will draw Swing/Pivot High/Low as circles at the same price level as the centre bar, till the next one shows up. Drawing is offset so it starts at the centre bar (the swing bar), showing exactly where the pivot bar is.
There are 2 main uses of pivot points, in various strategies:
Market Structure: to objectively define higher-highs/lows and lower-highs/lows in Trend Analysis.
More generally, to then determine if a trend might reverse, or continue as pivot levels are broken.
Messy pivot structures easily point out ranging markets.
There are a few of these, some closed source, which I don't like, since I think people should generally know what they are trading with, and I want to make sure I understand the logic exactly.
FibLines2This script is a new version of "FibLines" which automatically draws Fibonacci Lines on chart.
0% line and 100% line are determined by "Period" and "Delay" parameter.
◆Params
- Period: specifies periods to detect the highest (bearish) fractal and the lowest (bullish) fractal.
- Delay: specifies the number of new bars you ignore.
(👇 old version)
Smart RSI Divergence PRO | Auto Lines + Alerts📌 Purpose
This indicator automatically detects Regular and Hidden RSI Divergences between price action and the RSI oscillator.
It plots divergence lines directly on the chart, labels signals, and includes alerts for automated monitoring.
🧠 How It Works
1. RSI Calculation
RSI is calculated using the selected Source (default: Close) and RSI Length (default: 14).
2. Divergence Detection via Fractals
Swing points on both price and RSI are detected using fractal logic (5-bar patterns).
Regular Divergence:
Bearish: Price forms a higher high, RSI forms a lower high.
Bullish: Price forms a lower low, RSI forms a higher low.
Hidden Divergence:
Bearish: Price forms a lower high, RSI forms a higher high.
Bullish: Price forms a higher low, RSI forms a lower low.
3. Auto Drawing Lines
Lines are drawn automatically between divergence points:
Red = Regular Bearish
Green = Regular Bullish
Orange = Hidden Bearish
Blue = Hidden Bullish
Line width and transparency are adjustable.
4. Labels and Alerts
Labels mark divergence points with up/down arrows.
Alerts trigger for each divergence type.
📈 How to Use
Use Regular Divergences to anticipate trend reversals.
Use Hidden Divergences to confirm trend continuation.
Combine with support/resistance, trendlines, or volume for higher probability setups.
Recommended Timeframes: Works on all timeframes; more reliable on 1h, 4h, and Daily.
Markets: Forex, Crypto, Stocks.
⚙️ Inputs
Source (Close, HL2, etc.)
RSI Length
Toggle Regular / Hidden Divergence visibility
Toggle Lines / Labels
Line Width & Line Transparency
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before using in live trading.
OS AlligatorOS Alligator includes Bill and Justine Williams´ indicators explained both in their "New Trading Dimensions" and "Trading Chaos: Second Edition" books. This script replicates the visual alerts shown on their graphs.
OS Alligator includes:
- Fractals (with labels for easy reading)
- Divergent Bars (signaled by top and bottom triangles)
- Zone bar colors (the bar is green when both AO and AC are green, red when both are red, and black when different)
- Zone buys and sells (subsequent AO of the same color), with letter Z
- Saucer buys and sells, with letter S
- Highest High and Lowest Low tracking (for traling stop setting)
- Balance line (Teeth) crossover alerts
and of course the Alligator's Mouth (Lips, Teeth, Jaw) with SMMA.
All these functions are customizable both in periods and in color. For example if you want to modify the Fractal or HiLo periods you can do so.
You can also add alerts based on any or all indicators.
Thank you for reading. Any comments for improvement are welcome.
-ownsov
Gann Fan Analysis v 3.0The openness of this community is amazing and I have gained a lot from being a member. Hopefully you think this is useful so I can give something back.
This indicator constructs a reference framework of Support and Resistance levels based on Gann Fan ratios. Two fans are created: Support or Bullish fan, and a Resistance or Bearish fan. The origin of the analysis is the lowest pivot in the analysis window set by the length input. The upper bound of the analysis is the highest pivot in the analysis window. This is the only user input that affects the fan calculation. The remaining user input controls the visualization of the fans. The fan calculations are updated as the high and low within the analysis window change. The resistance fan range is based on an assumed 70% retracement.
Indicator also highlights the active Support and Resistance lines of each fan. An alert is also included, based on the price crossing one of these active levels.
Currently I can't figure out how to get the analysis to extend beyond 278 or so bars (not sure what the limitation is) so it isn't really useful for intraday timeframes, but it is reliable on daily and above. I use it on a Weekly view with the analysis length set to 52, and on a daily timeframe with the length set to 260.
I included fractal visualization using Ricardo Santos' Fractals v9 script as a means of confirming the Gann Fan pivots. The two methods seems to correlate well, in my opinion.
The coding is terrible, I'm sure, so please overlook that as this my first complex effort. I'm a total amateur!
Enigma Endgame with Dynamic Trend-Based FibonacciThe Enigma Endgame script combines dynamic trend-based Fibonacci levels with the core principles of the ENIGMA strategy. It provides traders with actionable signals by identifying key levels of fractal support and resistance and highlighting opportunities to trade with market momentum. This tool is designed for multi-timeframe analysis and is especially effective during high-volatility sessions like London and New York.
Purpose and Usefulness
This script was developed to simplify complex market dynamics by integrating Fibonacci principles with ENIGMA's logic of fractal support and resistance. Traders can use it to:
- Identify key breakout and retracement levels dynamically.
- Understand the shift between support and resistance as price action evolves.
- Gain confidence in their entries with real-time signals derived from logical fractal behavior.
By merging Fibonacci levels with fractal-based trading insights, this script offers a unique and comprehensive approach to analyzing market structure.
How It Works
The script uses a dual approach to provide insights:
1. Dynamic Fibonacci Levels:
- Automatically plots Fibonacci retracement and extension levels based on recent high and low swings, adjusting dynamically to current market trends.
- Allows traders to visualize key levels where price might reverse or extend.
2. Fractal Support and Resistance Logic:
- The script identifies fractal support and resistance by analyzing candle formations.
- When a candle body closes below the low of a previous candle, the previous low, which was fractal support, now becomes fractal resistance. The script generates a bearish signal, encouraging traders to look for sell opportunities at or above the previous low.
- Conversely, when a candle body closes above the high of a previous candle, the previous high, which was fractal resistance, becomes fractal support. The script generates a bullish signal, encouraging traders to look for buy opportunities at or below the previous high.
Real-Time Signals
The script marks these transitions with arrows on the chart:
- Bearish arrows indicate broken fractal support turning into resistance.
- Bullish arrows** indicate broken fractal resistance turning into support.
These signals help traders stay aligned with the trend and trade with market momentum.
Key Features
1. Session-Based Analysis: Focuses on high-probability setups by allowing traders to customize session times, such as London or US sessions.
2. Multi-Timeframe Support: Works seamlessly across multiple timeframes for both scalpers and swing traders.
3. Real-Time Alerts: Sends customizable alerts when price interacts with critical Fibonacci levels or fractal support/resistance shifts.
How to Use the Script
1. Apply the script to a clean chart for clear visualization. Avoid combining it with other scripts unless necessary.
2. Use the arrows to identify shifts in fractal support and resistance and validate opportunities for buy/sell trades.
3. Monitor the dynamic Fibonacci levels to find confluence with key price areas.
4. Customize session times to focus on high-probability trading hours.
Key Notes for Traders
- This script provides insights based on logical market structure but should be used alongside proper risk management and trading plans.
- The fractal-based approach works well in conjunction with dynamic Fibonacci levels, helping traders build confidence in their strategy.
- Adapt the script settings to match your unique trading style and timeframe preferences.
By offering a seamless integration of fractal logic and Fibonacci principles, Enigma Endgame empowers traders with actionable insights to navigate markets effectively.
Scalping PullBack Tool R1 by JustUncleLDescription
This study project is a Scalping Pullback trading Tool that incorporates the majority of the indicators needed to analyse and scalp Trends for Pull Backs and reversals on 1min, 5min or 15min charts. The set up utilies Heikin Ashi candle charts. Incorporated within this tool are the following indicators:
1. Major industry (Banks) recognised important EMAs in an EMA Ribbon:
Green = EMA89
Blue = EMA200
Black = EMA633
2. The 36EMA (default) High/Low+Close Price Action Channel (PAC).
3. Fractals
4. HH, LH, LL, HL finder to help with drawing Trend lines and mini Trend Lines.
5. Coloured coded Bar high lighting based on the PAC:
blue = bar closed above PAC
red = bar closed below PAC
gray = bar closed inside PAC
red line = EMA36 of bar close
Setup and hints:
Set the chart to Heikin Ashi Candles.
Add "Sweetspot Gold10" indicator to the chart as well to help with support and resistance finding and shows where the important "00" and "0" lines are.
When price is above the PAC(blue bars) we are only looking to buy as price comes back to the PAC
When price is below the PAC(red bars), we are only looking to sell when price comes back to the PAC
What we’re looking for when price comes back into the PAC we draw mini Trendlines utilising the Fractals and HH/LL points to guide your TL drawing.
Now look for the trend to pull back and break the drawn TL. That's is when we place the scalp trade.
So we are looking for continuation signals in terms of a strong, momentum driven pullbacks (normally short term 10-20 pips) of the EMA36.
The other EMAs are there to check for other Pullbacks when EMA36 is broken.
Other than the SweetSpot Gold10 indicator, you should not need any other indicator to scalp the pullbacks.
References:
Fractals V8 by RicardoSantos
Price Action Trading System v0.3 by JustUncleL
SweetSpot Gold10 R1 by JustUncleL
www.swing-trade-stocks.com
www.forexstrategiesresources.com
Uptrick: FRAMA Matrix RSIUptrick: FRAMA Matrix RSI
Introduction
The Uptrick: FRAMA Matrix RSI is a momentum-based indicator that integrates the Relative Strength Index (RSI) with the Fractal Adaptive Moving Average (FRAMA). By applying FRAMA's adaptive smoothing to RSI—and further refining it with a Zero-Lag Moving Average (ZLMA)—this script creates a refined and reliable momentum oscillator. The indicator now includes enhanced divergence detection, potential reversal signals, customizable buy/sell signal options, an internal stats table, and a fully customizable bar coloring system for an enhanced visual trading experience.
Why Combine RSI with FRAMA
Traditional RSI is a well-known momentum indicator but has several limitations. It is highly sensitive to price fluctuations, often generating false signals in choppy or volatile markets. FRAMA, in contrast, adapts dynamically to price changes by adjusting its smoothing factor based on market conditions.
By integrating FRAMA into RSI calculations, this indicator reduces noise while preserving RSI's ability to track momentum, adapts to volatility by reducing lag in trending markets and smoothing out choppiness in ranging conditions, enhances trend-following capability for more reliable momentum shifts, and refines overbought and oversold signals by adjusting to the current market structure.
With the new enhancements, such as a manual alpha input, noise filtering, divergence detection, and multiple buy/sell signal options, the indicator offers even greater flexibility and precision for traders. This combination improves the standard RSI by making it more adaptive and responsive to market changes.
Originality
This indicator is unique because it applies FRAMA's adaptive smoothing technique to RSI, creating a dynamic momentum oscillator that adjusts to different market conditions. Many traditional RSI-based indicators either use fixed smoothing methods like exponential moving averages or employ basic RSI calculations without adjusting for volatility.
This script stands out by integrating several elements, including the fractal dimension-based smoothing of FRAMA to reduce noise while retaining responsiveness, the use of Zero-Lag Moving Average smoothing to enhance trend sensitivity and reduce lag, divergence detection to highlight mismatches between price action and RSI momentum, a noise filter and manual alpha option to prevent minor fluctuations from generating false signals, customizable buy/sell signal options that let traders choose between ZLMA-based or FRAMA RSI-based signals, an internal stats table displaying real-time FRAMA calculations such as fractal dimension and the adaptive alpha factor, and a fully customizable bar coloring system to visually distinguish bullish, bearish, and neutral conditions.
Features
Adaptive FRAMA RSI
The indicator applies FRAMA to RSI values, making the momentum oscillator adaptive to volatility while filtering out noise. Unlike a traditional RSI that reacts equally to all price movements, FRAMA RSI adjusts its smoothing factor based on market structure, making it more effective for identifying true momentum shifts.
Zero-Lag Moving Average (ZLMA)
A smoothing technique that minimizes lag while preserving the responsiveness of price movements. It is applied to the FRAMA RSI to further refine signals and ensure smoother trend detection.
Bullish and Bearish Threshold Crossovers
This system compares FRAMA RSI to a user-defined threshold (default is 50). When FRAMA RSI moves above the threshold, it indicates bullish momentum, while movement below signals bearish conditions. The enhanced noise filter ensures that only significant moves trigger signals.
Noise Filter and Manual Alpha
A new noise filter input prevents tiny fluctuations from triggering false signals. In addition, a manual alpha option allows traders to override the automatically computed smoothing factor with a custom value, providing extra control over the indicator’s sensitivity.
Divergence Detection
The indicator identifies divergence patterns by comparing FRAMA RSI pivots to price action. Bullish divergence occurs when price makes a lower low while FRAMA RSI makes a higher low, and bearish divergence occurs when price makes a higher high while FRAMA RSI makes a lower high. These signals can help traders anticipate potential reversals.
Reversal Signals
Labels appear on the chart when FRAMA RSI confirms classic RSI overbought (70) or oversold (30) conditions, providing visual cues for potential trend reversals.
Buy and Sell Signal Options
Traders can now choose between two signal-generation methods. ZLMA-based signals trigger when the ZLMA of FRAMA RSI crosses key overbought (70) or oversold (30) levels, while FRAMA RSI-based signals trigger when FRAMA RSI itself crosses these levels. This added flexibility allows users to tailor the indicator to their preferred trading style.
ZLMA:
FRAMA:
Customizable Alerts
Alerts notify traders when FRAMA RSI crosses key levels, divergence signals occur, reversal conditions are met, or buy/sell signals trigger. This ensures that important trading events are not missed.
Fully Customizable Bar Coloring System
Users can color bars based on different conditions, enhancing visual clarity. Bar coloring modes include: FRAMA RSI threshold (bars change color based on whether FRAMA RSI is above or below the threshold), ZLMA crossover (bars change when ZLMA crosses overbought or oversold levels), buy/sell signals (bars change when official signals trigger), divergence (bars highlight when bullish or bearish divergence is detected), and reversals (bars indicate when RSI reaches overbought or oversold conditions confirmed by FRAMA RSI). The system also remembers the last applied bar color, ensuring a smooth visual transition.
Input Parameters and Features
Core Inputs
RSI Length (default: 14) defines the period for RSI calculations.
FRAMA Lookback (default: 16) determines the length for the FRAMA smoothing function.
RSI Bull Threshold (default: 50) sets the level above which the market is considered bullish and below which it is bearish.
Noise Filter (default: 1.0) ensures that small fluctuations do not trigger false bullish or bearish signals.
Additional Features
Show Bull and Bear Alerts (default: true) enables notifications when FRAMA RSI crosses the threshold.
Enable Divergence Detection (default: false) highlights bullish and bearish divergences based on price and FRAMA RSI pivots.
Show Potential Reversal Signals (default: false) identifies overbought (70) and oversold (30) levels as possible trend reversal points.
Buy and Sell Signal Option (default: ZLMA) allows traders to choose between ZLMA-based signals or FRAMA RSI-based signals for trade entry.
ZLMA Enhancements
ZLMA Length (default: 14) determines the period for the Zero-Lag Moving Average applied to FRAMA RSI.
Visualization Options
Show Internal Stats Table (default: false) displays real-time FRAMA calculations, including fractal dimension and the adaptive alpha smoothing factor.
Show Threshold FRAMA Signals (default: false) plots buy and sell labels when FRAMA RSI crosses the threshold level.
How It Works
FRAMA Calculation
FRAMA dynamically adjusts smoothing based on the price fractal dimension. The alpha smoothing factor is derived from the fractal dimension or can be set manually to maintain responsiveness.
RSI with FRAMA Smoothing
RSI is calculated using the user-defined lookback period. FRAMA is then applied to the RSI to make it more adaptive to volatility. Optionally, ZLMA is applied to further refine the signals and reduce lag.
Bullish and Bearish Threshold Crosses
A bullish condition occurs when FRAMA RSI crosses above the threshold, while a bearish condition occurs when it falls below. The noise filter ensures that only significant trend shifts generate signals.
Buy and Sell Signal Options
Traders can choose between ZLMA crossovers or FRAMA RSI crossovers as the basis for buy and sell signals, offering flexibility in trade entry timing.
Divergence Detection
The indicator identifies divergences where price action and FRAMA RSI momentum do not align, potentially signaling upcoming reversals.
Reversal Signal Labels
When classic RSI overbought or oversold levels are confirmed by FRAMA RSI conditions, reversal labels are added on the chart to highlight potential exhaustion points.
Bar Coloring System
Bars are dynamically colored based on various conditions such as RSI thresholds, ZLMA crossovers, buy/sell signals, divergence, and reversals, allowing traders to quickly interpret market sentiment.
Alerts and Internal Stats
Customizable alerts notify traders of key events, and an optional internal stats table displays real-time calculations (fractal dimension, alpha value, and RSI values) to help users understand the underlying dynamics of the indicator.
Summary
The Uptrick: FRAMA Matrix RSI offers an enhanced approach to momentum analysis by combining RSI with adaptive FRAMA smoothing and additional layers of signal refinement. The indicator now includes adaptive RSI smoothing to reduce noise and improve responsiveness, Zero-Lag Moving Average filtering to minimize lag, divergence and reversal detection to identify potential turning points, customizable buy/sell signal options that let traders choose between different signal methodologies, a fully customizable bar coloring system to visually distinguish market conditions, and an internal stats table for real-time insight into FRAMA calculation parameters.
Whether used for trend confirmation, divergence detection, or momentum-based strategies, this indicator provides a powerful and adaptive approach to trading.
Disclaimer
This script is for informational and educational purposes only. Trading involves risk, and past performance does not guarantee future results. Always conduct proper research and consult with a financial advisor before making trading decisions.
Pivot Points LIVE [CHE]Title:
Pivot Points LIVE Indicator
Subtitle:
Advanced Pivot Point Analysis for Real-Time Trading
Presented by:
Chervolino
Date:
September 24, 2024
Introduction
What are Pivot Points?
Definition:
Pivot Points are technical analysis indicators used to determine potential support and resistance levels in financial markets.
Purpose:
They help traders identify possible price reversal points and make informed trading decisions.
Overview of Pivot Points LIVE :
A comprehensive indicator designed for real-time pivot point analysis.
Offers advanced features for enhanced trading strategies.
Key Features
Pivot Points LIVE Includes:
Dynamic Pivot Highs and Lows:
Automatically detects and plots pivot high (HH, LH) and pivot low (HL, LL) points.
Customizable Visualization:
Multiple options to display markers, price labels, and support/resistance levels.
Fractal Breakouts:
Identifies and marks breakout and breakdown events with symbols.
Line Connection Modes:
Choose between "All Separate" or "Sequential" modes for connecting pivot points.
Pivot Extension Lines:
Extends lines from the latest pivot point to the current bar for trend analysis.
Alerts:
Configurable alerts for breakout and breakdown events.
Inputs and Configuration
Grouping Inputs for Easy Customization:
Source / Length Left / Length Right:
Pivot High Source: High price by default.
Pivot Low Source: Low price by default.
Left and Right Lengths: Define the number of bars to the left and right for pivot detection.
Colors: Customizable colors for pivot high and low markers.
Options:
Display Settings:
Show HH, LL, LH, HL markers and price labels.
Display support/resistance level extensions.
Option to show levels as a fractal chaos channel.
Enable fractal breakout/down symbols.
Line Connection Mode:
Choose between "All Separate" or "Sequential" for connecting lines.
Line Management:
Set maximum number of lines to display.
Customize line colors, widths, and styles.
Pivot Extension Line:
Visibility: Toggle the display of the last pivot extension line.
Customization: Colors, styles, and width for extension lines.
How It Works - Calculating Pivot Points
Pivot High and Pivot Low Detection:
Pivot High (PH):
Identified when a high price is higher than a specified number of bars to its left and right.
Pivot Low (PL):
Identified when a low price is lower than a specified number of bars to its left and right.
Higher Highs, Lower Highs, Higher Lows, Lower Lows:
Higher High (HH): Current PH is higher than the previous PH.
Lower High (LH): Current PH is lower than the previous PH.
Higher Low (HL): Current PL is higher than the previous PL.
Lower Low (LL): Current PL is lower than the previous PL.
Visual Elements
Markers and Labels:
Shapes:
HH and LH: Downward triangles above the bar.
HL and LL: Upward triangles below the bar.
Labels:
Optionally display the price levels of HH, LH, HL, and LL on the chart.
Support and Resistance Levels:
Extensions:
Lines extending from pivot points to indicate potential support and resistance zones.
Chaos Channels:
Display levels as a fractal chaos channel for enhanced trend analysis.
Fractal Breakout Symbols:
Buy Signals: Upward triangles below the bar.
Sell Signals: Downward triangles above the bar.
Slide 7: Line Connection Modes
All Separate Mode:
Description:
Connects pivot highs with pivot highs and pivot lows with pivot lows separately.
Use Case:
Ideal for traders who want to analyze highs and lows independently.
Sequential Mode:
Description:
Connects all pivot points in the order they occur, regardless of being high or low.
Use Case:
Suitable for identifying overall trend direction and momentum.
Pivot Extension Lines
Purpose:
Trend Continuation:
Visualize the continuation of the latest pivot point's price level.
Customization:
Colors:
Differentiate between bullish and bearish extensions.
Styles:
Solid, dashed, or dotted lines based on user preference.
Width:
Adjustable line thickness for better visibility.
Dynamic Updates:
The extension line updates in real-time as new bars form, providing ongoing trend insights.
Alerts and Notifications
Configurable Alerts:
Fractal Break Arrow:
Triggered when a breakout or breakdown occurs.
Long and Short Signals:
Specific alerts for bullish breakouts (Long) and bearish breakdowns (Short).
Benefits:
Timely Notifications:
Stay informed of critical market movements without constant monitoring.
Automated Trading Strategies:
Integrate with trading bots or automated systems for executing trades based on alerts.
Customization and Optimization
User-Friendly Inputs:
Adjustable Parameters:
Tailor pivot detection sensitivity with left and right lengths.
Color and Style Settings:
Match the indicator aesthetics to personal or platform preferences.
Line Management:
Maximum Lines Displayed:
Prevent chart clutter by limiting the number of lines.
Dynamic Line Handling:
Automatically manage and delete old lines to maintain chart clarity.
Flexibility:
Adapt to Different Markets:
Suitable for various financial instruments including stocks, forex, and cryptocurrencies.
Scalability:
Efficiently handles up to 500 labels and 100 lines for comprehensive analysis.
Practical Use Cases
Identifying Key Support and Resistance:
Entry and Exit Points:
Use pivot levels to determine optimal trade entry and exit points.
Trend Confirmation:
Validate market trends through the connection of pivot points.
Breakout and Breakdown Strategies:
Trading Breakouts:
Enter long positions when price breaks above pivot highs.
Trading Breakdowns:
Enter short positions when price breaks below pivot lows.
Risk Management:
Setting Stop-Loss and Take-Profit Levels:
Utilize pivot levels to place strategic stop-loss and take-profit orders.
Slide 12: Benefits for Traders
Real-Time Analysis:
Provides up-to-date pivot points for timely decision-making.
Enhanced Visualization:
Clear markers and lines improve chart readability and analysis efficiency.
Customizable and Flexible:
Adapt the indicator to fit various trading styles and strategies.
Automated Alerts:
Stay ahead with instant notifications on key market events.
Comprehensive Toolset:
Combines pivot points with fractal analysis for deeper market insights.
Conclusion
Pivot Points LIVE is a robust and versatile indicator designed to enhance your trading strategy through real-time pivot point analysis. With its advanced features, customizable settings, and automated alerts, it equips traders with the tools needed to identify key market levels, execute timely trades, and manage risks effectively.
Ready to Elevate Your Trading?
Explore Pivot Points LIVE and integrate it into your trading toolkit today!
Q&A
Questions?
Feel free to ask any questions or request further demonstrations of the Pivot Points LIVE indicator.
Harish Algo 2The script "Harish Algo 2" is a Pine Script-based TradingView indicator that automatically identifies significant trendlines based on fractal points and tracks price interactions with those trendlines. Key features include:
Fractal Detection: The script identifies fractal highs and lows, using a configurable fractal period, to serve as pivot points for generating trendlines. Fractal highs are marked in blue, and fractal lows are marked in red.
Dynamic Trendlines: It draws trendlines between consecutive fractal points, with a limit on the maximum number of active trendlines. The trendlines can be extended either in both directions or to the right, as per user input. The line width can also be customized.
Support/Resistance Counting: Each trendline tracks how many times the price interacts with it. If the price approaches the line from above and touches or stays near it, the line is considered a support. If the price approaches from below, it is considered a resistance. These counts are used to modify the trendline's color and appearance.
Trendlines with 2 support interactions turn green.
Trendlines with 2 resistance interactions turn red.
Trendlines with 3 or more interactions turn black.
Trendline Styling: Trendlines that extend over a long period (more than 100 bars) change to a dotted style to highlight their persistence.
Break Detection: The script monitors if the price crosses a trendline, signaling a potential breakout or breakdown. Once a trendline is broken, it stops extending further.
Trendline Removal: The script ensures that only a limited number of trendlines are active at a time. If the maximum number of trendlines is reached, the oldest trendline is removed to make space for new ones.
This indicator is designed to help traders visualize important trendlines, spot potential support and resistance levels, and detect breakouts or breakdowns based on price movement.
Moving Averages ProxyLibrary "MovingAveragesProxy"
Moving Averages Proxy - Library of all moving averages spread out in different libraries
rvwap(_src, fixedTfInput, minsInput, hoursInput, daysInput, minBarsInput)
Calculates the Rolling VWAP (customized VWAP developed by the team of TradingView)
Parameters:
_src : (float) Source. Default: close
fixedTfInput : (bool) Use a fixed time period. Default: false
minsInput : (int) Minutes. Default: 0
hoursInput : (int) Hours. Default: 0
daysInput : (int) Days. Default: 1
minBarsInput : (int) Bars. Default: 10
Returns: (float) Rolling VWAP
correlationMa(src, len, factor)
Correlation Moving Average
Parameters:
src : (float) Source. Default: close
len : (int) Length
factor : (float) Factor. Default: 1.7
Returns: (float) Correlation Moving Average
regma(src, len, lambda)
Regularized Exponential Moving Average
Parameters:
src : (float) Source. Default: close
len : (int) Length
lambda : (float) Lambda. Default: 0.5
Returns: (float) Regularized Exponential Moving Average
repma(src, len)
Repulsion Moving Average
Parameters:
src : (float) Source. Default: close
len : (int) Length
Returns: (float) Repulsion Moving Average
epma(src, length, offset)
End Point Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
offset : (float) Offset. Default: 4
Returns: (float) End Point Moving Average
lc_lsma(src, length)
1LC-LSMA (1 line code lsma with 3 functions)
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) 1LC-LSMA Moving Average
aarma(src, length)
Adaptive Autonomous Recursive Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Adaptive Autonomous Recursive Moving Average
alsma(src, length)
Adaptive Least Squares
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Adaptive Least Squares
ahma(src, length)
Ahrens Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Ahrens Moving Average
adema(src)
Ahrens Moving Average
Parameters:
src : (float) Source. Default: close
Returns: (float) Moving Average
autol(src, lenDev)
Auto-Line
Parameters:
src : (float) Source. Default: close
lenDev : (int) Length for standard deviation
Returns: (float) Auto-Line
fibowma(src, length)
Fibonacci Weighted Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
fisherlsma(src, length)
Fisher Least Squares Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
leoma(src, length)
Leo Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
linwma(src, period, weight)
Linear Weighted Moving Average
Parameters:
src : (float) Source. Default: close
period : (int) Length
weight : (int) Weight
Returns: (float) Moving Average
mcma(src, length)
McNicholl Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
srwma(src, length)
Square Root Weighted Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
EDSMA(src, len)
Ehlers Dynamic Smoothed Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: EDSMA smoothing.
dema(x, t)
Double Exponential Moving Average.
Parameters:
x : Series to use ('close' is used if no argument is supplied).
t : Lookback length to use.
Returns: DEMA smoothing.
tema(src, len)
Triple Exponential Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: TEMA smoothing.
smma(src, len)
Smoothed Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: SMMA smoothing.
hullma(src, len)
Hull Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: Hull smoothing.
frama(x, t)
Fractal Reactive Moving Average.
Parameters:
x : Series to use ('close' is used if no argument is supplied).
t : Lookback length to use.
Returns: FRAMA smoothing.
kama(x, t)
Kaufman's Adaptive Moving Average.
Parameters:
x : Series to use ('close' is used if no argument is supplied).
t : Lookback length to use.
Returns: KAMA smoothing.
vama(src, len)
Volatility Adjusted Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: VAMA smoothing.
donchian(len)
Donchian Calculation.
Parameters:
len : Lookback length to use.
Returns: Average of the highest price and the lowest price for the specified look-back period.
Jurik(src, len)
Jurik Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: JMA smoothing.
xema(src, len)
Optimized Exponential Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: XEMA smoothing.
ehma(src, len)
EHMA - Exponential Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Exponential Hull Moving Average (EHMA)
covwema(src, len)
Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
covwma(src, len)
Coefficient of Variation Weighted Moving Average (COVWMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Moving Average (COVWMA)
eframa(src, len, FC, SC)
Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
Parameters:
src : Source
len : Period
FC : Lower Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
SC : Upper Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
Returns: Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
etma(src, len)
Exponential Triangular Moving Average (ETMA)
Parameters:
src : Source
len : Period
Returns: Exponential Triangular Moving Average (ETMA)
rma(src, len)
RMA - RSI Moving average
Parameters:
src : Source
len : Period
Returns: RSI Moving average (RMA)
thma(src, len)
THMA - Triple Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Triple Hull Moving Average (THMA)
vidya(src, len)
Variable Index Dynamic Average (VIDYA)
Parameters:
src : Source
len : Period
Returns: Variable Index Dynamic Average (VIDYA)
zsma(src, len)
Zero-Lag Simple Moving Average (ZSMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Simple Moving Average (ZSMA)
zema(src, len)
Zero-Lag Exponential Moving Average (ZEMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Exponential Moving Average (ZEMA)
evwma(src, len)
EVWMA - Elastic Volume Weighted Moving Average
Parameters:
src : Source
len : Period
Returns: Elastic Volume Weighted Moving Average (EVWMA)
tt3(src, len, a1_t3)
Tillson T3
Parameters:
src : Source
len : Period
a1_t3 : Tillson T3 Volume Factor
Returns: Tillson T3
gma(src, len)
GMA - Geometric Moving Average
Parameters:
src : Source
len : Period
Returns: Geometric Moving Average (GMA)
wwma(src, len)
WWMA - Welles Wilder Moving Average
Parameters:
src : Source
len : Period
Returns: Welles Wilder Moving Average (WWMA)
cma(src, len)
Corrective Moving average (CMA)
Parameters:
src : Source
len : Period
Returns: Corrective Moving average (CMA)
edma(src, len)
Exponentially Deviating Moving Average (MZ EDMA)
Parameters:
src : Source
len : Period
Returns: Exponentially Deviating Moving Average (MZ EDMA)
rema(src, len)
Range EMA (REMA)
Parameters:
src : Source
len : Period
Returns: Range EMA (REMA)
sw_ma(src, len)
Sine-Weighted Moving Average (SW-MA)
Parameters:
src : Source
len : Period
Returns: Sine-Weighted Moving Average (SW-MA)
mama(src, len)
MAMA - MESA Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: MESA Adaptive Moving Average (MAMA)
fama(src, len)
FAMA - Following Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Following Adaptive Moving Average (FAMA)
hkama(src, len)
HKAMA - Hilbert based Kaufman's Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Hilbert based Kaufman's Adaptive Moving Average (HKAMA)
getMovingAverage(type, src, len, lsmaOffset, inputAlmaOffset, inputAlmaSigma, FC, SC, a1_t3, fixedTfInput, daysInput, hoursInput, minsInput, minBarsInput, lambda, volumeWeighted, gamma_aarma, smooth, linweight, volatility_lookback, jurik_phase, jurik_power)
Abstract proxy function that invokes the calculation of a moving average according to type
Parameters:
type : (string) Type of moving average
src : (float) Source of series (close, high, low, etc.)
len : (int) Period of loopback to calculate the average
lsmaOffset : (int) Offset for Least Squares MA
inputAlmaOffset : (float) Offset for ALMA
inputAlmaSigma : (float) Sigma for ALMA
FC : (int) Lower Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
SC : (int) Upper Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
a1_t3 : (float) Tillson T3 Volume Factor
fixedTfInput : (bool) Use a fixed time period in Rolling VWAP
daysInput : (int) Days in Rolling VWAP
hoursInput : (int) Hours in Rolling VWAP
minsInput : (int) Minutrs in Rolling VWAP
minBarsInput : (int) Bars in Rolling VWAP
lambda : (float) Regularization Constant in Regularized EMA
volumeWeighted : (bool) Apply volume weighted calculation in selected moving average
gamma_aarma : (float) Gamma for Adaptive Autonomous Recursive Moving Average
smooth : (float) Smooth for Adaptive Least Squares
linweight : (float) Weight for Volume Weighted Moving Average
volatility_lookback : (int) Loopback for Volatility Adjusted Moving Average
jurik_phase : (int) Phase for Jurik Moving Average
jurik_power : (int) Power for Jurik Moving Average
Returns: (float) Moving average
Information-Geometric Market DynamicsInformation-Geometric Market Dynamics
The Information Field: A Geometric Approach to Market Dynamics
By: DskyzInvestments
Foreword: Beyond the Shadows on the Wall
If you have traded for any length of time, you know " the feeling ." It is the frustration of a perfect setup that fails, the whipsaw that stops you out just before the real move, the nagging sense that the chart is telling you only half the story. For decades, technical analysis has relied on interpreting the shadows—the patterns left behind by price. We draw lines on these shadows, apply indicators to them, and hope they reveal the future.
But what if we could stop looking at the shadows and, instead, analyze the object casting them?
This script introduces a new paradigm for market analysis: Information-Geometric Market Dynamics (IGMD) . The core premise of IGMD is that the price chart is merely a one-dimensional projection of a much richer, higher-dimensional reality—an " information field " generated by the collective actions and beliefs of all market participants.
This is not just another collection of indicators. It is a unified framework for measuring the geometry of the market's information field—its memory, its complexity, its uncertainty, its causal flows—and making high-probability decisions based on that deeper reality. By fusing advanced mathematical and informational concepts, IGMD provides a multi-faceted lens through which to view market behavior, moving beyond simple price action into the very structure of market information itself.
Prepare to move beyond the flatland of the price chart. Welcome to the information field.
The IGMD Framework: A Multi-Kernel Approach
What is a Kernel? The Heart of Transformation
In mathematics and data science, a kernel is a powerful and elegant concept. At its core, a kernel is a function that takes complex, often inscrutable data and transforms it into a more useful format. Think of it as a specialized lens or a mathematical "probe." You cannot directly measure abstract concepts like "market memory" or "trend quality" by looking at a price number. First, you must process the raw price data through a specific mathematical machine—a kernel—that is designed to output a measurement of that specific property. Kernels operate by performing a sort of "similarity test," projecting data into a higher-dimensional space where hidden patterns and relationships become visible and measurable.
Why do creators use them? We use kernels to extract features —meaningful pieces of information—that are not explicitly present in the raw data. They are the essential tools for moving beyond surface-level analysis into the very DNA of market behavior. A simple moving average can tell you the average price; a suite of well-chosen kernels can tell you about the character of the price action itself.
The Alchemist's Challenge: The Art of Fusion
Using a single kernel is a challenge. Using five distinct, computationally demanding mathematical engines in unison is an immense undertaking. The true difficulty—and artistry—lies not just in using one kernel, but in fusing the outputs of many . Each kernel provides a different perspective, and they can often give conflicting signals. One kernel might detect a strong trend, while another signals rising chaos and uncertainty. The IGMD script's greatest strength is its ability to act as this alchemist, synthesizing these disparate viewpoints through a weighted fusion process to produce a single, coherent picture of the market's state. It required countless hours of testing and calibration to balance the influence of these five distinct analytical engines so they work in harmony rather than cacophony.
The Five Kernels of Market Dynamics
The IGMD script is built upon a foundation of five distinct kernels, each chosen to probe a unique and critical dimension of the market's information field.
1. The Wavelet Kernel (The "Microscope")
What it is: The Wavelet Kernel is a signal processing function designed to decompose a signal into different frequency scales. Unlike a Fourier Transform that analyzes the entire signal at once, the wavelet slides across the data, providing information about both what frequencies are present and when they occurred.
The Kernels I Use:
Haar Kernel: The simplest wavelet, a square-wave shape defined by the coefficients . It excels at detecting sharp, sudden changes.
Daubechies 2 (db2) Kernel: A more complex and smoother wavelet shape that provides a better balance for analyzing the nuanced ebb and flow of typical market trends.
How it Works in the Script: This kernel is applied iteratively. It first separates the finest "noise" (detail d1) from the first level of trend (approximation a1). It then takes the trend a1 and repeats the process, extracting the next level of cycle (d2) and trend (a2), and so on. This hierarchical decomposition allows us to separate short-term noise from the long-term market "thesis."
2. The Hurst Exponent Kernel (The "Memory Gauge")
What it is: The Hurst Exponent is derived from a statistical analysis kernel that measures the "long-term memory" or persistence of a time series. It is the definitive measure of whether a series is trending (H > 0.5), mean-reverting (H < 0.5), or random (H = 0.5).
How it Works in the Script: The script employs a method based on Rescaled Range (R/S) analysis. It calculates the average range of price movements over increasingly larger time lags (m1, m2, m4, m8...). The slope of the line plotting log(range) vs. log(lag) is the Hurst Exponent. Applying this complex statistical analysis not to the raw price, but to the clean, wavelet-decomposed trend lines, is a key innovation of IGMD.
3. The Fractal Dimension Kernel (The "Complexity Compass")
What it is: This kernel measures the geometric complexity or "jaggedness" of a price path, based on the principles of fractal geometry. A straight line has a dimension of 1; a chaotic, space-filling line approaches a dimension of 2.
How it Works in the Script: We use a version based on Ehlers' Fractal Dimension Index (FDI). It calculates the rate of price change over a full lookback period (N3) and compares it to the sum of the rates of change over the two halves of that period (N1 + N2). The formula d = (log(N1 + N2) - log(N3)) / log(2) quantifies how much "longer" and more convoluted the price path was than a simple straight line. This kernel is our primary filter for tradeable (low complexity) vs. untradeable (high complexity) conditions.
4. The Shannon Entropy Kernel (The "Uncertainty Meter")
What it is: This kernel comes from Information Theory and provides the purest mathematical measure of information, surprise, or uncertainty within a system. It is not a measure of volatility; a market moving predictably up by 10 points every bar has high volatility but zero entropy .
How it Works in the Script: The script normalizes price returns by the ATR, categorizes them into a discrete number of "bins" over a lookback window, and forms a probability distribution. The Shannon Entropy H = -Σ(p_i * log(p_i)) is calculated from this distribution. A low H means returns are predictable. A high H means returns are chaotic. This kernel is our ultimate gauge of market conviction.
5. The Transfer Entropy Kernel (The "Causality Probe")
What it is: This is by far the most advanced and computationally intensive kernel in the script. Transfer Entropy is a non-parametric measure of directed information flow between two time series. It moves beyond correlation to ask: "Does knowing the past of Volume genuinely reduce our uncertainty about the future of Price?"
How it Works in the Script: To make this work, the script discretizes both price returns and the chosen "driver" (e.g., OBV) into three states: "up," "down," or "neutral." It then builds complex conditional probability tables to measure the flow of information in both directions. The Net Transfer Entropy (TE Driver→Price minus TE Price→Driver) gives us a direct measure of causality . A positive score means the driver is leading price, confirming the validity of the move. This is a profound leap beyond traditional indicator analysis.
Chapter 3: Fusion & Interpretation - The Field Score & Dashboard
Each kernel is a specialist providing a piece of the puzzle. The Field Score is where they are fused into a single, comprehensive reading. It's a weighted sum of the normalized scores from all five kernels, producing a single number from -1 (maximum bearish information field) to +1 (maximum bullish information field). This is the ultimate "at-a-glance" metric for the market's net state, and it is interpreted through the dashboard.
The Dashboard: Your Mission Control
Field Score & Regime: The master metric and its plain-English interpretation ("Uptrend Field", "Downtrend Field", "Transitional").
Kernel Readouts (Wave Align, H(w), FDI, etc.): The live scores of each individual kernel. This allows you to see why the Field Score is what it is. A high Field Score with all components in agreement (all green or red) is a state of High Coherence and represents a high-quality setup.
Market Context: Standard metrics like RSI and Volume for additional confluence.
Signals: The raw and adjusted confluence counts and the final, calculated probability scores for potential long and short entries.
Pattern: Shows the dominant candlestick pattern detected within the currently forming APEX range box and its calculated confidence percentage.
Chapter 4: Mastering the Controls - The Inputs Menu
Every parameter is a lever to fine-tune the IGMD engine.
📊 Wavelet Transform: Kernel ( Haar for sharp moves, db2 for smooth trends) and Scales (depth of analysis) let you tune the script's core microscope to your asset's personality.
📈 Hurst Exponent: The Window determines if you're assessing short-term or long-term market memory.
🔍 Fractal Dimension & ⚡ Entropy Volatility: Adjust the lookback windows to make these kernels more or less sensitive to recent price action. Always keep "Normalize by ATR" enabled for Entropy for consistent results.
🔄 Transfer Entropy: Driver lets you choose what causal force to measure (e.g., OBV, Volume, or even an external symbol like VIX). The throttle setting is a crucial performance tool, allowing you to balance precision with script speed.
⚡ Field Fusion • Weights: This is where you can customize the model's "brain." Increase the weights for the kernels that best align with your trading philosophy (e.g., w_hurst for trend followers, w_fdi for chop avoiders).
📊 Signal Engine: Mode offers presets from Conservative to Aggressive . Min Confluence sets your evidence threshold. Dynamic Confluence is a powerful feature that automatically adapts this threshold to the market regime.
🎨 Visuals & 📏 Support/Resistance: These inputs give you full control over the chart's appearance, allowing you to toggle every visual element for a setup that is as clean or as data-rich as you desire.
Chapter 5: Reading the Battlefield - On-Chart Visuals
Pattern Boxes (The Large Rectangles): These are not simple range boxes. They appear when the Field Score crosses a significance threshold, signaling a potential ignition point.
Color: The color reflects the dominant candlestick pattern that has occurred within that box's duration (e.g., green for Bull Engulf).
Label: Displays the dominant pattern, its duration in bars, and a calculated Confidence % based on field strength and pattern clarity.
Bar Pattern Boxes (The Small Boxes): If enabled, these highlight individual, significant candlestick patterns ( BE for Bull Engulf, H for Hammer) on a bar-by-bar basis.
Signal Markers (▲ and ▼): These appear only when the Signal Engine's criteria are all met. The number is the calculated Probability Score .
RR Rails (Dashed Lines): When a signal appears, these lines automatically plot the Entry, Stop Loss (based on ATR), and two Take Profit targets (based on Risk/Reward ratios). They dynamically break and disappear as price touches each level.
Support & Resistance Lines: Plots of the highest high ( Resistance ) and lowest low ( Support ) over a lookback, providing key structural levels.
Chapter 6: Development Philosophy & A Final Word
One single question: " What is the market really doing? " It represents a triumph of complexity, blending concepts from signal processing, chaos theory, and information theory into a cohesive framework. It is offered for educational and analytical purposes and does not constitute financial advice. Its goal is to elevate your analysis from interpreting flat shadows to measuring the rich, geometric reality of the market's information field.
As the great mathematician Benoit Mandelbrot , father of fractal geometry, noted:
"Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line."
Neither does the market. IGMD is a tool designed to navigate that beautiful, complex, and fractal reality.
— Dskyz, Trade with insight. Trade with anticipation.
Smart MTF Bias Detector v3 (Debug)Here's a breakdown of the "Smart MTF Bias Detector v3 (Debug)" indicator's five main filters:
Main Trend (Multi-Timeframe Heikin Ashi)
The green/red background indicates the trend from Heikin Ashi candles on the H1 timeframe (or your set timeframe).
If the Heikin Ashi candle closes above its open, the background is green (indicating an upward bias).
If the Heikin Ashi candle closes below its open, the background is red (indicating a downward bias).
Short-Term Trend Filter (EMA50)
The yellow line represents the EMA50.
Buy only when the price closes above the EMA50.
Sell only when the price closes below the EMA50.
Abnormal Buy/Sell Pressure Detection (Volume Spike)
Purple dots signify candles where the volume is greater than the SMA (Simple Moving Average) of volume over N previous candles, multiplied by a specified multiplier.
This confirms there's "force" driving the price up or serious selling pressure.
Momentum Filter (Stochastic RSI)
Blue upward triangles and orange downward triangles indicate when %K crosses %D.
It uses Oversold/Overbought targets (20/80) to avoid crosses in the middle ranges.
Pivot Break (Fractal Breakout)
Red "X" marks represent Fractal Highs, and green "X" marks represent Fractal Lows.
Red/green up/down arrows indicate breakouts of these levels (e.g., a previous High being broken means an upward breakout, or a previous Low being broken means a downward breakout).
BUY Signal Conditions
A BUY signal will be generated when:
The background is green (HTF Trend ↑).
The Stoch RSI crosses up from below the Oversold zone (blue arrow).
A Fractal Low breakout occurs (Fract UP arrow).
The price is above the EMA50.
There is a Volume Spike (purple dot).
SELL Signal Conditions
A SELL signal will be generated when:
The background is red (HTF Trend ↓).
The Stoch RSI crosses down from above the Overbought zone (orange arrow).
A Fractal High breakout occurs (Fract DOWN arrow).
The price is below the EMA50.
There is a Volume Spike (purple dot).
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
GQT GPT - Volume-based Support & Resistance Zones V2搞钱兔，搞钱是为了更好的生活。
Title: GQT GPT - Volume-based Support & Resistance Zones V2
Overview:
This strategy is implemented in PineScript v5 and is designed to identify key support and resistance zones based on volume-driven fractal analysis on a 1-hour timeframe. It computes fractal high points (for resistance) and fractal low points (for support) using volume moving averages and specific price action criteria. These zones are visually represented on the chart with customizable lines and zone fills.
Trading Logic:
• Entry: The strategy initiates a long position when the price crosses into the support zone (i.e., when the price drops into a predetermined support area).
• Exit: The long position is closed when the price enters the resistance zone (i.e., when the price rises into a predetermined resistance area).
• Time Frame: Trading signals are generated solely from the 1-hour chart. The strategy is only active within a specified start and end date.
• Note: Only long trades are executed; short selling is not part of the strategy.
Visualization and Parameters:
• Support/Resistance Zones: The zones are drawn based on calculated fractal values, with options to extend the lines to the right for easier tracking.
• Customization: Users can configure the appearance, such as line style (solid, dotted, dashed), line width, colors, and label positions.
• Volume Filtering: A volume moving average threshold is used to confirm the fractal signals, enhancing the reliability of the support and resistance levels.
• Alerts: The strategy includes alert conditions for when the price enters the support or resistance zones, allowing for timely notifications.
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搞钱兔，搞钱是为了更好的生活。
标题： GQT GPT - 基于成交量的支撑与阻力区间 V2
概述：
本策略使用 PineScript v5 实现，旨在基于成交量驱动的分形分析，在1小时级别的图表上识别关键支撑与阻力区间。策略通过成交量移动平均线和特定的价格行为标准计算分形高点（阻力）和分形低点（支撑），并以自定义的线条和区间填充形式直观地显示在图表上。
交易逻辑：
• 进场条件： 当价格进入支撑区间（即价格跌入预设支撑区域）时，策略在没有持仓的情况下发出做多信号。
• 离场条件： 当价格进入阻力区间（即价格上升至预设阻力区域）时，持有多头头寸则会被平仓。
• 时间范围： 策略的信号仅基于1小时级别的图表，并且仅在指定的开始日期与结束日期之间生效。
• 备注： 本策略仅执行多头交易，不进行空头操作。
可视化与参数设置：
• 支撑/阻力区间： 根据计算得出的分形值绘制支撑与阻力线，可选择将线条延伸至右侧，便于后续观察。
• 自定义选项： 用户可以调整线条样式（实线、点线、虚线）、线宽、颜色及标签位置，以满足个性化需求。
• 成交量过滤： 策略使用成交量移动平均阈值来确认分形信号，提高支撑和阻力区间的有效性。
• 警报功能： 当价格进入支撑或阻力区间时，策略会触发警报条件，方便用户及时关注市场变化。
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Quarterly Theory ICT 01 [TradingFinder] XAMD + Q1-Q4 Sessions🔵 Introduction
The Quarterly Theory ICT indicator is an advanced analytical system based on the concepts of ICT (Inner Circle Trader) and fractal time. It divides time into quarterly periods and accurately determines entry and exit points for trades by using the True Open as the starting point of each cycle. This system is applicable across various time frames including annual, monthly, weekly, daily, and even 90-minute sessions.
Time is divided into four quarters: in the first quarter (Q1), which is dedicated to the Accumulation phase, the market is in a consolidation state, laying the groundwork for a new trend; in the second quarter (Q2), allocated to the Manipulation phase (also known as Judas Swing), sudden price changes and false moves occur, marking the true starting point of a trend change; the third quarter (Q3) is dedicated to the Distribution phase, during which prices are broadly distributed and price volatility peaks; and the fourth quarter (Q4), corresponding to the Continuation/Reversal phase, either continues or reverses the previous trend.
By leveraging smart algorithms and technical analysis, this system identifies optimal price patterns and trading positions through the precise detection of stop-run and liquidity zones.
With the division of time into Q1 through Q4 and by incorporating key terms such as Quarterly Theory ICT, True Open, Accumulation, Manipulation (Judas Swing), Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, this system enables traders to identify market trends and make informed trading decisions using real data and precise analysis.
♦ Important Note :
This indicator and the "Quarterly Theory ICT" concept have been developed based on material published in primary sources, notably the articles on Daye( traderdaye ) and Joshuuu . All copyright rights are reserved.
🔵 How to Use
The Quarterly Theory ICT strategy is built on dividing time into four distinct periods across various time frames such as annual, monthly, weekly, daily, and even 90-minute sessions. In this approach, time is segmented into four quarters, during which the phases of Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal appear in a systematic and recurring manner.
The first segment (Q1) functions as the Accumulation phase, where the market consolidates and lays the foundation for future movement; the second segment (Q2) represents the Manipulation phase, during which prices experience sudden initial changes, and with the aid of the True Open concept, the real starting point of the market’s movement is determined; in the third segment (Q3), the Distribution phase takes place, where prices are widely dispersed and price volatility reaches its peak; and finally, the fourth segment (Q4) is recognized as the Continuation/Reversal phase, in which the previous trend either continues or reverses.
This strategy, by harnessing the concepts of fractal time and smart algorithms, enables precise analysis of price patterns across multiple time frames and, through the identification of key points such as stop-run and liquidity zones, assists traders in optimizing their trading positions. Utilizing real market data and dividing time into Q1 through Q4 allows for a comprehensive and multi-level technical analysis in which optimal entry and exit points are identified by comparing prices to the True Open.
Thus, by focusing on keywords like Quarterly Theory ICT, True Open, Accumulation, Manipulation, Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, the Quarterly Theory ICT strategy acts as a coherent framework for predicting market trends and developing trading strategies.
🔵b]Settings
Cycle Display Mode: Determines whether the cycle is displayed on the chart or on the indicator panel.
Show Cycle: Enables or disables the display of the ranges corresponding to each quarter within the micro cycles (e.g., Q1/1, Q1/2, Q1/3, Q1/4, etc.).
Show Cycle Label: Toggles the display of textual labels for identifying the micro cycle phases (for example, Q1/1 or Q2/2).
Table Display Mode: Enables or disables the ability to display cycle information in a tabular format.
Show Table: Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed.
Show More Info: Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle.
🔵 Conclusion
Quarterly Theory ICT provides a fractal and recurring approach to analyzing price behavior by dividing time into four quarters (Q1, Q2, Q3, and Q4) and defining the True Open at the beginning of the second phase.
The Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal phases repeat in each cycle, allowing traders to identify price patterns with greater precision across annual, monthly, weekly, daily, and even micro-level time frames.
Focusing on the True Open as the primary reference point enables faster recognition of potential trend changes and facilitates optimal management of trading positions. In summary, this strategy, based on ICT principles and fractal time concepts, offers a powerful framework for predicting future market movements, identifying optimal entry and exit points, and managing risk in various trading conditions.
