VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics
Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves.
This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities.
🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS
VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos.
1. The VoVix Score: Measuring Volatility Thrust
The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration.
Mathematical Formula:
VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε)
Where:
ATR(fast) is the Average True Range over a short period, representing current, immediate volatility.
ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility.
StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility.
ε (epsilon) is a very small number to prevent division by zero.
Market Implementation:
Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding.
Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting.
Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market.
2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility
The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself.
Mathematical Formula:
DEV = StDev(VoVix Score, lookback_period)
Market Implementation:
This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional.
3. The DEVMA Crossover: Identifying Regime Shifts
This is the primary signal generator. We take two moving averages of the DEV value.
Mathematical Formula:
fastDEVMA = SMA(DEV, fast_period)
slowDEVMA = SMA(DEV, slow_period)
The Core Signal:
The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility.
Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime.
Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation.
⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE
Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style.
🌀 VoVix DEVMA Configuration
🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts.
⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts.
🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared.
How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles.
🧠 Adaptive Intelligence
🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate.
⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long.
⚡ Intelligent Execution
📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing.
🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism.
🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise.
💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio).
🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run.
🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility.
⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets.
⏰ Session Management
These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open).
🎨 Visual Effects & Dashboard
These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you.
📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER
The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance.
🎯 VOVIX ANALYSIS
Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line.
Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend.
Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force.
PERFORMANCE
Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart.
EXECUTION
Trade Qty: Shows your configured position size per trade.
Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings.
POSITION
Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade.
🧠 ADAPTIVE STATUS
Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart.
🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY
The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state.
The Core Lines:
FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling.
SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling.
🌊 Morphism Flow (Flowing Lines with Circles):
What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength.
Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force.
📐 Homotopy Paths (Layered Transparent Boxes):
What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value.
Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment.
🧠 Consciousness Field (The Grid):
What it represents: This grid provides a historical lookback at the DEV range.
Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state.
📏 Functorial Levels (Projected Horizontal Lines):
What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future.
Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level.
🌊 Flow Boxes (Spaced Out Boxes):
What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction.
Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color.
Background Color:
This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second.
📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS
The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change.
Test Parameters & Conditions
To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario.
Instrument: CME E-mini Nasdaq 100 Futures (NQ1!)
Timeframe: 5-Minute Chart
Backtesting Range: March 24, 2024, to July 09, 2024
Initial Capital: $100,000
Commission: $0.62 per contract (A realistic cost for futures trading).
Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution).
Trade Size: 1 contract per trade.
Performance Overview (Historical Data)
The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation.
Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained.
Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations.
Risk & Trade Characteristics
Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior.
Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated.
Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss.
Conclusion and Final Disclaimer
This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk.
🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY
The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself.
The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation.
⚠️ RISK DISCLAIMER AND BEST PRACTICES
VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures
"The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis."
— George Soros
— Dskyz, Trade with insight. Trade with anticipation.
Komut dosyalarını "如何用wind搜索股票的发行价和份数" için ara
Multy Dynamic POCThis script displays up to 4 independent Point of Control (POC) levels based on volume profile logic.
📌 Each POC can be configured individually:
Period options: Daily (D), Weekly (W), Monthly (M), or BARS (rolling bar window).
Dynamic recalculation when the period changes (e.g., new day/week/month or custom bar count).
Price-anchored lines for each POC level that scale correctly with the chart.
Customizable line color and thickness.
🔍 How it works:
For each active POC line, the script builds a simple volume distribution based on the candle’s average price (hl2) and volume.
The price range is split into 100 buckets. The one with the highest accumulated volume is selected as the Point of Control (POC).
In BARS mode, POC is recalculated every N bars. In D/W/M modes, it resets exactly at the beginning of a new period (according to TradingView’s time() function).
✅ Useful for:
Traders applying volume profile analysis without needing the full built-in volume profile tool.
Spotting dynamic high-volume zones in trends or ranges.
Strategy development or confirmation around high-interest price levels.
_______________________________________________________________________________
Данный индикатор отображает до 4 независимых уровней Point of Control (POC), рассчитанных по объёмам.
📌 Каждый POC можно настраивать отдельно:
Периоды: День (D), Неделя (W), Месяц (M) или BARS (скользящее окно по количеству баров).
Автоматический пересчёт при смене периода (например, новый день, неделя или месяц).
Линии POC привязаны к цене и масштабируются вместе с графиком.
Настраиваемый цвет и толщина линий.
🔍 Как работает:
Для каждой активной линии POC создаётся объёмное распределение: берется средняя цена свечи (hl2) и объем.
Диапазон цен делится на 100 уровней. Тот, где накоплено больше всего объёма, и есть POC.
В режиме BARS уровень пересчитывается каждые N баров. В режимах D/W/M — строго в начале нового периода.
✅ Подходит для:
Трейдеров, использующих объёмный анализ, но не имеющих платной подписки на Volume Profile.
Поиска уровней интереса и подтверждения сигналов.
Разработки стратегий с опорой на объём.
Range Breakout [sgbpulse]Range Breakout
1. Overview
The "Range Breakout " indicator is a powerful tool designed to identify and visually display price ranges on your chart using pivot points. It dynamically draws two distinct boxes – an External Range and an Internal Range – helping traders pinpoint potential support and resistance zones. Beyond its visual representation, the indicator offers a comprehensive set of 12 unique breakout alerts, providing real-time notifications for significant price movements outside these defined ranges. Additionally, it integrates RSI and MFI metrics for momentum confirmation.
2. How It Works
The indicator operates by identifying pivot points based on user-defined "left" and "right" bar lengths. A high pivot is a bar with a specified number of lower highs both to its left and right, and similarly for a low pivot.
External Range: Calculated using longer pivot lengths (default: 15 bars left, 6 bars right). This range represents broader, more significant price consolidation areas.
Internal Range: Calculated using shorter pivot lengths (default: 4 bars left, 3 bars right). This range captures tighter, more immediate price consolidations within the broader trend.
The External Range will always be greater than or equal to the Internal Range, as it's based on a wider historical context. Both ranges are displayed as transparent boxes on your chart, dynamically adjusting as new pivots are formed.
3. Key Features and Settings
Customizable Pivot Lengths:
External Range (Left/Right Bars): Adjust sensitivity for identifying the broader price range. Longer lengths lead to more stable, but less frequent, range updates.
Internal Range (Left/Right Bars): Adjust sensitivity for the tighter, more immediate price range.
Tool Tips: Minimum 6 bars for the External Range, and minimum 2 bars for the Internal Range.
Customizable Range Colors: Easily change the background colors of the External and Internal Range boxes to match your chart's aesthetic.
Dynamic Range Display: The indicator automatically updates the range boxes as new pivot highs and lows are formed, always presenting the most current valid ranges.
RSI / MFI Settings:
Timeframe Source: Select the timeframe for RSI and MFI calculation.
- Chart: Calculation based on the current chart timeframe.
- Daily: Always calculated based on the daily ("D") timeframe, even if the chart is on a lower timeframe.
RSI Length: Period length for RSI calculation (default: 14).
RSI Overbought Level: Overbought level for RSI (default: 70.0).
RSI Oversold Level: Oversold level for RSI (default: 30.0).
MFI Length: Period length for MFI calculation (default: 14).
MFI Overbought Level: Overbought level for MFI (default: 80.0).
MFI Oversold Level: Oversold level for MFI (default: 20.0).
4. Synergy of Ranges & Breakout Strength
The interaction between the External and Internal Ranges provides deep insights into price movement and breakout strength:
Immediate Direction: The movement of the Internal Range (up or down) indicates the short-term directional bias within the broader framework of the External Range.
Strength Confirmation: A breakout of the External Range, followed by a breakout of the Internal Range, confirms the strength of the move and increases confidence in the breakout.
Strong Momentum ("Leaving" Ranges Behind): When price breaks out with exceptionally strong momentum, it continues to move aggressively and does not immediately form new pivots. In such situations, the existing ranges (External and Internal) remain in place while the candles "leave them behind." A "Full Candle" breakout, where the entire candle moves past both ranges, indicates a particularly powerful and decisive move.
Momentum (RSI / MFI) as Confirmation:
- RSI (Relative Strength Index): Measures the speed and change of price movements. Extreme values (above 70 or below 30) indicate overbought/oversold conditions respectively, confirming strong momentum in a breakout.
- MFI (Money Flow Index): Similar to RSI but incorporates volume. Extreme values (above 80 or below 20) indicate strong money flow in/out, reinforcing breakout confirmation.
- Importance of Confirmation: If a breakout occurs but momentum indicators do not confirm it (for example, an upside breakout while RSI is declining), this could signal weakness in the move and the risk of a false breakout (Fakeout).
5. Visuals
The indicator provides clear visual representations on the chart:
Range Boxes:
Two dynamic boxes are drawn on the chart: one for the External Range and one for the Internal Range.
These boxes update continuously, displaying the current range boundaries based on the latest pivots. They provide an immediate visual indication of support and resistance levels.
RSI/MFI Status Labels:
Small text labels appear to the right of the current bar, vertically centered.
They display the status of RSI and MFI: RSI OB (Overbought), RSI OS (Oversold), MFI OB, MFI OS, along with the exact value.
Important: The labels remain on the chart as long as the condition holds (indicator is above/below the level), unlike alerts which mark a singular crossover event.
Plotting of Key Values:
The indicator plots six invisible series on the chart, primarily to allow the user to view the exact numerical values of:
- The upper and lower bounds of the External Range (External High, External Low).
- The upper and lower bounds of the Internal Range (Internal High, Internal Low).
- The calculated RSI and MFI values (RSI, MFI).
These values are accessible for viewing through TradingView's Data Window and also via the Status Line when hovering over the relevant candle. This enables more precise quantitative analysis of range levels and momentum.
6. Comprehensive Breakout Alerts
The "Range Breakout " indicator provides 12 distinct alert conditions for breakouts, allowing you to select the required level of confirmation for each alert. All alerts are triggered only upon a fully confirmed bar close (barstate.isconfirmed) to minimize false signals and ensure reliability.
All breakout alerts are configured to detect a Crossover/Crossunder of the levels, meaning a specific event where the price moves from one side of the range to the other.
External Range Breakout UP
- Close: Price closes above the External Range.
- Real Body: The entire "real body" of the candle (min of open/close prices) closes above the External Range.
- Full Candle: The entire candle (the lowest point of the candle) closes above the External Range.
External Range Breakout DOWN
- Close: Price closes below the External Range.
- Real Body: The entire "real body" of the candle (max of open/close prices) closes below the External Range.
- Full Candle: The entire candle (the highest point of the candle) closes below the External Range.
Internal Range Breakout UP
- Close: Price closes above the Internal Range.
- Real Body: The "real body" of the candle closes above the Internal Range.
- Full Candle: The entire candle closes above the Internal Range.
Internal Range Breakout DOWN
- Close: Price closes below the Internal Range.
- Real Body: The "real body" of the candle closes below the Internal Range.
- Full Candle: The entire candle closes below the Internal Range.
7. Ideal Use Cases
This indicator is ideal for traders who:
Want to clearly identify and monitor price consolidation zones.
Seek confirmation for breakout strategies across various timeframes.
Require reliable and automated alerts for potential entry or exit points based on range expansion.
8. Complementary Indicator
For even more comprehensive market analysis, we highly recommend using this indicator in conjunction with Market Structure Support & Resistance External/Internal & BoS .
This powerful complementary indicator automatically and accurately identifies significant support and resistance levels by locating high and low pivot points, as well as key Pre-Market High/Low levels. Its strength lies in its dynamic adaptability to any timeframe and asset, providing precise and relevant real-time levels while maintaining a clean chart. It also identifies Break of Structure (BoS) to signal potential trend changes or continuations.
Using both indicators together provides a robust framework for identifying defined ranges and potential trend shifts, enabling more informed trading decisions.
View Market Structure Support & Resistance External/Internal & BoS Indicator
9. Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
True Breakout Pattern [TradingFinder] Breakout Signal Indicator🔵 Introduction
In many market conditions, what initially appears to be a decisive breakout often turns out to be nothing more than a false breakout or fake breakout. Price breaks through a key swing level or an important support and resistance zone, only to quickly return to its previous range.
These failed breakouts, which are often the result of liquidity traps or market manipulation, serve more as a warning sign of structural weakness than confirmation of a new trend.
This indicator is designed around the concept of the fake breakout.
The logic is simple but precise : when price breaks a swing level and returns to that level within a maximum of five candles, the move is considered a false breakout. At this point, a Fibonacci retracement is applied to the recent price swing to evaluate the pullback area.
If price, within ten candles after the return to the breakout level, enters the Fibonacci zone between 0.618 and 1.0, the setup becomes valid for a potential entry. This area is identified as a long entry zone, with the stop loss placed just beyond the 1.0 level and the take profit defined based on the desired risk-to-reward ratio.
By combining accurate detection of false breakouts, analysis of price reaction to swing levels, and alignment with Fibonacci retracement logic, this framework allows traders to identify opportunities often missed by others. In a market where failed breakouts are a common and recurring phenomenon, this indicator aims to transform these traps into measurable trading opportunities.
Long Setup :
Short Setup :
🔵 How to Use
This indicator operates based on the recognition of false breakouts from structural levels in the market, specifically swing levels, and combines that with Fibonacci retracement analysis.
In this strategy, trades are only considered when price returns to the broken level within a defined time window and reacts appropriately inside a predefined Fibonacci range. Depending on the direction of the initial breakout, the system outlines two scenarios for long and short setups.
🟣 Long Setup
In the long setup, price initially breaks below a support level or swing low. If the price returns to the broken level within a maximum of five candles, the move is identified as a fake breakout.
At this stage, a Fibonacci retracement is drawn from the recent high to the low. If price, within ten candles of returning to the level, moves into the 0.618 to 1.0 Fibonacci zone, the conditions for a long entry are met.
The stop loss is placed slightly below the 1.0 level, while the take profit is set based on the trader’s preferred risk-reward ratio. This setup aims to capture deeply discounted entries at low risk, aligned with smart money reversals.
🟣 Short Setup
In the short setup, the price breaks above a resistance level or swing high. If the price returns to that level within five candles, the move is again treated as a false breakout. Fibonacci is then drawn from the recent low to the high to observe the retracement area.
Should price enter the 0.618 to 1.0 Fibonacci range within ten candles of returning, a short entry is considered valid. In this case, the stop loss is placed just above the 1.0 level, and the take profit is adjusted based on the intended risk-reward target. This method allows traders to identify high-probability short setups by focusing on failed breakouts and deep pullbacks.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
Valid After Trigger Bars : Limits how many candles after a fake breakout the entry zone remains valid.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert False Breakout : Enables alerts for Breakout.
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
A sound understanding of the false breakout phenomenon and its relationship to structural price behavior is essential for technical traders aiming to improve precision and consistency. Many poor trading decisions stem from misinterpreting failed breakouts and entering too early into weak signals.
A structured approach, grounded in the analysis of swing levels and validated through specific price action and timing rules, can turn these misleading moves into valuable trade opportunities.
This indicator, by combining fake breakout detection with time filters and Fibonacci-based retracement zones, helps traders only engage with the market when multiple confirming factors are in alignment. The result is a strategy that emphasizes probability, risk control, and clarity in decision-making, offering a solid edge in navigating today’s volatile markets.
5 EMA STRATEGY by Power of Stocks(StockYogi)5 EMA STRATEGY by Power of Stocks(StockYogi)
This is a 5 EMA Breakout Strategy inspired by the trading principles taught by Shubhashi Pani, founder of the Power of Stocks (POS) community.
The strategy is designed to:
• Detect breakout setups when price breaks the high/low of a signal candle (based on EMA conditions)
• Enter trades only if the breakout occurs within the next 3 candles
• Allow multiple trades in the same direction without closing the earlier one
• Use independent stop-loss (SL) and take-profit (TP) targets for each trade based on a user-defined risk-reward ratio
• Optionally enter trades only at candle close
• Optionally avoid trades during a custom time window (e.g., 3:00 PM to 3:30 PM IST)
• Optionally close all open positions at a defined time (e.g., 3:30 PM IST)
The goal of this strategy is to provide greater flexibility and realism for intraday or short-term traders following structured breakout systems.
Disclaimer: This script is an implementation of technical ideas for educational purposes only. It is not financial advice. All trading involves risk, and past performance does not guarantee future results.
Strategy Credits:
This strategy is based on publicly known breakout rules taught by Shubhashi Pani (Power of Stocks). This is not an official POS script, and I am not affiliated with the Power of Stocks team. This implementation was developed independently to follow the logic shared for educational use.
Feel free to use, backtest, and modify according to your needs. Constructive feedback is welcome!
Fast Fourier Transform [ScorsoneEnterprises]The SCE Fast Fourier Transform (FFT) is a tool designed to analyze periodicities and cyclical structures embedded in price. This is a Fourier analysis to transform price data from the time domain into the frequency domain, showing the rhythmic behaviors that are otherwise invisible on standard charts.
Instead of merely observing raw prices, this implementation applies the FFT on the logarithmic returns of the asset:
Log Return(𝑚) = log(close / close )
This ensures stationarity and stabilizes variance, making the analysis statistically robust and less influenced by trends or large price swings.
For a user-defined lookback window 𝑁:
Each frequency component 𝑘 is computed by summing real and imaginary projections of log-returns multiplied by complex exponential functions:
𝑒^−𝑖𝜃 = cos(𝜃)−𝑖sin(𝜃)
where:
θ = 2πkm / N
he result is the magnitude spectrum, calculated as:
Magnitude(𝑘) = sqrt(Real_Sum(𝑘)^2 + Imag_Sum(𝑘)^2)
This spectrum represents the strength of oscillations at each frequency over the lookback period, helping traders identify dominant cycles.
Visual Analysis & Interpretation
To give traders context for the FFT spectrum’s values, this script calculates:
25th Percentile (Purple Line)
Represents relatively low cyclical intensity.
Values below this threshold may signal quiet, noisy, or trendless periods.
75th Percentile (Red Line)
Represents heightened cyclical dominance.
Values above this threshold may indicate significant periodic activity and potential trend formation or rhythm in price action.
The FFT magnitude of the lowest frequency component (index 0) is plotted directly on the chart in teal. Observing how this signal fluctuates relative to its percentile bands provides a dynamic measure of cyclical market activity.
Chart examples
In this NYSE:CL chart, we see the regime of the price accurately described in the spectral analysis. We see the price above the 75th percentile continue to trend higher until it breaks back below.
In long trending markets like NYSE:PL has been, it can give a very good explanation of the strength. There was confidence to not switch regimes as we never crossed below the 75th percentile early in the move.
The script is also usable on the lower timeframes. There is no difference in the usability from the different timeframes.
Script Parameters
Lookback Value (N)
Default: 30
Defines how many bars of data to analyze. Larger N captures longer-term cycles but may smooth out shorter-term oscillations.
EVaR Indicator and Position SizingThe Problem:
Financial markets consistently show "fat-tailed" distributions where extreme events occur with higher frequency than predicted by normal distributions (Gaussian or even log-normal). These fat tails manifest in sudden price crashes, volatility spikes, and black swan events that traditional risk measures like volatility can underestimate. Standard deviation and conventional VaR calculations assume normally distributed returns, leaving traders vulnerable to severe drawdowns during market stress.
Cryptocurrencies and volatile instruments display particularly pronounced fat-tailed behavior, with extreme moves occurring 5-10 times more frequently than normal distribution models would predict. This reality demands a more sophisticated approach to risk measurement and position sizing.
The Solution: Entropic Value at Risk (EVAR)
EVaR addresses these limitations by incorporating principles from statistical mechanics and information theory through Tsallis entropy. This advanced approach captures the non-linear dependencies and power-law distributions characteristic of real financial markets.
Entropy is more adaptive than standard deviations and volatility measures.
I was inspired to create this indicator after reading the paper " The End of Mean-Variance? Tsallis Entropy Revolutionises Portfolio Optimisation in Cryptocurrencies " by by Sana Gaied Chortane and Kamel Naoui.
Key advantages of EVAR over traditional risk measures:
Superior tail risk capture: More accurately quantifies the probability of extreme market moves
Adaptability to market regimes: Self-calibrates to changing volatility environments
Non-parametric flexibility: Makes less assumptions about the underlying return distribution
Forward-looking risk assessment: Better anticipates potential market changes (just look at the charts :)
Mathematically, EVAR is defined as:
EVAR_α(X) = inf_{z>0} {z * log(1/α * M_X(1/z))}
Where the moment-generating function is calculated using q-exponentials rather than conventional exponentials, allowing precise modeling of fat-tailed behavior.
Technical Implementation
This indicator implements EVAR through a q-exponential approach from Tsallis statistics:
Returns Calculation: Price returns are calculated over the lookback period
Moment Generating Function: Approximated using q-exponentials to account for fat tails
EVAR Computation: Derived from the MGF and confidence parameter
Normalization: Scaled to for intuitive visualization
Position Sizing: Inversely modulated based on normalized EVAR
The q-parameter controls tail sensitivity—higher values (1.5-2.0) increase the weighting of extreme events in the calculation, making the model more conservative during potentially turbulent conditions.
Indicator Components
1. EVAR Risk Visualization
Dynamic EVAR Plot: Color-coded from red to green normalized risk measurement (0-1)
Risk Thresholds: Reference lines at 0.3, 0.5, and 0.7 delineating risk zones
2. Position Sizing Matrix
Risk Assessment: Current risk level and raw EVAR value
Position Recommendations: Percentage allocation, dollar value, and quantity
Stop Parameters: Mathematically derived stop price with percentage distance
Drawdown Projection: Maximum theoretical loss if stop is triggered
Interpretation and Application
The normalized EVAR reading provides a probabilistic risk assessment:
< 0.3: Low risk environment with minimal tail concerns
0.3-0.5: Moderate risk with standard tail behavior
0.5-0.7: Elevated risk with increased probability of significant moves
> 0.7: High risk environment with substantial tail risk present
Position sizing is automatically calculated using an inverse relationship to EVAR, contracting during high-risk periods and expanding during low-risk conditions. This is a counter-cyclical approach that ensures consistent risk exposure across varying market regimes, especially when the market is hyped or overheated.
Parameter Optimization
For optimal risk assessment across market conditions:
Lookback Period: Determines the historical window for risk calculation
Q Parameter: Controls tail sensitivity (higher values increase conservatism)
Confidence Level: Sets the statistical threshold for risk assessment
For cryptocurrencies and highly volatile instruments, a q-parameter between 1.5-2.0 typically provides the most accurate risk assessment because it helps capturing the fat-tailed behavior characteristic of these markets. You can also increase the q-parameter for more conservative approaches.
Practical Applications
Adaptive Risk Management: Quantify and respond to changing tail risk conditions
Volatility-Normalized Positioning: Maintain consistent exposure across market regimes
Black Swan Detection: Early identification of potential extreme market conditions
Portfolio Construction: Apply consistent risk-based sizing across diverse instruments
This indicator is my own approach to entropy-based risk measures as an alterative to volatility and standard deviations and it helps with fat-tailed markets.
Enjoy!
ARSI – (VWAP & ATR) 3QKRAKThe ARSI Long & Short – Dynamic Risk Sizing (VWAP & ATR) indicator combines three core components—an adjusted RSI oscillator (ARSI), Volume‐Weighted Average Price (VWAP), and Average True Range (ATR)—so that entry/exit signals and position sizing are always tailored to current market conditions. ARSI, plotted from 0 to 100 with clearly marked overbought and oversold zones, is the primary signal driver: when ARSI falls below the lower threshold it indicates an excessive sell‐off and flags a long opportunity, whereas a break above the upper threshold signals overextended gains and foreshadows a short. A midpoint line at 50 can serve as an early exit or reduction signal when crossed against your position.
VWAP, showing the volume‐weighted average price over the chosen period, acts as a trend filter—long trades are only taken when price sits above VWAP, and shorts only when it’s below—ensuring each trade aligns with the prevailing market momentum. ATR measures current volatility and is used both to set safe stop‐loss levels and to dynamically size each position. In practice, this means positions automatically shrink in high‐volatility environments and grow in quieter markets, all while risking a fixed percentage of your capital.
Everything appears on a single chart: the ARSI pane below the price window with its reference levels; VWAP overlaid on the price; and the ATR‐based stop‐loss distances graphically displayed. Traders thus get a comprehensive, at-a-glance view of entries, exits, trend confirmation, and exactly how large a position they can safely take. The indicator runs in real time, removing the need for manual parameter calculations and letting you focus on strategic decision-making.
log.info() - 5 Exampleslog.info() is one of the most powerful tools in Pine Script that no one knows about. Whenever you code, you want to be able to debug, or find out why something isn’t working. The log.info() command will help you do that. Without it, creating more complex Pine Scripts becomes exponentially more difficult.
The first thing to note is that log.info() only displays strings. So, if you have a variable that is not a string, you must turn it into a string in order for log.info() to work. The way you do that is with the str.tostring() command. And remember, it's all lower case! You can throw in any numeric value (float, int, timestamp) into str.string() and it should work.
Next, in order to make your output intelligible, you may want to identify whatever value you are logging. For example, if an RSI value is 50, you don’t want a bunch of lines that just say “50”. You may want it to say “RSI = 50”.
To do that, you’ll have to use the concatenation operator. For example, if you have a variable called “rsi”, and its value is 50, then you would use the “+” concatenation symbol.
EXAMPLE 1
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//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
log.info(“RSI= ” + str.tostring(rsi))
Example Output =>
RSI= 50
Here, we use double quotes to create a string that contains the name of the variable, in this case “RSI = “, then we concatenate it with a stringified version of the variable, rsi.
Now that you know how to write a log, where do you view them? There isn’t a lot of documentation on it, and the link is not conveniently located.
Open up the “Pine Editor” tab at the bottom of any chart view, and you’ll see a “3 dot” button at the top right of the pane. Click that, and right above the “Help” menu item you’ll see “Pine logs”. Clicking that will open that to open a pane on the right of your browser - replacing whatever was in the right pane area before. This is where your log output will show up.
But, because you’re dealing with time series data, using the log.info() command without some type of condition will give you a fast moving stream of numbers that will be difficult to interpret. So, you may only want the output to show up once per bar, or only under specific conditions.
To have the output show up only after all computations have completed, you’ll need to use the barState.islast command. Remember, barState is camelCase, but islast is not!
EXAMPLE 2
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//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
if barState.islast
log.info("RSI=" + str.tostring(rsi))
plot(rsi)
However, this can be less than ideal, because you may want the value of the rsi variable on a particular bar, at a particular time, or under a specific chart condition. Let’s hit these one at a time.
In each of these cases, the built-in bar_index variable will come in handy. When debugging, I typically like to assign a variable “bix” to represent bar_index, and include it in the output.
So, if I want to see the rsi value when RSI crosses above 0.5, then I would have something like
EXAMPLE 3
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//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,0.5)
if rsiCrossedOver
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
Example Output =>
bix=19964 - RSI=51.8449459867
bix=19972 - RSI=50.0975830828
bix=19983 - RSI=53.3529808079
bix=19985 - RSI=53.1595745146
bix=19999 - RSI=66.6466337654
bix=20001 - RSI=52.2191767466
Here, we see that the output only appears when the condition is met.
A useful thing to know is that if you want to limit the number of decimal places, then you would use the command str.tostring(rsi,”#.##”), which tells the interpreter that the format of the number should only be 2 decimal places. Or you could round the rsi variable with a command like rsi2 = math.round(rsi*100)/100 . In either case you’re output would look like:
bix=19964 - RSI=51.84
bix=19972 - RSI=50.1
bix=19983 - RSI=53.35
bix=19985 - RSI=53.16
bix=19999 - RSI=66.65
bix=20001 - RSI=52.22
This would decrease the amount of memory that’s being used to display your variable’s values, which can become a limitation for the log.info() command. It only allows 4096 characters per line, so when you get to trying to output arrays (which is another cool feature), you’ll have to keep that in mind.
Another thing to note is that log output is always preceded by a timestamp, but for the sake of brevity, I’m not including those in the output examples.
If you wanted to only output a value after the chart was fully loaded, that’s when barState.islast command comes in. Under this condition, only one line of output is created per tick update — AFTER the chart has finished loading. For example, if you only want to see what the the current bar_index and rsi values are, without filling up your log window with everything that happens before, then you could use the following code:
EXAMPLE 4
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//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
bix = bar_index
if barstate.islast
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
Example Output =>
bix=20203 - RSI=53.1103309071
This value would keep updating after every new bar tick.
The log.info() command is a huge help in creating new scripts, however, it does have its limitations. As mentioned earlier, only 4096 characters are allowed per line. So, although you can use log.info() to output arrays, you have to be aware of how many characters that array will use.
The following code DOES NOT WORK! And, the only way you can find out why will be the red exclamation point next to the name of the indicator. That, and nothing will show up on the chart, or in the logs.
// CODE DOESN’T WORK
//@version=6
indicator("MW - log.info()")
var array rsi_arr = array.new()
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,50)
if rsiCrossedOver
array.push(rsi_arr, rsi)
if barstate.islast
log.info("rsi_arr:" + str.tostring(rsi_arr))
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
// No code errors, but will not compile because too much is being written to the logs.
However, after putting some time restrictions in with the i_startTime and i_endTime user input variables, and creating a dateFilter variable to use in the conditions, I can limit the size of the final array. So, the following code does work.
EXAMPLE 5
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// CODE DOES WORK
//@version=6
indicator("MW - log.info()")
i_startTime = input.time(title="Start", defval=timestamp("01 Jan 2025 13:30 +0000"))
i_endTime = input.time(title="End", defval=timestamp("1 Jan 2099 19:30 +0000"))
var array rsi_arr = array.new()
dateFilter = time >= i_startTime and time <= i_endTime
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,50) and dateFilter // <== The dateFilter condition keeps the array from getting too big
if rsiCrossedOver
array.push(rsi_arr, rsi)
if barstate.islast
log.info("rsi_arr:" + str.tostring(rsi_arr))
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
Example Output =>
rsi_arr:
bix=20210 - RSI=56.9030578034
Of course, if you restrict the decimal places by using the rounding the rsi value with something like rsiRounded = math.round(rsi * 100) / 100 , then you can further reduce the size of your array. In this case the output may look something like:
Example Output =>
rsi_arr:
bix=20210 - RSI=55.6947486019
This will give your code a little breathing room.
In a nutshell, I was coding for over a year trying to debug by pushing output to labels, tables, and using libraries that cluttered up my code. Once I was able to debug with log.info() it was a game changer. I was able to start building much more advanced scripts. Hopefully, this will help you on your journey as well.
Better MACD📘 Better MACD – Adaptive Momentum & Divergence Suite
Better MACD is a comprehensive momentum-trend tool that evolves the traditional MACD into a multi-dimensional, divergence-aware oscillator. It leverages exponential smoothing across logarithmic rate-of-change of OHLC data, adaptive signal processing, and intelligent divergence detection logic to provide traders with earlier, smoother, and more reliable momentum signals.
This indicator is built for professional-level analysis, suitable for scalping, swing trading, and trend-following systems.
🧬 Core Concept
Unlike the classic MACD which subtracts two EMAs of price, Better MACD constructs a signal by:
Applying logarithmic transformation on the change between OHLC components (Close, High, Low, Open).
Using double EMA smoothing to filter noise and volatility, Triangular method. 1st to 2nd Smoothing.
Averaging and de-biasing the results through a custom linear regression model, 4th Smoothing.
Subtracting a fast SMA and slow SMA response to yield a dynamic MACD value, 3rd Smoothing.
The result is a smooth, adaptive, and high-resolution MACD-style oscillator that responds more naturally to trend conditions and price geometry.
🧠 Features Breakdown
1. 📈 Multi-Layer MACD Engine
Src1: Smoothed Log Rate-of-Change on Close
Src2: Smoothed Log Rate-of-Change on High
Src3: Smoothed Log Rate-of-Change on Low
Src4: Smoothed Log Rate-of-Change on Open
These are blended using highest high, lowest low, and average Close price over a configurable window for more complete trend detection. The open-based Src4 is subtracted using SMA.
2. 🧮 Signal Line
A fast EMA (signalLength) of the Better MACD value is used for crossover logic.
Crossovers of MACD and Signal line signal potential entries or exits.
3. 📊 MACD Histogram
Visualizes the difference between MACD and Signal line.
Dynamically color-coded:
Green/Light Green for bullish impulse
Red/Pink for bearish impulse
Width and color intensity reflect strength and momentum slope.
🎨 Visual Enhancements
Feature Description
✅ Ribbon Fill Optional fill between MACD and Signal line, colored by trend direction
✅ Zero-Line Background Background highlights above/below 0 to easily read bullish/bearish bias
✅ Crossover Highlights Tiny circles plotted when MACD crosses Signal line
🔍 Divergence Detection Suite
The script includes a full Divergence Engine to detect:
🔼 Bullish Regular Divergence (Price lower lows + Indicator higher lows)
🔽 Bearish Regular Divergence (Price higher highs + Indicator lower highs)
🟢 Bullish Hidden Divergence (Price higher lows + Indicator lower lows)
🔴 Bearish Hidden Divergence (Price lower highs + Indicator higher highs)
🧩 Divergence Modes:
Supports both Regular, Hidden, or Both simultaneously
Detects from either Close Price or Heikin Ashi-derived candles
Uses dynamic pivot tracking with configurable lookback and divergence sensitivity
Divergence lines are labeled, colored, and plotted in real-time
🔁 Styling & Customization:
Choose from Solid, Dashed, or Dotted line styles
Configure separate colors and widths for all divergence types
Control number of divergence lines visible or only show the most recent
Divergences update live without repainting
⚠️ Alerts
Alerts are built-in for real-time notification:
MACD Histogram reversals (rising → falling, or vice versa)
Divergence signals (all 4 types, grouped and individually)
Combines seamlessly with TradingView alerts for actionable triggers
🔧 Input Controls (Grouped by Purpose)
Better MACD Group
1st–4th Smoothing Lengths: Controls responsiveness of MACD core engine
Signal Length: Smoothness of signal line
Toggles for crossover highlights, zero cross fills, and ribbon fills
Divergence Settings
Enable/disable divergence lines
Choose divergence type (Regular, Hidden, Both)
Set confirmation requirements
Customize pivot detection and bar search depth
Styling Options
Colors, line widths, and line styles for each divergence type
Heikin Ashi Mode for smoother pivots and divergences
🧠 How to Use
✅ For Trend Traders:
Use MACD > Signal + Histogram > 0 → Bullish confirmation
MACD < Signal + Histogram < 0 → Bearish confirmation
Wait for pullbacks with hidden divergences to enter in trend direction
✅ For Reversal Traders:
Look for Regular Divergences at trend exhaustion points
Combine with price action (e.g., support/resistance or candle pattern)
✅ For Swing & Day Traders:
Enable Heikin Ashi Mode for smoother divergence pivots
Use zero line background + histogram color to time entries
📌 Summary
Feature Description
🚀 Advanced MACD Core Smoother, more reliable, multi-source-based MACD
🔍 Divergence Engine Detects 4 divergence types with pivot logic
🎯 Real-Time Alerts Alerts for histogram slope and divergences
🎛️ Deep Customization Full styling, smoothing, and detection controls
📉 Heikin Ashi Support Improved signal quality in trend-based markets
Normalized Volume IndexIn the realm of technical analysis, volume is more than just a measure of market activity—it’s a window into trader psychology. Two classic indicators that harness this insight are the Positive Volume Index (PVI) and Negative Volume Index (NVI). Developed in the early 20th century by Paul L. Dysart and later refined by Norman G. Fosback in 1976, these tools aim to distinguish between the behavior of the so-called “smart money” and the broader market crowd.
- Positive Volume Index (PVI) tracks price changes only on days when trading volume increases. It assumes that rising volume reflects the actions of less-informed retail traders—those who follow the herd.
- Negative Volume Index (NVI), on the other hand, focuses on days when volume decreases, under the premise that institutional investors (the “smart money”) are more active when the market is quiet.
This dichotomy allows traders to interpret market sentiment through the lens of volume behavior. For example, a rising NVI during a price uptrend may suggest that institutional investors are quietly accumulating positions—often a bullish signal.
Traders use PVI and NVI to:
- Confirm trends: If NVI is above its moving average, it often signals a strong underlying trend supported by smart money.
- Spot reversals: Divergences between price and either index can hint at weakening momentum or upcoming reversals.
- Gauge participation: PVI rising faster than price may indicate overenthusiastic retail buying—potentially a contrarian signal.
These indicators are often paired with moving averages (e.g., 255-day EMA) to generate actionable signals. Fosback’s research suggested that when NVI is above its one-year EMA, there’s a high probability of a bull market.
While PVI and NVI are cumulative indices, normalizing them—for example, by rebasing to 100 or converting to percentage changes—offers several benefits:
- Comparability: Normalized indices can be compared across different assets or timeframes.
- Clarity: It becomes easier to visualize relative strength or weakness.
- Backtesting: Normalized values are more suitable for algorithmic strategies and statistical analysis.
Normalization also helps when combining PVI/NVI with other indicators in multi-factor models, ensuring no single metric dominates due to scale differences
In essence, PVI and NVI offer a nuanced view of market dynamics by separating the noise of volume surges from the quiet confidence of institutional moves. When normalized and interpreted correctly, they become powerful allies in a trader’s decision-making toolkit.
How to use this (Educational material):
For instance, on average, when the Negative Volume Index (NVI) remains above its midline, the market tends to trend positively, reflecting consistent institutional participation. However, when the NVI dips and stays below the midline, it often signals a negative trend, indicating that smart money is stepping away or reducing exposure.
Another telling scenario occurs when the Positive Volume Index (PVI) drops below the NVI. While this might coincide with a brief price dip, institutions often interpret this as an opportunity to buy the dip, quietly accumulating positions while retail participants exit in panic. The result? A market recovery driven by smart money.
Conversely, when the PVI consistently remains above the NVI, it may point to retail enthusiasm outpacing institutional support. This imbalance can flag a tired or overextended trend, where the smart money has already positioned itself defensively. When this pattern persists, there's a high likelihood that institutions will pull the plug, leading to a pronounced trend reversal.
F&O Time Zones – Final Fixed📌 This indicator highlights high-probability intraday time zones used in Indian F&O (Futures & Options) strategies. Ideal for scalping, breakout setups, and trap avoidance.
🕒 Covered Time Zones:
• 9:15 – 9:21 AM → Flash Trades (first 1-minute volatility)
• 9:21 – 9:30 AM → Smart Money Trap (VWAP fakeouts)
• 9:30 – 9:50 AM → Fake Breakout Zone
• 9:50 – 10:15 AM → Institutional Entry Timing
• 10:15 – 10:45 AM → VWAP Range Scalps
• 10:45 – 11:15 AM → Second Trap Zone
• 11:15 – 1:00 PM → Trend Continuation Window
• 1:00 – 1:45 PM → Volatility Compression
• 1:45 – 2:15 PM → Institutional Exit Phase 1
• 2:15 – 2:45 PM → Trend Acceleration / Reversals
• 2:45 – 3:15 PM → Expiry Scalping Zone
• 3:15 – 3:30 PM → Dead Zone (square-off time)
🔧 Features:
✓ Clean vertical lines per zone
✓ Optional label positions (top or bottom)
✓ Adjustable line style, width, and color
🧠 Best used on: NIFTY, BANKNIFTY, FINNIFTY (5-min or lower)
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🔒 **Disclaimer**:
This script is for **educational purposes only**. It is not financial advice. Trading involves risk. Please consult a professional or do your own research before taking any positions.
—
👤 Script by: **JoanJagan**
🛠️ Built in Pine Script v5
Rolling 250-Day Sharpe RatioThis Pine Script indicator, “Rolling 250-Day Sharpe Ratio”, computes the trailing Sharpe Ratio for any traded asset over a 250-session window, equivalent to approximately one trading year. The script first derives daily log returns and adjusts them by subtracting the daily equivalent of the 3-month US Treasury yield to obtain the excess return. It then calculates the rolling mean and standard deviation of these excess returns to produce the annualized Sharpe Ratio, which is displayed as a continuous time series on the chart. This allows traders and analysts to assess how the asset’s risk-adjusted performance evolves over time relative to a risk-free benchmark.
A persistently high Sharpe Ratio can indicate strong risk-adjusted returns, but it is essential to approach extreme values with caution. Elevated Sharpe readings can sometimes reflect unsustainable trends, excessive leverage, or periods of unusually low volatility that may revert abruptly. Conversely, a low or negative Sharpe Ratio does not automatically imply an asset should be avoided; it might signal an opportunity if the risk environment normalizes.
True Close – Institutional Trading Sessions (Zeiierman)█ Overview
True Close – Institutional Trading Sessions (Zeiierman) is a professional-grade session mapping tool designed to help traders align with how institutions perceive the market’s true close. Unlike the textbook “daily close” used by retail traders, institutional desks often anchor their risk management, execution benchmarks, and exposure metrics to the first hour of the next session.
This indicator visualizes that logic directly on your chart — drawing session boxes, true close levels, and time-aligned labels across Sydney, Tokyo, London, and New York. It highlights the first hour of each session, projects the institutional closing price, and builds a live dashboard that tells you which sessions are active, which are in the critical opening phase, and what levels matter most right now.
More than just a visual tool, this indicator embeds institutional rhythm directly into your workflow — giving you a window into where big players finalize yesterday’s business, rebalance exposure, and execute delayed orders. It’s not just about painting sessions on your chart — it’s about adopting the mindset of those who truly move the market. Institutions don’t settle risk at the bell; they complete it in the next session. This tool lets you see that transition in real time, giving you an edge that goes beyond candles and indicators.
█ How It Works
⚪ Session Detection Engine
Each session is identified by its own time block (e.g., 09:00–17:30 for London). Once a session opens:
A full-session box is drawn to track its range.
The first hour is highlighted separately.
Once the first hour completes, the true close line is plotted, representing the price institutions often treat as the "real" close of the prior day.
⚪ Institutional True Close Logic
The script captures the close of the first hour, not the end of the day.
This line becomes a static reference across your chart, letting you visualize how price interacts with that institutional anchor:
Rejections from it show where yesterday's flow is respected.
Breaks through it may indicate that today's flows are rewriting the narrative.
⚪ Dynamic Dashboard Table
A live table appears in the corner of your screen, showing:
Each session's active status
Whether we’re inside the first hour
The current “true close” price if available
Each cell comes with advanced tooltips giving institutional context, flow dynamics, and market microstructure insights — from rebalancing spillovers to VWAP/TWAP lag effects.
█ How to Use
⚪ Use the First-Hour Line as Your Institutional Anchor
Treat it like the price level that big funds care about. Watch how the price behaves around level. Fades, re-tests, or continuation moves often occur as the market finishes recapping yesterday’s leftover orders.
⚪ Structure Entries Around the Session Context
Are you inside the first hour? Expect more volatility, more decisive flow. After the first session hour, expect fading liquidity as the market slows down and awaits the next session to open.
█ Settings
UTC Offset – Select your preferred time zone; all sessions adjust accordingly.
Session Toggles – Enable/disable Sydney, Tokyo, London, or NY.
Box Display Options – Show/hide session background, first-hour fill, borders.
True Close Line Controls – Enable line, label, and customize width & color.
Execution Hour Labels – Optional toggle for first-hour label placement.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Uptrick: Fusion Trend Reversion SystemOverview
The Uptrick: Fusion Trend Reversion System is a multi-layered indicator designed to identify potential price reversals during intraday movement while keeping traders informed of the dominant short-term trend. It blends a composite fair value model with deviation logic and a refined momentum filter using the Relative Strength Index (RSI). This tool was created with scalpers and short-term traders in mind and is especially effective on lower timeframes such as 1-minute, 5-minute, and 15-minute charts where price dislocations and quick momentum shifts are frequent.
Introduction
This indicator is built around the fusion of two classic concepts in technical trading: identifying trend direction and spotting potential reversion points. These are often handled separately, but this system merges them into one process. It starts by computing a fair value price using five moving averages, each with its own mathematical structure and strengths. These include the exponential moving average (EMA), which gives more weight to recent data; the simple moving average (SMA), which gives equal weight to all periods; the weighted moving average (WMA), which progressively increases weight with recency; the Arnaud Legoux moving average (ALMA), known for smoothing without lag; and the volume-weighted average price (VWAP), which factors in volume at each price level.
All five are averaged into a single value — the raw fusion line. This fusion acts as a dynamically balanced centerline that adapts to price conditions with both smoothing and responsiveness. Two additional exponential moving averages are applied to the raw fusion line. One is slower, giving a stable trend reference, and the other is faster, used to define momentum and cloud behavior. These two lines — the fusion slow and fusion fast — form the backbone of trend and signal logic.
Purpose
This system is meant for traders who want to trade reversals without losing sight of the underlying directional bias. Many reversal indicators fail because they act too early or signal too frequently in choppy markets. This script filters out noise through two conditions: price deviation and RSI confirmation. Reversion trades are considered only when the price moves a significant distance from fair value and RSI suggests a legitimate shift in momentum. That filtering process gives the trader a cleaner, higher-quality signal and reduces false entries.
The indicator also visually supports the trader through colored bars, up/down labels, and a filled cloud between the fast and slow fusion lines. These features make the market context immediately visible: whether the trend is up or down, whether a reversal just occurred, and whether price is currently in a high-risk reversion zone.
Originality and Uniqueness
What makes this script different from most reversal systems is the way it combines layers of logic — not just to detect signals, but to qualify and structure them. Rather than relying on a single MA or a raw RSI level, it uses a five-MA fusion to create a baseline fair value that incorporates speed, stability, and volume-awareness.
On top of that, the system introduces a dual-smoothing mechanism. It doesn’t just smooth price once — it creates two layers: one to follow the general trend and another to track faster deviations. This structure lets the script distinguish between continuation moves and possible turning points more effectively than a single-line or single-metric system.
It also uses RSI in a more refined way. Instead of just checking if RSI is overbought or oversold, the script smooths RSI and requires directional confirmation. Beyond that, it includes signal memory. Once a signal is generated, a new one will not appear unless the RSI becomes even more extreme and curls back again. This memory-based gating reduces signal clutter and prevents repetition, a rare feature in similar scripts.
Why these indicators were merged
Each moving average in the fusion serves a specific role. EMA reacts quickly to recent price changes and is often favored in fast-trading strategies. SMA acts as a long-term filter and smooths erratic behavior. WMA blends responsiveness with smoothing in a more balanced way. ALMA focuses on minimizing lag without losing detail, which is helpful in fast markets. VWAP anchors price to real trade volume, giving a sense of where actual positioning is happening.
By combining all five, the script creates a fair value model that doesn’t lean too heavily on one logic type. This fusion is then smoothed into two separate EMAs: one slower (trend layer), one faster (signal layer). The difference between these forms the basis of the trend cloud, which can be toggled on or off visually.
RSI is then used to confirm whether price is reversing with enough force to warrant a trade. The RSI is calculated over a 14-period window and smoothed with a 7-period EMA. The reason for smoothing RSI is to cut down on noise and avoid reacting to short, insignificant spikes. A signal is only considered if price is stretched away from the trend line and the smoothed RSI is in a reversal state — below 30 and rising for bullish setups, above 70 and falling for bearish ones.
Calculations
The script follows this structure:
Calculate EMA, SMA, WMA, ALMA, and VWAP using the same base length
Average the five values to form the raw fusion line
Smooth the raw fusion line with an EMA using sens1 to create the fusion slow line
Smooth the raw fusion line with another EMA using sens2 to create the fusion fast line
If fusion slow is rising and price is above it, trend is bullish
If fusion slow is falling and price is below it, trend is bearish
Calculate RSI over 14 periods
Smooth RSI using a 7-period EMA
Determine deviation as the absolute difference between current price and fusion slow
A raw signal is flagged if deviation exceeds the threshold
A raw signal is flagged if RSI EMA is under 30 and rising (bullish setup)
A raw signal is flagged if RSI EMA is over 70 and falling (bearish setup)
A final signal is confirmed for a bullish setup if RSI EMA is lower than the last bullish signal’s RSI
A final signal is confirmed for a bearish setup if RSI EMA is higher than the last bearish signal’s RSI
Reset the bullish RSI memory if RSI EMA rises above 30
Reset the bearish RSI memory if RSI EMA falls below 70
Store last signal direction and use it for optional bar coloring
Draw the trend cloud between fusion fast and fusion slow using fill()
Show signal labels only if showSignals is enabled
Bar and candle colors reflect either trend slope or last signal direction depending on mode selected
How it works
Once the script is loaded, it builds a fusion line by averaging five different types of moving averages. That line is smoothed twice into a fast and slow version. These two fusion lines form the structure for identifying trend direction and signal areas.
Trend bias is defined by the slope of the slow line. If the slow line is rising and price is above it, the market is considered bullish. If the slow line is falling and price is below it, it’s considered bearish.
Meanwhile, the script monitors how far price has moved from that slow line. If price is stretched beyond a certain distance (set by the threshold), and RSI confirms that momentum is reversing, a raw reversion signal is created. But the script only allows that signal to show if RSI has moved further into oversold or overbought territory than it did at the last signal. This blocks repetitive, weak entries. The memory is cleared only if RSI exits the zone — above 30 for bullish, below 70 for bearish.
Once a signal is accepted, a label is drawn. If the signal toggle is off, no label will be shown regardless of conditions. Bar colors are controlled separately — you can color them based on trend slope or last signal, depending on your selected mode.
Inputs
You can adjust the following settings:
MA Length: Sets the period for all moving averages used in the fusion.
Show Reversion Signals: Turns on the plotting of “Up” and “Down” labels when a reversal is confirmed.
Bar Coloring: Enables or disables colored bars based on trend or signal direction.
Show Trend Cloud: Fills the space between the fusion fast and slow lines to reflect trend bias.
Bar Color Mode: Lets you choose whether bars follow trend logic or last signal direction.
Sens 1: Smoothing speed for the slow fusion line — higher values = slower trend.
Sens 2: Smoothing speed for the fast line — lower values = faster signal response.
Deviation Threshold: Minimum distance price must move from fair value to trigger a signal check.
Features
This indicator offers:
A composite fair value model using five moving average types.
Dual smoothing system with user-defined sensitivity.
Slope-based trend definition tied to price position.
Deviation-triggered signal logic filtered by RSI reversal.
RSI memory system that blocks repetitive signals and resets only when RSI exits overbought or oversold zones.
Real-time tracking of the last signal’s direction for optional bar coloring.
Up/Down labels at signal points, visible only when enabled.
Optional trend cloud between fusion layers, visualizing current market bias.
Full user control over smoothing, threshold, color modes, and visibility.
Conclusion
The Fusion Trend-Reversion System is a tool for short-term traders looking to fade price extremes without ignoring trend bias. It calculates fair value using five diverse moving averages, smooths this into two dynamic layers, and applies strict reversal logic based on RSI deviation and momentum strength. Signals are triggered only when price is stretched and momentum confirms it with increasingly strong behavior. This combination makes the tool suitable for scalping, intraday entries, and fast market environments where precision matters.
Disclaimer
This indicator is for informational and educational purposes only. It does not constitute financial advice. All trading involves risk, and no tool can predict market behavior with certainty. Use proper risk management and do your own research before making trading decisions.
RifleShooterLibLibrary "RifleShooterLib"
Provides a collection of helper functions in support of the Rifle Shooter Indicators.
Functions support the key components of the Rifle Trade algorithm including
* measuring momentum
* identifying paraboloic price action (to disable the algorthim during such time)
* determine the lookback criteria of X point movement in last N minutes
* processing and navigating between the 23/43/73 levels
* maintaining a status table of algorithm progress
toStrRnd(val, digits)
Parameters:
val (float)
digits (int)
_isValidTimeRange(startTimeInput, endTimeInput)
Parameters:
startTimeInput (string)
endTimeInput (string)
_normalize(_src, _min, _max)
_normalize Normalizes series with unknown min/max using historical min/max.
Parameters:
_src (float) : Source series to normalize
_min (float) : minimum value of the rescaled series
_max (float) : maximum value of the rescaled series
Returns: The series scaled with values between min and max
arrayToSeries(arrayInput)
arrayToSeries Return an array from the provided series.
Parameters:
arrayInput (array) : Source array to convert to a series
Returns: The array as a series datatype
f_parabolicFiltering(_activeCount, long, shooterRsi, shooterRsiLongThreshold, shooterRsiShortThreshold, fiveMinuteRsi, fiveMinRsiLongThreshold, fiveMinRsiShortThreshold, shooterRsiRoc, shooterRsiRocLongThreshold, shooterRsiRocShortThreshold, quickChangeLookbackBars, quckChangeThreshold, curBarChangeThreshold, changeFromPrevBarThreshold, maxBarsToholdParabolicMoveActive, generateLabels)
f_parabolicFiltering Return true when price action indicates a parabolic active movement based on the provided inputs and thresholds.
Parameters:
_activeCount (int)
long (bool)
shooterRsi (float)
shooterRsiLongThreshold (float)
shooterRsiShortThreshold (float)
fiveMinuteRsi (float)
fiveMinRsiLongThreshold (float)
fiveMinRsiShortThreshold (float)
shooterRsiRoc (float)
shooterRsiRocLongThreshold (float)
shooterRsiRocShortThreshold (float)
quickChangeLookbackBars (int)
quckChangeThreshold (int)
curBarChangeThreshold (int)
changeFromPrevBarThreshold (int)
maxBarsToholdParabolicMoveActive (int)
generateLabels (bool)
rsiValid(rsi, buyThreshold, sellThreshold)
rsiValid Returns true if the provided RSI value is withing the associated threshold. For the unused threshold set it to na
Parameters:
rsi (float)
buyThreshold (float)
sellThreshold (float)
squezeBands(source, length)
squezeBands Returns the squeeze bands momentum color of current source series input
Parameters:
source (float)
length (int)
f_momentumOscilator(source, length, transperency)
f_momentumOscilator Returns the squeeze pro momentum value and bar color states of the series input
Parameters:
source (float)
length (int)
transperency (int)
f_getLookbackExtreme(lowSeries, highSeries, lbBars, long)
f_getLookbackExtreme Return the highest high or lowest low over the look back window
Parameters:
lowSeries (float)
highSeries (float)
lbBars (int)
long (bool)
f_getInitialMoveTarget(lbExtreme, priveMoveOffset, long)
f_getInitialMoveTarget Return the point delta required to achieve an initial rifle move (X points over Y lookback)
Parameters:
lbExtreme (float)
priveMoveOffset (int)
long (bool)
isSymbolSupported(sym)
isSymbolSupported Return true if provided symbol is one of the supported DOW Rifle Indicator symbols
Parameters:
sym (string)
getBasePrice(price)
getBasePrice Returns integer portion of provided float
Parameters:
price (float)
getLastTwoDigitsOfPrice(price)
getBasePrice Returns last two integer numerals of provided float value
Parameters:
price (float)
getNextLevelDown(price, lowestLevel, middleLevel, highestLevel)
getNextLevelDown Returns the next level above the provided price value
Parameters:
price (float)
lowestLevel (float)
middleLevel (float)
highestLevel (float)
getNextLevelUp(price, lowestLevel, middleLevel, highestLevel)
getNextLevelUp Returns the next level below the provided price value
Parameters:
price (float)
lowestLevel (float)
middleLevel (float)
highestLevel (float)
isALevel(price, lowestLevel, middleLevel, highestLevel)
isALevel Returns true if the provided price is onve of the specified levels
Parameters:
price (float)
lowestLevel (float)
middleLevel (float)
highestLevel (float)
getClosestLevel(price, lowestLevel, middleLevel, highestLevel)
getClosestLevel Returns the level closest to the price value provided
Parameters:
price (float)
lowestLevel (float)
middleLevel (float)
highestLevel (float)
f_fillSetupTableCell(_table, _col, _row, _text, _bgcolor, _txtcolor, _text_size)
f_fillSetupTableCell Helper function to fill a setup table celll
Parameters:
_table (table)
_col (int)
_row (int)
_text (string)
_bgcolor (color)
_txtcolor (color)
_text_size (string)
f_fillSetupTableRow(_table, _row, _col0Str, _col1Str, _col2Str, _bgcolor, _textColor, _textSize)
f_fillSetupTableRow Helper function to fill a setup table row
Parameters:
_table (table)
_row (int)
_col0Str (string)
_col1Str (string)
_col2Str (string)
_bgcolor (color)
_textColor (color)
_textSize (string)
f_addBlankRow(_table, _row)
f_addBlankRow Helper function to fill a setup table row with empty values
Parameters:
_table (table)
_row (int)
f_updateVersionTable(versionTable, versionStr, versionDateStr)
f_updateVersionTable Helper function to fill the version table with provided values
Parameters:
versionTable (table)
versionStr (string)
versionDateStr (string)
f_updateSetupTable(_table, parabolicMoveActive, initialMoveTargetOffset, initialMoveAchieved, shooterRsi, shooterRsiValid, rsiRocEnterThreshold, shooterRsiRoc, fiveMinuteRsi, fiveMinuteRsiValid, requireValid5MinuteRsiForEntry, stallLevelOffset, stallLevelExceeded, stallTargetOffset, recoverStallLevelValid, curBarChangeValid, volumeRoc, volumeRocThreshold, enableVolumeRocForTrigger, tradeActive, entryPrice, curCloseOffset, curSymCashDelta, djiCashDelta, showDjiDelta, longIndicator, fontSize)
f_updateSetupTable Manages writing current data to the setup table
Parameters:
_table (table)
parabolicMoveActive (bool)
initialMoveTargetOffset (float)
initialMoveAchieved (bool)
shooterRsi (float)
shooterRsiValid (bool)
rsiRocEnterThreshold (float)
shooterRsiRoc (float)
fiveMinuteRsi (float)
fiveMinuteRsiValid (bool)
requireValid5MinuteRsiForEntry (bool)
stallLevelOffset (float)
stallLevelExceeded (bool)
stallTargetOffset (float)
recoverStallLevelValid (bool)
curBarChangeValid (bool)
volumeRoc (float)
volumeRocThreshold (float)
enableVolumeRocForTrigger (bool)
tradeActive (bool)
entryPrice (float)
curCloseOffset (float)
curSymCashDelta (float)
djiCashDelta (float)
showDjiDelta (bool)
longIndicator (bool)
fontSize (string)
