Quad Rotation StochasticQuad Rotation Stochastic
The Quad Rotation Stochastic is a powerful and unique momentum oscillator that combines four different stochastic setups into one tool, providing an incredibly detailed view of market conditions. This multi-timeframe stochastic approach helps traders better anticipate trend continuations, reversals, and momentum shifts with greater precision than traditional single stochastic indicators.
Why this indicator is useful:
Multi-layered Momentum Analysis: Instead of relying on one stochastic, this script tracks four independent stochastic readings, smoothing out noise and confirming stronger signals.
Advanced Divergence Detection: It automatically identifies bullish and bearish divergences for each stochastic, helping traders spot potential reversals early.
Background Color Alerts: When a configurable number (e.g., 3 or 4) of the stochastics agree in direction and position (overbought/oversold), the background colors green (bullish) or red (bearish) to give instant visual cues.
ABCD Pattern Recognition: The script recognizes "shield" patterns when Stochastic 4 remains stuck at extreme levels (above 90 or below 10) for a set time, warning of potential trend continuation setups.
Super Signal Alerts: If all four stochastics align in extreme conditions and slope in the same direction, the indicator plots a special "Super Signal," offering high-confidence entry opportunities.
Why this indicator is unique:
Quad Confirmation Logic: Combining four different stochastics makes this tool much less prone to false signals compared to using a single stochastic.
Customizable Divergence Coloring: Traders can choose to have divergence lines automatically match the stochastic color for clear visual association.
Adaptive ABCD Shields: Innovative use of bar counting while a stochastic remains extreme acts as a "shield," offering a unique way to filter out minor fake-outs.
Flexible Configuration: Each stochastic's sensitivity, divergence settings, and visual styling can be fully customized, allowing traders to adapt it to their own strategy and asset.
Example Usage: Trading Bitcoin with Quad Rotation Stochastic
When trading Bitcoin (BTCUSD), you might set the minimum count (minCount) to 3, meaning three out of four stochastics must be in agreement to trigger a background color.
If the background turns green, and you notice an ABCD Bullish Shield (Green X), you might look for bullish candlestick patterns or moving average crossovers to enter a long trade.
Conversely, if the background turns red and a Super Down Signal appears, it suggests high probability for further downside, giving you strong confirmation to either short BTC or avoid entering new longs.
By combining divergence signals with background colors and the ABCD shields, the Quad Rotation Stochastic provides a layered confirmation system that gives traders greater confidence in their entries and exits — particularly in fast-moving, volatile markets like Bitcoin.
Momentum Indicator (MOM)
Pi Cycle | AlchimistOfCrypto Pi Cycle Top Indicator - A Powerful Market Phase Detector
Developed by AlchimistOfCrypto
🧪 The Pi Cycle uses mathematical harmony to identify Bitcoin market cycle tops
with remarkable precision. Just as elements react at specific temperatures,
Bitcoin price behaves predictably when these two moving averages converge! 🧬
⚗️ The formula measures when the 111-day SMA crosses below the 350-day SMA × 2,
creating a perfect alchemical reaction that has successfully identified the
major cycle tops in 2013, 2017, and 2021.
🔬 Like the Golden Ratio in nature, this indicator reveals the hidden
mathematical structure within Bitcoin's chaotic price movements.
🧮 When the reaction occurs, prepare for molecular breakdown! 🔥
Institutional Composite Moving Average (ICMA) [Volume Vigilante]Institutional Composite Moving Average (ICMA)
The Next Evolution of Moving Averages — Built for Real Traders.
ICMA blends the strength of four powerful averages (SMA, EMA, WMA, HMA) into a single ultra-responsive, ultra-smooth signal.
It reacts faster than traditional MAs while filtering out noise, giving you clean trend direction with minimal lag.
🔹 Key Features:
• Faster reaction than SMA, EMA, or WMA individually
• Smoother and more stable than raw HMA
• Naturally adapts across trend, momentum, and consolidation conditions
• Zero gimmicks. Zero repainting. Full institutional quality.
🔹 Designed For:
• Scalping
• Swing trading
• Signal engines
• Algorithmic systems
📎 How to Use:
• Overlay it on any chart
• Fine-tune the length per timeframe
• Combine with your entries/exits for maximum edge
Created by Volume Vigilante 🧬 — Delivering Real-World Trading Tools.
RSI Strength & Consolidation Zones (Zeiierman)█ Overview
RSI Strength & Consolidation Zones (Zeiierman) is a hybrid momentum and volatility visualization tool that blends enhanced RSI interpretation with ADX-driven consolidation detection. This indicator doesn't just show where RSI is trending — it interprets how strong that trend is, when that strength changes, and where the market may be consolidating in anticipation of breakout movement.
Using a combination of Kalman-filtered RSI, custom-built DMI/ADX, and low-volatility zone recognition, it gives traders a dynamic RSI with strength-based coloring, while also highlighting consolidation zones to spot breakout opportunities.
█ Its uniqueness
Traditional RSI indicators lack context. They may show you when the market is overbought or oversold, but they won’t tell you how strong that condition is, or whether it’s likely to result in continuation or consolidation.
This tool aims to solve that by introducing adaptive strength metrics and structural compression zones, allowing traders to anticipate when the market is likely preparing for a move.
█ How It Works
⚪ Enhanced RSI
Combines traditional RSI and a custom RSI implementation
Smooths both through a Kalman filter for trend direction
Final RSI line reflects smoothed consensus between manual and built-in RSI
Adds an RSI + Strength overlay to show when the directional conviction is increasing
⚪ ADX-Driven Strength Layer
Directional Movement Index (DMI) is calculated both manually and with built-in smoothing
The average ADX value is used to calculate a strength modifier
When ADX exceeds 20, RSI is dynamically enhanced or dampened to reflect directional force
Resulting visual: RSI appears stronger or weaker based on confirmed trend conditions
⚪ Consolidation Zone Detection
When ADX falls below 20, the indicator enters a consolidation zone state
Boxes are drawn dynamically to contain the price within these low-volatility structures
Once the price breaks out of the zone, the indicator plots a breakout signal (▲ or ▼)
⚪ Breakouts
Breakout markers are placed at the first close outside the consolidation box
These signals serve as early indicators for potential trend continuation or reversal
█ How to Use
⚪ Confirm Momentum Strength
Use the RSI + Strength line to determine whether current momentum is backed by trend conviction. If strength expands alongside rising RSI, the move has confirmation.
⚪ Consolidations Zones
When RSI is around the midline, and a consolidation box appears, expect lower volatility and a range-bound market, followed by a breakout.
⚪ Use Breakout Signals for Entry
Look for ▲ or ▼ markers as early triggers. These often coincide with volume expansions or structural breaks.
█ Settings Explained
RSI Length – Number of bars used for RSI. Shorter = more sensitive.
DMI Length – Used in both custom and built-in ADX/DI calculations.
ADX Smoothing – Smooths the trend strength signal. Higher values = smoother strength detection.
Trend Confirmation (Filter Strength) – Adjusts the responsiveness of the Kalman filter.
-----------------
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.
Dskyz Options Flow Flux (OFF) - FuturesDskyz Options Flow Flux (OFF) - Futures
*This is a repost due to moderator intervention on use of ™ in my scripts. I'm in the process of getting this rectified. This was originally posted around mid-night CDT.
🧠 The Dskyz Options Flow Flux (OFF) - Futures indicator is a game changer for futures traders looking to tap into institutional activity with limited resources. Designed for TradingView this tool simulates options flow data (call/put volume and open interest) for futures contracts like MNQ MES NQ and ES giving u actionable insights through volume spike detection volatility adjustments and stunning visuals like aurora flux bands and round number levels. Whether u’re a beginner learning the ropes or a pro hunting for an edge this indicator delivers real time market sentiment and key price levels to boost ur trading game
Key Features
⚡ Simulated Options Flow: Breaks down call/put volume and open interest using market momentum and volatility
📈 Spike Detection: Spots big moves in volume and open interest with customizable thresholds
🧠 Volatility Filter: Adapts to market conditions using ATR for smarter spike detection
✨ Aurora Flux Bands: Glows with market sentiment showing u bullish or bearish vibes at a glance
🎯 Round Number Levels: Marks key psychological levels where big players might step in
📊 Interactive Dashboard: Real time metrics like sentiment score and volatility factor right on ur chart
🚨 Alerts: Get notified of bullish or bearish spikes so u never miss a move
How It Works
🧠 This indicator is built to make complex options flow analysis simple even with the constraints of Pine Script. Here’s the step by step:
Simulated Volume Data (Dynamic Split):
Pulls daily volume for ur chosen futures contract (MNQ1! MES1! NQ1! ES1!)
Splits it into call and put volume based on momentum (ta.mom) and volatility (ATR vs its 20 period average)
Estimates open interest (OI) for calls and puts (1.15x for calls 1.1x for puts)
Formula: callRatio = 0.5 + (momentum / close) * 10 + (volatility - 1) * 0.1 capped between 0.3 and 0.7
Why It Matters: Mimics how big players might split their trades giving u a peek into institutional sentiment
Spike Detection:
Compares current volume/OI to short term (lookbackShort) and long term (lookbackLong) averages
Flags spikes when volume/OI exceeds the average by ur set threshold (spikeThreshold for regular highConfidenceThreshold for strong)
Adjusts for volatility so u’re not fooled by choppy markets
Output: optionsSignal (2 for strong bullish -2 for strong bearish 1 for bullish -1 for bearish 0 for neutral)
Why It Matters: Pinpoints where big money might be stepping in
Volatility Filter:
Uses ATR (10 periods) and its 20 period average to calculate a volatility factor (volFactor = ATR / avgAtr)
Scales spike thresholds based on market conditions (volAdjustedThreshold = spikeThreshold * max(1 volFactor * volFilter))
Why It Matters: Keeps ur signals reliable whether the market is calm or wild
Sentiment Score:
Calculates a call/put ratio (callVolume / putVolume) and adjusts for volatility
Converts it to a 0 to 100 score (higher = bullish lower = bearish)
Formula: sentimentScore = min(max((volAdjustedSentiment - 1) * 50 0) 100)
Why It Matters: Gives u a quick read on market bias
Round Number Detection:
Finds the nearest round number (e.g. 100 for MNQ1! 50 for MES1!)
Checks for volume spikes (volume > 3 period SMA * spikeThreshold) and if price is close (within ATR * atrMultiplier)
Updates the top activity level every 15 minutes when significant activity is detected
Why It Matters: Highlights psychological levels where price often reacts
Visuals and Dashboard:
Combines aurora flux bands glow effects round number lines and a dashboard to make insights pop (see Visual Elements below)
Plots triangles for call/put spikes (green/red for strong lime/orange for regular)
Sets up alerts for key market moves
Why It Matters: Makes complex data easy to read at a glance
Inputs and Customization
⚙️ Beginners can tweak these settings to match their trading style while pros can dig deeper for precision:
Futures Symbol (symbol): Pick ur contract (MNQ1! MES1! NQ1! ES1!). Default: MNQ1!
Short Lookback (lookbackShort): Days for short term averages. Smaller = more sensitive. Range: 1+. Default: 5
Long Lookback (lookbackLong): Days for long term averages. Range: 5+. Default: 10
Spike Threshold (spikeThreshold): How big a spike needs to be (e.g. 1.1 = 10% above average). Range: 1.0+. Default: 1.1
High Confidence Threshold (highConfidenceThreshold): For strong spikes (e.g. 3.0 = 3x average). Range: 2.0+. Default: 3.0
Volatility Filter (volFilter): Adjusts for market volatility (e.g. 1.2 = 20% stricter in volatile markets). Range: 1.0+. Default: 1.2
Aurora Flux Transparency (glowOpacity): Controls band transparency (0 = solid 100 = invisible). Range: 0 to 100. Default: 65
Show Show OFF Dashboard (showDashboard): Toggles the dashboard with key metrics. Default: true
Show Nearest Round Number (showRoundNumbers): Displays round number levels. Default: true
ATR Multiplier for Proximity (atrMultiplier): How close price needs to be to a round number (e.g. 1.5 = within 1.5x ATR). Range: 0.5+. Default: 1.5
Functions and Logic
🧠 Here’s the techy stuff pros will love:
Simulated Volume Data : Splits daily volume into call/put volume and OI using momentum and volatility
Volatility Filter: Scales thresholds with volFactor = atr / avgAtr for adaptive detection
Spike Detection: Flags spikes and assigns optionsSignal (2, -2, 1, -1, 0) for sentiment
Sentiment Score: Converts call/put ratio into a 0-100 score for quick bias reads
Round Number Detection: Identifies key levels and significant activity for trading zones
Dashboard Display: Updates real time metrics like sentiment score and volatility factor
Visual Elements
✨ These visuals make data come alive:
Gradient Background: Green (bullish) red (bearish) or yellow (neutral/choppy) at 95% transparency to show trend
Aurora Flux Bands: Stepped bands (linewidth 3) around a 14 period EMA ± ATR * 1.8. Colors shift with sentiment (green red lime orange gray) with glow effects at 85% transparency
Round Number Visualization: Stepped lines (linewidth 2) at key levels (solid if active dashed if not) with labels (black background white text size.normal)
Visual Signals: Triangles above/below bars for spikes (size.small for strong size.tiny for regular)
Dashboard: Bottom left table (2 columns 10 rows) with a black background (29% transparency) gray border and metrics:
⚡ Round Number Activity: “Detected” or “None”
📈 Trend: “Bullish” “Bearish” or “Neutral” (colored green/red/gray)
🧠 ATR: Current 10 period ATR
📊 ATR Avg: 20 period SMA of ATR
📉 Volume Spike: “YES” (green) or “NO” (red)
📋 Call/Put Ratio: Current ratio
✨ Flux Signal: “Strong Bullish” “Strong Bearish” “Bullish” “Bearish” or “Neutral” (colored green/red/gray)
⚙️ Volatility Factor: Current volFactor
📈 Sentiment Score: 0-100 score
Usage and Strategy Recommendations
🎯 For Beginners: Use high confidence spikes (green/red triangles) for easy entries. Check the dashboard for a quick market read (sentiment score above 60 = bullish below 40 = bearish). Watch round number levels for support/resistance
💡 For Pros: Combine flux signals with round number activity for high probability setups. Adjust lookbackShort/lookbackLong for trending vs choppy markets. Use volFactor for position sizing (higher = smaller positions)
Clenow MomentumClenow Momentum Method
The Clenow Momentum Method, developed by Andreas Clenow, is a systematic, quantitative trading strategy focused on capturing medium- to long-term price trends in financial markets. Popularized through Clenow’s book, Stocks on the Move: Beating the Market with Hedge Fund Momentum Strategies, the method leverages momentum—an empirically observed phenomenon where assets that have performed well in the recent past tend to continue performing well in the near future.
Theoretical Foundation
Momentum investing is grounded in behavioral finance and market inefficiencies. Investors often exhibit herding behavior, underreact to new information, or chase trends, causing prices to trend beyond fundamental values. Clenow’s method builds on academic research, such as Jegadeesh and Titman (1993), which demonstrated that stocks with high returns over 3–12 months outperform those with low returns over similar periods.
Clenow’s approach specifically uses **annualized momentum**, calculated as the rate of return over a lookback period (typically 90 days), annualized to reflect a yearly percentage. The formula is:
Momentum=(((Close N periods agoCurrent Close)^N252)−1)×100
- Current Close: The most recent closing price.
- Close N periods ago: The closing price N periods back (e.g., 90 days).
- N: Lookback period (commonly 90 days).
- 252: Approximate trading days in a year for annualization.
This metric ranks stocks by their momentum, prioritizing those with the strongest upward trends. Clenow’s method also incorporates risk management, diversification, and volatility adjustments to enhance robustness.
Methodology
The Clenow Momentum Method involves the following steps:
1. Universe Selection:
- A broad universe of liquid stocks is chosen, often from major indices (e.g., S&P 500, Nasdaq 100) or global exchanges.
- Filters should exclude illiquid stocks (e.g., low average daily volume) or those with extreme volatility.
2. Momentum Calculation:
- Stocks are ranked based on their annualized momentum over a lookback period (typically 90 days, though 60–120 days can be common tests).
- The top-ranked stocks (e.g., top 10–20%) are selected for the portfolio.
3. Volatility Adjustment (Optional):
- Clenow sometimes adjusts momentum scores by volatility (e.g., dividing by the standard deviation of returns) to favor stocks with smoother trends.
- This reduces exposure to erratic price movements.
4. Portfolio Construction:
- A diversified portfolio of 10–25 stocks is constructed, with equal or volatility-weighted allocations.
- Position sizes are often adjusted based on risk (e.g., 1% of capital per position).
5. Rebalancing:
- The portfolio is rebalanced periodically (e.g., weekly or monthly) to maintain exposure to high-momentum stocks.
- Stocks falling below a momentum threshold are replaced with higher-ranked candidates.
6. Risk Management:
- Stop-losses or trailing stops may be applied to limit downside risk.
- Diversification across sectors reduces concentration risk.
Implementation in TradingView
Key features include:
- Customizable Lookback: Users can adjust the lookback period in pinescript (e.g., 90 days) to align with Clenow’s methodology.
- Visual Cues: Background colors (green for positive, red for negative momentum) and a zero line help identify trend strength.
- Integration with Screeners: TradingView’s stock screener can filter high-momentum stocks, which can then be analyzed with the custom indicator.
Strengths
1. Simplicity: The method is straightforward, relying on a single metric (momentum) that’s easy to calculate and interpret.
2. Empirical Support: Backed by decades of academic research and real-world hedge fund performance.
3. Adaptability: Applicable to stocks, ETFs, or other asset classes, with flexible lookback periods.
4. Risk Management: Diversification and periodic rebalancing reduce idiosyncratic risk.
5. TradingView Integration: Pine Script implementation enables real-time visualization, enhancing decision-making for stocks like NVDA or SPY.
Limitations
1. Mean Reversion Risk: Momentum can reverse sharply in bear markets or during sector rotations, leading to drawdowns.
2. Transaction Costs: Frequent rebalancing increases trading costs, especially for retail traders with high commissions. This is not as prevalent with commission free trading becoming more available.
3. Overfitting Risk: Over-optimizing lookback periods or filters can reduce out-of-sample performance.
4. Market Conditions: Underperforms in low-momentum or highly volatile markets.
Practical Applications
The Clenow Momentum Method is ideal for:
Retail Traders: Use TradingView’s screener to identify high-momentum stocks, then apply the Pine Script indicator to confirm trends.
Portfolio Managers: Build diversified momentum portfolios, rebalancing monthly to capture trends.
Swing Traders: Combine with volume filters to target short-term breakouts in high-momentum stocks.
Cross-Platform Workflow: Integrate with Python scanners to rank stocks, then visualize on TradingView for trade execution.
Comparison to Other Strategies
Vs. Minervini’s VCP: Clenow’s method is purely quantitative, while Minervini’s Volatility Contraction Pattern (your April 11, 2025 query) combines momentum with chart patterns. Clenow is more systematic but less discretionary.
Vs. Mean Reversion: Momentum bets on trend continuation, unlike mean reversion strategies that target oversold conditions.
Vs. Value Investing: Momentum outperforms in bull markets but may lag value strategies in recovery phases.
Conclusion
The Clenow Momentum Method is a robust, evidence-based strategy that capitalizes on price trends while managing risk through diversification and rebalancing. Its simplicity and adaptability make it accessible to retail traders, especially when implemented on platforms like TradingView with custom Pine Script indicators. Traders must be mindful of transaction costs, mean reversion risks, and market conditions. By combining Clenow’s momentum with volume filters and alerts, you can optimize its application for swing or position trading.
StochRSI+ LiteStochRSI+ Lite is an enhanced version of the classic Stochastic RSI.
It includes:
✅ Adaptive smoothing using ATR
✅ EMA-based trend filter to reduce false signals
✅ RSI calculated on HLC3 for smoother response
✅ Transparent 20–80 range highlight
✅ Basic divergence detection with visual markers
Ideal for crypto and volatile markets.
Open source & free to use — if you like it, tips are appreciated 🙏
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Momentum + Keltner Stochastic Combo)The Momentum-Keltner-Stochastic Combination Strategy: A Technical Analysis and Empirical Validation
This study presents an advanced algorithmic trading strategy that implements a hybrid approach between momentum-based price dynamics and relative positioning within a volatility-adjusted Keltner Channel framework. The strategy utilizes an innovative "Keltner Stochastic" concept as its primary decision-making factor for market entries and exits, while implementing a dynamic capital allocation model with risk-based stop-loss mechanisms. Empirical testing demonstrates the strategy's potential for generating alpha in various market conditions through the combination of trend-following momentum principles and mean-reversion elements within defined volatility thresholds.
1. Introduction
Financial market trading increasingly relies on the integration of various technical indicators for identifying optimal trading opportunities (Lo et al., 2000). While individual indicators are often compromised by market noise, combinations of complementary approaches have shown superior performance in detecting significant market movements (Murphy, 1999; Kaufman, 2013). This research introduces a novel algorithmic strategy that synthesizes momentum principles with volatility-adjusted envelope analysis through Keltner Channels.
2. Theoretical Foundation
2.1 Momentum Component
The momentum component of the strategy builds upon the seminal work of Jegadeesh and Titman (1993), who demonstrated that stocks which performed well (poorly) over a 3 to 12-month period continue to perform well (poorly) over subsequent months. As Moskowitz et al. (2012) further established, this time-series momentum effect persists across various asset classes and time frames. The present strategy implements a short-term momentum lookback period (7 bars) to identify the prevailing price direction, consistent with findings by Chan et al. (2000) that shorter-term momentum signals can be effective in algorithmic trading systems.
2.2 Keltner Channels
Keltner Channels, as formalized by Chester Keltner (1960) and later modified by Linda Bradford Raschke, represent a volatility-based envelope system that plots bands at a specified distance from a central exponential moving average (Keltner, 1960; Raschke & Connors, 1996). Unlike traditional Bollinger Bands that use standard deviation, Keltner Channels typically employ Average True Range (ATR) to establish the bands' distance from the central line, providing a smoother volatility measure as established by Wilder (1978).
2.3 Stochastic Oscillator Principles
The strategy incorporates a modified stochastic oscillator approach, conceptually similar to Lane's Stochastic (Lane, 1984), but applied to a price's position within Keltner Channels rather than standard price ranges. This creates what we term "Keltner Stochastic," measuring the relative position of price within the volatility-adjusted channel as a percentage value.
3. Strategy Methodology
3.1 Entry and Exit Conditions
The strategy employs a contrarian approach within the channel framework:
Long Entry Condition:
Close price > Close price periods ago (momentum filter)
KeltnerStochastic < threshold (oversold within channel)
Short Entry Condition:
Close price < Close price periods ago (momentum filter)
KeltnerStochastic > threshold (overbought within channel)
Exit Conditions:
Exit long positions when KeltnerStochastic > threshold
Exit short positions when KeltnerStochastic < threshold
This methodology aligns with research by Brock et al. (1992) on the effectiveness of trading range breakouts with confirmation filters.
3.2 Risk Management
Stop-loss mechanisms are implemented using fixed price movements (1185 index points), providing definitive risk boundaries per trade. This approach is consistent with findings by Sweeney (1988) that fixed stop-loss systems can enhance risk-adjusted returns when properly calibrated.
3.3 Dynamic Position Sizing
The strategy implements an equity-based position sizing algorithm that increases or decreases contract size based on cumulative performance:
$ContractSize = \min(baseContracts + \lfloor\frac{\max(profitLoss, 0)}{equityStep}\rfloor - \lfloor\frac{|\min(profitLoss, 0)|}{equityStep}\rfloor, maxContracts)$
This adaptive approach follows modern portfolio theory principles (Markowitz, 1952) and Kelly criterion concepts (Kelly, 1956), scaling exposure proportionally to account equity.
4. Empirical Performance Analysis
Using historical data across multiple market regimes, the strategy demonstrates several key performance characteristics:
Enhanced performance during trending markets with moderate volatility
Reduced drawdowns during choppy market conditions through the dual-filter approach
Optimal performance when the threshold parameter is calibrated to market-specific characteristics (Pardo, 2008)
5. Strategy Limitations and Future Research
While effective in many market conditions, this strategy faces challenges during:
Rapid volatility expansion events where stop-loss mechanisms may be inadequate
Prolonged sideways markets with insufficient momentum
Markets with structural changes in volatility profiles
Future research should explore:
Adaptive threshold parameters based on regime detection
Integration with additional confirmatory indicators
Machine learning approaches to optimize parameter selection across different market environments (Cavalcante et al., 2016)
References
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L., Nobrega, J. P., & Oliveira, A. L. (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55, 194-211.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (2000). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
Kaufman, P. J. (2013). Trading systems and methods (5th ed.). John Wiley & Sons.
Kelly, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Keltner, C. W. (1960). How to make money in commodities. The Keltner Statistical Service.
Lane, G. C. (1984). Lane's stochastics. Technical Analysis of Stocks & Commodities, 2(3), 87-90.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250.
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Pardo, R. (2008). The evaluation and optimization of trading strategies (2nd ed.). John Wiley & Sons.
Raschke, L. B., & Connors, L. A. (1996). Street smarts: High probability short-term trading strategies. M. Gordon Publishing Group.
Sweeney, R. J. (1988). Some new filter rule tests: Methods and results. Journal of Financial and Quantitative Analysis, 23(3), 285-300.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
SMT SwiftEdge PowerhouseSMT SwiftEdge Powerhouse: Precision Trading with Divergence, Liquidity Grabs, and OTE Zones
The SMT SwiftEdge Powerhouse is a powerful trading tool designed to help traders identify high-probability entry points during the most active market sessions—London and New York. By combining Smart Money Technique (SMT) Divergence, Liquidity Grabs, and Optimal Trade Entry (OTE) Zones, this script provides a unique and cohesive strategy for capturing market reversals with precision. Whether you're a scalper or a swing trader, this indicator offers clear visual signals to enhance your trading decisions on any timeframe.
What Does This Script Do?
This script integrates three key concepts to identify potential trading opportunities:
SMT Divergence:
SMT Divergence compares the price action of two correlated assets (e.g., Nasdaq and S&P 500 futures) to detect hidden market reversals. When one asset makes a higher high while the other makes a lower high (bearish divergence), or one makes a lower low while the other makes a higher low (bullish divergence), it signals a potential reversal. This technique leverages institutional "smart money" behavior to anticipate market shifts.
Liquidity Grabs:
Liquidity Grabs occur when price breaks above recent highs or below recent lows on higher timeframes (5m and 15m), often triggering stop-loss orders from retail traders. These breakouts are identified using pivot points and confirm institutional activity, setting the stage for a reversal. The script focuses on liquidity grabs during the London and New York sessions for maximum market activity.
Optimal Trade Entry (OTE) Zones:
OTE Zones are Fibonacci-based retracement areas (e.g., 61.8%) calculated after a liquidity grab. These zones highlight where price is likely to retrace before continuing in the direction of the reversal, offering a high-probability entry point. The script adjusts the width of these zones using the Average True Range (ATR) to adapt to market volatility.
By combining these components, the script identifies when institutional activity (liquidity grabs) aligns with market reversals (SMT divergence) and pinpoints precise entry points (OTE zones) during high-liquidity sessions.
Why Combine These Components?
The integration of SMT Divergence, Liquidity Grabs, and OTE Zones creates a robust trading system for several reasons:
Synergy of Institutional Signals: SMT Divergence and Liquidity Grabs both reflect "smart money" behavior—divergence shows hidden reversals, while liquidity grabs confirm institutional intent to trap retail traders. Together, they provide a strong foundation for identifying high-probability setups.
Session-Based Precision: Focusing on the London and New York sessions ensures signals occur during periods of high volatility and liquidity, increasing their reliability.
Precision Entries with OTE: After confirming a setup with divergence and liquidity grabs, OTE zones provide a clear entry area, reducing guesswork and improving trade accuracy.
Adaptability: The script works on any timeframe, with adjustable settings for signal sensitivity, session times, and Fibonacci levels, making it versatile for different trading styles.
This combination makes the script unique by aligning institutional insights with actionable entry points, tailored to the most active market hours.
How to Use the Script
Setup:
Add the script to your chart (works on any timeframe, e.g., 1m, 5m, 15m).
Configure the settings in the indicator's inputs:
Session Settings: Adjust the start/end times for London and New York sessions (default: London 8-11 UTC, New York 13-16 UTC). You can disable session restrictions if desired.
Asset Settings: Set the primary and secondary assets for SMT Divergence (default: NQ1! and ES1!). Ensure the assets are correlated.
Signal Settings: Adjust the lookback period, ATR period, and signal sensitivity (Low/Medium/High) to control the frequency of signals.
OTE Settings: Choose the Fibonacci level for OTE zones (default: 61.8%).
Visual Settings: Enable/disable OTE zones, SMT labels, and debug labels for troubleshooting.
Interpreting Signals:
Blue Circles: Indicate a liquidity grab (price breaking a 5m or 15m pivot high/low), marking the start of a potential setup.
Blue OTE Zones: Appear after a liquidity grab, showing the retracement area (e.g., 61.8% Fibonacci level) where price is likely to enter for a reversal trade. The label "OTE Trigger 5m/15m" confirms the direction (Short/Long) and session.
Green/Red Entry Boxes: Mark precise entry points when price enters the OTE zone and confirms the SMT Divergence. Green boxes indicate a long entry, red boxes a short entry.
Trading Example:
On a 1m chart, a blue circle appears when price breaks a 5m pivot high during the London session.
A blue OTE zone forms, showing a retracement area (e.g., 61.8% Fibonacci level) with the label "OTE Trigger 5m/15m (Short, London)".
Price retraces into the OTE zone, and a red "Short Entry" box appears, confirming a bearish SMT Divergence.
Enter a short trade at the red box, with a stop-loss above the OTE zone and a take-profit at the next support level.
Originality and Utility
The SMT SwiftEdge Powerhouse stands out by merging SMT Divergence, Liquidity Grabs, and OTE Zones into a single, session-focused indicator. Unlike traditional indicators that focus on one aspect of price action, this script combines institutional reversal signals with precise entry zones, tailored to the most active market hours. Its adaptability across timeframes, customizable settings, and clear visual cues make it a versatile tool for traders seeking to capitalize on smart money movements with confidence.
Tips for Best Results
Use on correlated assets like NQ1! (Nasdaq futures) and ES1! (S&P 500 futures) for accurate SMT Divergence.
Test on lower timeframes (1m, 5m) for scalping or higher timeframes (15m, 1H) for swing trading.
Adjust the "Signal Sensitivity" to "High" for more signals or "Low" for fewer, high-quality setups.
Enable "Show Debug Labels" if signals are not appearing as expected, to troubleshoot pivot points and liquidity grabs.
MG Thrust Indicator🚀 Explanation 🚀
The MG thrust indicator uses thrust momentum in price with some smoothing to detect uptrend and downtrend shifts.
✨ Key Features ✨
🗡smoothing_length (default: 37): length for smoothing price and thrust values (EMA or SMA).
🗡thrust_threshold (default: 1.5): multiples of ATR to identify significant thrusts.
🗡use_ema (default: true): toggle between EMA (faster response) and SMA (smoother) for smoothing.
🗡lookback_atr (default: 14): lookback period for ATR to normalize thrust.
📈 Thrust Calculation 📈
Thrust = (close - smoothed_price) / atr: measures how far the current price deviates from the smoothed price, normalized by ATR to account for volatility.
Background Highlights: colors the background faintly green/red for bullish/bearish thrusts.
❓ Seeing a bug or an issue ❓
Feel free to DM me if you see a component that seems badly calculated.
I will be happy to fix it.
❗❗ Disclaimer ❗❗
This is a single indicator, even though it's aggregating many, do not use it as a standalone.
Past performance is not indicative of future results.
Always backtest, check, and align parameters before live trading.
Volume-Price Momentum IndicatorVolume-Price Momentum Indicator (VPMI)
Overview
The Volume-Price Momentum Indicator (VPMI), developed by Kevin Svenson , is a powerful technical analysis tool designed to identify strong bullish and bearish momentum in price movements, driven by volume dynamics. By analyzing price changes and volume surges over a user-defined lookback period, VPMI highlights potential trend shifts and continuation patterns through a smoothed histogram, optional labels, and background highlights. Ideal for traders seeking to capture momentum-driven opportunities, VPMI is suitable for various markets, including stocks, forex, and cryptocurrencies.
How It Works
VPMI calculates the difference between volume-weighted buying and selling pressure based on price changes over a specified lookback period. It amplifies signals during high-volume periods, applies smoothing to reduce noise, and uses momentum checks to detect sustained trends.
Indicator display:
A histogram that oscillates above (bullish) or below (bearish) a zero line, with brighter colors indicating stronger momentum and faded colors for weaker signals.
Optional labels ("Bullish" or "Bearish") to mark significant momentum shifts.
Optional background highlights to visually emphasize strong trend conditions.
Alerts to notify users when strong bullish or bearish momentum is detected.
Key Features
Customizable Settings:
Adjust the lookback period, volume threshold, momentum length, and smoothing to suit your trading style.
Volume Sensitivity:
Emphasizes price movements during high-volume surges, enhancing signal reliability.
Momentum Detection: Uses linear regression and momentum change to confirm sustained trends, reducing false signals.
Visual Clarity:
Offers a clear histogram with color-coded signals, plus optional labels and backgrounds for enhanced chart readability.
Alerts:
Configurable alerts for strong momentum signals, enabling timely trade decisions.
Inputs and Customization
Lookback Period (Default: 9):
Sets the number of bars to analyze price changes. Higher values smooth signals but may lag.
Volume Threshold (Default: 1.4):
Defines the volume level (relative to a 20-period SMA) that qualifies as a surge, amplifying signals.
High Volume Multiplier (Default: 1.5):
Boosts histogram values during high-volume periods for stronger signals.
Histogram Smoothing Length (Default: 4):
Controls the EMA smoothing applied to the histogram, reducing noise.
Momentum Check Length (Default: 4):
Sets the period for momentum trend analysis (recommended to be less than Lookback Period).
Momentum Threshold (Default: 6):
Defines the minimum momentum change required for strong signals.
Show Labels (Default: Off):
Toggle to display "Bullish" or "Bearish" labels on significant momentum shifts.
Show Backgrounds (Default: Off):
Toggle to highlight chart backgrounds during strong momentum periods.
Bullish/Bearish Colors:
Customize colors for bullish (default: green) and bearish (default: red) signals.
Faded Transparency (Default: 40):
Adjusts the transparency of weaker signals for visual distinction.
How to Use
Interpret Signals:
Above Zero (Green):
Indicates bullish momentum. Bright green suggests strong, sustained buying pressure.
Below Zero (Red):
Indicates bearish momentum. Bright red suggests strong, sustained selling pressure.
Faded Colors:
Weaker momentum, potentially signaling consolidation or trend exhaustion.
Enable Visuals:
Turn on "Show Labels" and "Show Backgrounds" in the settings for additional context on strong momentum signals.
Set Alerts:
Use the built-in alert conditions ("Strong Bullish Momentum" or "Strong Bearish Momentum") to receive notifications when significant trends emerge.
Combine with Other Tools:
Pair VPMI with support/resistance levels, trendlines, or other indicators (e.g., RSI, MACD) for confirmation.
Best Practices
Timeframe:
VPMI works on all timeframes, but shorter timeframes (e.g., 5m, 15m) may produce more signals, while longer timeframes (e.g., 1h, 4h, 1D) offer higher reliability.
Market Conditions:
Most effective in trending markets. In choppy or sideways markets, consider increasing the smoothing length or momentum threshold to filter noise.
Risk Management:
Always use VPMI signals in conjunction with a robust trading plan, including stop-losses and position sizing.
Limitations
Lagging Nature:
As a momentum indicator, VPMI may lag in fast-moving markets due to smoothing and lookback calculations.
False Signals:
In low-volume or ranging markets, signals may be less reliable. Adjust the volume threshold or momentum settings to improve accuracy.
Customization Required:
Optimal settings vary by asset and timeframe. Experiment with inputs to align with your trading strategy.
Why Use VPMI?
VPMI offers a unique blend of volume and price momentum analysis, making it a versatile tool for traders seeking to identify high-probability trend opportunities. Its customizable inputs, clear visuals, and alert capabilities empower users to tailor the indicator to their needs, whether for day trading, swing trading, or long-term analysis.
Get Started
Apply VPMI to your chart, tweak the settings to match your trading style, and start exploring momentum-driven opportunities. For questions or feedback, consult TradingView’s community forums or documentation. Happy trading!
Momentum Table - Felipe📊 Momentum Table – By Felipe
This multi-timeframe momentum dashboard displays a clean and color-coded overview of key trend and momentum indicators across 6 major timeframes (5m to 1W), directly on your chart. It’s ideal for quickly identifying market strength, trend alignment, and potential reversals at a glance.
🔍 Features:
EMA Trend Check (EMA 9, 20, 100, 200):
Compares the current close against each EMA.
✅ Green check = price is above the EMA (bullish bias).
🔻 Red arrow = price is below the EMA (bearish bias).
Visual trend alignment helps you spot strong directional setups.
RSI (Relative Strength Index):
Displays current RSI (14) value per timeframe.
Background color highlights momentum conditions:
🔴 Red = Overbought (>70)
🟢 Green = Oversold (<30)
⚪ Gray = Neutral
Stochastic RSI:
Uses Stoch RSI applied to RSI (14) for sensitivity.
Background color follows the same logic as RSI for quick visual cues.
Compact Visual Table:
Located in the bottom-right corner.
Clean design with headers and rows labeled by timeframe.
Helps traders monitor trend and momentum confluence across multiple timeframes in real time.
This tool supports momentum-based strategies, EMA stacking confirmation, and multi-timeframe alignment, making it ideal for scalpers, swing traders, and trend followers alike.
Aesthetic RSI [AlchimistOfCrypto]🌌 Aesthetic RSI – Unveiling the Fractal Forces of Markets 🌌
Category: Momentum Indicators 📈
"The RSI oscillator, formalized through an advanced mathematical prism, reveals the underlying fractal structures of price movements. This indicator draws inspiration from quantum principles of divergence-convergence where the probability of a return to equilibrium increases proportionally to the distance from the median point. Our implementation employs sophisticated algorithmic smoothing to filter out the stochastic noise inherent in financial markets, allowing visualization of the true momentum forces according to thermodynamic entropy principles applied to trading systems."
📊 Professional Trading Application
The Aesthetic RSI is a visually stunning and mathematically refined take on the classic Relative Strength Index. With customizable settings, advanced smoothing, and eight unique visual palettes, it empowers traders to detect momentum shifts and divergences with unparalleled clarity.
⚙️ Indicator Configuration
- Length 📏
The core parameter (default: 20) that determines the calculation period.
- Lower values (8-14): Increase sensitivity for short-term trading.
- Higher values (21-34): Provide stronger signals for position trading.
- OverBought/OverSold Thresholds 🎯
Customizable boundaries (default: 75/25) to identify extreme market conditions.
- Calibrate based on asset volatility: Higher volatility assets may need wider thresholds (80/20) to reduce false signals.
- Style 🎨
Eight meticulously crafted visual palettes optimized for pattern recognition:
- Miami Vice (default): High-contrast cyan/magenta scheme for spotting divergences.
- Cyberpunk: Yellow/purple combo to highlight momentum shifts.
- Classic: Traditional green/red for conventional analysis.
- High Contrast: Maximum visual separation for traders with visual impairments.
- Specialized palettes (Forest, Ocean, Fire, Monochrome): Tailored for diverse market conditions.
- Mode Selection 🔄
- Full: Displays a complete gradient spectrum across the RSI range, emphasizing momentum transitions between 35-65.
- OverZone: Focuses on actionable extreme zones, reducing noise in ranging markets.
🚀 How to Use
1. Adjust Length ⏰: Set the period based on your trading style (short-term or long-term).
2. Fine-Tune Thresholds 🎚️: Customize overbought/oversold levels to match the asset’s volatility.
3. Select a Palette 🌈: Choose a visual style that enhances your pattern recognition.
4. Choose Mode 🔍: Use "Full" for detailed momentum analysis or "OverZone" for extreme zone focus.
5. Spot Divergences ✅: Look for price-RSI divergences to anticipate reversals.
6. Trade with Precision 🛡️: Combine with other indicators for high-probability setups.
📅 Release Notes (April 2025)
Aesthetic RSI blends quantum-inspired mathematics with artistic visualization, redefining momentum analysis. Stay tuned for future enhancements! ✨
🏷️ Tags
#Trading #TechnicalAnalysis #RSI #Momentum #Divergence #MultiTimeframe #TradingStrategy #RiskManagement #Forex #Stocks #Crypto #Bitcoin #AlgoTrading #DayTrading #SwingTrading #TheAlchimist #QuantumTrading #VisualTrading #PatternRecognition
MACD [AlchimistOfCrypto]🌠 MACD Optimized with Python – Decoding the Chaos of Markets 🌠
Category: Trend Analysis 📈
"Like the dynamic systems studied in chaos theory, financial markets appear unpredictable at first glance. Yet, as Edward Lorenz demonstrated, even in apparent chaos reside harmonious mathematical structures. The MACD (Moving Average Convergence Divergence) represents this quest for order within disorder—a mathematical formulation that extracts coherent signals from price noise. By combining moving averages of different periods, this indicator reveals hidden cycles and precise moments when market energy shifts, like a pendulum obeying the immutable laws of physics."
📊 Technical Overview
The MACD Optimized with Python is a revolutionary take on the classic Moving Average Convergence Divergence indicator. Powered by Python-driven optimizations 🐍, it adapts to specific timeframes, delivering razor-sharp signals for traders seeking to navigate the market’s chaos with precision.
⚙️ How It Works
- Python-Optimized Parameters 🔧: Unlike the standard MACD (12,26,9), our version uses mathematically tailored parameters for each timeframe:
- 1H: 11/38/27
- 4H: 9/98/27
- 1D: 45/90/29
- 1W: 9/16/3
- 2W: 5/20/5
- Intuitive Visuals 🎨:
- Crossovers marked by colored dots 🟢🔴 for clear entry/exit signals.
- Histogram with a color gradient 🌈 to show direction and momentum intensity.
- Customizable Signals 🎯: Choose to display long, short, or both signals to match your trading style.
🚀 How to Use This Indicator
1. Select Your Timeframe ⏰: Choose the timeframe aligned with your trading horizon (1H, 4H, 1D, 1W, or 2W).
2. Spot Crossovers 🔍: Watch for the MACD line (green) crossing the signal line (red) to identify potential trend changes.
3. Confirm with Divergence ✅: Combine crossovers with price-MACD divergence for high-probability trend reversal signals.
📅 Release Notes
Unlock the hidden order of markets with this Python-optimized MACD. Stay tuned for future enhancements! ✨
🏷️ Tags
#Trading #TechnicalAnalysis #MACD #TrendAnalysis #Python #MultiTimeframe #Divergence #Momentum #TradingStrategy #RiskManagement #Forex #Stocks #Crypto #ChaosTheory #OptimizedTrading
Slope Change Rate Volume ConfirmationSlope Change Rate Volume Confirmation (SCR)
█ OVERVIEW
This indicator identifies moments where the price trend is not just moving, but accelerating (i.e., the rate of change of the trend's slope is increasing or decreasing significantly), and crucially, whether this acceleration is confirmed by high volume . The core idea is that price acceleration backed by strong volume suggests higher conviction behind the move, potentially indicating the start or continuation of a strong thrust. Conversely, acceleration without volume might be less reliable.
It calculates the slope (velocity) of price movement, then the change in that slope (acceleration). This acceleration is normalized to a -100 to 100 range for consistent threshold application. Finally, it checks if significant acceleration coincides with volume exceeding its recent average.
█ HOW IT WORKS
The indicator follows these steps:
1. Slope Calculation (Velocity):
Calculates the slope of a linear regression line based on the input `Source` over the `Slope Calculation Length`. This represents the instantaneous rate of change or "velocity" of the price trend.
// Calculate linear regression slope (current value - previous value)
slope = ta.linreg(src, slopeLen, 0) - ta.linreg(src, slopeLen, 1)
2. Acceleration Calculation & Normalization:
Determines the bar-to-bar change in the calculated `slope` (`slope - slope `). This raw change represents the "acceleration". This value is then immediately normalized to a fixed range of -100 to +100 using the internal `f_normalizeMinMax` function over the `Volume SMA Length` lookback period. Normalization allows the `Acceleration Threshold` input to be applied consistently.
// Calculate slope change rate (acceleration) and normalize it
// f_normalizeMinMax(source, length, newMin, newMax)
accel = f_normalizeMinMax(slope - slope , volSmaLen, -100, 100)
*( Note: `f_normalizeMinMax` is a standard min-max scaling function adapted to the -100/100 range, included within the script's code.*)*
3. Volume Confirmation Check:
Calculates the Simple Moving Average (SMA) of volume over the `Volume SMA Length`. It then checks if the current bar's volume is significantly higher than this average, defined by exceeding the average multiplied by the `Volume Multiplier Threshold`.
// Calculate average volume
avgVolume = ta.sma(volume, volSmaLen)
// Determine if current volume is significantly high
isHighVolume = volume > avgVolume * volMultiplier
4. Confirmation Signals:
Combines the normalized acceleration and volume check to generate the final confirmation boolean flags:
// Bullish: Price is accelerating upwards (accel > threshold) AND volume confirms
confirmBullishAccel = accel > accelThreshold and isHighVolume
// Bearish: Price is accelerating downwards (accel < -threshold) AND volume confirms
confirmBearishAccel = accel < -accelThreshold and isHighVolume
█ HOW TO USE
Confirmation Filter: The primary intended use is to filter entry signals from another strategy. Only consider long entries when `confirmBullishAccel` is true, or short entries when `confirmBearishAccel` is true. This helps ensure you are entering during periods of strong, volume-backed momentum.
// Example Filter Logic
longEntry = yourPrimaryBuySignal and confirmBullishAccel
shortEntry = yourPrimarySellSignal and confirmBearishAccel
Momentum Identification: High absolute values of the plotted `Acceleration` (especially when confirmed by the shapes) indicate strong directional conviction.
Potential Exhaustion/Divergence: Consider instances where price accelerates significantly (large absolute `accel` values) without volume confirmation (`isHighVolume` is false). This *might* suggest weakening momentum or potential exhaustion, although this requires further analysis.
█ INPUTS
Slope Calculation Length: Lookback period for the linear regression slope calculation.
Volume SMA Length: Lookback period for the Volume SMA and also for the normalization range of the acceleration calculation.
Volume Multiplier Threshold: Factor times average volume to define 'high volume'. (e.g., 1.5 means > 150% of average volume).
Acceleration Threshold: The minimum absolute value the normalized acceleration (-100 to 100 range) must reach to trigger a confirmation signal (when combined with volume).
Source: The price source (e.g., close, HLC3) used for the slope calculation.
█ VISUALIZATION
The indicator plots in a separate pane:
Acceleration Plot: A column chart showing the normalized acceleration (-100 to 100). Columns are colored dynamically based on acceleration's direction (positive/negative) and change (increasing/decreasing).
Threshold Lines: White horizontal dashed lines drawn at the positive and negative `Acceleration Threshold` levels.
Confirmation Shapes:
Green Upward Triangle (▲) below the bar when Bullish Acceleration is confirmed by volume (`confirmBullishAccel` is true).
Red Downward Triangle (▼) above the bar when Bearish Acceleration is confirmed by volume (`confirmBearishAccel` is true).
█ SUMMARY
The SCR indicator is a tool designed to highlight periods of significant price acceleration that are validated by increased market participation (high volume). It can serve as a valuable filter for momentum-based trading strategies by helping to distinguish potentially strong moves from weaker ones. As with any indicator, use it as part of a comprehensive analysis framework and always practice sound risk management.
🔥 PratikMoneyCPTY – AI Crypto Swing SignalCreated by Pratik Patel, this advanced crypto trading tool fuses AI logic with technical indicators—EMA, SuperTrend, MACD, RSI, and candlestick patterns—to identify profitable swing entries. Built for crypto markets like BTC, ETH, and top altcoins on 4H/1D charts. Includes smart alerts, BUY/SELL tags, and popup notifications for actionable insights.
Liquidity Fracture DetectorThe Liquidity Fracture Detector is an advanced tool designed to identify micro-liquidity traps and structural fakeouts on intraday charts. These occur when the market appears to break out, only to quickly reverse — often triggered by stop hunts, inefficient fills, or manipulated order flow.
The script combines volume spikes, volatility anomalies, and price structure breaks to signal "fractures" — points where the market temporarily breaks its behavior, often followed by strong reversals or trend accelerations.
Detection logic in the script:
Volume spike greater than 2x the average (adjustable)
Volatility spike: candle range is > 1.5x the average
Extreme wicks: wick is larger than the candle body (a classic trap signal)
Structure break: price breaks previous high/low but closes back within the old range
Combine these elements → a “fracture” is marked
Visual representation:
Red background = potential bull trap (fake breakout to the upside)
Green background = potential bear trap (fake breakdown to the downside)
A label appears at each fracture: “Echo” with the number of previous hits
Ideal use cases:
Intraday trading (1m, 5m, 15m)
Crypto, indices, futures, and forex
Detecting reactive zones where the market takes a false direction
Confluence with S/R zones, order blocks, or liquidity pools
Fully customizable:
Volume and range sensitivity
Heatmap intensity
Toggle labels on/off
Note:
This script is intended to support discretionary analysis. It does not provide buy or sell signals and is not an automated strategy. Combine it with your own price action or order flow setup for optimal results.
Frozen Bias Zones – Sentiment Lock-insOverview
The Frozen Bias Zones indicator visualizes market sentiment lock-ins using a combination of RSI, MACD, and OBV. It creates "bias zones" that indicate whether the market is in a sustained bullish or bearish phase. These zones are then highlighted on the chart, helping traders spot when the market is locked in a bias. The script also detects breakout events from these zones and marks them with clear labels for easier decision-making.
Features
Multi-Indicator Sentiment Analysis: Combines RSI, MACD, and OBV to detect synchronized bullish or bearish sentiment.
Frozen Bias Zones: Identifies and visually represents zones where the market has remained in a particular sentiment (bullish or bearish) for a defined period.
Breakout Alerts: Displays labels to indicate when the price breaks out of the established bias zone.
Customizable Inputs: Adjust the zone duration, RSI, MACD, and breakout label visibility.
Input Parameters
Bias Duration (biasLength)
The minimum number of candles the market must stay in a specific sentiment to consider it a "Frozen Bias Zone".
Default: 5 candles.
RSI Period (rsiPeriod)
Period for the Relative Strength Index (RSI) calculation.
Default: 14 periods.
MACD Settings
MACD Fast (macdFast): The fast-moving average period for the MACD calculation.
Default: 12.
MACD Slow (macdSlow): The slow-moving average period for the MACD calculation.
Default: 26.
MACD Signal (macdSig): The signal line period for MACD.
Default: 9.
Show Break Label (showBreakLabel)
Toggle to show labels when the price breaks out of the bias zone.
Default: True (shows label).
Bias Zone Colors
Bullish Bias Color (bullColor): The color for bullish zones (light green).
Bearish Bias Color (bearColor): The color for bearish zones (light red).
How It Works
This indicator analyzes three key market metrics to determine whether the market is in a bullish or bearish phase:
RSI (Relative Strength Index)
Measures the speed and change of price movements. RSI > 50 indicates a bullish phase, while RSI < 50 indicates a bearish phase.
MACD (Moving Average Convergence Divergence)
Measures the relationship between two moving averages of the price. A positive MACD histogram indicates bullish momentum, while a negative histogram indicates bearish momentum.
OBV (On-Balance Volume)
Uses volume flow to determine if a trend is likely to continue. A rising OBV indicates bullish accumulation, while a falling OBV indicates bearish distribution.
Bias Zone Detection
The market sentiment is considered bullish if all three indicators (RSI, MACD, and OBV) are bullish, and bearish if all three indicators are bearish.
Bullish Zone: A zone is created when the market sentiment remains bullish for the duration of the specified biasLength.
Bearish Zone: A zone is created when the market sentiment remains bearish for the duration of the specified biasLength.
These bias zones are visually represented on the chart as colored boxes (green for bullish, red for bearish).
Breakout Detection
The script automatically detects when the market exits a bias zone. If the price moves outside the bounds of the established zone (either up or down), the script will display one of the following labels:
Bias Break (Up): Indicates that the price has broken upwards out of the zone (with a green label).
Bias Break (Down): Indicates that the price has broken downwards out of the zone (with a red label).
These labels help traders easily identify potential breakout points.
Example Use Case
Bullish Market Conditions: If the RSI is above 50, the MACD histogram is positive, and OBV is increasing, the script will highlight a green bias zone. Traders can watch for potential bullish breakouts or trend continuation after the zone ends.
Bearish Market Conditions: If the RSI is below 50, the MACD histogram is negative, and OBV is decreasing, the script will highlight a red bias zone. Traders can look for potential bearish breakouts when the zone ends.
Conclusion
The Frozen Bias Zones indicator is a powerful tool for traders looking to visualize prolonged market sentiment, whether bullish or bearish. By combining RSI, MACD, and OBV, it helps traders spot when the market is "locked in" to a bias. The breakout labels make it easier to take action when the price moves outside of the established zone, potentially signaling the start of a new trend.
Instructions
To use this script:
Add the Frozen Bias Zones indicator to your TradingView chart.
Adjust the input parameters to suit your trading strategy.
Observe the colored bias zones on your chart, along with breakout labels, to make informed decisions on trend continuation or reversal.
Institutional MACD (Z-Score Edition) [VolumeVigilante]📈 Institutional MACD (Z-Score Edition) — Professional-Grade Momentum Signal
This is not your average MACD .
The Institutional MACD (Z-Score Edition) is a statistically enhanced momentum tool, purpose-built for serious traders and breakout hunters . By applying Z-Score normalization to the classic MACD structure, this indicator uncovers statistically significant momentum shifts , enabling cleaner reads on price extremes, trend continuation, and potential reversals.
💡 Why It Matters
The classic MACD is powerful — but raw momentum values can be noisy and relative , especially on volatile assets like BTC/USD . By transforming the MACD line, signal line, and histogram into Z-scores , we anchor these signals in statistical context . This makes the Institutional MACD:
✔️ Timeframe-agnostic and asset-normalized
✔️ Ideal for spotting true breakouts , not false flags
✔️ A reliable tool for detecting momentum divergence and exhaustion
🧪 Key Features
✅ Full Z-Score normalization (MACD, Signal, Histogram)
✅ Highlighted ±Z threshold bands for overbought/oversold zones
✅ Customizable histogram coloring for visual momentum shifts
✅ Built-in alerts for zero-crosses and Z-threshold breaks
✅ Clean overlay with optional display toggles
🔁 Strategy Tip: Mean Reversion Signals with Statistical Confidence
This indicator isn't just for spotting breakouts — it also shines as a mean reversion tool , thanks to its Z-Score normalization .
When the Z-Score histogram crosses beyond ±2, it marks a statistically significant deviation from the mean — often signaling that momentum is overstretched and the asset may be due for a pullback or reversal .
📌 How to use it:
Z > +2 → Price action is in overbought territory. Watch for exhaustion or short setups.
Z < -2 → Momentum is deeply oversold. Look for reversal confirmation or long opportunities.
These zones often precede snap-back moves , especially in range-bound or corrective markets .
🎯 Combine Z-Score extremes with:
Candlestick confirmation
Support/resistance zones
Volume or price divergence
Other mean reversion tools (e.g., RSI, Bollinger Bands)
Unlike the raw MACD, this version delivers statistical thresholds , not guesswork — helping traders make decisions rooted in probability, not emotion.
📢 Trade Smart. Trade Vigilantly.
Published by VolumeVigilante
Volume Flow RatioVolume Flow Ratio (VFR) Indicator
Overview
The Volume Flow Ratio (VFR) is a sophisticated volume analysis tool that measures current trading volume relative to the maximum volume of the previous period. Unlike traditional volume indicators that show raw volume or simple moving averages, VFR provides context by comparing current activity to recent maximum activity levels.
Core Features
1. Split Period Analysis
- Multiple Timeframe Options:
- Daily: Compares to previous day's maximum
- Weekly: Week-to-week comparison
- NYSE Weekly: Specialized for stock market trading (Monday-Friday only)
- Monthly: Month-to-month analysis
- Quarterly: Quarter-to-quarter perspective
- Yearly: Year-over-year volume comparison
2. Ratio-Based Measurement
- Displays volume as a ratio (0 to 1+) rather than raw numbers
- 1.0 represents volume equal to previous period's maximum
- Example: If previous max was 50,000 contracts:
- Current volume of 25,000 shows as 0.5
- Current volume of 75,000 shows as 1.5
3. Triple Coloring Modes
- Moving Average Based:
- Compares current ratio to its moving average
- Customizable MA period
- Green: Above MA (higher than average activity)
- Red: Below MA (lower than average activity)
- Previous Candle Comparison:
- Simple increase/decrease from previous bar
- Green: Higher than previous bar
- Red: Lower than previous bar
- Candle Color Based:
- Syncs with price action
- Green: Bullish candles (close > open)
- Red: Bearish candles (close < open)
Primary Use Cases
1. Volume Profile Analysis
- Perfect for traders who need to understand when markets are most active
- Helps identify unusual volume spikes relative to recent history
- Useful for timing entries and exits based on market participation
2. Market Activity Traders
Ideal for traders who:
- Need to identify high-liquidity periods
- Want to avoid low-volume periods
- Look for volume breakouts or divergences
- Trade based on institutional participation levels
3. Mean Reversion Traders
Helps identify:
- Overextended volume conditions (potential reversals)
- Volume exhaustion points
- Return to normal volume levels after spikes
4. Momentum Traders
Useful for:
- Confirming trend strength through volume
- Identifying potential trend exhaustion
- Validating breakouts with volume confirmation
Advantages Over Traditional Volume Indicators
1. Contextual Analysis
- Shows relative strength rather than raw numbers
- Easier to compare across different time periods
- Automatically adjusts to changing market conditions
2. Period-Specific Insights
- Respects natural market cycles (daily, weekly, monthly)
- Special handling for NYSE trading days
- Eliminates weekend noise in stock market analysis
3. Flexible Visualization
- Three distinct coloring methods for different trading styles
- Clear reference line at 1.0 for quick analysis
- Histogram style for easy pattern recognition
Best Practices
For Day Traders
- Use Daily split for intraday volume patterns
- MA coloring mode with shorter periods (5-10)
- Focus on ratios during market hours
For Swing Traders
- Weekly or NYSE Weekly splits
- Longer MA periods (15-20)
- Look for sustained volume patterns
For Position Traders
- Monthly or Quarterly splits
- Candle color mode for trend confirmation
- Focus on major volume shifts
Limitations
- Requires one full period to establish baseline
- May be less effective in extremely low volume conditions
- NYSE Weekly mode specific to stock market hours
This indicator is particularly valuable for traders who understand that volume is a crucial component of price action but need a more sophisticated way to analyze it than simple volume bars. It's especially useful for those who trade based on market participation levels and need to quickly identify whether current volume is significant relative to recent history.
Parabolic RSI [ChartPrime]The Parabolic RSI indicator applies the Parabolic SAR directly to the Relative Strength Index (RSI) . This combination helps traders identify trend shifts and potential reversal points within the RSI framework. The indicator provides both regular and strong signals based on whether the Parabolic SAR crosses above or below key RSI thresholds.
⯁ KEY FEATURES
Parabolic SAR Applied to RSI – Tracks momentum shifts within the RSI indicator.
Dynamic SAR Dots – Plots SAR levels directly on the RSI for visual clarity.
Threshold-Based Signal Filtering – Uses upper (70) and lower (30) RSI levels to determine strong signals.
Simple and Strong Signal System :
Big Diamonds (Strong Signals) – Appear when Parabolic SAR crosses above 70 or below 30 RSI, indicating potential reversals.
Small Diamonds (Regular Signals) – Appear when Parabolic SAR flips inside the RSI range, signaling weaker trend shifts.
Chart Overlay Signals – Highlights strong RSI-based trend shifts directly on the price chart.
Fully Customizable – Modify RSI length, SAR parameters, colors, and signal displays.
⯁ HOW TO USE
Look for strong signals (big diamonds) when SAR flips above 70 RSI (overbought) or below 30 RSI (oversold) for potential reversals.
Use regular signals (small diamonds) for minor trend shifts within the RSI range.
Combine with price action and other indicators to confirm entry and exit points.
Adjust the SAR acceleration factors to fine-tune sensitivity based on market conditions.
⯁ CONCLUSION
The Parabolic RSI indicator merges trend-following and momentum-based analysis by applying the Parabolic SAR to RSI. This allows traders to detect trend shifts inside the RSI space with an intuitive diamond-based signal system . Whether used alone or as part of a broader trading strategy, this indicator provides a clear and structured approach to identifying momentum reversals and potential trading opportunities.
MACD Crossover + AlertMACD Proximity & Crossover Alert Script
This script is designed to help traders stay ahead of MACD crossovers by providing:
Early alerts when the MACD and Signal lines are getting close (within a customizable threshold)
Instant alerts when a bullish or bearish crossover occurs
Whether you're swing trading or scalping, this tool gives you advanced notice to prepare — and a confirmation signal to act on. It works on any timeframe and helps avoid late entries by alerting you when momentum is shifting.
Features:
Customizable MACD settings (fast, slow, signal length)
Adjustable "proximity" threshold
Visual background highlight when lines are close
Built-in alert conditions for:
MACD crossing above Signal (bullish)
MACD crossing below Signal (bearish)
MACD and Signal getting close (early warning)
Perfect for traders who want a heads-up before momentum shifts — not just a reaction afterward.
Institutional Quantum Momentum Impulse [BullByte]## Overview
The Institutional Quantum Momentum Impulse (IQMI) is a sophisticated momentum oscillator designed to detect institutional-level trend strength, volatility conditions, and market regime shifts. It combines multiple advanced technical concepts, including:
- Quantum Momentum Engine (Hilbert Transform + MACD Divergence + Stochastic Energy)
- Fractal Volatility Scoring (GARCH + Keltner-based volatility)
- Dynamic Adaptive Bands (Self-adjusting thresholds based on efficiency)
- Market Phase Detection (Volume + Momentum alignment)
- Liquidity & Cumulative Delta Analysis
The indicator provides a Z-score normalized momentum reading, making it ideal for mean-reversion and trend-following strategies.
---
## Key Features
### 1. Quantum Momentum Core
- Combines Hilbert Transform, MACD divergence, and Stochastic Energy into a single composite momentum score.
- Normalized using a Z-score for statistical significance.
- Smoothed with EMA/WMA/HMA for cleaner signals.
### 2. Dynamic Adaptive Bands
- Upper/Lower bands adjust based on volatility and efficiency ratio .
- Acts as overbought/oversold zones when momentum reaches extremes.
### 3. Market Phase Detection
- Identifies bullish , bearish , or neutral phases using:
- Volume-Weighted MA alignment
- Fractal momentum extremes
### 4. Volatility & Liquidity Filters
- Fractal Volatility Score (0-100 scale) shows market instability.
- Liquidity Check ensures trades are taken in favorable spread conditions.
### 5. Dashboard & Visuals
- Real-time dashboard with key metrics:
- Momentum strength, volatility, efficiency, cumulative delta, and market regime.
- Gradient coloring for intuitive momentum visualization .
---
## Best Trade Setups
### 1. Trend-Following Entries
- Signal :
- QM crosses above zero + Market Phase = Bullish + ADX > 25
- Cumulative Delta rising (buying pressure)
- Confirmation :
- Efficiency > 0.5 (strong momentum quality)
- Liquidity = High (tight spreads)
### 2. Mean-Reversion Entries
- Signal :
- QM touches upper band + Volatility expanding
- Market Regime = Ranging (ADX < 25)
- Confirmation :
- Efficiency < 0.3 (weak momentum follow-through)
- Cumulative Delta divergence (price high but delta declining)
### 3. Breakout Confirmation
- Signal :
- QM holds above zero after a pullback
- Market Phase shifts to Bullish/Bearish
- Confirmation :
- Volatility rising (expansion phase)
- Liquidity remains high
---
## Recommended Timeframes
- Intraday (5M - 1H): Works well for scalping & swing trades.
- Swing Trading (4H - Daily): Best for trend-following setups.
- Position Trading (Weekly+): Useful for macro trend confirmation.
---
## Input Customization
- Resonance Factor (1.0 - 3.618 ): Adjusts MACD divergence sensitivity.
- Entropy Filter (0.382/0.50/0.618) : Controls stochastic damping.
- Smoothing Type (EMA/WMA/HMA) : Changes momentum responsiveness.
- Normalization Period : Adjusts Z-score lookback.
---
The IQMI is a professional-grade momentum indicator that combines institutional-level concepts into a single, easy-to-read oscillator. It works across all markets (stocks, forex, crypto) and is ideal for traders who want:
✅ Early trend detection
✅ Volatility-adjusted signals
✅ Institutional liquidity insights
✅ Clear dashboard for quick analysis
Try it on TradingView and enhance your trading edge! 🚀
Happy Trading!
- BullByte
