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Futures Scalping Signal by AK_Trades – RISK PROTECTED MODEFutures Scalping Signal by AK_Trades – RISK PROTECTED MODE This precision-built scalping indicator is designed for futures traders who demand clarity, speed, and protection. ✅ Smart Signal Logic: Based on UT Bot ATR trailing stop logic Requires minimum price movement for confirmation Prevents repeated signals in the same direction using trend memory ✅ Visuals That Guide You, Not Distract: Clear Buy/Sell signals labeled on the chart Dynamic support or resistance line always visible Price-tagged signal entries (Buy @, Sell @) ✅ Candlestick Awareness: Highlights key patterns: Engulfing, Doji, Hammer, Shooting Star Patterns are visual only — no interference with signal flow ✅ Trend Label: Clean top-right corner label updates periodically to guide sentiment ⚠️ Disclaimer: This tool is for educational purposes only. No financial advice is provided. Use at your own risk. Built by @AK_Trades to help scalpers trade smarter, not harder.
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adeelk714 tarafından
ZMVZMV-STRATEGY Z – Zero-Based Thinking At the core of the ZMV-STRATEGY lies zero-based thinking: the practice of assessing actions, projects, or goals as if starting from scratch. This principle encourages: Eliminating outdated assumptions Prioritizing current relevance over historical momentum Making decisions based on present and future potential, not sunk costs M – Momentum Mapping Momentum is essential for sustained progress. The "M" emphasizes: Identifying key areas where traction exists Mapping energy flows within a team, project, or market Leveraging small wins to catalyze exponential growth V – Value Alignment Finally, the “V” represents value alignment, which ensures that: Every move aligns with core values and purpose Stakeholders are engaged through shared vision Ethical, meaningful impact is prioritized alongside metrics
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ATDEBARON tarafından
KingJakesFx CRTThis TradingView indicator is a comprehensive tool that identifies and marks significant high and low points of Candle Range Type (CRT) candles. Its standout feature is the ability to visualize these key levels across multiple timeframes, allowing traders to maintain awareness of important price zones even when analyzing shorter timeframes. The indicator extends high and low lines into the future, creating dynamic support and resistance levels that help anticipate potential price reactions. With extensive customization options, users can tailor the visual appearance of lines, labels, and alerts to match their trading setup and preferences. Perfect for traders who analyze multiple timeframes and want to maintain awareness of significant price levels, this indicator combines powerful technical analysis with flexible visual customization to enhance any trading strategy.
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gdsbillion tarafından
UNITED TRADING COMMUNITY WaterMarkWATER MARK indicator. Will allow you to improve the order of the entries you need on the chart. 1. Name and date for the traded instrument 2. Watermarks to protect your charts (in the center and around the perimeter of the chart) 3. The new "notes" option will allow you to keep focus on the factors that are important to you on the chart. Very flexible settings for any notes, labels, watermarks on the chart that are important to you. Индикатор WATER MARK . Даст возможность вам улучшить порядок нужных вам записей на графике. 1. Название и дата для торгуемого инструмента 2. Водные знаки для защиты ваших графиков ( в центре и по периметру графика) 3. Новая опция "заметки" позволит вам держать фокус на важных для вас факторах на графике. Очень гибкая настройка , любых значимых для вас заметок , лейблов , вотермарк на графике.
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UTDCrypto tarafından
Correlation Drift📈 Correlation Drift The Correlation Drift indicator is designed to detect shifts in market momentum by analyzing the relationship between correlation and price lag. It combines the principles of correlation analysis and lag factor measurement to provide a unique perspective on trend alignment and momentum shifts. 🔍 Core Concept: The indicator calculates the Correlation vs PLF Ratio, which measures the alignment between an asset’s price movement and a chosen benchmark (e.g., BTCUSD). This ratio reflects how well the asset’s momentum matches the market trend while accounting for price lag. 📊 How It Works: Correlation Calculation: The script calculates the correlation between the asset and the selected benchmark over a specified period. A higher correlation indicates that the asset’s price movements are in sync with the benchmark. Price Lag Factor (PLF) Calculation: The PLF measures the difference between long-term and short-term price momentum, dynamically scaled by recent volatility. It highlights potential overextensions or lags in the asset’s price movements. Combining Correlation and PLF: The Correlation vs PLF Ratio combines these metrics to detect momentum shifts relative to the trend. The result is a dynamic, smoothed histogram that visualizes whether the asset is leading or lagging behind the trend. 💡 How to Interpret: Positive Values (Green/Aqua Bars): Indicates bullish alignment with the trend. Aqua: Rising bullish momentum, suggesting continuation. Teal: Decreasing bullish momentum, signaling caution. Negative Values (Purple/Fuchsia Bars): Indicates bearish divergence from the trend. Fuchsia: Falling bearish momentum, indicating increasing pressure. Purple: Rising bearish momentum, suggesting potential reversal. Clipping for Readability: Values are clipped between -3 and +3 to prevent outliers from compressing the histogram. This ensures clear visualization of typical momentum shifts while still marking extreme cases. 🚀 Best Practices: Use Correlation Drift as a confirmation tool in conjunction with trend indicators (e.g., moving averages) to identify momentum alignment or divergence. Look for transitions from positive to negative (or vice versa) as signals of potential trend shifts. Combine with volume analysis to strengthen confidence in breakout or breakdown signals. ⚠️ Key Features: Customizable Settings: Adjust the correlation length, PLF length, and smoothing factor to fine-tune the indicator for different market conditions. Visual Gradient: The histogram changes color based on the strength and direction of the ratio, making it easy to identify shifts at a glance. Zero Line Reference: Clearly distinguishes between bullish and bearish momentum zones. 🔧 Recommended Settings: Correlation Length: 14 (for short to medium-term analysis) PLF Length: 50 (to smooth out noise while capturing trend shifts) Smoothing Factor: 3 (for enhanced clarity without excessive lag) Benchmark Symbol: BTCUSD (or another relevant market indicator) By providing a quantitative measure of trend alignment while accounting for price lag, the Correlation Drift indicator helps traders make more informed decisions during periods of momentum change. Whether you are trading crypto, forex, or equities, this tool can be a powerful addition to your momentum-based trading strategies. ⚠️ Disclaimer: The Correlation Drift indicator is a technical analysis tool designed to aid in identifying potential shifts in market momentum and trend alignment. It is intended for informational and educational purposes only and should not be considered as financial advice or a recommendation to buy, sell, or hold any financial instrument. Trading financial instruments, including cryptocurrencies, involves significant risk and may result in the loss of your capital. Past performance is not indicative of future results. Always conduct thorough research and seek advice from a certified financial professional before making any trading decisions. The developer (RWCS_LTD) is not responsible for any trading losses or adverse outcomes resulting from the use of this indicator. Users are encouraged to test and validate the indicator in a simulated environment before applying it to live trading. Use at your own risk.
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RWCS_LTD tarafından
ORB & Key Levels [$100 Strategy]This is a script for anyone trading options with a small account ($100). I utilizes the ORB from 9:30am-9:45am. Key levels of the premarket high/low, Option contracts under $100 and the top 3-5 tickers from your watch list showing strong gap/volume signals Small account tickers SOFI PLTR RIVN LCID DKNG AMD There are others, these are just examples. This is for anyone just starting out on this journey and learning. Everyone has their own way of doing it, this is what I used to grow my account until I became knowledgeable enough to come up with a new strategy. //@version=5 indicator("ORB & Key Levels ", overlay=true) // === Settings === showPreHighLow = input(true, "Show Pre-Market High/Low") showPrevHighLow = input(true, "Show Previous Day High/Low") showORB = input(true, "Show 15-min ORB") // === Previous Day High/Low === prevHigh = request.security(syminfo.tickerid, "D", high ) prevLow = request.security(syminfo.tickerid, "D", low ) plot(showPrevHighLow ? prevHigh : na, color=color.green, linewidth=1, title="Previous Day High") plot(showPrevHighLow ? prevLow : na, color=color.red, linewidth=1, title="Previous Day Low") // === Pre-Market High/Low === var float premHigh = na var float premLow = na isPremarket = (hour >= 4 and hour < 9) or (hour == 9 and minute < 30) premHigh := isPremarket ? na(premHigh) ? high : math.max(premHigh, high) : premHigh premLow := isPremarket ? na(premLow) ? low : math.min(premLow, low) : premLow plot(showPreHighLow and not isPremarket ? premHigh : na, color=color.orange, linewidth=1, title="Pre-Market High") plot(showPreHighLow and not isPremarket ? premLow : na, color=color.orange, linewidth=1, title="Pre-Market Low") // === 15-Min Opening Range === var float orbHigh = na var float orbLow = na isORB = (hour == 9 and minute >= 30 and minute < 45) orbHigh := isORB ? na(orbHigh) ? high : math.max(orbHigh, high) : orbHigh orbLow := isORB ? na(orbLow) ? low : math.min(orbLow, low) : orbLow plot(showORB and not isORB and not na(orbHigh) ? orbHigh : na, color=color.blue, linewidth=1, title="ORB High") plot(showORB and not isORB and not na(orbLow) ? orbLow : na, color=color.blue, linewidth=1, title="ORB Low")
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cryptojay75 tarafından
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® göstergesi
EdgeTools tarafından
Power Block Consolidation with Volume @MaxMaserati 2.0Power Block Consolidation with Volume @MaxMaserati 2.0 Overview Price action hinges on consolidation, the foundation of market moves. The "Power Block Consolidation with Volume @MaxMaserati 2.0" (MMPB) indicator uses a proprietary, ingenious system to identify high-probability consolidation zones—termed "power blocks"—where smart money drives accumulation or distribution. By leveraging a unique limitorphe closing candle system, to plots volume to signal price direction: significant volume at the high price indicates bullish continuation, while volume at the low price suggests bearish momentum. This tool empowers traders to exploit bullish and bearish trends with precision. Key Features Consolidation Detection: Pinpoints power blocks using a secret system, marking zones of smart money activity. Volume Analysis: A proprietary limitrophe closing candle system splits volume into buying (high price) and selling (low price), revealing accumulation (buying pressure) or distribution (selling pressure). Trend Visualization: Bullish Trends: Green boxes and lines highlight consolidation zones with high volume at the high price, signaling upward continuation. Bearish Trends: Red boxes and lines mark zones with high volume at the low price, indicating downward momentum. NB: The volume matter more than the color of the box. Example High volume up at the box vs low volume at the low we expect an up move Even we had a bearish Body close below the box price reconfirmed the up move Price make the bullish upside move Price retest the box and reject it strongly Breakout and Retest: Captures breakouts from power blocks, with price often retesting the zone before resuming the trend. Volume Labels: Displays buying (green) and selling (red) volume on lines for clear pressure analysis. Breakout Alerts: Triggers alerts for bullish ("BuBC") and bearish ("BeBC") breakouts, with optional visual markers (triangles). Strategy MMPB is designed to capture smart money behavior in consolidation zones, where markets prepare for significant moves. Key principles: Volume-Driven Direction: High volume at the high price within a power block signals strong bullish continuation; high volume at the low price indicates bearish potential. Accumulation/Distribution: Buying volume reflects accumulation, priming bullish trends; selling volume signals distribution, fueling bearish trends. Breakout and Retest: Price often breaks out from power blocks and retests the zone, offering low-risk entry points. Consolidation as Precursor: Markets require consolidation to build momentum, making power blocks critical for trend prediction. Traders can: Enter on breakouts with strong volume confirmation. Target retests of power blocks for high-probability setups. Use volume labels to assess trend strength. Use Cases Trend Trading: Ride bullish or bearish trends post-breakout from high-volume power blocks. Swing Trading: Use power blocks as dynamic support/resistance for entries and exits. Smart Money Analysis: Identify accumulation (bullish) or distribution (bearish) zones. Risk Management: Place stops at power block edges during retests. Conclusion The MMPB indicator, powered by a proprietary system, transforms consolidation analysis by identifying power blocks where smart money operates. Its limitrophe closing candle system highlights volume-driven trends, enabling traders to capitalize on bullish and bearish moves with confidence. Ideal for trend and swing traders, MMPB shines in markets where consolidation precedes significant trends, offering clear signals for breakouts and retests.
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MaxMaserati tarafından
NIFTY Option Chain Table with Custom CE/PE Price FiltersThis Pine Script creates a powerful and visually organized option chain dashboard for NIFTY Index Options, showing 10 Call Options (CE) and 10 Put Options (PE), with real-time prices updated on a 5-minute chart. You can filter and view only the most relevant option contracts based on your preferred price ranges, helping you make quick decisions for scalping, intraday, or positional trades. 🔍 How It Works: You manually select up to 10 Call Option symbols and 10 Put Option symbols from NSE (e.g., NIFTY240530C18000, NIFTY240530P18000, etc.). Keep that time options this are old options in defalt so there will be a error The script fetches the real-time close price of each option using the request.security() function. You define the minimum and maximum price range separately for Calls and Puts. The script filters out any options that fall outside of your desired price range. Only a limited number of matching options (as set by you) are displayed in the table for both Calls and Puts. The table is shown at your preferred location on the chart (Bottom Right, Top Left, etc.). ✅ Features: 🔟 Supports exactly 10 CE and 10 PE options for tracking. 📈 Live price updates pulled directly from the chart timeframe (5-min). 🎯 Custom price filters for CE and PE (separate inputs). 📊 Show only the top X number of contracts that meet your filter criteria. 🧱 Vertical layout with clear headers and color-coded sections (green for Calls, red for Puts). 🎛️ Position the table wherever it's most convenient on your chart. ⚡ Helps you quickly spot low premium or range-bound options during the day. 📌 Use Case: Ideal for: Option scalpers and day traders who want to focus only on options within a specific price zone. Traders who want to monitor multiple strikes simultaneously without clutter. Users building custom NIFTY strategies based on option premiums.
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poligrowvenkatpolisetty tarafından
Strike Price selection by GoldenJetThis script is designed to assist options traders in selecting appropriate strike prices based on the latest prices of two financial instruments. It retrieves the latest prices, rounds them to the nearest significant value, and calculates potential strike prices for both call and put options. The results are displayed in a customizable table, allowing traders to quickly see the relevant strike prices for their trading decisions. The strike prices shown are In-The-Money (ITM), which helps options traders in several ways: Saving from Theta Decay: On expiry day, ITM options experience less time decay (Theta), which can help preserve the option's value. Capturing Good Points: ITM options have a higher Delta, meaning they move more in line with the underlying asset's price. This can help traders capture a good amount of points as the underlying asset's price changes. In essence, this tool simplifies the process of determining strike prices, making it easier for traders to make informed decisions and potentially improve their trading outcomes.
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GoldenJet55 tarafından
Alpha1Alpha1 is a streamlined trend analysis tool designed to offer visual clarity for directional bias in various market conditions. This script combines adaptive price tracking with dynamic smoothing logic to help traders stay aligned with the prevailing trend. It is optimized for both short-term and mid-term chart analysis and integrates seamlessly with a wide range of trading strategies. It best works on 15 minute time frame. This is an invite-only tool intended for private research and use. For educational purposes only — not financial advice.
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caabhay25 tarafından
ALGO Sniper[Trade Snipers]🔰 ALGO Sniper – Invite-Only Scalping Tool for Precise Trend Detection & Trade Management ALGO Sniper is a precision-based trading tool designed specifically for scalpers and short-term trend traders. This invite-only script combines custom smoothed trend filtering, candle confirmation logic, and automated risk/reward management to deliver actionable trade signals backed by dynamic price movement behavior. 📌 How it Works: 📊 Custom Trend Filter: 1.The core of the script is a proprietary smoothing algorithm that processes the source price using a dynamic range filter. This filter adjusts based on volatility (ATR-based) and reacts only when the price deviates beyond a calculated threshold, reducing noise and fake-outs. 2. Uptrends and downtrends are tracked using a real-time counter that evaluates directional strength. 📍 Entry Signals (Buy/Sell): 1. Signals are confirmed only on candle close and trigger when there's a confirmed trend reversal. 2. The system avoids sideways market signals by detecting neutral zones using custom logic, helping traders avoid false entries in low-volume or range-bound markets. 🛡️ Stop-Loss Management: 1. Offers two options: (1) Manual SL: Based on ATR (Average True Range) + custom offset. (2)Auto SL: Randomized SL between 20–40 pips to simulate dynamic market protection in volatile environments. 2. Visual SL lines and labels are plotted for every entry to ensure transparency and easy tracking. 🎯 Take-Profit System: 1. Like SL, you can use either: (1)Manual TP (user-defined pips). (2)Auto TP: Randomized between 300–800 pips for variability. 2. When TP is hit, visual markers (BUY BOOK / SELL BOOK) are displayed instantly on the chart. ⚙️ Features: 1. Trend-filtered signals that reduce noise. 2. Dynamic SL/TP lines plotted directly on the chart. 3.Instant alerts for Buy, Sell, and Take-Profit events. 4. Designed for BTC, Gold, Nifty, Bank nifty, Forex, 1to 15-min chart, but customizable for other timeframes and assets. 5. High configurability: users can adjust SL/TP style, offset, and filter sensitivity. 🎯 Use Case: This tool is ideal for traders looking for a non-repainting, price-reactive scalping system that avoids common lagging indicator flaws. With visual clarity and strict entry logic, ALGO Sniper enhances confidence and risk management in fast-moving markets.
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TradeSnipers tarafından