[blackcat] L3 Mean Reversion ATR Stop Loss OVERVIEW
The L3 Mean Reversion ATR Stop Loss indicator is meticulously crafted to empower traders by offering statistically-driven stop-loss levels that adapt seamlessly to evolving market dynamics. By harmoniously blending mean reversion concepts with Advanced True Range (ATR) metrics, it delivers a robust framework for managing risks more effectively. 🌐 The primary objective is to furnish traders with intelligent exit points grounded in both short-term volatility assessments and long-term trend evaluations.
Key highlights encompass:
• Dynamic calculation of Z-scores to evaluate deviations from established means
• Adaptive stop-loss pricing leveraging real-time ATR measurements
• Clear visual cues enabling swift decision-making processes
TECHNICAL ANALYSIS COMPONENTS
📉 Z-SCORE CALCULATION
Measures how many standard deviations an asset's current price lies away from its average
Facilitates identification of extreme conditions indicative of impending reversals
Utilizes simple moving averages and standard deviation computations
📊 STANDARD DEVIATION MEASUREMENT
Quantifies dispersion of closing prices around the mean
Provides insights into underlying price distribution characteristics
Crucial for assessing potential volatility levels accurately
🕵️♂️ ADAPTIVE STOP-LOSS DETECTION
Employs ATR as a proxy for prevailing market volatility
Modulates stop-loss placements dynamically responding to shifting trends
Ensures consistent adherence to predetermined risk management protocols
INDICATOR FUNCTIONALITY
🔢 Core Algorithms
Integrate Smooth Moving Averages (SMAs) alongside standardized deviation formulas
Generate precise Z-scores reflecting true price deviations
Leverage ATR-derived multipliers for fine-grained stop-loss adjustments
🖱️ User Interface Elements
Interactive plots displaying real-time stop-loss markers
Context-sensitive color coding enhancing readability
Background shading indicating proximity to stop-level activations
STRATEGY IMPLEMENTATION
✅ Entry Conditions
Confirm bullish/bearish setups validated through multiple confirmatory signals
Ensure alignment between Z-score readings and broader trend directions
Validate entry decisions considering concurrent market sentiment factors
🚫 Exit Mechanisms
Trigger exits upon hitting predefined ATR-based stop-loss thresholds
Monitor continuous breaches signifying potential trend reversals
Execute partial/total closes contingent upon cumulative loss limits
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines
Period Length: Governs responsiveness versus smoothing trade-offs
ATR Length: Dictates the temporal scope for volatility analysis
Stop Loss ATR Multiplier: Tunes sensitivity towards stop-trigger activations
💬 Customization Recommendations
Commence with baseline defaults; iteratively refine parameters
Evaluate impacts independently prior to combined adjustments
Prioritize minimizing erroneous trigger occurrences first
Sustain balanced risk-reward profiles irrespective of chosen settings
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques
Enforce strict compliance with pre-defined maximum leverage constraints
Mandatorily apply trailing stop-loss orders conforming to script outputs
Allocate positions proportionately relative to available capital reserves
Conduct periodic reviews gauging strategy effectiveness rigorously
⚠️ Potential Pitfalls & Solutions
Address frequent violations arising during heightened volatility phases
Manage false alerts warranting manual interventions judiciously
Prepare contingency plans mitigating margin call possibilities
Continuously assess automated system reliability amidst fluctuating conditions
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics
Assess win percentages consistently across diverse trading instruments
Calculate average profit ratios per successful execution
Measure peak drawdown durations alongside associated magnitudes
Analyze signal generation frequencies revealing hidden patterns
📈 Historical Data Analysis Tools
Maintain comprehensive records capturing every triggered event
Compare realized profits/losses against backtested simulations
Identify recurrent systematic errors demanding corrective actions
Implement iterative refinements bolstering overall efficacy steadily
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges
Unpredictable behaviors emerging within thinly traded markets
Latency issues manifesting during abrupt price fluctuations
Overfitted models yielding suboptimal results post-extensive tuning
Inaccuracies stemming from incomplete or delayed data inputs
💡 Effective Resolution Pathways
Exclude low-liquidity assets prone to erratic movements
Introduce buffer intervals safeguarding major news/event impacts
Limit ongoing optimization attempts preventing model degradation
Verify seamless connectivity ensuring uninterrupted data flows
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
A heartfelt acknowledgment extends to all developers contributing invaluable insights about adaptive stop-loss strategies using statistical measures! ✨
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CVD Divergenz System – modular with Exchange + LabelsA smart volume-based strategy tool using CVD divergence, ATR-based risk management, and Open Interest filters — now with visual chart labels and exchange switching.
Designed for crypto traders who want precise entry signals, volume insight, and a clean UI.
🔍 Key Features:
✅ CVD Divergence Detection
Automatically detects bullish or bearish divergences between price and cumulative delta (CVD)
✅ Open Interest Logic (Simulated)
Signals are only valid when OI is rising – otherwise a warning is issued
✅ ATR-Based Entry, Stop & Target Zones
Auto-calculated based on your chosen R multiple (e.g., 1.5R), plotted in the chart
✅ Visual Dashboard Panel (table)
Compact panel with CVD, OI change, ATR, signal status, and selected exchange — always visible in top-right
✅ Exchange Selector + Fallback to Binance
Choose between Binance, Bybit, Bitget, or Coinbase — if data is unavailable, Binance is used automatically
✅ Modular Chart Labels
Optionally display 📈 LONG, 📉 SHORT or ⚠️ WARNING labels directly on the chart with a toggle
✅ Alerts Built-In
Get notified instantly when a setup triggers (long, short, or warning) — works with app, popup, or webhook
✅ Fully Modular Controls
Enable or disable the dashboard, trade zones, and labels via simple checkboxes
⚠️ Technical Notes:
CVD is calculated from delta volume (volume * sign(close - open)) — not true order flow
Open Interest is simulated using volume as a placeholder (due to Pine Script limitations)
Best suited for 5–30min timeframes on crypto futures pairs like BTCUSDT, ETHUSDT, etc.
💡 Pro Tips:
Use near key support/resistance zones or liquidity levels
Combine with price action and higher timeframe confluence
Alerts work best with "Once Per Bar Close" trigger setting
📈 Built to support faster decisions, cleaner setups, and institutional-level insights — all in one tool.
Bloomberg Financial Conditions Index (Proxy)The Bloomberg Financial Conditions Index (BFCI): A Proxy Implementation
Financial conditions indices (FCIs) have become essential tools for economists, policymakers, and market participants seeking to quantify and monitor the overall state of financial markets. Among these measures, the Bloomberg Financial Conditions Index (BFCI) has emerged as a particularly influential metric. Originally developed by Bloomberg L.P., the BFCI provides a comprehensive assessment of stress or ease in financial markets by aggregating various market-based indicators into a single, standardized value (Hatzius et al., 2010).
The original Bloomberg Financial Conditions Index synthesizes approximately 50 different financial market variables, including money market indicators, bond market spreads, equity market valuations, and volatility measures. These variables are normalized using a Z-score methodology, weighted according to their relative importance to overall financial conditions, and then aggregated to produce a composite index (Carlson et al., 2014). The resulting measure is centered around zero, with positive values indicating accommodative financial conditions and negative values representing tighter conditions relative to historical norms.
As Angelopoulou et al. (2014) note, financial conditions indices like the BFCI serve as forward-looking indicators that can signal potential economic developments before they manifest in traditional macroeconomic data. Research by Adrian et al. (2019) demonstrates that deteriorating financial conditions, as measured by indices such as the BFCI, often precede economic downturns by several months, making these indices valuable tools for predicting changes in economic activity.
Proxy Implementation Approach
The implementation presented in this Pine Script indicator represents a proxy of the original Bloomberg Financial Conditions Index, attempting to capture its essential features while acknowledging several significant constraints. Most critically, while the original BFCI incorporates approximately 50 financial variables, this proxy version utilizes only six key market components due to data accessibility limitations within the TradingView platform.
These components include:
Equity market performance (using SPY as a proxy for S&P 500)
Bond market yields (using TLT as a proxy for 20+ year Treasury yields)
Credit spreads (using the ratio between LQD and HYG as a proxy for investment-grade to high-yield spreads)
Market volatility (using VIX directly)
Short-term liquidity conditions (using SHY relative to equity prices as a proxy)
Each component is transformed into a Z-score based on log returns, weighted according to approximated importance (with weights derived from literature on financial conditions indices by Brave and Butters, 2011), and aggregated into a composite measure.
Differences from the Original BFCI
The methodology employed in this proxy differs from the original BFCI in several important ways. First, the variable selection is necessarily limited compared to Bloomberg's comprehensive approach. Second, the proxy relies on ETFs and publicly available indices rather than direct market rates and spreads used in the original. Third, the weighting scheme, while informed by academic literature, is simplified compared to Bloomberg's proprietary methodology, which may employ more sophisticated statistical techniques such as principal component analysis (Kliesen et al., 2012).
These differences mean that while the proxy BFCI captures the general direction and magnitude of financial conditions, it may not perfectly replicate the precision or sensitivity of the original index. As Aramonte et al. (2013) suggest, simplified proxies of financial conditions indices typically capture broad movements in financial conditions but may miss nuanced shifts in specific market segments that more comprehensive indices detect.
Practical Applications and Limitations
Despite these limitations, research by Arregui et al. (2018) indicates that even simplified financial conditions indices constructed from a limited set of variables can provide valuable signals about market stress and future economic activity. The proxy BFCI implemented here still offers significant insight into the relative ease or tightness of financial conditions, particularly during periods of market stress when correlations among financial variables tend to increase (Rey, 2015).
In practical applications, users should interpret this proxy BFCI as a directional indicator rather than an exact replication of Bloomberg's proprietary index. When the index moves substantially into negative territory, it suggests deteriorating financial conditions that may precede economic weakness. Conversely, strongly positive readings indicate unusually accommodative financial conditions that might support economic expansion but potentially also signal excessive risk-taking behavior in markets (López-Salido et al., 2017).
The visual implementation employs a color gradient system that enhances interpretation, with blue representing neutral conditions, green indicating accommodative conditions, and red signaling tightening conditions—a design choice informed by research on optimal data visualization in financial contexts (Few, 2009).
References
Adrian, T., Boyarchenko, N. and Giannone, D. (2019) 'Vulnerable Growth', American Economic Review, 109(4), pp. 1263-1289.
Angelopoulou, E., Balfoussia, H. and Gibson, H. (2014) 'Building a financial conditions index for the euro area and selected euro area countries: what does it tell us about the crisis?', Economic Modelling, 38, pp. 392-403.
Aramonte, S., Rosen, S. and Schindler, J. (2013) 'Assessing and Combining Financial Conditions Indexes', Finance and Economics Discussion Series, Federal Reserve Board, Washington, D.C.
Arregui, N., Elekdag, S., Gelos, G., Lafarguette, R. and Seneviratne, D. (2018) 'Can Countries Manage Their Financial Conditions Amid Globalization?', IMF Working Paper No. 18/15.
Brave, S. and Butters, R. (2011) 'Monitoring financial stability: A financial conditions index approach', Economic Perspectives, Federal Reserve Bank of Chicago, 35(1), pp. 22-43.
Carlson, M., Lewis, K. and Nelson, W. (2014) 'Using policy intervention to identify financial stress', International Journal of Finance & Economics, 19(1), pp. 59-72.
Few, S. (2009) Now You See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press, Oakland, CA.
Hatzius, J., Hooper, P., Mishkin, F., Schoenholtz, K. and Watson, M. (2010) 'Financial Conditions Indexes: A Fresh Look after the Financial Crisis', NBER Working Paper No. 16150.
Kliesen, K., Owyang, M. and Vermann, E. (2012) 'Disentangling Diverse Measures: A Survey of Financial Stress Indexes', Federal Reserve Bank of St. Louis Review, 94(5), pp. 369-397.
López-Salido, D., Stein, J. and Zakrajšek, E. (2017) 'Credit-Market Sentiment and the Business Cycle', The Quarterly Journal of Economics, 132(3), pp. 1373-1426.
Rey, H. (2015) 'Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence', NBER Working Paper No. 21162.
Dynamic Volume Clusters with Retest Signals (Zeiierman)█ Overview
The Dynamic Volume Clusters with Retest Signals indicator is designed to detect key Volume Clusters and provide Retest Signals. This tool is specifically engineered for traders looking to capitalize on volume-based trends, reversals, and key price retest points.
The indicator seamlessly combines volume analysis, dynamic cluster calculations, and retest signal logic to present a comprehensive trading framework. It adapts to market conditions, identifying clusters of volume activity and signaling when the price retests critical zones.
█ How It Works
⚪ Volume Cluster Detection
The indicator dynamically calculates volume clusters by analyzing the highest and lowest price points within a specified lookback period.
Cluster Logic:
Bright Lines (Strong Red/Green):
These indicate that the price has frequently revisited these levels, creating a dense cluster.
Such areas serve as support or resistance, where significant historical trading has occurred, often acting as barriers to price movement.
Traders should consider these levels as potential reversal zones or consolidation points.
Faded or Darker Lines:
These lines indicate areas where the price has less historical activity, suggesting weaker clustering.
These zones have less market memory and are more likely to break, supporting trend continuation and rapid price movement.
⚪ Candle Color Logic (Market Memory)
Blue Candles (High Cluster Density):
Candles turn blue when the price has revisited a particular area many times.
This signals a highly clustered zone, likely to act as a barrier, creating consolidation or range phases.
These areas indicate strong market memory, potentially rejecting price attempts to break through.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these dense clusters, the candles turn green (bullish) or red (bearish).
This suggests the price has moved into a less clustered territory, where the path forward is clearer and trends are likely to extend without immediate resistance.
⚪ Retest Signal Logic
The indicator identifies critical retest points where the price crosses a cluster boundary and then reverses. These points are essential for traders looking to catch continuation or reversal setups.
⚪ Dynamic Price Clustering
The indicator dynamically adapts the clustering logic based on price movement and volume shifts.
Uses a dynamic moving average (VPMA) to maintain adaptive cluster levels.
Integrates a Kalman Filter for smoothing, reducing noise, and improving trend clarity.
Automatically updates as new data is received, keeping the clusters relevant in real-time.
█ How to Use
⚪ Trend Following & Reversal Detection
Use Retest signals to identify potential trend continuation or reversal points.
⚪ Trading Volume Clusters and Market Memory
Identify Key Zones:
Focus on bright, saturated cluster lines (strong red or green) as they indicate high market memory, where price has spent significant time in the past.
These zones are likely to exhibit a more choppy market. Apply range or mean reversion strategies.
Spot Potential Breakouts:
Faded or darker cluster lines indicate areas of low market memory, where the price has moved quickly and spent less time.
Use these areas to identify possible trend setups, as they represent lower resistance to price movement.
⚪ Interpreting Candle Colors for Market Phases
Blue Candles (High Cluster Density):
When candles turn blue, it signals that the price has revisited this area multiple times, creating a dense cluster.
These zones often trap price movement, leading to consolidations or range phases.
Use these areas as caution zones, where price can slow down or reverse.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these clustered zones, the candles turn green (bullish) or red (bearish), indicating lower market memory.
This signals a trend initiation with less immediate resistance, ideal for momentum and breakout trades.
Use these signals to identify emerging trends and ride the momentum.
█ Settings
Range Lookback Period: Sets the number of bars for calculating the range.
Zone Width (% of Range): Determines how wide the volume clusters are relative to the calculated range.
Volume Line Colors: Customize the appearance of bullish and bearish lines.
Retest Signals: Toggle the appearance of Triangle Up/Down retest markers.
Minimum Bars for Retest: Define the minimum number of bars required before a retest is valid.
Maximum Bars for Retest: Set the maximum number of bars within which a retest can occur.
Price Cluster Period: Adjusts the sensitivity of the dynamic clustering logic.
Cluster Confirmation: Controls how tightly the clusters respond to price action.
Price Cluster Start/Peak: Sets the minimum and maximum touches required to fully form a cluster.
-----------------
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.
SSRO Z-ScoreSSRO Z-Score Indicator — Description
What it does:
This indicator measures the Stablecoin Supply Ratio (SSR) relative to Bitcoin’s market cap and calculates a normalized Z-Score of this ratio to help identify potential market tops and bottoms in the crypto market.
How it works:
The Stablecoin Supply Ratio (SSR) is calculated by dividing Bitcoin’s market capitalization by the combined market capitalization of major stablecoins (USDT, USDC, TUSD, DAI, FRAX).
The SSR is then smoothed over a user-defined lookback period to reduce noise.
A Z-Score is computed by normalizing the SSR over a specified moving window, which shows how far the current SSR deviates from its historical average in terms of standard deviations.
This Z-Score is further smoothed using an exponential moving average (EMA) to filter short-term volatility.
How to read the Z-Score:
Z-Score = 0: SSR is at its historical average.
Z-Score > 0: SSR is above average, indicating Bitcoin’s market cap is relatively high compared to stablecoin supply, potentially signaling bullish market conditions.
Z-Score < 0: SSR is below average, indicating stablecoin supply is high relative to Bitcoin’s market cap, possibly signaling bearish pressure or increased liquidity waiting to enter the market.
Upper and Lower Bands: These user-defined levels (e.g., +2 and -2) represent thresholds for extreme conditions. Values above the upper band may indicate overbought or overheated market conditions, while values below the lower band may indicate oversold or undervalued conditions.
Additional Features:
A dynamic table displays a linear scaled Z-Score alongside the main plot, clamped between -2 and +2 relative to the upper and lower bands for intuitive interpretation.
Usage Tips:
Combine the SSRO Z-Score with other technical indicators or volume analysis for more reliable signals.
Look for divergence between price and Z-Score extremes as potential reversal signals.
Velez Price Action Signals (with 20 & 200 SMA)Velez Price Action Signals – With 20 & 200 SMA Overlay
This TradingView Pine Script is a clean and powerful reversal signal tool inspired by Oliver Velez’s price action philosophy, enhanced with trend context via two Simple Moving Averages.
🔍 Signal Logic
Buy Signal:
Current candle sweeps below the previous 5-bar low (liquidity grab).
Candle is bullish (close > open).
The lower wick is significantly larger than the body (e.g. ratio > 1.5).
Sell Signal:
Current candle sweeps above the previous 5-bar high.
Candle is bearish (close < open).
The upper wick is significantly larger than the body.
Signals appear as BUY/SELL labels on the chart (non-repainting).
LULD Bands & Trading Halt Detector [Volume Vigilante]📖 LULD Bands & Trading Halt Detector
This advanced tool visualizes official Limit Up / Limit Down (LULD) price bands and detects regulatory trading halts and resumptions based on SEC and NASDAQ rules. It is engineered for high accuracy by anchoring all calculations to the 1-minute timeframe, ensuring reliable signals across any chart resolution.
📌 What Does This Script Do?
- Draws real-time LULD price band estimations and optional buffer (caution) zones directly on the chart.
- Detects trading halt resumptions by monitoring time gaps between candles and other regulatory criteria. (Note: Due to Pine Script limitations, halts cannot be detected in real-time, only resumptions after they occur.)
- Triggers real-time alerts for:
- Trading Resumptions (Limit Up & Limit Down)
- LULD Zone Entries (Caution Zone)
- Band Breaches (Limit Up and Limit Down)
- Plots historical halt resumption markers to analyse past events.
📐 How It Works:
- Implements official SEC/NASDAQ LULD rules for Tier 1 and Tier 2 securities.
- Applies special band adjustments for the final 25 minutes of trading (after 3:35 PM ET).
- Anchors all logic to the 1-minute timeframe for precise calculations, even on higher timeframe charts.
- Includes adjustable volume and volatility filters to eliminate false signals (ghost halts) on low-- liquidity assets, especially Tier 2 securities when TradingView fails to print candles.
⚙️ How to Use It:
1.) Apply the script to any asset or timeframe.
2.) Adjust Volume and Volatility Filters to reduce noise. (Recommended: 500,000+ volume, 10%+ volatility.)
3.) Enable or disable visual components like bands, buffer zones, and halt resumption labels.
4.) Configure alerts directly from the script settings panel.
5.) Apply alerts to individual assets via "Add Alert On..." or to entire watchlists using "Add Alert on the List."
🧩 What Makes This Script Unique?
- True 1-Minute Anchored Calculations: Ensures alerts and visuals match official trading halt criteria regardless of chart timeframe.
- Customisable Buffered Zones: Visualise proximity to regulatory price limits and avoid volatility traps.
- Combines halt resumption detection, limit up/down band visualisation, and real-time alerts into one clean, modular tool.
📚 Disclaimer:
This script is for educational purposes only and does not constitute financial advice. Use at your own discretion and consult a licensed financial advisor before making trading decisions based on it.
Official Resources:
- NASDAQ LULD Regulations (FAQ):
www.nasdaqtrader.com
Current Nasdaq Trading Halts:
www.nasdaqtrader.com
Goldman Sachs Risk Appetite ProxyRisk appetite indicators serve as barometers of market psychology, measuring investors' collective willingness to engage in risk-taking behavior. According to Mosley & Singer (2008), "cross-asset risk sentiment indicators provide valuable leading signals for market direction by capturing the underlying psychological state of market participants before it fully manifests in price action."
The GSRAI methodology aligns with modern portfolio theory, which emphasizes the importance of cross-asset correlations during different market regimes. As noted by Ang & Bekaert (2002), "asset correlations tend to increase during market stress, exhibiting asymmetric patterns that can be captured through multi-asset sentiment indicators."
Implementation Methodology
Component Selection
Our implementation follows the core framework outlined by Goldman Sachs research, focusing on four key components:
Credit Spreads (High Yield Credit Spread)
As noted by Duca et al. (2016), "credit spreads provide a market-based assessment of default risk and function as an effective barometer of economic uncertainty." Higher spreads generally indicate deteriorating risk appetite.
Volatility Measures (VIX)
Baker & Wurgler (2006) established that "implied volatility serves as a direct measure of market fear and uncertainty." The VIX, often called the "fear gauge," maintains an inverse relationship with risk appetite.
Equity/Bond Performance Ratio (SPY/IEF)
According to Connolly et al. (2005), "the relative performance of stocks versus bonds offers significant insight into market participants' risk preferences and flight-to-safety behavior."
Commodity Ratio (Oil/Gold)
Baur & McDermott (2010) demonstrated that "gold often functions as a safe haven during market turbulence, while oil typically performs better during risk-on environments, making their ratio an effective risk sentiment indicator."
Standardization Process
Each component undergoes z-score normalization to enable cross-asset comparisons, following the statistical approach advocated by Burdekin & Siklos (2012). The z-score transformation standardizes each variable by subtracting its mean and dividing by its standard deviation: Z = (X - μ) / σ
This approach allows for meaningful aggregation of different market signals regardless of their native scales or volatility characteristics.
Signal Integration
The four standardized components are equally weighted and combined to form a composite score. This democratic weighting approach is supported by Rapach et al. (2010), who found that "simple averaging often outperforms more complex weighting schemes in financial applications due to estimation error in the optimization process."
The final index is scaled to a 0-100 range, with:
Values above 70 indicating "Risk-On" market conditions
Values below 30 indicating "Risk-Off" market conditions
Values between 30-70 representing neutral risk sentiment
Limitations and Differences from Original Implementation
Proprietary Components
The original Goldman Sachs indicator incorporates additional proprietary elements not publicly disclosed. As Goldman Sachs Global Investment Research (2019) notes, "our comprehensive risk appetite framework incorporates proprietary positioning data and internal liquidity metrics that enhance predictive capability."
Technical Limitations
Pine Script v6 imposes certain constraints that prevent full replication:
Structural Limitations: Functions like plot, hline, and bgcolor must be defined in the global scope rather than conditionally, requiring workarounds for dynamic visualization.
Statistical Processing: Advanced statistical methods used in the original model, such as Kalman filtering or regime-switching models described by Ang & Timmermann (2012), cannot be fully implemented within Pine Script's constraints.
Data Availability: As noted by Kilian & Park (2009), "the quality and frequency of market data significantly impacts the effectiveness of sentiment indicators." Our implementation relies on publicly available data sources that may differ from Goldman Sachs' institutional data feeds.
Empirical Performance
While a formal backtest comparison with the original GSRAI is beyond the scope of this implementation, research by Froot & Ramadorai (2005) suggests that "publicly accessible proxies of proprietary sentiment indicators can capture a significant portion of their predictive power, particularly during major market turning points."
References
Ang, A., & Bekaert, G. (2002). "International Asset Allocation with Regime Shifts." Review of Financial Studies, 15(4), 1137-1187.
Ang, A., & Timmermann, A. (2012). "Regime Changes and Financial Markets." Annual Review of Financial Economics, 4(1), 313-337.
Baker, M., & Wurgler, J. (2006). "Investor Sentiment and the Cross-Section of Stock Returns." Journal of Finance, 61(4), 1645-1680.
Baur, D. G., & McDermott, T. K. (2010). "Is Gold a Safe Haven? International Evidence." Journal of Banking & Finance, 34(8), 1886-1898.
Burdekin, R. C., & Siklos, P. L. (2012). "Enter the Dragon: Interactions between Chinese, US and Asia-Pacific Equity Markets, 1995-2010." Pacific-Basin Finance Journal, 20(3), 521-541.
Connolly, R., Stivers, C., & Sun, L. (2005). "Stock Market Uncertainty and the Stock-Bond Return Relation." Journal of Financial and Quantitative Analysis, 40(1), 161-194.
Duca, M. L., Nicoletti, G., & Martinez, A. V. (2016). "Global Corporate Bond Issuance: What Role for US Quantitative Easing?" Journal of International Money and Finance, 60, 114-150.
Froot, K. A., & Ramadorai, T. (2005). "Currency Returns, Intrinsic Value, and Institutional-Investor Flows." Journal of Finance, 60(3), 1535-1566.
Goldman Sachs Global Investment Research (2019). "Risk Appetite Framework: A Practitioner's Guide."
Kilian, L., & Park, C. (2009). "The Impact of Oil Price Shocks on the U.S. Stock Market." International Economic Review, 50(4), 1267-1287.
Mosley, L., & Singer, D. A. (2008). "Taking Stock Seriously: Equity Market Performance, Government Policy, and Financial Globalization." International Studies Quarterly, 52(2), 405-425.
Oppenheimer, P. (2007). "A Framework for Financial Market Risk Appetite." Goldman Sachs Global Economics Paper.
Rapach, D. E., Strauss, J. K., & Zhou, G. (2010). "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy." Review of Financial Studies, 23(2), 821-862.
TK47 36 ChambersTK47 36 Chambers is a precision-crafted EMA (Exponential Moving Average) tool designed to help traders align with multi-timeframe trends while keeping price action clear and uncluttered. Built around the powerful 36 EMA, this script plots the current timeframe’s high, low, and median EMAs as a visual "chamber" or cloud, giving instant feedback on intrabar dynamics.
Shoutout to Insilico, who introduced the 36 EMA as a core trend-following tool — this indicator wouldn’t exist without that spark.
How It Works
Core EMA:
The central element is the 36-period EMA, applied to close, high, and low prices on your current chart.
These three EMAs form a channel or “chamber” that acts as a dynamic zone of control.
The cloud between the high and low EMA can optionally be filled to help visualize volatility.
Higher Timeframe EMAs (HTF EMAs):
Optionally displays Daily, Weekly, 4H, and 1H EMAs (all using the same configurable EMA length, default: 36).
These are interpolated smoothly between HTF candles, creating elegant transitions and avoiding jumpy plotting.
Helps traders spot broader trend bias directly on lower timeframe charts without switching views.
Customizations
Adjustable colors for each EMA layer (current + HTFs).
Toggle cloud fill on/off.
Toggle visibility of each HTF line.
Option to show labels at the edge of the chart (e.g., “W” for Weekly) for clarity.
Use Cases
Confirming trend direction across multiple timeframes.
Identifying pullback entries or mean reversion zones.
Combining with candlestick patterns, liquidity sweeps, or oscillator divergence for high-probability entries.
Notes
All EMAs use the same configurable length to keep things clean and consistent.
Interpolation ensures the HTF EMAs remain smooth and aligned with the LTF candles.
The fill between high and low EMA gives a visual representation of the market’s breathing room — useful for spotting expansions and contractions.
Multi-Indicator Swing [TIAMATCRYPTO]v6# Strategy Description:
## Multi-Indicator Swing
This strategy is designed for swing trading across various markets by combining multiple technical indicators to identify high-probability trading opportunities. The system focuses on trend strength confirmation and volume analysis to generate precise entry and exit signals.
### Core Components:
- **Supertrend Indicator**: Acts as the primary trend direction filter with optimized settings (Factor: 3.0, ATR Period: 10) to balance responsiveness and reliability.
- **ADX (Average Directional Index)**: Confirms the strength of the prevailing trend, filtering out sideways or choppy market conditions where the strategy avoids taking positions.
- **Liquidity Delta**: A volume-based indicator that analyzes buying and selling pressure imbalances to validate trend direction and potential reversals.
- **PSAR (Optional)**: Can be enabled to add additional confirmation for trend changes, turned off by default to reduce signal filtering.
### Key Features:
- **Flexible Direction Trading**: Choose between long-only, short-only, or bidirectional trading to adapt to market conditions or account restrictions.
- **Conservative Risk Management**: Implements fixed percentage-based stop losses (default 2%) and take profits (default 4%) for a positive risk-reward ratio.
- **Realistic Backtesting Parameters**: Includes commission (0.1%) and slippage (2 points) to reflect real-world trading conditions.
- **Visual Signals**: Clear buy/sell arrows with customizable sizes for easy identification on the chart.
- **Information Panel**: Dynamic display showing active indicators and current risk settings.
### Best Used On:
Daily timeframes for cryptocurrencies, forex, or stock indices. The strategy performs optimally on assets with clear trending behavior and sufficient volatility.
### Default Settings:
Optimized for conservative position sizing (5% of equity per trade) with an initial capital of $10,000. The backtesting period (2021-2023) provides a statistically significant sample of varied market conditions.
Order Block Matrix [Alpha Extract]The Order Block Matrix indicator identifies and visualizes key supply and demand zones on your chart, helping traders recognize potential reversal points and high-probability trading setups.
This tool helps traders:
Visualize key order blocks with volume profile histograms showing liquidity distribution.
Identify high-volume price levels where institutional activity occurs.
rank historical order blocks and analyze their strength based on volume.
Receive alerts for potential trading opportunities based on price-block interactions.
🔶 CALCULATION
The indicator processes chart data to identify and analyze order blocks:
Order Block Detection
Inputs:
Price action patterns (consolidation areas followed by breakouts).
Volume data from current and lower timeframes.
User-defined lookback periods and thresholds.
Detection Logic:
Identifies consolidation areas using a dynamic range comparison.
Confirms breakout patterns with percentage threshold validation.
Maps volume distribution across price levels within each order block.
🔶Volume Analysis
Volume Profiling:
Divides each order block into configurable grid segments.
Maps volume distribution across price segments within blocks.
Highlights zones with highest volume concentration.
Strength Assessment:
Calculates total block volume and relative strength metrics.
Compares block volume to historical averages.
Determines probability of reversal based on volume patterns.
isConsolidation(len) =>
high_range = ta.highest(high, len) - ta.lowest(high, len)
low_range = ta.highest(low, len) - ta.lowest(low, len)
avg_range = (high_range + low_range) / 2
current_range = high - low
current_range <= avg_range * (1 + obThreshold)
🔶 DETAILS
Visual Features
Volume Profile Histograms:
Color-coded bars showing volume concentration within order blocks.
Gradient coloring based on relative volume (high volume = brighter colors).
Bull blocks (green/teal) and bear blocks (red) with varying opacity.
Block Visualization:
Dynamic box sizing based on volume concentration.
Optional block borders and background fills.
Volume labels showing total block volume.
Screener Table:
Real-time analysis of order block metrics.
Shows block direction, proximity, retest count, and volume metrics.
Color-coded for quick reference.
Interpretation
High Volume Areas: Zones with institutional interest and potential reversal points.
Block Direction: Bullish blocks typically support price, bearish blocks typically resist price.
Retests: Multiple tests of an order block may strengthen or weaken its influence.
Block Age: Newer blocks often have stronger influence than older ones.
Volume Concentration: Brightest segments within blocks represent the highest volume areas.
🔶 EXAMPLES
The indicator helps identify key trading opportunities:
Bullish Order Blocks
Support Zones: Identify strong support levels where price is likely to bounce.
Breakout Confirmation: Validate breakouts with volume analysis to avoid false moves.
Retest Strategies: Enter trades when price retests a bullish order block with high volume.
Bearish Order Blocks
Resistance Zones: Identify strong resistance levels where price is likely to reverse.
Distribution Areas: Detect zones where smart money is distributing to retail.
Short Opportunities: Find optimal short entry points at high-volume bearish blocks.
Combined Strategies
Order Block Stacking: Multiple aligned blocks create stronger support/resistance zones.
Block Mitigation: When price breaks through a block, it often indicates a strong trend continuation.
Volume Profile Applications: Higher volume segments provide more precise entry and exit points.
🔶 SETTINGS
Customization Options
Order Block Detection:
Consolidation Lookback: Adjust the period for consolidation detection.
Breakout Threshold: Set minimum percentage for breakout confirmation.
Historical Lookback Limit: Control how far back to scan for historical order blocks.
Maximum Order Blocks: Limit the number of visible blocks on the chart.
Visual Style:
Grid Segments: Adjust the number of volume profile segments.
Extend Blocks to Right: Enable/disable extending blocks to current price.
Show Block Borders: Toggle border visibility.
Border Width: Adjust thickness of block borders.
Show Volume Text: Enable/disable volume labels.
Volume Text Position: Control placement of volume labels.
Color Settings:
Bullish High/Low Volume Colors: Customize appearance of bullish blocks.
Bearish High/Low Volume Colors: Customize appearance of bearish blocks.
Border Color: Set color for block outlines.
Background Fill: Adjust color and transparency of block backgrounds.
Volume Text Color: Customize label appearance.
Screener Table:
Show Screener Table: Toggle table visibility.
Table Position: Select positioning on the chart.
Table Size: Adjust display size.
The Order Block Matrix indicator provides traders with powerful insights into market structure, helping to identify key levels where smart money is active and where high-probability trading opportunities may exist.
TLC sessionA Professional Intraday Session Tracker with VWAP and Economic Event Integration
Description
This indicator provides visual tracking of major trading sessions (Asian, London, New York) combined with VWAP calculations and macroeconomic event zones. It's designed for intraday traders who need to monitor session overlaps, liquidity periods, and high-impact news events.
The basic script of trading sessions was taken as a basis and refined for greater convenience.
Key Features:
Customizable Session Tracking: Visualize up to 3 trading sessions with adjustable time zones (supports IANA & GMT formats)
Dynamic VWAP Integration: Built-in Volume-Weighted Average Price calculation
Macro Event Zones: Highlights key economic announcement windows (adjustable for summer/winter time)
Price Action Visualization: Displays open/close prices, session ranges, and average price levels
Automatic DST Adjustment: Uses IANA timezone database for daylight savings awareness
How It Works
1. Trading Session Detection
Three fully configurable sessions (e.g., Asia, London, New York)
Each session displays:
Colored background zone
Opening price (dashed line)
Closing price (dashed line)
Average price (dotted line)
Optional label with session name
2. VWAP Calculation
Standard Volume-Weighted Average Price plotted as circled line
Helps identify fair value within each session
3. Macro Event Zones
Special highlighted period for economic news releases
Automatically adjusts for summer/winter time
Default set to 1000-1200 (summer) or 0900-1100 (winter) GMT-5 (US session open)
Why This Indicator is Unique
Multi-Session Awareness
Unlike simple session indicators, this tool:
Tracks price development within each session
Shows session overlaps (critical for volatility periods)
Maintains separate VWAP calculations across sessions
Professional-Grade Features
IANA timezone support (automatic DST handling)
Customizable visual elements (toggle labels, ranges, averages)
Object-based architecture (clean, efficient rendering)
News event integration (helps avoid trading during high-impact releases)
Usage Recommendations
Best Timeframes
1-minute to 1-hour charts (intraday focus)
Not recommended for daily+ timeframes
Trading Applications
1. Session Breakout Strategy: Trade breakouts when London/New York sessions open
2. VWAP Reversion: Fade moves that deviate too far from VWAP
3. News Avoidance: Reduce position sizing during macro event windows
Visual Example
Asian session (red)
London session (blue)
New York session (purple)
Macro event zone (white)
VWAP line (gold circles)
The basic script of trading sessions was taken as a basis and refined for greater convenience.
[blackcat] L3 Market Pulse InsightOVERVIEW
The L3 Market Pulse Insight provides comprehensive analytics by evaluating key price metrics to reveal critical market sentiment and potential trade opportunities 📊🔍. This advanced indicator leverages proprietary calculations involving Simple Moving Averages (SMAs), Exponential Moving Averages (EMAs), and custom thresholds to deliver detailed insights into current market dynamics 🚀✨.
By plotting various lines representing core fundamentals and directional cues, traders gain visibility into underlying trends and shifts within the market pulse. The visual aids simplify complex data interpretation, making it easier for users to make strategic decisions based on clear, actionable information ✅⛈️.
FEATURES
Advanced Calculation Techniques:
Employs sophisticated formulas integrating SMAs and EMAs for precise trend analysis.
Incorporates fundamental lines and confirmations based on recent price extremes.
Comprehensive Visualization:
Plots multiple informational lines: Fundamental Line, Thresholds, Institutional Directions, etc., each reflecting unique aspects of price behavior.
Uses distinct colors for easy differentiation between bearish and bullish indications.
Customizable Alerts:
Generates "Buy" and "Sell" labels at pivotal moments, highlighting entry/exit points visually.
Offers flexibility to modify alert styles and positions according to user preferences.
Dynamic Adaptability:
Continuously updates plots and alerts based on incoming real-time data for timely responses.
Provides dynamic support/resistance levels adapting to evolving market conditions.
HOW TO USE
Installing the Indicator:
To start using the L3 Market Pulse Insight, add it via the Pine Editor on TradingView:
Open the editor from the bottom panel.
Copy-paste the provided script code.
Click “Add to Chart” after pasting.
Understanding Key Lines:
Familiarize yourself with what each plotted line signifies:
Fundamental Line: Represents core price movements adjusted through SMA transformations.
Low Confirmation & Warnings: Provide early signals about potential reversals or continuation scenarios.
Threshold B: Acts as a significant barrier indicating overbought/sold conditions.
Institutional Directions: Offer insights into larger player activities and intentions.
Interpreting Signals:
Pay close attention to generated "Buy" and "Sell" labels appearing directly on your chart:
"Buy" Label: Indicates favorable momentum crossing from below the confirmation level upwards.
"Sell" Label: Suggests bearish transitions when moving beneath set thresholds.
Adjusting Parameters:
While this version primarily uses default settings derived from optimal testing ranges, feel free to experiment:
Modify lookback periods in SMA/EMA functions if different timeframes align better with your strategy.
Customize plot colors/styles for enhanced readability and personal taste.
Integrating with Other Tools:
Enhance the reliability of signals produced by combining them with complementary indicators like RSI, MACD, or volume profiles for thorough validation.
Continuous Monitoring:
Regularly review performance and refine strategies incorporating insights gathered from L3 Market Pulse Insight across varying markets and assets.
LIMITATIONS
Data Dependency: Performance heavily relies on accurate historical data without anomalies.
Market Conditions Variability: Effectiveness may vary during extreme volatility or thin liquidity environments.
Parameter Fine-Tuning: Optimal configuration might differ significantly across instruments; continuous adjustments are necessary.
No Guarantees: Like any tool, this doesn't ensure profits and should be part of a broader analytical framework.
NOTES
Ensure solid grounding in technical analysis principles before deploying solely upon these insights.
Utilize backtesting rigorously under diverse market cycles to assess robustness thoroughly.
Consider external factors such as economic reports, geopolitical events influencing asset prices beyond purely statistical models.
Maintain discipline adhering predefined risk management protocols regardless of signal strength displayed here.
THANKS
We appreciate every member's contributions who have engaged actively throughout our development journey, offering constructive feedback driving improvements continually 🙏. Together we strive toward creating ever-more robust tools empowering traders worldwide!
Current Fractal High/Low (Dynamic)
This indicator dynamically tracks the most recent confirmed Fractal High and Fractal Low across any timeframe using custom left/right bar configurations.
🔍 Key Features:
Detects Fractal Highs and Lows based on user-defined pivot settings.
Draws a green line and label ("FH") at the most recent Fractal High.
Draws a red line and label ("FL") at the most recent Fractal Low.
All lines extend from the confirmation bar to the current candle.
Automatically removes old lines and labels for a clean, uncluttered chart.
🛠️ Customizable Inputs:
Left & Right bars for pivot sensitivity
Line width for visibility
📌 Use Cases:
Identifying structure shifts
Recognizing key swing points
Supporting liquidity and breakout strategies
💡 Fractals are confirmed only after the full formation of the pattern (left and right bars). This ensures reliability over reactivity.
This script is designed for intraday to swing traders who want a reliable way to visualize market turning points with minimal noise.
Multitimeframe Order Block Finder (Zeiierman)█ Overview
The Multitimeframe Order Block Finder (Zeiierman) is a powerful tool designed to identify potential institutional zones of interest — Order Blocks — across any timeframe, regardless of what chart you're viewing.
Order Blocks are critical supply and demand zones formed by the last opposing candle before an impulsive move. These areas often act as magnets for price and serve as smart-money footprints — ideal for anticipating reversals, retests, or breakouts.
This indicator not only detects such zones in real-time, but also visualizes their mitigation, bull/bear volume pressure, and a smoothed directional trendline based on Order Block behavior.
█ How It Works
The script fetches OHLCV data from your chosen timeframe using request.security() and processes it using strict pattern logic and volume-derived strength conditions. It detects Order Blocks only when the structure aligns with dominant pressure and visually extends valid zones forward for as long as they remain unmitigated.
⚪ Bull/Bear Volume Power Visualization
Each OB includes proportional bars representing estimated buy/sell effort:
Buy Power: % of volume attributed to buyers
Sell Power: % of volume attributed to sellers
This adds a visual, intuitive layer of intent — showing who controlled the price before the OB formed.
⚪ Order Block Trendline (Butterworth Filtered)
A smoothed trendline is derived from the average OB value over time using a two-pole Butterworth low-pass filter. This helps you understand the broader directional pressure:
Trendline up → favor bullish OBs
Trendline down → favor bearish OBs
█ How to Use
⚪ Trade From Order Blocks Like Institutions
Use this tool to find institutional footprints and reaction zones:
Enter at unmitigated OBs
⚪ Volume Power
Volume Pressure Bars inside each OB help you:
Confirm strong buyer/seller dominance
Detect possible traps or exhaustion
Understand how each zone formed
⚪ Find Trend & Pullbacks
The trendline not only helps traders detect the current trend direction, but the built-in trend coloring also highlights potential pullback areas within these trends.
█ Settings
Timeframe – Selects which timeframe to scan for Order Blocks.
Lookback Period – Defines how many bars back are used to detect bullish or bearish momentum shifts.
Sensitivity – When enabled, the indicator uses smoothed price (RMA) with rising/falling logic instead of raw candle closes. This allows more flexible detection of trend shifts and results in more Order Blocks being identified.
Minimum Percent Move – Filters out weak moves. Higher = only strong price shifts.
Mitigated on Mid – OB is removed when price touches its midpoint.
Show OB Table – Displays a panel listing all active (unmitigated) Order Blocks.
Extend Boxes – Controls how far OB boxes stretch into the future.
Show OB Trend – Toggles the trendline derived from Order Block strength.
Passband Ripple (dB) – Controls trendline reactivity. Higher = more sensitive.
Cutoff Frequency – Controls smoothness of trendline (0–0.5). Lower = smoother.
-----------------
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.
[blackcat] L3 Smart Money FlowCOMPREHENSIVE ANALYSIS OF THE L3 SMART MONEY FLOW INDICATOR
🌐 OVERVIEW:
The L3 Smart Money Flow indicator represents a sophisticated multi-dimensional analytics tool combining traditional momentum measurements with advanced institutional investor tracking capabilities. It's particularly effective at identifying large-scale capital movement dynamics that often precede significant price shifts.
Core Objectives:
• Detect subtle but meaningful price action anomalies indicating major player involvement
• Provide clear entry/exit markers based on multiple validated criteria
• Offer risk-managed positioning strategies suitable for various account sizes
• Maintain operational efficiency even during high volatility regimes
THEORETICAL BACKDROP AND METHODOLOGY
🎓 Conceptual Foundation Principles:
Utilizes Time-Varying Moving Averages (TVMA) responding adaptively to changing market states
Implements Extended Smoothing Algorithm (XSA) providing enhanced filtration characteristics
Employs asymmetric weight distribution favoring recent price observations over historical ones
→ Analyzes price-weighted closing prices incorporating volume influence indirectly
← Applies Asymmetric Local Maximum (ALMA) filters generating institution-specific trends
⟸ Combines multiple temporal perspectives producing robust directional assessments
✓ Calculates normalized momentum ratios comparing current state against extended range extremes
✗ Filters out insignificant fluctuations via double-stage verification process
⤾ Generates actionable alerts upon exceeding predefined significance boundaries
CONFIGURABLE PARAMETERS IN DEPTH
⚙️ Input Customization Options Detailed Explanation:
Temporal Resolution Control:
→ TVMA Length Setting:
Minimum value constraint ensuring mathematical validity
Higher numbers increase smoothing effect reducing reaction velocity
Lower intervals enhance responsiveness potentially increasing noise exposure
Validation Threshold Definition:
↓ Bull-Bear Boundary Level:
Establishes fundamental acceptance/rejection zones
Typically set near extreme values reflecting rare occurrence probability
Can be adjusted per instrument liquidity profiles if necessary
ADVANCED ALGORITHMIC PROCEDURES BREAKDOWN
💻 Internal Operation Architecture:
Base Calculations Infrastructure:
☑ Raw Data Preparation and Normalization
☐ High/Low/Closing Aggregation Processes
☒ Range Estimation Algorithms
Intermediate Transform Engine:
📈 Momentum Ratio Computation Workflow
↔ First Pass XSA Application Details
➖ Second Stage Refinement Mechanics
Final Output Synthesis Framework:
➢ Composite Reading Compilation Logic
➣ Validation Status Determination Process
➤ Alert Trigger Decision Making Structure
INTERACTIVE VISUAL INTERFACE COMPONENTS
🎨 User Experience Interface Elements:
🔵 Plotting Series Hierarchy:
→ Primary FundFlow Signal: White trace marking core oscillator progression
↑ Secondary Confirmation Overlay: Orange/Yellow highlighting validation status
🟥 Risk/Reward Boundaries: Aqua line delineating strategic areas requiring attention
🏷️ Interactive Marker System:
✔ "BUY": Green upward-pointing labels denoting confirmed long entries
❌ "SELL": Red downward-facing badges signaling short setups
PRACTICAL APPLICATION STRATEGY GUIDE
📋 Operational Deployment Instructions:
Strategic Planning Initiatives:
• Define precise profit targets considering realistic reward/risk scenarios
→ Set maximum acceptable loss thresholds protecting available resources adequately
↓ Develop contingency plans addressing unexpected adverse developments promptly
Live Trading Engagement Protocols:
→ Maintaining vigilant monitoring of label placement activities continuously
↓ Tracking order fill success rates across implemented grids regularly
↑ Evaluating system effectiveness compared alternative methodologies periodically
Performance Optimization Techniques:
✔ Implement incremental improvements iteratively throughout lifecycle
❌ Eliminate ineffective component variations systematically
⟹ Ensure proportional growth capability matching user needs appropriately
EFFICIENCY ENHANCEMENT APPROACHES
🚀 Ongoing Development Strategy:
Resource Management Focus Areas:
→ Minimizing redundant computation cycles through intelligent caching mechanisms
↓ Leveraging parallel processing capabilities where feasible efficiently
↑ Optimizing storage access patterns improving response times substantially
Scalability Consideration Factors:
✔ Adapting to varying account sizes/market capitalizations seamlessly
❌ Preventing bottlenecks limiting concurrent operation capacity
⟹ Ensuring balanced growth capability matching evolving requirements accurately
Maintenance Routine Establishment:
✓ Regular codebase updates incorporation keeping functionality current
↓ Periodic performance audits conducting verifying continued effectiveness
↑ Documentation refinement updating explaining any material modifications made
SYSTEMATIC RISK CONTROL MECHANISMS
🛡️ Comprehensive Protection Systems:
Position Sizing Governance:
∅ Never exceed predetermined exposure limitations strictly observed
± Scale entries proportionally according to available resources carefully
× Include slippage allowances within planning stages realistically
Emergency Response Procedures:
↩ Well-defined exit strategies including trailing stops activation logic
🌀 Contingency plan formulation covering worst-case scenario contingencies
⇄ Recovery procedure documentation outlining restoration steps methodically
WaveFunction MACD (TechnoBlooms)WaveFunction MACD — The Next Generation of Market Momentum
WaveFunction MACD is an advanced hybrid momentum indicator that merges:
• The classical MACD crossover logic (based on moving averages)
• Wave physics (modeled through phase energy and cosine functions)
• Hilbert Transform theory from signal processing
• The concept of a wavefunction from quantum mechanics, where price action is seen as a probabilistic energy wave—not just a trend.
✨ Key Features of WaveFunction MACD
• Wave Energy Logic : Instead of using just price and MA differences, this indicator computes phase-corrected momentum using the cosine of the wave phase angle — revealing the true energy behind market moves.
• Phase-Based Trend Detection : It reads cycle phases using Hilbert Transform-like logic, allowing you to spot momentum before it becomes visible in price.
• Ultra-Smooth Flow : The main line and histogram are built to follow price flow smoothly — eliminating much of the noise found in traditional MACD indicators.
• Signal Amplification via Energy Histogram : The histogram doesn’t just show momentum changes — it shows the intensity of wave energy, allowing you to confirm the strength of the trend.
• Physics-Driven Structure : The algorithm is rooted in real-world wave mechanics, bringing a scientific edge to trading — ideal for traders who believe in natural models like cycles and harmonics.
• Trend Confirmation & Early Reversals : It can confirm strong trends and also catch subtle shifts that often precede big reversals — giving you both reliability and anticipation.
• Ready for Fusion : Designed to work seamlessly with liquidity zones, price action, order blocks, and structure trading — a perfect fit for modern trading systems.
🧪 The Science Behind It
This tool blends:
• Hilbert Transform: Measures the phase of a waveform (price cycle) to detect turning points
• Cosine Phase Energy: Calculates true wave energy using the cosine of the phase angle, revealing the strength behind price movements
• Quantum Modeling: Views price like a wavefunction, offering predictive insight based on phase dynamics
Stochastics + VixFix Buy/Sell SignalsThis script is designed for long-term investors using ETFs on a weekly timeframe, where catching high-probability bottoms is the goal. It combines the Stochastic Oscillator with the Williams VixFix to identify moments of extreme fear and potential reversals.
A Buy signal is triggered when:
Stochastic %K drops below 20
VixFix forms a green spike (suggesting a panic-driven market flush)
A Sell signal is triggered when:
Stochastic %K rises above 90
VixFix falls below 5 (indicating excessive complacency)
Catching tops is much harder than catching bottoms.
These Sell signals are not designed to fully exit positions. Instead, they suggest trimming a small portion of ETF holdings — simply to free up liquidity for future opportunities.
This strategy is ideal for:
Long-term ETF investors
Weekly charts
Systematic decision-making in volatile markets
Use in conjunction with macro indicators, sector rotation, and valuation frameworks for best results.
Missing Candle AnalyzerMissing Candle Analyzer: Purpose and Importance
Overview The Missing Candle Analyzer is a Pine Script tool developed to detect and analyze gaps in candlestick data, specifically for cryptocurrency trading. In cryptocurrency markets, it is not uncommon to observe missing candles—time periods where no price data is recorded. These gaps can occur due to low liquidity, exchange downtime, or data feed issues.
Purpose The primary purpose of this tool is to identify missing candles in a given timeframe and provide detailed statistics about these gaps. Missing candles can introduce significant errors in trading strategies, particularly those relying on continuous price data for technical analysis, backtesting, or automated trading. By detecting and quantifying these gaps, traders can: Assess the reliability of the price data. Adjust their strategies to account for incomplete data. Avoid potential miscalculations in indicators or trade signals that assume continuous candlestick data.
Why It Matters In cryptocurrency trading, where volatility is high and trading decisions are often made in real-time, missing candles can lead to: Inaccurate Technical Indicators : Indicators like moving averages, RSI, or MACD may produce misleading signals if candles are missing. Faulty Backtesting : Historical data with gaps can skew backtest results, leading to over-optimistic or unreliable strategy performance. Execution Errors : Automated trading systems may misinterpret gaps, resulting in unintended trades or missed opportunities.
By using the Missing Candle Analyzer, traders gain visibility into the integrity of their data, enabling them to make informed decisions and refine their strategies to handle such anomalies.
Functionality
The script performs the following tasks: Gap Detection : Identifies time gaps between candles that exceed the expected timeframe duration (with a configurable multiplier for tolerance). Statistics Calculation : Tracks total candles, missing candles, missing percentage, and the largest gap duration. Visualization : Displays a table with analysis results and optional markers on the chart to highlight gaps. User Customization : Allows users to adjust font size, table position, and whether to show gap markers.
Conclusion The Missing Candle Analyzer is a critical tool for cryptocurrency traders who need to ensure the accuracy and completeness of their price data. By highlighting missing candles and providing actionable insights, it helps traders mitigate risks and build more robust trading strategies. This tool is especially valuable in the volatile and often unpredictable cryptocurrency market, where data integrity can directly impact trading outcomes.
Volume Intelligence Suite (VIS) v2📊 Volume Intelligence Suite – Smart Volume, Smart Trading
The Volume Intelligence Suite is a powerful, all-in-one TradingView indicator designed to give traders deeper insight into market activity by visualizing volume behavior with price action context. Whether you're a scalper, day trader, or swing trader, this tool helps uncover hidden momentum, institutional activity, and potential reversals with precision.
🔍 Key Features:
Dynamic Volume Zones – Highlights high and low volume areas to spot accumulation/distribution ranges.
Volume Spikes Detector – Automatically marks abnormal volume bars signaling potential breakout or trap setups.
Smart Delta Highlighting – Compares bullish vs bearish volume in real time to reveal buyer/seller strength shifts.
Session-Based Volume Profiling – Breaks volume into key trading sessions (e.g., London, New York) for clearer context.
Volume Heatmap Overlay – Optional heatmap to show intensity and velocity of volume flow per candle.
Custom Alerts – Built-in alerts for volume surges, divergences, and exhaustion signals.
Optimized for Kill Zone Analysis – Pairs perfectly with ICT-style session strategies and Waqar Asim’s trading methods.
🧠 Why Use Volume Intelligence?
Most traders overlook the story behind each candle. Volume Intelligence Suite helps you "see the why behind the move" — exposing key areas of interest where smart money may be active. Instead of reacting late, this tool puts you in position to anticipate.
Use it to:
Validate breakouts
Detect fakeouts and liquidity grabs
Confirm bias during kill zones
Analyze volume divergence with price swings
⚙️ Fully Customizable:
From volume thresholds to visual styles and session timings, everything is user-adjustable to fit your market, timeframe, and strategy.
✅ Best For:
ICT/Smart Money Concepts (SMC) traders
Breakout & reversal traders
Kill zone session scalpers
Institutional footprint followers
FVG [TakingProphets]🧠 Purpose
This indicator is built for traders applying Inner Circle Trader (ICT) methodology. It detects and manages Fair Value Gaps (FVGs) — price imbalances that often act as future reaction zones. It also highlights New Day Opening Gaps (NDOGs) and New Week Opening Gaps (NWOGs) that frequently play a role in early-session price behavior.
📚 What is a Fair Value Gap?
A Fair Value Gap forms when price moves rapidly, skipping over a portion of the chart between three candles — typically between the high of the first candle and the low of the third. These zones are considered inefficient, meaning institutions may return to them later to:
-Rebalance unfilled orders
-Enter or scale into positions
-Engineer liquidity with minimal slippage
In ICT methodology, FVGs are seen as both entry zones and targets, depending on market structure and context.
⚙️ How It Works
-This script automatically identifies and manages valid FVGs using the following logic:
-Bullish FVGs: When the low of the current candle is above the high from two candles ago
-Bearish FVGs: When the high of the current candle is below the body of two candles ago
-Minimum Gap Filter: Gaps must be larger than 0.05% of price
-Combine Consecutive Gaps (optional): Merges adjacent gaps of the same type
-Consequent Encroachment Line (optional): Plots the midpoint of each gap
-NDOG/NWOG Tracking: Labels gaps created during the 5–6 PM session transition
-Automatic Invalidation: Gaps are removed once price closes beyond their boundary
🎯 Practical Use
-Use unmitigated FVGs as potential entry points or targets
-Monitor NDOG and NWOG for context around daily or weekly opens
-Apply the midpoint (encroachment) line for precise execution decisions
-Let the script handle cleanup — only active, relevant zones remain visible
🎨 Customization
-Control colors for bullish, bearish, and opening gaps
-Toggle FVG borders and midpoint lines
-Enable or disable combining of consecutive gaps
-Fully automated zone management, no manual intervention required
✅ Summary
This tool offers a clear, rules-based approach to identifying price inefficiencies rooted in ICT methodology. Whether used for intraday or swing trading, it helps traders stay focused on valid, active Fair Value Gaps while filtering out noise and maintaining chart clarity.
Central Bank Assets YoY % with StdDev BandsCentral Bank Assets YoY % with StdDev Bands - Indicator Documentation
Overview
This indicator tracks the year-over-year (YoY) percentage change in combined central bank assets using a custom formula. It displays the annual growth rate along with statistical bands showing when the growth is significantly above or below historical norms.
Formula Components
The indicator is based on a custom symbol combining multiple central bank balance sheets:
Federal Reserve balance sheet (FRED)
Bank of Japan assets converted to USD (FX_IDC*FRED)
European Central Bank assets converted to USD (FX_IDC*FRED)
Subtracting Fed reverse repo operations (FRED)
Subtracting Treasury General Account (FRED)
Calculations
Year-over-Year Percentage Change: Calculates the percentage change between the current value and the value from exactly one year ago (252 trading days).
Formula: ((current - year_ago) / year_ago) * 100
Statistical Measures:
Mean (Average): The 252-day simple moving average of the YoY percentage changes
Standard Deviation: The 252-day standard deviation of YoY percentage changes
Display Components
The indicator displays:
Main Line: YoY percentage change (green when positive, red when negative)
Zero Line: Reference line at 0% (gray dashed)
Mean Line: Average YoY change over the past 252 days (blue)
Standard Deviation Bands: Shows +/- 1 standard deviation from the mean
Upper band (+1 StdDev): Green, line with breaks style
Lower band (-1 StdDev): Red, line with breaks style
Interpretation
Values above zero indicate YoY growth in central bank assets
Values below zero indicate YoY contraction
Values above the +1 StdDev line indicate unusually strong growth
Values below the -1 StdDev line indicate unusually severe contraction
Crossing above/below the mean line can signal shifts in central bank policy trends
Usage
This indicator is useful for:
Monitoring global central bank liquidity trends
Identifying unusual periods of balance sheet expansion/contraction
Analyzing correlations between central bank activity and market performance
Anticipating potential market impacts from changes in central bank policy
The 252-day lookback period (approximately one trading year) provides a balance between statistical stability and responsiveness to changing trends in central bank behavior.
Volume Peak RectangleOutlines the 'Latest' Highest Volume Bar. Typically High Volume bars create very good support and resistance levels. This is a draw off the Opening Range Breakout theory, with the idea that high volume candles create very good upper and lower levels of liquidity zones.
