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OG TTM Histogram [Elite Edition] © 2025🧠 OG TTM Histogram Elite © 2025 | by OG WEALTH™ Built for sniper entries, this enhanced TTM Squeeze indicator includes: • 🎯 Histogram Momentum Bars (Smoothed) • ⚫ Black Dots = Squeeze Building (tight coil) • 🟢 Green Dots = Squeeze Released (entry zone forming) • 🔺/🔻 Entry Arrows based on Momentum + MTF Confirmation • ⏱️ Customizable MTF Settings • 🏷️ Compact Top-Right Squeeze Status Tag • 🔔 Audio + Push Alerts for all major signals Perfect for SPY, TSLA, AAPL, and crypto breakout traders. Ideal for scalping, intraday, and swing strategies.
Penunjuk Pine Script®
oleh OG_Wealth
Yelober - Sector Rotation Detector# Yelober - Sector Rotation Detector: User Guide ## Overview The Yelober - Sector Rotation Detector is a TradingView indicator designed to track sector performance and identify market rotations in real-time. It monitors key sector ETFs, calculates performance metrics, and provides actionable stock recommendations based on sector strength and weakness. ## Purpose This indicator helps traders identify when capital is moving from one sector to another (sector rotation), which can provide valuable trading opportunities. It also detects risk-off conditions in the market and highlights sectors with abnormal trading volume. ## Table Columns Explained ### 1. Sector Displays the sector name being monitored. The indicator tracks six primary sectors plus the S&P 500: - Energy (XLE) - Financial (XLF) - Technology (XLK) - Consumer Staples (XLP) - Utilities (XLU) - Consumer Discretionary (XLY) - S&P 500 (SPY) ### 2. Perf % Shows the daily percentage performance of each sector ETF. Values are color-coded: - Green: Positive performance - Red: Negative performance Positive values display with a "+" sign (e.g., +1.25%) ### 3. RSI Displays the Relative Strength Index value for each sector, which helps identify overbought or oversold conditions: - Values above 70 (highlighted in red): Potentially overbought - Values below 30 (highlighted in green): Potentially oversold - Values between 30-70 (highlighted in blue): Neutral territory ### 4. Vol Ratio Shows the volume ratio, which compares today's volume to the average volume over the lookback period: - Values above 1.5x (highlighted in yellow): Indicates abnormally high trading volume - Values below 1.5x (highlighted in blue): Normal trading volume This helps identify sectors with unusual activity that may signal important price movements. ### 5. Trend Displays the current price trend direction with symbols: - ▲ (green): Uptrend (today's close > yesterday's close) - ▼ (red): Downtrend (today's close < yesterday's close) - ◆ (gray): Neutral (today's close = yesterday's close) ## Summary & Recommendations Section The summary section provides: 1. **Sector Rotation Detection**: Identifies when there's a significant performance gap (>2%) between the strongest and weakest sectors. 2. **Risk-Off Mode Detection**: Alerts when defensive sectors (Consumer Staples and Utilities) are positive while Technology is negative, which often signals investors are moving to safer assets. 3. **Strong Volume Detection**: Indicates when any sector shows abnormally high trading volume. 4. **Stock Recommendations**: Suggests specific stocks to consider for long positions (from the strongest sectors) and short positions (from the weakest sectors). ## Example Interpretations ### Example 1: Sector Rotation If you see: - Technology: -1.85% - Financial: +2.10% - Summary shows: "SECTOR ROTATION DETECTED: Rotation from Technology to Financial" **Interpretation**: Capital is moving out of tech stocks and into financial stocks. This could be due to rising interest rates, which typically benefit banks while pressuring high-growth tech companies. Consider looking at financial stocks like JPM, BAC, and WFC for potential long positions. ### Example 2: Risk-Off Conditions If you see: - Consumer Staples: +0.80% - Utilities: +1.20% - Technology: -1.50% - Summary shows: "RISK-OFF MODE DETECTED" **Interpretation**: Investors are seeking safety in defensive sectors while selling growth-oriented tech stocks. This often occurs during market uncertainty or ahead of economic concerns. Consider reducing exposure to high-beta stocks and possibly adding defensive names like PG, KO, or NEE. ### Example 3: Volume Spike If you see: - Energy: +3.20% with Volume Ratio 2.5x (highlighted in yellow) - Summary shows: "STRONG VOLUME DETECTED" **Interpretation**: The energy sector is making a strong move with significantly higher-than-average volume, suggesting conviction behind the price movement. This could indicate the beginning of a sustained trend in energy stocks. Consider names like XOM, CVX, and COP. ## How to Use the Indicator 1. Apply the indicator to any chart (works best on daily timeframes). 2. Customize settings if needed: - Timeframe: Choose between intraday (60 or 240 minutes), daily, or weekly - Lookback Period: Adjust the historical comparison period (default: 20) - RSI Period: Modify the RSI calculation period (default: 14) 3. To refresh the data: Click the settings icon, increase the "Click + to refresh data" counter, and click "OK". 4. Identify opportunities based on sector performance, RSI levels, volume ratios, and the summary recommendations. This indicator helps traders align with market rotation trends and identify which sectors (and specific stocks) may outperform or underperform in the near term.
Penunjuk Pine Script®
oleh yelober
7
SHYY TFC SPX Sectors list This script provides a clean, configurable table displaying real-time data for the major SPX sectors, key indices, and market sentiment indicators such as VIX and the 10-year yield (US10Y). It includes 16 columns with two rows: * The top row shows the sector/asset symbol. * The bottom row shows the most recent daily close price. Each price cell is dynamically color-coded based on: * Direction (green/red) during regular trading hours * Separate colors during extended hours (pre-market or post-market) * VIX values greater than 30 trigger a distinct background highlight Users can fully control the position of the table on the chart via input settings. This flexibility allows traders to place the table in any screen corner or center without overlapping key price action. The script is designed for: * Monitoring broad market health at a glance * Understanding sector performance in real-time * Spotting risk-on/risk-off behavior (via SPY, QQQ, VIX, US10Y) Unlike traditional watchlists, this table visually encodes directional movement and trading session context (regular vs. extended hours), making it highly actionable for intraday, swing, or macro-level analysis. All data is pulled using `request.security()` on daily candles and uses pure Pine logic without external dependencies. To use: 1. Add the indicator to your chart. 2. Adjust the table position via the input dropdown. 3. Read sector strength or weakness directly from the table.
Penunjuk Pine Script®
oleh shayy110
Options Betting Range - FixedOptions Betting Range Options Betting Range is a powerful TradingView indicator designed to streamline options trading by visualizing high-probability price ranges for key symbols. With automated trendlines and clear labels, it empowers traders to make precise, data-driven decisions based on customizable prediction and execution dates. ## Key Features Broad S&P 500 Coverage: Supports most S&P 500 stock symbols, excluding those with insufficient options volume for reliable data, alongside major ETFs and indices like SPY, IWM, QQQ, DIA, TLT, ^GSPC, ^IXIC, ^RUT, ^NDX, and ^SOX. Automated Trendlines: Plots dashed and solid trendlines to mark high/low price boundaries, triggered only on specified prediction dates for clean, uncluttered charts. Customizable Inputs: Configure prediction and execution dates to align with your trading strategy. Clear Visuals: Color-coded labels (green for highs, purple for lows) display price ranges and percentage spreads for rapid decision-making. Single-Execution Logic: Draws trendlines once per prediction date, ensuring chart clarity and efficiency. ## How It Works Based on the latest daily open interest data, the indicator calculates swing ranges for different strike dates, drawing trendlines and labels to visualize potential price boundaries for options trading. ## Why Use It? Streamlined Analysis: Automates range visualization, saving time and reducing manual charting. Strategic Clarity: Objective price levels minimize emotional bias and enhance trade planning. Versatile Application: Ideal for day traders, swing traders, and options strategists across multiple markets. ## Tips for Best Use Regular Updates: To maintain the accuracy of options betting ranges, periodically update the indicator. On the view page, hover over the indicator name and click the blue whirlwind icon to complete the update. ## Get Started Add Options Betting Range to your TradingView chart, select a supported symbol, and customize your prediction/execution dates. Leverage the visualized price ranges to execute precise options trading strategies with confidence.
Penunjuk Pine Script®
oleh dragonjia
BBS – Bond Breadth Signal"When bonds scream, breadth collapses, and fear spikes — BBS listens." 🧠 BBS – Bond Breadth Signal A reversal timing tool built on macro conviction, not price noise. The Bond Breadth Signal (BBS) was developed to identify major market inflection points by combining four key market stress indicators: 1) 10-Year Yield ROC – Measures sharp moves in the bond market 2) Z-Score of the 10Y – Captures statistical extremes 3) NSHF (Net Highs–Lows) – Signals internal market strength or weakness 4) TLT ROC + VIX – Confirmations of flight to safety and volatility-driven fear When all conditions align, BBS marks either a For-Sure Buy or For-Sure Sell — these are rare, high-confidence signals designed to cut through noise and focus on true market dislocations. 🔧 Features: -Background color and signal arrows on confirmation days -Signals remain visually active for 3 days for added clarity -Fully adjustable thresholds and alert toggles -Plot panel for yield, TLT, NSHF, VIX, and Z-score visuals This tool isn’t designed to fire every day. It’s meant to wait for those moments when the market truly bends — not just wiggles. Best used on major indices (SPY, QQQ, IWM) to assess macro turning points.
Penunjuk Pine Script®
oleh Scatman_Jeff
$ADD LevelsThis Pine Script is designed to track and visualize the NYSE Advance-Decline Line (ADD). The Advance-Decline Line is a popular market breadth indicator, showing the difference between advancing and declining stocks on the NYSE. It’s often used to gauge overall market sentiment and strength. 1. //@version=5 This line tells TradingView to use Pine Script v5, the latest and most powerful version of Pine. 2. indicator(" USI:ADD Levels", overlay=false) • This creates a new indicator called ” USI:ADD Levels”. • overlay=false means it will appear in a separate pane, not on the main price chart. 3. add = request.security(...) This fetches real-time data from the symbol USI:ADD (Advance-Decline Line) using a 1-minute timeframe. You can change the timeframe if needed. add_symbol = input.symbol(" USI:ADD ", "Market Breadth Symbol") add = request.security(add_symbol, "1", close) 4. Key Thresholds These define the market sentiment zones: Zone. Value. Meaning Overbought +1500 Extremely bullish Bullish +1000 Generally bullish trend Neutral ±500 Choppy, unclear market Bearish -1000 Generally bearish trend Oversold -1500 Extremely bearish 5. Plot the ADD Line hline(...) Draws static lines at +1500, +1000, +500, -500, -1000, -1500 for reference so you can visually assess where ADD stands. 6. Horizontal Threshold Lines bgcolor(...) • Green background if ADD > +1500 → extremely bullish. • Red background if ADD < -1500 → extremely bearish. 7. Background Highlights alertcondition(...) • Green background if ADD > +1500 → extremely bullish. • Red background if ADD < -1500 → extremely bearish. 8. Alert Conditions. alertcondition(...) Lets you create automatic alerts for: • USI:ADD being very high or low. • Crosses above +1000 (bullish trigger). • Crosses below -1000 (bearish trigger). You can use these to trigger trades or monitor sentiment shifts. Summary: When to Use It • Use this script in a market breadth dashboard. • Combine it with price action and volume analysis. • Monitor for ADD crosses to signal potential market reversals or momentum.
Penunjuk Pine Script®
oleh Iskymanusa
RRC Sniper SetupRRC Sniper Setup, this looks at candles this way: Go to Market Scanner Create New Scan → "RRC Sniper Setup" Add filters listed below with timeframe logic (e.g. 1m/5m) Run scan on: Your Watchlist SPY 500 QQQ 100 AI/Momentum names 1. Reclaim Filter Find price breaking back above a key level (VWAP or EMA113) Last 1m Close > EMA 113 (1m) OR Last 5m Close > VWAP 2. Retrace Filter Price pulls back into the zone and holds within a tight range Current Price < VWAP * 1.0025 AND Current Price > VWAP * 0.9975 AND Volume (Current Candle) < Volume (Previous Candle) ✅ 3. Confirm Filter Price begins moving back up with confirmation candle and volume Last Candle Close > Last Candle Open AND Volume (Current Candle) > Volume (Previous Candle)
Penunjuk Pine Script®
oleh Gimmedatgamma
Multi-Session ORBThe Multi-Session ORB Indicator is a customizable Pine Script (version 6) tool designed for TradingView to plot Opening Range Breakout (ORB) levels across four major trading sessions: Sydney, Tokyo, London, and New York. It allows traders to define specific ORB durations and session times in Central Daylight Time (CDT), making it adaptable to various trading strategies. Key Features: 1. Customizable ORB Duration: Users can set the ORB duration (default: 15 minutes) via the inputMax parameter, determining the time window for calculating the high and low of each session’s opening range. 2. Flexible Session Times: The indicator supports user-defined session and ORB times for: ◦ Sydney: Default ORB (17:00–17:15 CDT), Session (17:00–01:00 CDT) ◦ Tokyo: Default ORB (19:00–19:15 CDT), Session (19:00–04:00 CDT) ◦ London: Default ORB (02:00–02:15 CDT), Session (02:00–11:00 CDT) ◦ New York: Default ORB (08:30–08:45 CDT), Session (08:30–16:00 CDT) 3. Session-Specific ORB Levels: For each session, the indicator calculates and tracks the high and low prices during the specified ORB period. These levels are updated dynamically if new highs or lows occur within the ORB timeframe. 4. Visual Representation: ◦ ORB high and low lines are plotted only during their respective session times, ensuring clarity. ◦ Each session’s lines are color-coded for easy identification: ▪ Sydney: Light Yellow (high), Dark Yellow (low) ▪ Tokyo: Light Pink (high), Dark Pink (low) ▪ London: Light Blue (high), Dark Blue (low) ▪ New York: Light Purple (high), Dark Purple (low) ◦ Lines are drawn with a linewidth of 2 and disappear when the session ends or if the timeframe is not intraday (or exceeds the ORB duration). 5. Intraday Compatibility: The indicator is optimized for intraday timeframes (e.g., 1-minute to 15-minute charts) and only displays when the chart’s timeframe multiplier is less than or equal to the ORB duration. How It Works: • Session Detection: The script uses the time() function to check if the current bar falls within the user-defined ORB or session time windows, accounting for all days of the week. • ORB Logic: At the start of each session’s ORB period, the script initializes the high and low based on the first bar’s prices. It then updates these levels if subsequent bars within the ORB period exceed the current high or fall below the current low. • Plotting: ORB levels are plotted as horizontal lines during the respective session, with visibility controlled to avoid clutter outside session times or on incompatible timeframes. Use Case: Traders can use this indicator to identify key breakout levels for each trading session, facilitating strategies based on price action around the opening range. The flexibility to adjust ORB and session times makes it suitable for various markets (e.g., forex, stocks, or futures) and time zones. Limitations: • The indicator is designed for intraday timeframes and may not display on higher timeframes (e.g., daily or weekly) or if the timeframe multiplier exceeds the ORB duration. • Time inputs are in CDT, requiring users to adjust for their local timezone or market requirements. • If you need to use this for GC/CL/SPY/QQQ you have to adjust the times by one hour. This indicator is ideal for traders focusing on session-based breakout strategies, offering clear visualization and customization for global market sessions.
Penunjuk Pine Script®
oleh Eskemo_Bob
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.
Penunjuk Pine Script®
oleh EdgeTools
3
VWAP Adaptive (RelVol-Adjusted)This indicator provides an Adaptive VWAP that adjusts volume weighting using RelVol (Relative Volume at Time), offering a more accurate and context-aware price reference during sessions with irregular volume behavior. Classic VWAP calculates the average price weighted by raw volume, without considering the time of day. This becomes a serious limitation during major market events such as CPI releases, FOMC announcements, NFP, or large-cap earnings. These events often trigger massive volume spikes within one or two candles. As a result, the classic VWAP gets pulled toward those extreme prices and becomes permanently skewed for the rest of the session. In such conditions, classic VWAP becomes unreliable. It no longer reflects fair value and often misleads traders relying on it for dynamic support, resistance, or reversion signals. This Adaptive VWAP improves on that by using RelVol, which compares the current volume to the average volume seen at the same time over previous sessions. It gives more weight to price when volume is typical for that moment, and adjusts the influence when volume is statistically abnormal. This reduces the impact of isolated volume spikes and stabilizes the VWAP path, even in high-volatility environments. For example, on SPY 1-minute or 5-minute charts during a CPI release, a massive spike in volume and price can occur within a single candle. Classic VWAP will immediately anchor itself to that spike. Adaptive VWAP using RelVol softens that effect and maintains a more realistic trajectory. Key features: - Adaptive VWAP weighted by time-adjusted Relative Volume (RelVol) - Designed to maintain VWAP reliability during macroeconomic events - Flexible anchoring: Session, Week, Month, Quarter, Earnings, etc. - Optional display of Classic VWAP for comparison - Up to 3 customizable deviation bands (standard deviation or percentage) This tool is ideal for intraday traders who need a VWAP that remains usable and unbiased, even in volatile sessions. It adds robustness to VWAP-based strategies by incorporating time-sensitive volume normalization.
Penunjuk Pine Script®
oleh Julien_Eche
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.
Penunjuk Pine Script®
oleh EdgeTools
Market Warning Dashboard Enhanced📊 Market Warning Dashboard Enhanced A powerful macro risk dashboard that tracks and visualizes early signs of market instability across multiple key indicators—presented in a clean, professional layout with a real-time thermometer-style danger gauge. 🔍 Included Macro Signals: Yield Curve Inversion: 10Y-2Y and 10Y-3M spreads Credit Spreads: High-yield (HYG) vs Investment Grade (LQD) Volatility Structure: VIX/VXV ratio Breadth Estimate: SPY vs 50-day MA (as a proxy) 🔥 Features: Real-time Danger Score: 0 (Safe) to 100 (Extreme Risk) Descriptive warnings for each signal Color-coded thermometer gauge Alert conditions for each macro risk Background shifts on rising systemic risk ⚠️ This dashboard can save your portfolio by alerting you to macro trouble before it hits the headlines—ideal for swing traders, long-term investors, and anyone who doesn’t want to get blindsided by systemic risk.
Penunjuk Pine Script®
oleh StonkJuicer
Anchored Bollinger Band Range [SS]This is the anchored Bollinger band indicator. What it does? The anchored BB indicator: Takes a user defined range and calculates the Standard Deviation of the entire selected range for the high and low values. Computes a moving average of the high and low during the selected period (which later becomes the breakout range average) Anchors to the last high and last low of the period range to add up to 4 standard deviations to the upside and downside, giving you 4 high and low targets. How can you use it? The anchored BB indicator has many applicable uses, including Identifying daily ranges based on premarket trading activity ( see below ): Finding breakout ranges for intraday pattern setups ( see below ): Identified pattern of interest: Applying Anchored BB: Identifying daily or pattern biases based on the position to the opening breakout range average (blue line). See the examples with explanations: ex#1: ex#2: The Opening Breakout Average As you saw in the examples above, the blue line represents the opening breakout range average. This is the average high of the period of interest and the average low of the period of interest. Price action above this line would be considered Bullish, and Bearish if below. This also acts as a retracement zone in non-trending markets. For example: Best Use Cases Identify breakout ranges for patterns on larger timeframes. For example This pattern on SPY, if we overlay the Anchored BB: You want to see it actually breakout from this range and hold to confirm a breakout. Failure to exceed the BB range, means that it is just ranging with no real breakout momentum. Identify conservative ranges for a specific period in time, for example QQQ: Worst Use Cases Using it as a hard and fast support and resistance indicator. This is not what it is for and ranges can be exceeded with momentum. The key is looking for whether ranges are exceeded (i.e. high momentum, thus breakout play) or they are not (thus low volume, rangy). Using it for longer term outlooks. This is not ideal for long term ranges, as with any Bollinger/standard deviation based approach, it is only responsive to CURRENT PA and cannot forecast FUTURE PA. User Inputs The indicator is really straight forward. There are 2 optional inputs and 1 required input. Period Selection: Required. Selects the period for the indicator to perform the analysis on. You just select it with your mouse on the chart. Visible MA: Optional. You can choose to have the breakout range moving average visible or not. Fills: Optional. You can choose to have the fills plotted or not. And that is the indicator! Very easy to use and hope you enjoy and find it helpful! As always, safe trades everyone! 🚀
Penunjuk Pine Script®
oleh Steversteves
7
Horizontal Price TableOverview: This script displays a dynamic price table on your chart, showing real-time prices and daily percentage changes for up to 7 user-defined tickers. You can customize both which tickers are shown and how many are visible, all through the settings panel. How it works (Step-by-Step): User-Defined Tickers: The script provides input fields for up to 7 tickers using input.symbol(). You can track stocks, indexes, ETFs, crypto, or futures — anything supported by TradingView. Choose How Many to Display: An additional dropdown lets you choose how many of the 7 tickers to actually display (between 1 and 7). This gives you control over screen space and focus. Market Data Fetching: For each displayed ticker, the script fetches: The current day’s closing price (close) The previous day’s closing price (close ) This data is pulled using request.security() on the daily timeframe (1D). % Change Calculation: The script calculates the daily percentage change using: (Current Price−Previous Close)/Previous Close×100(Current Price−Previous Close)/Previous Close×100 Cleaned Ticker Names: Ticker symbols often include an exchange prefix like NASDAQ:AAPL. The script automatically removes anything before the colon (:), so only the clean symbol (e.g., AAPL) is shown in the table. Table Display: A visual table appears at the top-center of your chart, showing: Row 1: Ticker symbol (cleaned) Row 2: Current price (rounded to 2 decimals) Row 3: Daily % change (green for gains, red for losses) Customization: You can choose the background color of the table. Ticker names appear in white text with a gray background. % change is color-coded: green for positive, red for negative. Why Use This Script? Track multiple tickers at once without leaving your chart. Clean, customizable layout. Useful for monitoring watchlists, portfolios, or related markets. Tips: Combine this with your favorite indicators for a personalized dashboard. Works great on any chart or timeframe. Ensure the tickers entered are valid on TradingView (e.g., SPY, BTCUSD, NQ1!, etc.).
Penunjuk Pine Script®
oleh PWSTrades
Compare Strength with SLOPE Description This indicator compares the relative strength between the current asset and a benchmark (e.g., BTC vs. ETH or AAPL vs. SPY) using a linear regression slope of their ratio over time. The ratio is calculated as: close / benchmark A linear regression slope is computed over a user-defined window The slope represents trend strength: if it’s rising, the current asset is outperforming the benchmark Plots Gray Line: The raw ratio between the asset and benchmark Orange Line: The slope of the ratio (shows momentum) Background Color : Green: The asset is significantly stronger than the benchmark Red: The asset is significantly weaker than the benchmark No color: No clear trend Settings Slope Window Length: Number of candles used in the regression (default = 10) Slope Threshold: Sensitivity of trend detection. Smaller values detect weaker trends. Example Use Cases Style Rotation Strategy: Use the slope to determine whether "Growth" or "Value" style is leading. Pair Trading / Relative Performance: Track which asset is leading in a pair (e.g., BTC vs ETH). Factor Timing: Serve as a timing model to allocate between different sectors or factors. Happy trading!
Penunjuk Pine Script®
oleh martinivon
Leavitt Convolution ProbabilityTechnical Analysis of Markets with Leavitt Market Projections and Associated Convolution Probability The aim of this study is to present an innovative approach to market analysis based on the research "Leavitt Market Projections." This technical tool combines one indicator and a probability function to enhance the accuracy and speed of market forecasts. Key Features Advanced Indicators : the script includes the Convolution line and a probability oscillator, designed to anticipate market changes. These indicators provide timely signals and offer a clear view of price dynamics. Convolution Probability Function : The Convolution Probability (CP) is a key element of the script. A significant increase in this probability often precedes a market decline, while a decrease in probability can signal a bullish move. The Convolution Probability Function: At each bar, i, the linear regression routine finds the two parameters for the straight line: y=mi​x+bi​. Standard deviations can be calculated from the sequence of slopes, {mi​}, and intercepts, {bi​}. Each standard deviation has a corresponding probability. Their adjusted product is the Convolution Probability, CP. The construction of the Convolution Probability is straightforward. The adjusted product is the probability of one times 1− the probability of the other. Customizable Settings : Users can define oversold and overbought levels, as well as set an offset for the linear regression calculation. These options allow for tailoring the script to individual trading strategies and market conditions. Statistical Analysis : Each analyzed bar generates regression parameters that allow for the calculation of standard deviations and associated probabilities, providing an in-depth view of market dynamics. The results from applying this technical tool show increased accuracy and speed in market forecasts. The combination of Convolution indicator and the probability function enables the identification of turning points and the anticipation of market changes. Additional information: Leavitt, in his study, considers the SPY chart. When the Convolution Probability (CP) is high, it indicates that the probability P1​ (related to the slope) is high, and conversely, when CP is low, P1​ is low and P2 is high. For the calculation of probability, an approximate formula of the Cumulative Distribution Function (CDF) has been used, which is given by: CDF(x)=21​(1+erf(σ2​x−μ​)) where μ is the mean and σ is the standard deviation. For the calculation of probability, the formula used in this script is: 0.5 * (1 + (math.sign(zSlope) * math.sqrt(1 - math.exp(-0.5 * zSlope * zSlope)))) Conclusions This study presents the approach to market analysis based on the research "Leavitt Market Projections." The script combines Convolution indicator and a Probability function to provide more precise trading signals. The results demonstrate greater accuracy and speed in market forecasts, making this technical tool a valuable asset for market participants.
Penunjuk Pine Script®
oleh dPEngineering
Bottom and Top finder [theUltimator5]🧭 Bottom and Top Finder — Multi-Symbol Momentum Divergence Detector The Bottom and Top Finder by theUltimator5 is a highly configurable, momentum-based indicator designed to identify potential market reversal points using a multi-symbol relative strength comparison framework. It evaluates Directional Movement Index (DMI) values from up to three correlated or macro-influential assets to determine when the current instrument may be approaching a bottom (oversold exhaustion) or a top (overbought exhaustion). 🧠 How It Works This script computes both the +DI (positive directional index) and -DI (negative directional index) for: The currently selected chart symbol Up to three user-defined reference symbols (e.g., sector leaders, macro ETFs, currencies, volatility proxies) It uses a logarithmic percent-change approach to normalize all movement metrics, ensuring results are scale-invariant and price-neutral — meaning it works consistently whether a stock trades at $1 or $100,000. This makes the comparison between different assets meaningful, even if they trade on different scales or volatility levels. The indicator then: Compares the +DI values of the reference symbols to the current symbol’s +DI → seeking bottoming signals (suggesting the current symbol is unusually weak). Compares the -DI values of the reference symbols to the current symbol’s -DI → seeking topping signals (suggesting the current symbol is unusually strong on the downside). These comparisons are aggregated using a weighted average, where you control the influence (multiplier) of each reference symbol. 🔁 Trigger Logic The indicator generates two dynamic lines: Bot Line (Bottom Line): Based on reference +DI vs. current +DI Top Line: Based on reference -DI vs. current -DI If the Bot Line rises above the user-defined threshold, it may signal that capitulation or oversold conditions are developing. Similarly, if the Top Line rises above its threshold, it may indicate a blow-off top or overbought selling pressure. To avoid false positives, a second smoothing-based condition must also be met: The line must significantly exceed its moving average, confirming momentum divergence. When both conditions are true, the indicator highlights the background in light red (bottom alert) or green (top alert) for easy visual scanning. 🔧 Key Inputs & Customization You can fine-tune this tool using the following parameters: Smoothing Length: Controls how smooth or sensitive the DI values are. Reference Symbols: Up to 3 assets (default: RSP, HYG, DXY) — customizable for sector, macro, or inverse relationships. Influence Multipliers: Adjust the weight each symbol has on the overall signal. Display Options: Toggle to highlight the chart background during trigger conditions. Toggle to display a real-time table of reference symbols and their influence levels. 📈 Visual Output Two plotted lines: One for bottoms and one for tops Dynamically colored based on how far they exceed thresholds Background highlights to mark trigger zones Optional table displaying the current reference symbol setup and weights 🛠 Best Use Cases This tool is ideal for: Identifying short-term tops or bottoms using momentum exhaustion Spotting divergences between an asset and broader market or sector health Macro analysis with assets like SPY, QQQ, GME, MSFT, BTC, etc... Pair trading signals or market breadth confirmation/disagreement It complements other technical indicators like RSI, MACD, Bollinger Bands, or price structure patterns (double bottoms/tops, etc.)
Penunjuk Pine Script®
oleh TheUltimator5
2
Risk-On vs Risk-Off Meter (Pro)Risk-On vs Risk-Off Meter (Pro) This macro-based tool analyzes capital flows across key assets to gauge overall market risk sentiment. It does not use ES, SPY, or stock data directly—making it a powerful confirmation tool for ES traders looking to align with macro forces. 🔹 Core Idea: Tracks capital rotation between copper/gold, bonds, dollar, crude oil, VIX, and yield spreads to generate a normalized risk score (0–1). This score reflects whether macro money is flowing into risk or safety. 🔹 Use: Use this indicator as confirmation of directional bias when scalping or day trading ES. – Green Zone (>0.75): Risk-On environment. Favor long setups. – Red Zone (<0.45): Risk-Off. Favor short setups or stand aside. – Yellow Zone: Neutral, use caution. – Divergence Alerts: Signals when ES price disagrees with macro risk trend—potential reversals or exhaustion zones. HOT TO USE – Combine with your existing price action or order flow signals – Avoid trading against the macro sentiment unless strong setup – Use divergence as a heads-up for fading or exiting trades This gives you a macro-informed lens to validate or filter your entries.
Penunjuk Pine Script®
oleh MindfulMarkets
Econometrica by [SS]This is Econometrica, an indicator that aims to bridge a big gap between the resources available for analysis of fundamental data and its impact on tickers and price action. I have noticed a general dearth of available indicators that offer insight into how fundamentals impact a ticker and provide guidance on how they these economic factors influence ticker behaviour. Enter Econometrica. Econometrica is a math based indicator that aims to co-integrate and model indicator price action in relation to critical economic metrics. Econometrica supports the following US based economic data: CPI Non-Farm Payroll Core Inflation US Money Supply US Central Bank Balance Sheet GDP PCE Let's go over the functions of Econometrica. Creating a Regression Cointegrated Model The first thing Econometrica does is creates a co-integrated regression, as you see in the main chart, predicting ticker value ranges from fundamental economic data. You can visualize this in the main chart above, but here are some other examples: SPY vs Core Inflation: BA vs PCE: QQQ vs US Balance Sheet: The band represents the anticipated range the ticker should theoretically fall in based on the underlying economic value. The indicator will breakdown the relationship between the economic indicator and the ticker more precisely. In the images above, you can see how there are some metrics provided, including Stationairty, lagged correlation, Integrated Correlation and R2. Let's discuss these very briefly: Stationarity: checks to ensure that the relationship between the economic indicator and ticker is stationary. Stationary data is important for making unbiased inferences and projections, so having data that is stationary is valuable. Lagged Correlation: This is a very interesting metric. Lagged correlation means whether there is a delay in the economic indicator and the response of the ticker. Typically, you will observed a lagged correlation between an economic indicator and price of a ticker, as it can take some time for economic changes to reach the market. This lagged correlation will provide you with how long it takes for the economic indicator to catch up with the ticker in months. Integrated Correlation: This metric tells you how good of a fit the regression bands are in relation to the ticker price. A higher correlation, means the model is better at consistent and accurate information about the anticipated range for the ticker in relation to the economic indicator. R2: Provides information on the variance and degree of model fit. A high R2 value means that the model is capable of explaining a large amount of variance between the economic indicator and the ticker price action. Explaining the Relationship Owning to the fact that the indicator is a bit on the mathy side (it has to be to do this kind of task), I have included ability for the indicator to explain and make suggestions based on the underlying data. It can assess the model's fit and make suggestions for tweaking. It can also explain the implications of the data being presented in the model. Here is an example with QQQ and the US Balance Sheet: This helps to simplify and interpret the results you are looking at. Forecasting the Economic Indicator In addition to assessing the economic indicator's impact on the ticker, the indicator is also capable of forecasting out the economic indicator over the next 25 releases. Here is an example of the CPI forecast: Overall use of the indicator The indicator is meant to bridge the gap between Technical Analysis and Fundamental Analysis. Any trader who is attune to fundamentals would benefit from this, as this provides you with objective data on how and to what extent fundamental and economic data impacts tickers. It can help affirm hypothesis and dispel myths objectively. It also omits the need from having to perform these types of analyses outside of Tradingview (i.e. in excel, R or Python), as you can get the data in just a few licks of enabling the indicator. Conclusion I have tried to make this indicator as user friendly as possible. Though it uses a lot of math, it is fairly straight forward to interpret. The band plotted can be considered the fair market value or FMV of the ticker based on the underlying economic data, provided the indicator tells you that the relationship is significant (and it will blatantly give you this information verbatim, you don't have to interpret the math stuff). This is US economic data only. It does not pull economic data from other countries. You can absolutely see how US economic data impacts other markets like the TSX, BANKNIFTY, NIFTY, DAX etc. but the indicator is only pulling US economic data. That is it! I hope you enjoy it and find this helpful! Thanks everyone and safe trades as always 🚀🚀🚀
Penunjuk Pine Script®
oleh Steversteves
4
OG Volume PowerDescription: The OG Volume Power is an elite-level volume analysis suite built for identifying momentum surges, trend continuation, and buyer/seller imbalances at critical price levels. It combines real-time VWAP tracking, a dynamic Point of Control (POC), and volume delta clusters to give traders a complete picture of price and volume interaction. 🔍 Key Features: Real-Time VWAP: Tracks volume-weighted average price to identify mean reversion and intraday fair value zones. Ideal for institutional-level entries and exits. Dynamic POC (Point of Control): Automatically finds the price level with the highest volume over the last N candles (default 50), helping traders pinpoint where market participants are most committed. Buyer/Seller Volume Delta Clusters: Highlights imbalances between buying and selling pressure using bullish and bearish volume deltas that exceed the 20-bar volume average — excellent for momentum detection and early trend recognition. ⚙️ How It Works: Green triangle: Buyer surge (bullish delta + above average volume) Red triangle: Seller surge (bearish delta + above average volume) Magenta line: Dynamic POC (highest volume price over recent candles) Orange line: VWAP (acts as a magnetic force for price) 📈 Best For: Intraday scalping or swing trading on SPY, QQQ, BTC, or Forex Volume flow confirmation before breakout entries Filtering false breakouts with delta strength signals 🧠 Pro Tip: Use OG Volume Power alongside your trend indicators (like OG EMA Stack or OG Supertrend) to confirm that volume is backing the move. Look for surges near VWAP or POC zones for sniper-level entries.
Penunjuk Pine Script®
oleh OG_Wealth