AlphaNatt | FINAL REVELATION [Visual God]AlphaNatt | The Final Revelation
"Where Information Theory meets Market Geometery."
The AlphaNatt is a comprehensive market structure and volumetric analysis suite designed for the institutional-grade trader. It merges advanced quantitative concepts—specifically Shannon Entropy and Neural Pattern Filtering—with a "Holographic" visual interface that prioritizes clarity over clutter.
This is not just an indicator; it is a complete decision-support system that answers three critical questions:
Is the market chaotic or ordered? (Entropy Engine)
Where is the liquidity? (Volumetric Heatmap)
What is the true structure? (Fractal Geometry)
🌌 The Gen 100 Math Engine
At the core of this script lies a unique implementation of Information Theory.
1. Shannon Entropy (The Chaos Filter)
Most indicators fail because they try to predict "Noise". This script calculates the Entropy (in Bits) of the recent price action.
High Entropy: The market is in a "Random Walk" state. Visuals fade out, transparency increases, and signals are suppressed.
Low Entropy: The market is "Ordered" and approaching a singularity/decision point. Visuals glow brightly to indicate a high-probability environment.
2. Neural Pattern Recognition
The diamond signals (Cyan/Magenta) are not simple simple crossovers. They are driven by a composite logic simulating a neural filter:
Inputs: Normalised RSI + Momentum Divergence + Volatility State.
Logic: Signals only trigger when the market is statistically overextended AND showing signs of momentum decay.
💎 Holographic Features
🔥 Volumetric Heatmap
The script scans historical price action to build a Volume Profile Heatmap on the right side of the chart.
Purple/Blue Zones: These represent High Volume Nodes (HVNs). These act as "Gravity Wells" for price—often stopping trends or acting as launchpads for reversals.
POC (Point of Control): The bright green line indicates the price level with the absolute highest volume in the lookback period.
🌀 Fractal Structure Lines
Price action is often noisy. The script uses a Fractal Pivot Algorithm (Length 5) to identify the "True Highs" and "True Lows".
It connects these points with dashed "Neural Lines" to show the naked market skeleton.
This instantly reveals if you are in a trend of Higher Highs or a breakdown of Lower Lows.
🖥️ The Heads-Up Display (HUD)
A minimalist dashboard keeps you informed of the math underneath:
ENTROPY: The raw bit-score of market chaos.
REGIME: Tells you instantly if you are in "ORDER" (Tradeable) or "CHAOS" (Sit out).
STRUCT: Real-time status of the fractal structure (Breakout/Breakdown/Ranging).
⚙️ Settings & Configuration
Theme: Choose between "Cyber" (Neon), "Aeon" (Deep Blue), or "Gold" (Luxury).
Max Entropy: Adjust the sensitivity of the Chaos Filter. Lower values = stricter filtering (fewer trades).
Heatmap Depth: Control how far back the volume profile scans.
⚠️ Disclaimer
This tool is designed for educational market analysis. "Entropy" and "Neural" refer to the mathematical algorithms used to process price data and do not guarantee future performance. Always manage risk responsible.
Strategy
US Market Long Horizon Momentum Summary in one paragraph
US Market Long Horizon Momentum is a trend following strategy for US index ETFs and futures built around a single eighteen month time series momentum measure. It helps you stay long during persistent bull regimes and step aside or flip short when long term momentum turns negative.
Scope and intent
• Markets. Large cap US equity indices, liquid US index ETFs, index futures
• Timeframes. 4h/ Daily charts
• Default demo used in the publication. SPY on 4h timeframe chart
• Purpose. Provide a minimal long bias index timing model that can reduce deep drawdowns and capture major cycles without parameter mining
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. One unscaled multiple month log return of an external benchmark symbol drives all entries and exits, with optional volatility targeting as a single risk control switch.
• Failure mode addressed. Fully passive buy and hold ignores the sign of long horizon momentum and can sit through multi year drawdowns. This script offers a way to step down risk in prolonged negative momentum without chasing short term noise.
• Testability. All parameters are visible in Inputs and the momentum series is plotted so users can verify every regime change in the Tester and on price history.
• Portable yardstick. The log return over a fixed window is a unit that can be applied to any liquid symbol with daily data.
Method overview in plain language
The method looks at how far the benchmark symbol has moved in log return terms over an eighteen month window in our example. If that long horizon return is positive the strategy allows a long stance on the traded symbol. If it is negative and shorts are enabled the strategy can flip short, otherwise it goes flat. There is an optional realised volatility estimate on the traded symbol that can scale position size toward a target annual volatility, but in the default configuration the model uses unit leverage and only the sign of momentum matters.
Base measures
Return basis. The core yardstick is the natural log of close divided by the close eighteen months ago on the benchmark symbol. Daily log returns of the traded symbol feed the realised volatility estimate when volatility targeting is enabled.
Components
• Component one Momentum eighteen months. Log of benchmark close divided by its close mom_lookback bars ago. Its sign defines the trend regime. No extra smoothing is applied beyond the long window itself.
• Component two Realised volatility optional. Standard deviation of daily log returns on the traded symbol over sixty three days. Annualised by the square root of 252. Used only when volatility targeting is enabled.
• Optional component Volatility targeting. Converts target annual volatility and realised volatility into a leverage factor clipped by a maximum leverage setting.
Fusion rule
The model uses a simple gate. First compute the sign of eighteen month log momentum on the benchmark symbol. Optionally compute leverage from volatility. The sign decides whether the strategy wants to be long, short, or flat. Leverage only rescales position size when enabled and does not change direction.
Signal rule
• Long suggestion. When eighteen month log momentum on the benchmark symbol is greater than zero, the strategy wants to be long.
• Short suggestion. When that log momentum is less than zero and shorts are allowed, the strategy wants to be short. If shorts are disabled it stays flat instead.
• Wait state. When the log momentum is exactly zero or history is not long enough the strategy stays flat.
• In position. In practice the strategy sits IN LONG while the sign stays positive and flips to IN SHORT or flat only when the sign changes.
Inputs with guidance
Setup
• Momentum Lookback (months). Controls the horizon of the log return on the benchmark symbol. Typical range 6 to 24 months. Raising it makes the model slower and more selective. Lowering it makes it more reactive and sensitive to medium term noise.
• Symbol. External symbol used for the momentum calculation, SPY by default. Changing it lets you time other indices or run signals from a benchmark while trading a correlated instrument.
Logic
• Allow Shorts. When true the strategy will open short positions during negative momentum regimes. When false it will stay flat whenever momentum is negative. Practical setting is tied to whether you use a margin account or an ETF that supports shorting.
Internal risk parameters (not exposed as inputs in this version) are:
• Target Vol (annual). Target annual volatility for volatility targeting, default 0.2.
• Vol Lookback (days). Window for realised volatility, default 63 trading days.
• Max Leverage. Cap on leverage when volatility targeting is enabled, default 2.
Usage recipes
Swing continuation
• Signal timeframe. Use the daily chart.
• Benchmark symbol. Leave at SPY for US equity index exposure.
• Momentum lookback. Eighteen months as a default, with twelve months as an alternative preset for a faster swing bias.
Properties visible in this publication
• Initial capital. 100000
• Base currency. USD
• Default order size method. 5% of the total capital in this example
• Pyramiding. 0
• Commission. 0.03 percent
• Slippage. 3 ticks
• Process orders on close. On
• Bar magnifier. Off
• Recalculate after order is filled. Off
• Calc on every tick. Off
• All request.security calls use lookahead = barmerge.lookahead_off
Realism and responsible publication
The strategy is for education and research only. It does not claim any guaranteed edge or future performance. All results in Strategy Tester are hypothetical and depend on the data vendor, costs, and slippage assumptions. Intrabar motion is not modeled inside daily bars so extreme moves and gaps can lead to fills that differ from live trading. The logic is built for standard candles and should not be used on synthetic chart types for execution decisions.
Performance is sensitive to regime structure in the US equity market, which may change over time. The strategy does not protect against single day crash risk inside bars and does not model gap risk explicitly. Past behavior of SPY and the momentum effect does not guarantee future persistence.
Honest limitations and failure modes
• Long sideways regimes with small net change over eighteen months can lead to whipsaw around the zero line.
• Very sharp V shaped reversals after deep declines will often be missed because the model waits for momentum to turn positive again.
• The sample size in a full SPY history is small because regime changes are infrequent, so any test must be interpreted as indicative rather than statistically precise.
• The model is highly dependent on the chosen lookback. Users should test nearby values and validate that behavior is qualitatively stable.
Legal
Education and research only. Not investment advice. You are responsible for your own decisions. Always test on historical data and in simulation with realistic costs before any live use.
BTC Trend Regime Heatmap (50/200 EMA) by FlyingOceanTigerThis is a simple BTC trend regime heatmap built on the 50 EMA and 200 EMA.
Price can only be in one of three zones:
• Strong uptrend: close above the 50 EMA (bright green background).
• Middle / neutral zone: close between the 50 and 200 EMAs (gold background).
• Deep drawdown: close below the 200 EMA (red background).
I’m not using it as a signal generator, just as a daily “where are we in the bigger picture?” dashboard.
How it works:
• Calculates 50 EMA (short-term trend) and 200 EMA (long-term trend).
• Classifies each bar as strong trend, middle zone, or deep drawdown based on where price closes relative to the EMAs.
• Requires N consecutive closes in a zone (Confirm Bars) before changing color, to avoid 1-bar flips and noise.
• Colors only one background per bar so the regimes are easy to read at a glance.
How I use it on BTC 1D:
• Strong uptrend (green): manage existing longs and avoid FOMO chasing every candle.
• Middle / neutral zone (gold): slow down, study how price behaves here, and look for my own entries on lower timeframes.
• Deep drawdown (red): mostly watch and wait instead of forcing trades into weakness.
Default settings:
• Timeframe: 1D
• Fast EMA: 50
• Slow EMA: 200
• Confirm Bars: 2 (increase this if you want slower, more “stable” regime changes)
Try it on BTC, ETH, SOL, or your favorite majors and see how your behavior changes when you respect the regimes instead of guessing where you are in the cycle.
Feel free to fork the script, change the colors, or add your own rules. If you build a variation you like, drop it in the comments so I can check it out.
Not financial advice.
Angular Resistance & Breakout/BreakdownAngular Resistance & Breakout/Breakdown (Dynamic Trendlines)
This indicator provides a dynamic approach to identifying major support and resistance levels by fitting Linear Regression lines to recent pivot points (swing highs and swing lows). Unlike static horizontal lines, these "Angular" trendlines adapt to the market's slope, providing continuously adjusting targets for resistance and support, along with signals for confirmed breakouts and breakdowns.
💡 Key Features
Dynamic Trendlines: Utilizes Linear Regression to automatically draw sloped trendlines based on a configurable number of the most recent swing pivots.
Confirmed Signals: Generates clear Breakout (▲) and Breakdown (▼) signals with optional buffer and sensitivity filters to reduce noise.
Customizable Inputs: Fine-tune the pivot detection period, the number of points used for regression, line extension, and signal sensitivity.
On-Chart Info Panel: A table displays real-time data, including the number of detected pivot points and the current calculated price level of the dynamic lines.
⚙️ How It Works (The Logic)
Pivot Detection: The script uses the standard ta.pivothigh() and ta.pivotlow() functions to reliably identify swing points, based on the Pivot Left and Pivot Right settings. These points are stored in dynamic arrays (highs for resistance, lows for support).
Angular Line Generation: A custom function, f_regression_from_array, performs a Linear Regression analysis using the bar index (X-axis) and the pivot price (Y-axis) for the Points to use. This calculation determines the optimal slope and intercept to draw a best-fit dynamic line through the identified pivot points.
Breakout/Breakdown Confirmation:
Breakout: Triggered when the current close price crosses above the dynamic resistance line plus the user-defined Breakout buffer.
Breakdown: Triggered when the current close price crosses below the dynamic support line minus the user-defined Breakout buffer.
Sensitivity Filter: An optional filter requires the price movement on the signal bar to exceed a minimum percentage (Label sensitivity) away from the line to confirm the momentum of the move.
Strategy: HMA 50 + Supertrend SniperHMA 50 + Supertrend Confluence Strategy (Trend Following with Noise Filtering)
Description:
Introduction and Concept This strategy is designed to solve a common problem in trend-following trading: Lag vs. False Signals. Standard Moving Averages often lag too much, while price action indicators can generate false signals during choppy markets. This script combines the speed of the Hull Moving Average (HMA) with the volatility-based filtering of the Supertrend indicator to create a robust "Confluence System."
The primary goal of this script is not just to overlay two indicators, but to enforce a strict rule where a trade is only taken when Momentum (HMA) and Volatility Direction (Supertrend) are in perfect agreement.
Why this combination? (The Logic Behind the Mashup)
Hull Moving Average (HMA 50): We use the HMA because it significantly reduces lag compared to SMA or EMA by using weighted calculations. It acts as our primary Trend Direction detector. However, HMA can be too sensitive and "whipsaw" during sideways markets.
Supertrend (ATR-based): We use the Supertrend (Factor 3.0, Period 10) as our Volatility Filter. It uses Average True Range (ATR) to determine the significant trend boundary.
How it Works (Methodology) The strategy uses a boolean logic system to filter out low-quality trades:
Bullish Confluence: The HMA must be rising (Slope > 0) AND the Close Price must be above the Supertrend line (Uptrend).
Bearish Confluence: The HMA must be falling (Slope < 0) AND the Close Price must be below the Supertrend line (Downtrend).
The "Choppy Zone" (Noise Filter): This is a unique feature of this script. If the HMA indicates one direction (e.g., Rising) but the Supertrend indicates the opposite (e.g., Downtrend), the market is considered "Choppy" or indecisive. In this state, the script paints the candles or HMA line Gray and exits all positions (optional setting) to preserve capital.
Visual Guide & Signals To make the script easy to interpret for traders who do not read Pine Script, I have implemented specific visual cues:
Green Cross (+): Indicates a LONG entry signal. Both HMA and Supertrend align bullishly.
Red Cross (X): Indicates a SHORT entry signal. Both HMA and Supertrend align bearishly.
Thick Line (HMA): The main line changes color based on the trend.
Green: Bullish Confluence.
Red: Bearish Confluence.
Gray: Divergence/Choppy (No Trade Zone).
Thin Step Line: This is the Supertrend line, serving as your dynamic Trailing Stop Loss.
Strategy Settings
HMA Length: Default is 50 (Mid-term trend).
ATR Factor/Period: Default is 3.0/10 (Standard for trend catching).
Exit on Choppy: A toggle switch allowing users to decide whether to hold through noise or exit immediately when indicators disagree.
Risk Warning This strategy performs best in trending markets (Forex, Crypto, Indices). Like all trend-following systems, it may experience drawdown during prolonged accumulation/distribution phases. Please backtest with your specific asset before using it with real capital.
OBV + WaveTrend Volume Scalper [GratefulFutures]This script is a combination script of three different strategies that provides buy and sell signals based on the change of volume with momentum confirmations.
Sources used:
This script relies on the outstanding scripts of the great script writer LazyBear: LazyBear
The following scripts were used in this publication:
1. A modified "On-Balance Volume Oscillator" modified from LazyBear's original script:
2. Wavetrend Oscillator with crosses, Author: LazyBear
3. Squeeze Momentum Oscillator, Author: LazyBear
This script functions based on the following criteria being true:
1. On balance volume oscillator turning from negative to positive (buy) or positive to negative (sell)
2. Squeeze Momentum value is increasing (buy) or decreasing (sell)
3. Wavetrend 1 (wt1) is greater than wavetrend 2 (wt2) (buy)/ Wavetrend 1 (wt1) is less than wavetrend 2 (wt2) (sell)
By combining these factors the indicator is able to signal exactly when net buying turns to net selling (OBV) and when this change is most advantageous to continue based on the momentum and price action of the underlying asset (SQMOMO and Wavetrend).
This allows you to pair volume and price action for a powerful tool to identify where price will reverse or continue providing exceptional entries for short term trades, especially when combined with other aspects such as support and resistance, or volume profile.
How to use:
Simply adjust the settings to your preference and read the given signals as generated.
Settings
There are multiple ways to tune the signals generated. It is set standard for my preferred use on a 1 minute chart.
OBV Oscillator Settings
The first 4 dropdowns in the Inputs section tune the On Balance Volume Oscillator (OBVO) portion of the indicator. You can choose if you want it to calculate based on close, open, high, low, or other value.
The most impactful in the entire settings is going to be the length and smoothing of the OBVO EMA. Making this number lower increasing the sensitivity to changes in volume, making the signals come quicker but is more susceptible to quick fluctuations. A value of between (5-20) is reasonable for the OBVO EMA length. There is a separate smoothing factor titled OBV Smoothing Length and below that, OBV Smoothing Type , a value of (2) is standard with "SMA" for smoothing type with a value of between 2-10 being reasonable. You may also play with these values to see what you like for your trading style.
Wavetrend Settings
The next 3 options are to modify the wavetrend portion of the indicator. I do not modify these from standard, and feel that they work appropriately on all time frames at the following values: n1 length (10), n2 length (20), Wavetrend Signal SMA length (4)
Squeeze Momentum Settings
The following 5 options through the end modify the Squeeze momentum portion of the indicator. The only one that modifies the signals generated is the KC Length , Making this number lower increasing the sensitivity to changes in price action, making the signals come quicker but is more susceptible to quick fluctuations. A value of between (18-25) is reasonable for KC Length .
Style Setting
You may select if you want to see the buy and sell signals. The following 5 options Raw OBV Osc through Squeeze Momentum allow you to see where each specific requirement was met, posted as a vertical line, but for live use it is recommended to turn all of these vertical lines off and only use the buy and sell signals.
Time Frames:
While this script is most effective on shorter time frames (1 minute for scalping and daytrading) it is also viable to use it on longer timeframes, due to the nature of its components being independent of time frame.
Examples of use - (Green and red vertical lines are for visualization purpose and are not part of the script)
SPY 1 Minute (Factory Settings):
SPX 15 minutes (Factory Settings):
Considerations
This script is meant primarily for short term trading, trades on the basis of seconds to minutes primarily. While they can be a good indication of volume lining up with momentum, it is always wise to use them in combination with other factors such as support, resistance, market structure, volume levels, or the many other techniques out there...
As Always... Happy Trading.
-Not_A_Mad_Scientist (GreatfulFutures Trade University)
Smart Money Setup 08 [TradingFinder] Binary Options Gold Scalper🔵 Introduction
In the Smart Money methodology, the market is understood as a structure driven by liquidity flow. This structure forms through the movement of large orders, the accumulation of liquidity, and the reactions that occur around key price zones. The logic of Smart Money is based on the idea that price movement is not random and usually evolves with the intention of collecting liquidity and creating price inefficiencies known as imbalances.
Within this framework, several important stages including the liquidity sweep, the formation of a point of interest, the appearance of an imbalance and the transition of market structure play major roles and collectively define the broader direction of price.
In many bullish scenarios, the market begins by sweeping sell side liquidity and targeting important lows in order to collect the liquidity resting below them. This liquidity collection often becomes the starting point for creating a point of interest which usually marks the area where Smart Money begins to enter the market.
After price moves away from this point, it breaks a structural high and forms a change of character. This shift marks a transition in the balance of power between buyers and sellers and is considered the first clear signal that the market structure is changing.
After the change of character, new institutional order flow often creates a strong and rapid movement that leaves behind an imbalance. This imbalance is one of the most important elements in Smart Money analysis because price tends to return to this area in order to complete structure and restore balance.
The return into the imbalance becomes meaningful when it occurs together with the liquidity sweep, the presence of a validated point of interest and a confirmed structural transition. These conditions frequently mark the beginning of powerful movements within the Smart Money cycle.
Understanding the sequence of liquidity, point of interest, imbalance, change of character and market structure builds the foundation of Smart Money analysis and provides a clear view of the true direction of institutional strength.
Bullish Setup :
Bearish Setup :
🔵 How to Use
To use this framework effectively, the trader must analyze the market through the principles of Smart Money and observe how liquidity drives price. A trade becomes valid only when several essential components appear together in a clear and consistent order.
These components include the liquidity sweep, the formation of a point of interest, the confirmation of a change of character, the transition of market structure and the return of price into an imbalance. The method is built on the understanding that the market first collects liquidity, then shifts order flow and finally provides an entry opportunity inside an inefficient area or inside a point of interest.
For this reason, the trader must follow the path of liquidity from the moment the sweep occurs, through the point of interest and the change of character and finally into the return of price toward the imbalance. When applied correctly, this approach creates entries that are more precise, more structural and more aligned with the real behavior of the market rather than with superficial signals.
🟣 Long Position
A bullish setup in Smart Money structure begins with a liquidity sweep on the sell side. The market first targets the areas where sell side liquidity is located and collects the stops and resting liquidity under previous lows. This collection is the condition that Smart Money requires to begin creating a new order flow. After this liquidity has been taken, a point of interest forms which is usually the last bearish candle or the effective demand zone that initiated the upward movement.
Price then moves away from the point of interest and breaks a structural high which creates a change of character. This event confirms that the market structure has moved from a bearish state to a bullish one and that buying pressure has taken control of the order flow. Following this shift, a strong upward movement often occurs and creates an imbalance between candles. This imbalance reflects the entrance of strong Smart Money orders and is seen as an important confirmation of bullish strength.
When price returns to this imbalance after the displacement, the market enters a phase where Smart Money aims to complete the corrective movement and continue the upward direction. The reaction inside the imbalance when combined with the liquidity sweep, the confirmed point of interest and the change of character completes the bullish setup and forms a structure that often leads to a continuation of the bullish trend.
🟣 Short Position
A bearish setup follows the same Smart Money logic but in the opposite direction. The market begins by collecting buy side liquidity and targets the highs where buy side liquidity and resting stops are located. This liquidity sweep on the buy side becomes the starting phase for Smart Money to initiate a downward order flow. After the liquidity is collected, a bearish point of interest forms which is usually the last bullish candle or the supply zone that created the initial drop.
Price then moves away from this point and breaks the first structural low. This creates a change of character to the downside which confirms that the market structure has transitioned from bullish to bearish and that selling pressure has gained control. After this shift, a strong downward displacement appears and leaves behind a bearish imbalance that clearly shows the dominance of sellers.
As price returns to this imbalance and corrects the inefficient movement, the bearish setup becomes complete as long as the market structure remains bearish. The combination of the buy side liquidity sweep, the bearish point of interest, the change of character, the imbalance and the corrective return creates the ideal structure that Smart Money uses to continue the downward movement and develop a reliable selling opportunity.
🔵 Settings
🟣 Logic Settings
Pivot Period : Defines how many bars are analyzed to identify swing highs and lows. Higher values detect larger, slower structures, while lower values respond to faster patterns. The default value of 5 offers a balanced sensitivity.
🟣 Alert Settings
Alert : Enables alerts for SMS08.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Smart Money approach demonstrates that price movement is not random or based on surface level patterns. Instead, it develops through a clear cycle of liquidity collection, structural transition and corrective movement toward key price zones. By recognizing events such as the liquidity sweep, the formation of the point of interest, the change of character and the return into the imbalance, the trader gains the ability to understand order flow more accurately and identify the true direction of market structure.
Both bullish and bearish setups show that the alignment of these elements creates a transparent view of institutional behavior and reveals the source of strong movements in the market. When the trader correctly identifies this sequence, entry points become more reliable and more aligned with liquidity flow. The combination of liquidity, structure and imbalance provides a consistent framework that removes guesswork and guides decisions through the real logic of the market.
Trendshift [CHE] StrategyTrendshift Strategy — First-Shift Structural Regime Trading
Profitfactor 2,603
Summary
Trendshift Strategy implements a structural regime-shift trading model built around the earliest confirmed change in directional structure. It identifies major swing highs and lows, validates breakouts through optional ATR-based conviction, and reacts only to the first confirmed shift in each direction. After a regime reversal, the strategy constructs a premium and discount band between the breakout candle and the previous opposite swing. This band is used as contextual bias and may optionally inform stop placement and position sizing.
The strategy focuses on clear, interpretable structural events rather than continuous signal generation. By limiting entries to the first valid shift, it reduces false recycles and allows the structural state to stabilize before a new trade occurs. All signals operate on closed-bar logic, and the strategy avoids higher-timeframe calls to stabilize execution behavior.
Motivation: Why this design?
Many structure-based systems repeatedly trigger as price fluctuates around prior highs and lows. This often leads to multiple flips during volatile or choppy conditions. Trendshift Strategy addresses this problem by restricting execution to the first confirmed structural event in each direction. ATR-based filters help differentiate genuine structural breaks from noise, while the contextual band ensures that the breakout is meaningful in relation to recent volatility.
The design aims to represent a minimalistic structural trading framework focused on regime turns rather than continuous trend signaling. This reduces chart noise and clarifies where the market transitions from one regime to another.
What’s different vs. standard approaches?
Baseline reference
Typical swing-based structure indicators report every break above or below recent swing points.
Architecture differences
First-shift-only regime logic that blocks repeated signals until direction reverses
ATR-filtered validation to avoid weak or momentum-less breaks
Premium and discount bands derived from breakout structure
Optional band-driven stop placement
Optional band-dependent position-sizing factor
Regime timeout system to neutralize structure after extended inactivity
Persistent-state architecture to prevent re-triggering
Practical effect
Only the earliest actionable structure change is traded
Fewer but higher-quality signals
Premium/discount tint assists contextual evaluation
Stops and sizing can be aligned with structural context rather than arbitrary volatility measures
Improved chart interpretability due to reduced marker frequency
How it works (technical)
The algorithm evaluates symmetric swing points using a fixed bar window. When a swing forms, its value and bar index are stored as persistent state. A structural shift occurs when price closes beyond the most recent major swing on the opposite side. If ATR filtering is enabled, the breakout must exceed a volatility-scaled distance to prevent micro-breaks from firing.
Once a valid shift is confirmed, the regime is updated to bullish or bearish. The script records the breakout level, the opposite swing, and derives a band between them. This band is checked for minimum size relative to ATR to avoid unrealistic contexts.
The first shift in a new direction generates both the strategy entry and a visual marker. Additional shifts in the same direction are suppressed until a reversal occurs. If a timeout is enabled, the regime resets after a specified number of bars without structural change, optionally clearing the band.
Stop placement, if enabled, uses either the opposite or same band edge depending on configuration. Position size is computed from account percentage and may optionally scale with the price-span-to-ATR relationship.
Parameter Guide
Market Structure
Swing length (default 5): Controls swing sensitivity. Lower values increase responsiveness.
Use ATR filter (default true): Requires breakouts to show momentum relative to ATR. Reduces false shifts.
ATR length (default 14): Volatility estimation for breakout and band validation.
Break ATR multiplier (default 1.0): Required breakout strength relative to ATR.
Premium/Discount Framework
Enable framework (default true): Activates premium/discount evaluation.
Persist band on timeout (default true): Keeps structural band after timeout.
Min band ATR mult (default 0.5): Rejects narrow bands.
Regime timeout bars (default 500): Neutralizes regime after inactivity.
Invert colors (default false): Color scheme toggle.
Visuals
Show zone tint (default true): Background shade in premium or discount region.
Show shift markers (default true): Display first-shift markers.
Execution and Risk
Risk per trade percent (default 1.0): Determines position size as account percentage.
Use band for size (default false): Scales size relative to band width behavior.
Flat on opposite shift (default true): Forces reversal behavior.
Use stop at band (default false): Stop anchored to band edges.
Stop band side: Chooses which band edge is used for stop generation.
Reading & Interpretation
A green background indicates discount conditions within the structural band; red indicates premium conditions. A green triangle below price marks the first bullish structural shift after a bearish regime. A red triangle above price marks the first bearish structural shift after a bullish regime.
When stops are active, the opposite band edge typically defines the protective level. Band width relative to ATR indicates how significant a structural change is: wider bands imply stronger volatility structure, while narrow bands may be suppressed by the minimum-size filter.
Practical Workflows & Combinations
Trend following: Use first-shift entries as initial regime confirmation. Add higher-timeframe trend filters for additional context.
Swing trading: Combine with simple liquidity or fair-value-gap concepts to refine entries.
Bias mapping: Use higher timeframes for structural regime and lower timeframes for execution within the premium/discount context.
Exit management: When using stops, consider ATR-scaling or multi-stage profit targets. When not using stops, reversals become the primary exit.
Behavior, Constraints & Performance
The strategy uses only confirmed swings and closed-bar logic, avoiding intrabar repaint. Pivot-based swings inherently appear after the pivot window completes, which is standard behavior. No higher-timeframe calls are used, preventing HTF-related repaint issues.
Persistent variables track regime and structural levels, minimizing recomputation. The maximum bars back setting is five-thousand. The design avoids loops and arrays, keeping performance stable.
Known limitations include limited signal density during consolidations, delayed swing confirmation, and sensitivity to extreme gaps that stretch band logic. ATR filtering mitigates some of these effects but does not eliminate them entirely.
Sensible Defaults & Quick Tuning
Fewer but stronger entries: Increase swing length or ATR breakout multiplier.
More responsive entries: Reduce swing length to capture earlier shifts.
More active band behavior: Lower the minimum band ATR threshold.
Stricter stop logic: Use the opposite band edge for stop placement.
Volatile markets: Increase ATR length slightly to stabilize behavior.
What this indicator is—and isn’t
Trendshift Strategy is a structural-regime trading engine that evaluates major directional shifts. It is not a complete trading system and does not include take-profit logic or prediction features. It does not attempt to forecast future price movement and should be used alongside broader market structure, volatility context, and disciplined risk management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Best Entry Swing MASTER v3 PUBLIC (S.S)Strategy Description (English)
Best Entry Swing MASTER v3 – Quality Mode
The Best Entry Swing MASTER v3 is a structured swing trading and trend-following strategy designed to identify high-probability long and short entries during directional markets.
It combines three core setup types commonly used by momentum and breakout traders:
Breakout (BO)
Pullback Reversal (PB)
Volatility Contraction Pattern (VCP)
The strategy applies multiple layers of confirmation, including multi-EMA trend structure, volatility contraction, volume filters, and an optional market regime filter.
It is suitable for swing trading on higher timeframes (4H, Daily), as well as medium-term trend continuation setups.
Core Concepts
1. Trend Structure
A trend is considered valid when:
Uptrend: Price > EMA20 > EMA50 > EMA100
Downtrend: Price < EMA20 < EMA50 < EMA100
In addition, a simple but effective trend-strength metric is calculated using the percentage spread between EMA20 and EMA100.
This helps avoid signals during sideways or low-volatility environments.
2. Market Regime Filter
The market environment is determined using a higher timeframe benchmark (default: SPY on Daily).
Only long trades are allowed in bullish market conditions
Only short trades in bearish conditions
This significantly reduces false signals in counter-trend conditions.
Entry Logic
Breakout (BO)
A long breakout triggers when:
Price closes above the highest high of the lookback period
Volume exceeds its 20-period average
Trend and market regime confirm
(Optional A+ mode): true volatility contraction is required
Similar logic applies for short breakdowns.
Pullback (PB)
A pullback entry triggers after:
At least two corrective candles
A strong reversal candle (close above previous high for long)
Volume confirmation
Price interacts with EMA20
This structure models classical trend-reentry conditions.
Volatility Contraction Pattern (VCP)
A VCP entry triggers when:
True range contracts over multiple bars
Price holds near the breakout zone
Volume contracts
Trend and market regime are aligned
This setup aims to capture explosive continuation moves.
Quality Modes
The strategy offers two modes:
Balanced Mode
Moderate signal frequency
Broader trend-strength allowance
Suitable for more active traders
A+ Only Mode
Strict confirmation requirements
Only high-quality setups with multiple confluences
Designed to avoid low-probability trades entirely
Risk Management
Risk is managed using an ATR-based stop and target:
Long SL = Close − ATR × 1.5
Long TP = Close + ATR × 3
(Equivalent logic for short positions)
This provides a balanced reward-to-risk profile and avoids overly tight stops.
Early Entry Signals (Optional)
The script offers optional “Early Entry” markers that highlight when a setup is forming but not yet confirmed.
These are not entry signals and are disabled by default for public use.
Intended Use
This strategy is designed for:
Swing trading
Momentum continuation
Trend-following
Multi-day to multi-week trades
It performs best on:
4H
Daily
High-liquidity equities, indices, and futures
Disclaimer
This script is intended for educational and research purposes.
Past performance does not guarantee future results.
Always backtest thoroughly and use appropriate risk management.
APEX TREND: Macro & Hard Stop SystemAPEX TREND: Macro & Hard Stop System
The APEX TREND System is a composite trend-following strategy engineered to solve the "Whipsaw" problem inherent in standard breakout systems. It orchestrates four distinct technical theories—Macro Trend Filtering, Volatility Squeeze, Momentum, and Volatility Stop-Loss—into a single, hierarchical decision-making engine.
This script is not merely a collection of indicators; it is a rules-based trading system designed for Swing Traders (Day/Week timeframes) who aim to capture major trend extensions while strictly managing downside risk through a "Hard Stop" mechanism.
🧠 Underlying Concepts & Originality
Many trend indicators fail because they treat all price movements equally. The APEX TREND differentiates itself by applying an "Institutional Filter" logic derived from classic Dow Theory and Modern Volatility Analysis.
1. The Macro Hard Stop (The 200 EMA Logic)
Origin: Based on the institutional mandate that “Nothing good happens below the 200-day moving average.”
Function: Unlike standard super trends that flip constantly in sideways markets, this system integrates a 200-period Exponential Moving Average (EMA) as a non-negotiable "Hard Stop."
Synergy: This acts as the primary gatekeeper. Even if the volatility engine signals a "Buy," the system suppresses the signal if the price is below the Macro Baseline, effectively filtering out counter-trend traps.
2. The Volatility Engine (Squeeze Theory)
Origin: Derived from John Carter’s TTM Squeeze concept.
Function: The script identifies periods where Bollinger Bands (Standard Deviation) contract inside Keltner Channels (ATR). This indicates a period of potential energy build-up.
Synergy: The system only triggers an entry when this energy is released (Breakout) AND coincides with Linear Regression Momentum, ensuring the breakout is genuine.
3. Anti-Chop Filter (ADX Integration)
Origin: J. Welles Wilder’s Directional Movement Theory.
Function: A common failure point for trend systems is low-volatility chop. This script utilizes the Average Directional Index (ADX).
Synergy: If the ADX is below the threshold (Default: 20), the market is deemed "Choppy." The script visually represents this by painting candles GRAY, signaling a "No-Trade Zone" regardless of price action.
4. The "Run Trend" Stop Loss (Factor 4.0 ATR)
Origin: Adapted from the Turtle Trading rules regarding volatility-based stops.
Function: Standard Trailing Stops (usually Factor 3.0) are too tight for crypto or volatile equities on daily timeframes.
Optimization: This system employs a wider ATR Multiplier of 4.0. This allows the asset to fluctuate naturally within a trend without triggering a premature exit, maximizing the "Run Trend" potential.
🛠 How It Works (The Algorithm)
The script processes data in a specific order to generate a signal:
Check Macro Trend: Is Price > EMA 200? (If No, Longs are disabled).
Check Volatility: Is ADX > 20? (If No, all signals are disabled).
Check Volume: Is Current Volume > 1.2x Average Volume? (Confirmation of institutional participation).
Trigger: Has a Volatility Breakout occurred in the direction of the Macro Trend?
Execution: If ALL above are true -> Generate Signal.
🎯 Strategy Guide
1. Long Setup (Bullish)
Signal: Look for the Green "APEX LONG" Label.
Condition: The price must be ABOVE the White Line (EMA 200).
Execution: Enter at the close of the signal candle.
Stop Loss: Initial stop at the Green Trailing Line.
2. Short Setup (Bearish)
Signal: Look for the Red "APEX SHORT" Label.
Condition: The price must be BELOW the White Line (EMA 200).
Execution: Enter at the close of the signal candle.
Stop Loss: Initial stop at the Red Trailing Line.
3. Exit Rules (Crucial)
This system employs a Dual-Exit Mechanism:
Soft Exit (Profit Taking): Close the position if the price crosses the Trailing Stop Line (Green/Red line). This locks in profits during a trend reversal.
Hard Exit (Emergency): Close the position IMMEDIATELY if the price crosses the White EMA 200 Line against your trade. This prevents holding a position during a major market regime change.
⚙️ Settings
Momentum Engine: Adjust Bollinger Band/Keltner Channel lengths to tune breakout sensitivity.
Apex Filters: Toggle the EMA 200 or ADX filters on/off to adapt to different asset classes.
Risk Management: The ATR Multiplier (Default 4.0) controls the width of the trailing stop. Lower values = Tighter stops (Scalping); Higher values = Looser stops (Swing).
Disclaimer: This script is designed for trend-following on higher timeframes (4H, 1D, 1W). Please backtest on your specific asset before live trading.
RSI Strategy [PrimeAutomation]⯁ OVERVIEW
The RSI Strategy is a momentum-driven trading system built around the behavior of the Relative Strength Index (RSI).
Instead of using traditional overbought/oversold zones, this strategy focuses on RSI breakouts with volatility-based trailing stops, adaptive profit-targets, and optional early-exit logic.
It is designed to capture strong continuation moves after momentum shifts while protecting trades using ATR-based dynamic risk management.
⯁ CONCEPTS
RSI Breakout Momentum: Entries happen when RSI breaks above/below custom thresholds, signaling a shift in momentum rather than mean reversion.
Volatility-Adjusted Risk: ATR defines both stop-loss and profit-target distances, scaling positions based on market volatility.
Dynamic Trailing Stop: The strategy maintains an adaptive trailing level that tightens as price moves in the trade’s favor.
Single-Position System: Only one trade at a time (no pyramiding), maximizing clarity and simplifying execution.
⯁ KEY FEATURES
RSI Signal Engine
• Long when RSI crosses above Upper threshold
• Short when RSI crosses below Lower threshold
These levels are configurable and optimized for trend-momentum detection.
ATR-Based Stop-Loss
A custom ATR multiplier defines the initial stop.
• Long stop = price – ATR × multiplier
• Short stop = price + ATR × multiplier
Stops adjust continuously using a trailing model.
ATR-Based Take Profit (Optional)
Profit targets scale with volatility.
• Long TP = entry + ATR × TP-multiplier
• Short TP = entry – ATR × TP-multiplier
Users can disable TP and rely solely on trailing stops.
Real-Time Trailing Logic
The stop updates bar-by-bar:
• In a long trade → stop moves upward only
• In a short trade → stop moves downward only
This keeps the stop tight as trends develop.
Early Exit Module (Optional)
After X bars in a trade, opposite RSI signals trigger exit.
This reduces holding time during weak follow-through phases.
Full Visual Layer
• RSI plotted with threshold fills
• Entry/TP/Stop visual lines
• Color-coded zones for clarity
⯁ HOW TO USE
Look for RSI Breakouts:
Focus on RSI crossing above the upper boundary (long) or below the lower boundary (short). These moments identify fresh momentum surges.
Use ATR Levels to Manage Risk:
Because stops and targets scale with volatility, the strategy adapts well to both quiet and explosive market phases.
Monitor Trailing Stops for Trend Continuation:
The trailing stop is the primary driver of exits—often outperforming fixed targets by catching larger runs.
Use on Liquid Markets & Mid-Higher Timeframes:
The system performs best where RSI and ATR signals are clean—crypto majors, FX, and indices.
⯁ CONCLUSION
The RSI Strategy is a modern RSI breakout system enhanced with volatility-adaptive risk management and flexible exit logic. It is designed for traders who prefer momentum confirmation over mean reversion, offering a disciplined framework with robust protections and dynamic trend-following capability.
Its blend of ATR-based stops, optional profit targets, and RSI-driven entries makes it a reliable strategy across a wide range of market conditions.
Hash Supertrend [Hash Capital Research]Hash Supertrend Strategy by Hash Capital Research
Overview
Hash Supertrend is a professional-grade trend-following strategy that combines the proven Supertrend indicator with institutional visual design and flexible time filtering.
The strategy uses ATR-based volatility bands to identify trend direction and executes position reversals when the trend flips.This implementation features a distinctive fluorescent color system with customizable glow effects, making trend changes immediately visible while maintaining the clean, professional aesthetic expected in quantitative trading environments.
Entry Signals:
Long Entry: Price crosses above the Supertrend line (trend flips bullish)
Short Entry: Price crosses below the Supertrend line (trend flips bearish)
Controls the lookback period for volatility calculation
Lower values (7-10): More sensitive to price changes, generates more signals
Higher values (12-14): Smoother response, fewer signals but potentially delayed entries
Recommended range: 7-14 depending on market volatility
Factor (Default: 3.0)
Restricts trading to specific hours
Useful for avoiding low-liquidity sessions, overnight gaps, or known choppy periods
When disabled, strategy trades 24/7
Start Hour (Default: 9) & Start Minute (Default: 30)
Define when the trading session begins
Uses exchange timezone in 24-hour format
Example: 9:30 = 9:30 AM
End Hour (Default: 16) & End Minute (Default: 0)
Controls the vibrancy of the fluorescent color system
1-3: Subtle, muted colors
4-6: Balanced, moderate saturation
7-10: Bright, highly saturated fluorescent appearance
Affects both the Supertrend line and trend zones
Glow Effect (Default: On)
Adds luminous halo around the Supertrend line
Creates a multi-layered visual with depth
Particularly effective during strong trends
Glow Intensity (Default: 5.0)
Displays tiny fluorescent dots at entry points
Green dot below bar: Long entry
Red dot above bar: Short entry
Provides clear visual confirmation of executed trades
Show Trend Zone (Default: On)
Strong trending markets (2020-style bull runs, sustained bear markets)
Markets with clear directional bias
Instruments with consistent volatility patterns
Timeframes: 15m to Daily (optimal on 1H-4H)
Challenging Conditions:
Choppy, range-bound markets
Low volatility consolidation periods
Highly news-driven instruments with frequent gaps
Very low timeframes (1m-5m) prone to noise
Recommended AssetsCryptocurrency:
ParabolicSAR+EMA[TS_Indie]🚀 EMA + Parabolic SAR Reversal Trading Strategy
This trading system effectively combines the use of Exponential Moving Averages (EMA) with the Parabolic SAR to identify both price trends and key reversal points. The EMA Fast is used to signal the primary short-term trend, while the EMA Slow acts as a filter for the long-term trend direction. The Parabolic SAR then helps to confirm the reversal signals.
🛠️ Tools Used
1. EMA Fast – Primary Short-Term Trend
2. EMA Slow – Long-Term Trend Filter
3. Parabolic SAR – Reversal Confirmation
🎯 Entry Rules
📈 Buy Setup
1. Trend Filter: EMA Fast > EMA Slow → Uptrend
2. Pullback: Price pulls back and closes below the EMA Fast line.
3. Reversal: Price reverses/pulls back up and closes above the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is above the high, and the dot in the current candle is below the low → Reversal signal confirmed.
5. Entry: Enter Buy immediately.
📉 Sell Setup
1. Trend Filter: EMA Fast < EMA Slow → Downtrend
2. Pullback: Price pulls back and closes above the EMA Fast line.
3. Reversal: Price reverses/pulls back down and closes below the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is below the low, and the dot in the current candle is above the high → Reversal signal confirmed.
5. Entry: Enter Sell immediately.
💰 Exit Management (Entry, Stop Loss, Take Profit)
1. Entry: Enter the order at the closing price of the signal candle.
2. Stop Loss (SL): Set the Stop Loss at the Parabolic SAR dot.
3. Take Profit (TP): Calculated from the Entry and Stop Loss points, multiplied by the Risk Reward Ratio.
⚙️ Optional Parameters
➭ Custom Risk/Reward Ratio for Take Profit.
➭ Option to add an ATR buffer to the Stop Loss.
➭ Adjustable EMA Fast period.
➭ Adjustable EMA Slow period.
➭ Adjustable Parabolic SAR parameters.
➭ Option to enable Long-only / Short-only positions.
➭ Customizable Backtest start and end date.
➭ Customizable trading session time.
🔔 Alert Function
Alerts display:
➭ Entry Price
➭ Stop Loss Price
➭ Take Profit Price
💡 This strategy allows for many parameter adjustments, such as the MA type, adding/subtracting from the Stop Loss using ATR, and selecting specific sessions for backtesting. If you find interesting or profitable results after adjusting the parameters, please share your comments with other traders!
⚠️ Disclaimer
This indicator is designed for educational and research purposes only. It does not guarantee profits and should not be considered financial advice. Trading in financial markets involves significant risk , including the potential loss of capital.
Simple MA Crossover w/ SLTPPicture two cheetahs on a racetrack made of price candles. One cheetah is fast and twitchy (the short-term EMA). The other is chill, lumbering, and takes its sweet time (the long-term EMA). When the twitchy cheetah sprints ahead and crosses above the chill one → “BUY, YOU MAGNIFICENT DEGEN!” When the twitchy one gets tired, slows down, and gets lapped from above → “SELL before this turns into a horror movie!”
That, my friend, is the EMA crossover strategy in its purest, most dramatic form.
ATR Trend + RSI Pullback Strategy [Profit-Focused]This strategy is designed to catch high-probability pullbacks during strong trends using a combination of ATR-based volatility filters, RSI exhaustion levels, and a trend-following entry model.
Strategy Logic
Rather than relying on lagging crossovers, this model waits for RSI to dip into oversold zones (below 40) while price remains above a long-term EMA (default: 200). This setup captures pullbacks in strong uptrends, allowing traders to enter early in a move while controlling risk dynamically.
To avoid entries during low-volatility conditions or sideways price action, it applies a minimum ATR filter. The ATR also defines both the stop-loss and take-profit levels, allowing the model to adapt to changing market conditions.
Exit logic includes:
A take-profit at 3× the ATR distance
A stop-loss at 1.5× the ATR distance
An optional early exit if RSI crosses above 70, signaling overbought conditions
Technical Details
Trend Filter: 200 EMA – must be rising and price must be above it
Entry Signal: RSI dips below 40 during an uptrend
Volatility Filter: ATR must be above a user-defined minimum threshold
Stop-Loss: 1.5× ATR below entry price
Take-Profit: 3.0× ATR above entry price
Exit on Overbought: RSI > 70 (optional early exit)
Backtest Settings
Initial Capital: $10,000
Position Sizing: 5% of equity per trade
Slippage: 1 tick
Commission: 0.075% per trade
Trade Direction: Long only
Timeframes Tested: 15m, 1H, and 30m on trending assets like BTCUSD, NAS100, ETHUSD
This model is tuned for positive P&L across trending environments and volatile markets.
Educational Use Only
This strategy is for educational purposes only and should not be considered financial advice. Past performance does not guarantee future results. Always validate performance on multiple markets and timeframes before using it in live trading.
Slope Rank ReversalThis tool is designed to solve the fundamental problem of "buying low and selling high" by providing objective entry/exit signals based on momentum extremes and inflection points.
The System employs three core components:
Trend Detection (PSAR): The Parabolic SAR is used as a filter to confirm that a trend reversal or transition is currently underway, isolating actionable trade setups.
Dynamic Momentum Ranking: The indicator continuously measures the slope of the price action. This slope is then ranked against historical data to objectively identify when an asset is in an extreme state (overbought or oversold).
Signal Generation (Inflection Points):
Oversold/Buy: A 🟢 Green X is generated only when the slope ranking indicates the market is steeply negative (oversold), and the slope value begins to tick upwards (the inflection point), signaling potential mean reversion.
Overbought/Sell: A 🔴 Red X is generated only when the slope ranking indicates the market is steeply positive (overbought), and the slope value begins to tick downwards, signaling momentum exhaustion.
The core philosophy is simple: Enter only when the market is exhausted and has started to turn.
Quasimodo Pattern Strategy Back Test [TradingFinder] QM Trading🔵 Introduction
The QM pattern, also known as the Quasimodo pattern, is one of the popular patterns in price action, and it is often used by technical analysts. The QM pattern is used to identify trend reversals and provides a very good risk-to-reward ratio. One of the advantages of the QM pattern is its high frequency and visibility in charts.
Additionally, due to its strength, it is highly profitable, and as mentioned, its risk-to-reward ratio is very good. The QM pattern is highly popular among traders in supply and demand, and traders also use this pattern.
The Price Action QM pattern, like other Price Action patterns, has two types: Bullish QM and Bearish QM patterns. To identify this pattern, you need to be familiar with its types to recognize it.
🔵 Identifying the QM Pattern
🟣 Bullish QM
In the bullish QM pattern, as you can see in the image below, an LL and HH are formed. As you can see, the neckline is marked as a dashed line. When the price reaches this range, it will start its upward movement.
🟣 Bearish QM
The Price Action QM pattern also has a bearish pattern. As you can see in the image below, initially, an HH and LL are formed. The neckline in this image is the dashed line, and when the LL is formed, the price reaches this neckline. However, it cannot pass it, and the downward trend resumes.
🔵 How to Use
The Quasimodo pattern is one of the clearest structures used to identify market reversals. It is built around the concept of a structural break followed by a pullback into an area of trapped liquidity. Instead of relying on lagging indicators, this pattern focuses purely on price action and how the market reacts after exhausting one side of liquidity. When understood correctly, it provides traders with precise entry points at the transition between trend phases.
🟣 Bullish Quasimodo
A bullish Quasimodo forms after a clear downtrend when sellers start losing control. The market continues to make lower lows until a sudden higher high appears, signaling that buyers are entering with strength. Price then pulls back to retest the previous low, creating what is known as the Quasimodo low.
This area often becomes the final trap for sellers before the market shifts upward. A visible rejection or displacement from this zone confirms bullish momentum. Traders usually place entries near this level, stops below the low, and targets at previous highs or the next resistance zone. Combining the setup with demand zones or Fair Value Gaps increases its accuracy.
🟣 Bearish Quasimodo
A bearish Quasimodo forms near the top of an uptrend when buyers begin to lose strength. The market continues to make higher highs until a sudden lower low breaks the bullish structure, showing that selling pressure is entering the market. Price then retraces upward to retest the previous high, forming the Quasimodo high, where breakout buyers are often trapped.
Once rejection appears at this level, it indicates a likely reversal. Traders can enter short near this area, with stop-losses placed above the high and targets near the next support or previous lows. The setup gains more reliability when aligned with supply zones, SMT divergence, or bearish Fair Value Gaps.
🔵 Setting
Pivot Period : You can use this parameter to use your desired period to identify the QM pattern. By default, this parameter is set to the number 5.
Take Profit Mode : You can choose your desired Take Profit in three ways. Based on the logic of the QM strategy, you can select two Take Profit levels, TP1 and TP2. You can also choose your take profit based on the Reward to Risk ratio. You must enter your desired R/R in the Reward to Risk Ratio parameter.
Stop Loss Refine : The loss limit of the QM strategy is based on its logic on the Head pattern. You can refine it using the ATR Refine option to prevent Stop Hunt. You can enter your desired coefficient in the Stop Loss ATR Adjustment Coefficient parameter.
Reward to Risk Ratio : If you set Take Profit Mode to R/R, you must enter your desired R/R here. For example, if your loss limit is 10 pips and you set R/R to 2, your take profit will be reached when the price is 20 pips away from your entry point.
Stop Loss ATR Adjustment Coefficient : If you set Stop Loss Refine to ATR Refine, you must adjust your loss limit coefficient here. For example, if your buy position's loss limit is at the price of 1000, and your ATR is 10, if you set Stop Loss ATR Adjustment Coefficient to 2, your loss limit will be at the price of 980.
Entry Level Validity : Determines how long the Entry level remains valid. The higher the level, the longer the entry level will remain valid. By default it is 2 and it can be set between 2 and 15.
🔵 Results
The following examples show the backtest results of the Quasimodo (QM) strategy in action. Each image is based on specific settings for the symbol, timeframe, and input parameters, illustrating how the QM logic can generate signals under different market conditions. The detailed configuration for each backtest is also displayed on the image.
⚠ Important Note : Even with identical settings and the same symbol, results may vary slightly across different brokers due to data feed variations and pricing differences.
Default Properties of Backtests :
OANDA:XAUUSD | TimeFrame: 5min | Duration: 1 Year :
BINANCE:BTCUSD | TimeFrame: 5min | Duration: 1 Year :
CAPITALCOM:US30 | TimeFrame: 5min | Duration: 1 Year :
NASDAQ:QQQ | TimeFrame: 5min | Duration: 5 Year :
OANDA:EURUSD | TimeFrame: 5min | Duration: 5 Year :
PEPPERSTONE:US500 | TimeFrame: 5min | Duration: 5 Year :
QQQ TimingThis is a trend-following position trading strategy designed for the QQQ and the leveraged ETF QLD (ProShares Ultra QQQ). The primary goal is to capture multi-month holds for maximal profit.
Key Instruments & Performance
The strategy performs best with QLD, which yields far superior results compared to QQQ.
TQQQ (triple-leveraged) results in higher drawdowns and is not the optimal choice.
Important: The system is not intended for use with other indexes, individual stocks, or investments (like crypto or gold), as performance can vary widely.
Buy Signals
The strategy's signals are rooted in the S&P 500 Index (SPX), as testing showed it provides more reliable triggers than using QQQ itself.
Primary Buy Signal (Credit to IBD/Mike Webster): The SPX triggers a buy when its low closes above the 21-day Exponential Moving Average (EMA) for three consecutive days.
Refinement with Downtrend Lines: During corrective or bear periods, results and drawdowns can be significantly improved by incorporating downtrend lines. These lines connect lower highs. The strategy waits for the price to close above a drawn downtrend line before executing a buy. This refinement can modify the primary signal, either by allowing for an earlier entry or, in some cases, completely nullifying a false signal until the trend change proves itself.
Risk Management & Exit Strategy
Initial Buy Risk: A 3.7% stop loss is applied immediately upon the initial entry.
Initial Exit Rule: An exit is required if the QQQ's low drops below the 50-day Simple Moving Average (SMA).
Note: The 3.7% stop often provides protection when the initial buy occurs below the 50-day SMA. However, if QQQ is already trading above its 50-day SMA at the time of the SPX signal (indicating relative strength), historically, it has been better to use the 50-day SMA rule to give the position more room to run.
Trend Exit (Profit-Taking): To stay in a strong trend for the optimal amount of time, the long position is exited when a moving average crossover to the downside is triggered, based around the 107-day Simple Moving Average (SMA).
Risk-On / Risk-Off Toolkit [SB1] (NQ, RTY, YM) VIXDescription:
The Risk-On / Risk-Off Toolkit is a professional-grade market context indicator designed to help traders quickly identify broad market sentiment shifts and gauge risk appetite. By combining major US equity futures (NQ, RTY, YM) with VIX dynamics, this toolkit provides clear visual signals of “Risk-On” (bullish, lower volatility environment) and “Risk-Off” (bearish, higher volatility environment) conditions. This is ideal for traders using discretionary analysis, swing strategies, intraday scalping, or portfolio positioning decisions.
My Personal Thoughts: Utilize all 3 charts to Identify which is Leading and who is lagging between the 3 (NQ, RTY, YM) Key Features:
Futures Trend Analysis:
Monitors the Nasdaq 100 (NQ), Russell 2000 (RTY), and Dow Jones (YM) futures in real-time.
Determines bullish/bearish bias based on each futures contract’s current close relative to its open.
Identifies when all three indices are moving in sync, highlighting broad market directional alignment.
VIX Confirmation:
Integrates the CBOE Volatility Index (VIX) to gauge market risk sentiment.
Confirms Risk-On conditions when VIX is falling while all three futures are bullish.
Confirms Risk-Off conditions when VIX is rising while all three futures are bearish.
Optional background shading visually highlights Risk-On (green) and Risk-Off (red) conditions for quick, intuitive assessment.
Strong Body Candle Signals:
Detects high conviction candlestick moves where the body represents at least 85% of the total range.
Confirms whether the candle closes near its extreme (top for bullish, bottom for bearish) within 15% of the range.
Plots arrows for strong bullish or bearish candles:
Green triangle-up for bullish strong candles
Red triangle-down for bearish strong candles
Provides a visual cue for intraday or swing traders to confirm trend momentum without cluttering the chart with labels.
Alert System:
Alerts can be set for Risk-On alignment: all monitored futures are bullish and VIX is falling.
Alerts can also be set for Risk-Off alignment: all monitored futures are bearish and VIX is rising.
Ensures traders never miss shifts in broad market sentiment, suitable for both intraday and end-of-day review.
Table Summary:
Provides a top-right summary table of each monitored market and VIX:
Displays Index Name and Current Bias (Bullish/Bearish/Neutral).
Highlights bullish conditions in green and bearish conditions in red.
Includes VIX status as “↓ Falling”, “↑ Rising”, or “Flat”, providing a quick visual reference of volatility trends.
Customizable Visuals:
Control the visibility of strong candle arrows.
Maintains dynamic bar coloring for strong candle moves (green for bullish, red for bearish).
How to Use the Risk-On / Risk-Off Toolkit:
Trend Confirmation: Use the alignment of NQ, RTY, and YM to determine whether the overall market environment is bullish or bearish.
Risk Sentiment Filter: Use VIX confirmation to identify if traders are in a risk-on or risk-off sentiment. This is especially useful for adjusting position sizing, hedging, or timing entries.
Momentum Validation: Strong candle arrows indicate decisive moves, providing additional confirmation for trade entries, breakouts, or trend continuation.
Alerts & Visual Cues: Set alerts to be notified whenever Risk-On or Risk-Off conditions are met, helping you act in real-time.
Quick Reference: Use the summary table for a bird’s-eye view of market alignment across indices and VIX, avoiding the need to track multiple charts simultaneously.
Why This Indicator is Unique:
Combines three major US indices with volatility confirmation to identify true macro market sentiment shifts.
Provides both visual and alert-based signals for actionable insights.
The inclusion of strong candle arrows gives intraday and swing traders a clear, low-latency cue for high-probability moves.
Perfect for multi-timeframe analysis and adaptable to both short-term and long-term strategies.
Indicator Name Justification:
The name “Risk-On / Risk-Off Toolkit ” accurately reflects the core function: identifying broad market risk appetite and sentiment alignment across key indices with volatility confirmation. It communicates instantly that the tool helps traders understand when the market is favoring risk-taking (Risk-On) versus risk-aversion (Risk-Off).
Turtles StrategyBorn from the 1980s "Turtle" experiment, this method of trading captures breakouts and places or closes trades with intrabar entries or exits and realized-equity risk controls.
How It Works
The strategy buys/sells on breakouts from recent highs/lows, using ATR for volatility-adjusted stops and sizing. It risks a fixed % (default 1%) of realized equity per trade—initial capital plus closed P&L, ignoring open positions for conservatism. Drawdown protection auto-reduces risk by 20% at 10% drops (up to three times), resetting only on full peak recovery. Single positions only, with 1-tick slippage simulated for realistic fills. Best for trending assets like forex,commodities, crypto, stocks. Backtest for optimal parameters.
Main Operations
The strategy works on any timeframe but it's meant to be used on daily charts.
Entry Signals:
Long: Buy-stop 1 tick above 20-bar high (default "Entry Period") when no position—enters intrabar on breakout.
Short: Sell-stop 1 tick below 20-bar low. OCA cancels opposites.
Size: (Realized equity × adjusted risk %) ÷ (2× ATR stop distance), scaled by point value.
Exit Signals:
Longs: Stop at tighter of (entry - 2× ATR) or (10-bar low - 1 tick trailing, default "Exit Period").
Shorts: Stop at tighter of (entry + 2× ATR) or (10-bar high + 1 tick trailing).
Locks profits in trends, exits fast on fades.
Risk Controls:
Tracks realized equity peak.
10% drawdown: Risk ×0.8; 20%/30%: Further ×0.8 (max 3x).
Full reset above peak—preserves capital in slumps.
Trend Entry_0 [TS_Indie]Trend Entry_0 — Mechanism Overview
The core structure of this strategy is based on a price action reversal pattern, as detailed below:
In the case of a Bullish Trend Reversal:
The price initially moves in a bearish direction. When candle A forms a low lower than the previous low, the high of candle A becomes a key reference point.
If the next candle closes above the high of candle A , it confirms a Bullish Trend Reversal.
* Upon a Bullish signal, a Long position is opened at the opening price of the next candle (candle B).
* When a subsequent Bearish signal occurs, the Long position is closed at the opening price of the next candle (candle C).
In the case of a Bearish Trend Reversal:
The price initially moves in a bullish direction. When candle A forms a high higher than the previous high, the low of candle A becomes a key reference point.
If the next candle closes below the low of candle A , it confirms a Bearish Trend Reversal.
* Upon a Bearish signal, a Short position is opened at the opening price of the next candle (candle B).
* When a subsequent Bullish signal occurs, the Short position is closed at the opening price of the next candle (candle C).
Options
* The start and end dates of the backtest can be customized.
* The swing lines of the trend can be displayed as an optional visual aid.
* The user can choose whether to open only Long or Short positions.
Backtest Results and Observations
Based on the backtesting results of this strategy across various assets and timeframes, it has been observed that this approach works best on trending assets such as Gold, BTC, and stocks.
It also performs well on higher timeframes, starting from the Daily timeframe and above, especially when taking Long positions only.
However, when applied to currency pairs such as EUR/USD, the results tend to be less impressive.
I encourage everyone to try backtesting and further developing this strategy — adding new conditions or filters may potentially lead to improved performance.
Disclaimer
This script is intended solely for backtesting purposes, based on a particular price action pattern.
It does not constitute financial or investment advice.
Backtest results do not guarantee future performance.
Vandan V2Vandan V2 is an automated trend-following strategy for NASDAQ E-mini Futures (NQ1!).
It uses multi-timeframe momentum and volatility filters to identify high-probability entries.
Includes dynamic risk management and trailing logic optimized for intraday trading.
RSI Divergence Strategy v6 What this does
Detects regular and hidden divergences between price and RSI using confirmed RSI pivots. Adds RSI@pivot entry gates, a normalized strength + volume filter, optional volume gate, delayed entries, and transparent risk management with rigid SL and activatable trailing. Visuals are throttled for clarity and include a gap-free horizontal RSI gradient.
How it works (simple)
🧮 RSI is calculated on your selected source/period.
📌 RSI pivots are confirmed with left/right lookbacks (lbL/lbR). A pivot becomes final only after lbR bars; before that, it can move (expected).
🔎 The latest confirmed pivot is compared against the previous confirmed pivot within your bar window:
• Regular Bullish = price lower low + RSI higher low
• Hidden Bullish = price higher low + RSI lower low
• Regular Bearish = price higher high + RSI lower high
• Hidden Bearish = price lower high + RSI higher high
💪 Each divergence gets a strength score that multiplies price % change, RSI change, and a volume ratio (Volume SMA / Baseline Volume SMA).
• Set Min divergence strength to filter tiny/noisy signals.
• Turn on the volume gate to require volume ratio ≥ your threshold (e.g., 1.0).
🎯 RSI@pivot gating:
• Longs only if RSI at the bullish pivot ≤ 30 (default).
• Shorts only if RSI at the bearish pivot ≥ 70 (default).
⏱ Entry timing:
• Immediate: on divergence confirm (delay = 0).
• Delayed: after N bars if RSI is still valid.
• RSI-only mode: ignore divergences; use RSI thresholds only.
🛡 Risk:
• Rigid SL is placed from average entry.
• Trailing activates only after unrealized gain ≥ threshold; it re-anchors on new highs (long) or new lows (short).
What’s NEW here (vs. the reference) — and why you may care
• Improved pivots + bar window → fewer early/misaligned signals; cleaner drawings.
• RSI@pivot gates → entries aligned with true oversold/overbought at the exact decision bar.
• Normalized strength + volume gate → ignore weak or low-volume divergences.
• Delayed entries → require the signal to persist N bars if you want more confirmation.
• Rigid SL + activatable trailing → trailing engages only after a cushion, so it’s less noisy.
• Clutter control + gradient → readable chart with a smooth RSI band look.
Suggested starting values (clear ranges)
• RSI@pivot thresholds: LONG ≤ 30 (oversold), SHORT ≥ 70 (overbought).
• Min divergence strength:
0.0 = off
3–6 = moderate filter
7–12 = strict filter for noisy LTFs
• Volume gate (ratio):
1.0 = at least baseline volume
1.2–1.5 = strong-volume only (fewer but cleaner signals)
• Pivot lookbacks:
lbL 1–2, lbR 3–4 (raise lbR to confirm later and reduce noise)
• Bar window (between pivots):
Min 5–10, Max 30–60 (increase Min if you see micro-pivots; increase Max for wider structures)
• Risk:
Rigid SL 2–5% on liquid majors; 5–10% on higher-volatility symbols
Trailing activation 1–3%, trailing 0.5–1.5% are common intraday starts
Plain-text examples
• BTCUSDT 1h → RSI 9, lbL 1, lbR 3, Min strength 5.0, Volume gate 1.0, SL 4.5%, Trail on 2.0%, Trail 1.0%.
• SPY 15m → RSI 8, lbL 1, lbR 3, Min strength 7.0, Volume gate 1.2, SL 3.0%, Trail on 1.5%, Trail 0.8%.
• EURUSD 4h → RSI 14, lbL 2, lbR 4, Min strength 4.0, Volume gate 1.0, SL 2.5%, Trail on 1.0%, Trail 0.5%.
Notes & limitations
• Pivot confirmation means the newest candidate pivot can move until lbR confirms it (expected).
• Results vary by timeframe/symbol/settings; always forward-test.
• Educational tool — no performance or profit claims.
Credits
• RSI by J. Welles Wilder Jr. (1978).
• Reference divergence script by eemani123:
• This version by tagstrading 2025 adds: improved pivot engine, RSI@pivot gating, normalized strength + optional volume gate, delayed entries, rigid SL and activatable trailing, and a gap-free RSI gradient.
