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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.
Pine Script®指標
由EdgeTools提供
3
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.
Pine Script®指標
由Zeiierman提供
12
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.
Pine Script®指標
由simonweisser_business提供
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).
Pine Script®指標
由viharka提供
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
Pine Script®指標
由VolumeVigilante提供
2
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.
Pine Script®指標
由EdgeTools提供
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.
Pine Script®指標
由Takeshi_47提供
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.
Pine Script®指標
由AlphaExtract提供
4
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.
Pine Script®指標
由TradersLifeCommmunity提供
1
[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!
Pine Script®指標
由blackcat1402提供
3
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.
Pine Script®指標
由stairwaytoprofit提供
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.
Pine Script®指標
由Zeiierman提供
2
[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
Pine Script®指標
由blackcat1402提供
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
Pine Script®指標
由TechnoBlooms提供
9
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.
Pine Script®指標
由aldofg提供
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.
Pine Script®指標
由rikyu04提供
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
Pine Script®指標
由Rishabh_btc提供
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.
Pine Script®指標
由TakingProphets提供
3
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.
Pine Script®指標
由luca_badoer提供
[blackcat] L3 Ichimoku FusionCOMPREHENSIVE ANALYSIS OF THE L3 ICHIMOKU FUSION INDICATOR 🌐 Overview: The L3 Ichimoku Fusion is a sophisticated multi-layered technical analysis tool integrating classic Japanese market forecasting techniques with enhanced dynamic elements designed specifically for identifying potential turning points in financial instruments' pricing action. Key Purpose: To provide traders with an intuitive yet powerful framework combining established ichimoku principles while incorporating additional validation checkpoints derived from cross-timeframe convergence studies. THEORETICAL FOUNDATION EXPLAINED 🎓 Conceptual Background: : • Conversion & Base Lines tracking intermediate term averages • Lagging Span providing delayed feedback mechanism • Lead Spans projecting future equilibrium states : • Adaptive parameter scaling options • Automated labeling system for critical junctures • Real-time alert infrastructure enabling immediate response capability PARAMETER CONFIGURATION GUIDE ⚙️ Input Parameters Explained In Detail: Regional Setting Selection:** → Oriental Configuration: Standardized approach emphasizing slower oscillation cycles → Occidental Variation: Optimized settings reducing lag characteristics typical of original methodology Multiplier Adjustment Functionality:** ↔ Allows fine-graining oscillator responsiveness without altering core relationship dynamics ↕ Enables adaptation to various instrument volatility profiles efficiently Displacement Value Control:** ↓ Controls lead/lag offset positioning relative to current prices ↑ Provides flexibility in adjusting visual representation alignment preferences DYNAMIC CALCULATION PROCESSES 💻 Algorithmic Foundation: : Utilizes highest/lowest extremes over specified lookback windows Produces more responsive conversions compared to simple MAs : → Confirms directional bias across multiple independent criteria ← Ensures higher probability outcomes reduce random noise influence : ♾ Creates persistent annotations documenting significant events 🔄 Handles complex state transitions maintaining historical record integrity VISUALIZATION COMPONENTS OVERVIEW 🎨 Display Architecture Details: : → Solid colored trendlines representing conversion/base relationships ↑ Fill effect overlay differentiating expansion/compression phases ↔ Offset spans positioned according to calculated displacement values : → Green shading indicates positive configuration scenarios ↘ Red filling highlights negative arrangement situations ⟳ Orange transition areas mark transitional periods requiring caution : ✔️ LE: Long Entry opportunity confirmed ❌ SE: Short Setup validated ☑ XL/XS: Position closure triggers active ✓ RL/RS: Potential re-entry chances emerging STRATEGIC APPLICATION FRAMEWORK 📋 Practical Deployment Guidelines: Initial Integration Phase: Select appropriate timeframe matching trading horizon preference Configure input parameters aligning with target asset behavior traits Test thoroughly under simulated conditions prior to live usage Active Monitoring Procedures: • Regular observation of cloud formation evolution • Tracking label placements against actual price movements • Noting pattern development leading up to signaled entry/exit moments Decision Making Process Flowchart: → Identify clear breakout/crossover events exceeding confirmation thresholds ← Evaluate contextual factors supporting/rejecting indicated direction ↑ Execute trades only after achieving required number of confirming inputs PERFORMANCE OPTIMIZATION TECHNIQUES 🚀 Refinement Strategies: Calibration Optimization Approach: → Start testing with default suggested configurations ↓ Gradually adjust individual components observing outcome changes ↑ Document findings systematically building personalized version profile Context Adaptability Methods: ➕ Add supplementary indicators enhancing overall reliability ➖ Remove unnecessary complexity layers if causing confusion ✨ Incorporate custom rules adapting to specific security behaviors Efficiency Improvement Tactics: 🔧 Streamline redundant processing routines where possible ♻️ Leverage shared data streams whenever feasible ⚡ Optimize refresh frequencies balancing update speed vs computational load RISK MITIGATION PROTOCOLS 🛡️ Safety Measures Implementation Guide: Position Sizing Principles: ∅ Never exceed preset maximum exposure limits defined by risk tolerance ± Scale positions proportionally per account size/market capitalization × Include slippage allowances within planning stages accounting for liquidity variations Validation Requirements Hierarchy: ☐ Verify signals meet minimum number of concurrent validations ⛔ Ignore isolated occurrences lacking adequate evidence backing ▶ Look for convergent evidence strengthening conviction level Emergency Response Planning: ↩ Establish predefined exit strategies including trailing stops mechanisms 🌀 Plan worst-case scenario responses ahead avoiding panic reactions ⇄ Maintain contingency plans addressing unexpected adverse developments USER EXPERIENCE ENHANCEMENT FEATURES 🌟 Additional Utility Functions: Alert System Infrastructure: → Automatic notifications delivered directly to user devices ↑ Message content customized explaining triggered condition specifics ↔ Timing optimization ensuring minimal missed opportunities due to latency issues Historical Review Capability: → Ability to analyze past performance retrospectively ↓ Assess effectiveness across varying market regimes objectively ↗ Generate statistics measuring success/failure rates quantitatively Community Collaboration Support: ↪ Share personal optimizations benefiting wider trader community ↔ Exchange experiences improving collective understanding base ✍️ Provide constructive feedback aiding ongoing refinement process CONCLUSION AND NEXT STEPS This comprehensive guide serves as your roadmap toward mastering the capabilities offered by the L3 Ichimoku Fusion indicator effectively. Success relies heavily on disciplined application combined with continuous learning and adjustment processes throughout implementation journey. Wishing you prosperous trading endeavors! 👋💰
Pine Script®指標
由blackcat1402提供
Dual-Phase Trend Regime Oscillator (Zeiierman)█ Overview Trend Regime: Dual-Phase Oscillator (Zeiierman) is a volatility-sensitive trend classification tool that dynamically switches between two oscillators, one optimized for low volatility, the other for high volatility. By analyzing standard deviation-based volatility states and applying correlation-derived oscillators, this indicator reveals not only whether the market is trending but also what kind of trend regime it is in —Bullish or Bearish —and how that regime reacts to market volatility. █ Its Uniqueness Most trend indicators assume a static market environment; they don't adjust their logic when the underlying volatility shifts. That often leads to false signals in choppy conditions or late entries in trending phases. Trend Regime: Dual-Phase Oscillator solves this by introducing volatility-aware adaptability. It switches between a slow, stable oscillator in calm markets and a fast, reactive oscillator in volatile ones, ensuring the right sensitivity at the right time. █ How It Works ⚪ Volatility State Engine Calculates returns-based volatility using standard deviation of price change Smooths the current volatility with a moving average Builds a volatility history window and performs median clustering to determine typical "Low" and "High" volatility zones Dynamically assigns the chart to one of two internal volatility regimes: Low or High ⚪ Dual Oscillators In Low Volatility, it uses a Slow Trend Oscillator (longer lookback, smoother) In High Volatility, it switches to a Fast Trend Oscillator (shorter lookback, responsive) Both oscillators use price-time correlation as a measure of directional strength The output is normalized between 0 and 1, allowing for consistent interpretation ⚪ Trend Regime Classification The active oscillator is compared to a neutral threshold (0.5) If above: Bullish Regime, if below: Bearish Regime, else: Neutral The background and markers update to reflect regime changes visually Triangle markers highlight bullish/bearish regime shifts █ How to Use ⚪ Identify Current Trend Regime Use the background color and chart table to immediately recognize whether the market is trending up or down. ⚪ Trade Regime Shifts Use triangle markers (▲ / ▼) to spot fresh regime entries, which are ideal for confirming breakouts within trends. ⚪ Pullback Trading Look for pullbacks when the trend is in a stable condition and the slow oscillator remains consistently near the upper or lower threshold. Watch for moments when the fast oscillator retraces back toward the midline, or slightly above/below it — this often signals a potential pullback entry in the direction of the prevailing trend. █ Settings Explained Length (Slow Trend Oscillator) – Used in calm conditions. Longer = smoother signals Length (Fast Trend Oscillator) – Used in volatile conditions. Shorter = more responsive Volatility Refit Interval – Controls how often the system recalculates Low/High volatility levels Current Volatility Period – Lookback used for immediate volatility measurement Volatility Smoothing Length – Applies an SMA to the raw volatility to reduce noise ----------------- 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.
Pine Script®指標
由Zeiierman提供
6
[blackcat] L3 Dynamic CrossOVERVIEW The L3 Dynamic Cross indicator is a powerful tool designed to assist traders in identifying potential buy and sell opportunities through the use of dynamic moving averages. This versatile script offers a wide range of customizable options, allowing users to tailor the moving averages to their specific needs and preferences. By providing clear visual cues and generating precise crossover signals, it helps traders make informed decisions about market trends and potential entry/exit points 📈💹. FEATURES Multiple Moving Average Types: Simple Moving Average (SMA): Provides a straightforward average of prices over a specified period. Exponential Moving Average (EMA): Gives more weight to recent prices, making it responsive to new information. Weighted Moving Average (WMA): Assigns weights to all prices within the look-back period, giving more importance to recent prices. Volume Weighted Moving Average (VWMA): Incorporates volume data to provide a more accurate representation of price movements. Smoothed Moving Average (SMMA): Averages out fluctuations to create a smoother trend line. Double Exponential Moving Average (DEMA): Reduces lag by applying two layers of exponential smoothing. Triple Exponential Moving Average (TEMA): Further reduces lag with three layers of exponential smoothing. Hull Moving Average (HullMA): Combines weighted moving averages to minimize lag and noise. Super Smoother Moving Average (SSMA): Uses a sophisticated algorithm to smooth out price data while preserving trend direction. Zero-Lag Exponential Moving Average (ZEMA): Eliminates lag entirely by adjusting the calculation method. Triangular Moving Average (TMA): Applies a double smoothing process to reduce volatility and enhance trend identification. Customizable Parameters: Length: Adjust the period for both fast and slow moving averages to match your trading style. Source: Select different price sources such as close, open, high, or low for more nuanced analysis. Visual Representation: Fast MA: Displayed as a green line representing shorter-term trends. Slow MA: Shown as a red line indicating longer-term trends. Crossover Signals: Generate buy ('BUY') and sell ('SELL') labels based on crossover events between the fast and slow moving averages 🏷️. Clear visual cues help traders quickly identify potential entry and exit points. Alert Functionality: Receive real-time notifications when crossover conditions are met, ensuring timely action 🔔. Customizable alert messages for personalized trading strategies. Advanced Trade Management: Support for pyramiding levels allows traders to manage multiple positions effectively. Fine-tune your risk management by setting the number of allowed trades per signal. HOW TO USE Adding the Indicator: Open your TradingView chart and go to the indicators list. Search for L3 Dynamic Cross and add it to your chart. Configuring Settings: Choose your desired Moving Average Type from the dropdown menu. Adjust the Fast MA Length and Slow MA Length according to your trading timeframe. Select appropriate Price Sources for both fast and slow moving averages. Monitoring Signals: Observe the plotted lines on the chart to track short-term and long-term trends. Look for buy and sell labels that indicate potential trade opportunities. Setting Up Alerts: Enable alerts based on crossover conditions to receive instant notifications. Customize alert messages to suit your trading plan. Managing Positions: Utilize the pyramiding feature to handle multiple entries and exits efficiently. Keep track of your position sizes relative to the defined pyramiding levels. Combining with Other Tools: Integrate this indicator with other technical analysis tools for confirmation. Use additional filters like volume, RSI, or MACD to enhance decision-making accuracy. LIMITATIONS Market Conditions: The effectiveness of the indicator may vary in highly volatile or sideways markets. Be cautious during periods of low liquidity or sudden price spikes 🌪️. Parameter Sensitivity: Different moving average types and lengths can produce varying results. Experiment with settings to find what works best for your asset class and timeframe. False Signals: Like any technical indicator, false signals can occur. Always confirm signals with other forms of analysis before executing trades. NOTES Historical Data: Ensure you have enough historical data loaded into your chart for accurate moving average calculations. Backtesting: Thoroughly backtest the indicator on various assets and timeframes using demo accounts before deploying it in live trading environments 🔍. Customization: Feel free to adjust colors, line widths, and label styles to better fit your chart aesthetics and personal preferences. EXAMPLE STRATEGIES Trend Following: Use the indicator to ride trends by entering positions when the fast MA crosses above/below the slow MA and exiting when the opposite occurs. Mean Reversion: Identify overbought/oversold conditions by combining the indicator with oscillators like RSI or Stochastic. Enter counter-trend positions when the moving averages diverge significantly from the mean. Scalping: Apply tight moving average settings to capture small, quick profits in intraday trading. Combine with volume indicators to filter out weak signals.
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