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Harvey's Super Trend & Signals📈 Harvey’s Super Trend & Trade Signals – Multi-Tool ATR Precision ⚠️ Disclaimer For educational purposes only. Not financial advice. Test thoroughly and manage your own risk. ⸻ 🚀 One-Liner Intro Catch trends, mark key levels, and manage trades — all in one tool. Harvey’s Super Trend & Trade Signals blends a Smart Trend Average, ATR-tightened trails, and auto-plotted trade levels to keep you ahead of the move and in control. ⸻ 📝 Overview Harvey’s Super Trend & Trade Signals is an advanced, all-in-one market tool that: • Detects clean Buy (“B”) and Sell (“S”) opportunities using a Smart Trend Average crossover with ATR-based confirmation. • Auto-plots entry, stop-loss, and 3 profit targets for each trade. • Marks Previous Day High/Low, New York Open, and NY Opening Range Breakout (ORB) for added confluence. ⸻ ⚙️ How It Works • Calculates a smoothed Smart Trend Average from your selected candle source and optional higher timeframe. • Wraps the Smart Trend with tighten-only ATR bands to reduce noise and false flips. • Triggers Buy/Sell flips when price pierces the opposite ATR trail. • Filters signals to prevent duplicates or conflicts within user-defined lookback windows. • Auto-draws trade management lines (entry, SL, TP1–TP3) with live updates until trade completion. • Continuously updates PDH/PDL, NYO, and ORB levels with optional alerts. ⸻ 🎛 User Inputs • Trend chill factor – Higher = smoother, fewer flips. Lower = faster, more sensitive. • Timeframe cheat – Apply Smart Trend & ATR calc on a higher timeframe. • Candle flavor – Select your price source (Close, HL2, OHLC4, etc.). • Show ATR line / trades – Toggle individual visual elements. ⸻ 📊 How to Use 1. Wait for a “B” or “S” flip confirmed by your filters. 2. Follow plotted entry, SL, and profit target lines for reference. 3. Watch PDH/PDL, NYO, and ORB levels for reaction points. 4. Use alerts to get notified instantly of flips, targets, or key level hits. ⸻ 💡 Pro Tips • Pair with volume spikes or price action patterns at PDH/PDL for high-probability trades. • Use higher “Trend chill factor” + HTF cheat for swing trading bias; lower values for scalping. • ORB levels can act as intraday breakout/fade reference points.
Penunjuk Pine Script®
oleh Thorpiggy
Adaptive Scalping with Take ProfitThis is a comprehensive and adaptive trading system designed specifically for scalping XAUUSD (Gold) on a 3-minute timeframe. Its main feature is that it "adapts" to current market conditions rather than using fixed parameters. It provides clear BUY, SELL, and EXIT signals directly on the chart. Key Components 1. Adaptive Entry Signal (KAMA) Instead of using standard moving averages (like EMA or SMA), the entry logic is based on Kaufman's Adaptive Moving Average (KAMA). How it's adaptive: KAMA automatically adjusts its speed based on market noise. It moves slowly when the market is choppy and sideways, filtering out many false signals. It speeds up when a clear trend emerges, allowing you to enter a move early. A BUY signal is generated when the faster KAMA crosses above the slower KAMA. A SELL signal is generated on a cross-under. 2. Volatility Filter The system includes an optional filter that uses the Average True Range (ATR) to measure market volatility. A trade signal will only appear if the market is volatile enough for scalping. This prevents you from entering trades when the market is flat and there's little opportunity for profit. 3. Dual Exit Strategy (Adaptive) This is the most advanced part of the system. It gives you two ways to exit a trade to maximize and protect profits: Dynamic Take Profit: When a trade starts, a profit target (the blue circles) is immediately plotted on the chart. This target is calculated using the ATR, so on a volatile day, the target will be further away. If the price hits this level, it's a signal to take your profits. ATR Trailing Stop: This is your safety net. It's a stop loss that automatically "trails" behind the price as it moves in your favor (the green/red line). If the market suddenly reverses, the trade is closed when the price hits this trailing stop, locking in any accumulated profit. An EXIT label appears on the chart as soon as one of these two conditions is met. 4. On-Chart Visuals BUY/SELL/EXIT Labels: Clear, unmissable labels appear to show you exactly when to enter and exit. Bar Coloring: The chart candles are colored green when the trend is bullish (fast KAMA > slow KAMA) and red when the trend is bearish, giving you an instant visual confirmation of the market sentiment.
Penunjuk Pine Script®
oleh Starlight73
Bar TimeBar Time is a simple utility for traders who rely on backtesting, Bar Replay, and detailed price action analysis. It solves a common but frustrating problem: knowing the exact time of the bar you are looking at. While most time indicators show your computer's live clock time, this tool displays the bar's own timestamp, perfectly synchronized with your chart's data and timezone. Why Is This Important? When you are deep in a Bar Replay session or analyzing a historical setup, the live clock is irrelevant. You need to know when that critical breakout or reversal candle actually happened. Was it during the pre-market? At the London open? In the last five minutes of the US session? This indicator provides that vital context instantly, without you needing to squint at the small print on the x-axis. Key Use Cases 1. Mastering Bar Replay As you click through bars in Replay mode, the displayed time updates with each new bar. This allows you to simulate a live trading session with full awareness of the time of day, helping you train your decision-making under more realistic conditions. 2. Analyzing Screener Signals This is one of the most powerful uses. Imagine your screener finds a "BUY" signal on a stock from two bars ago. You switch to that stock's chart to investigate. Instead of hunting for the exact bar, this tool instantly shows you the date and time of the bar you are currently hovering over. It dramatically speeds up the workflow of moving from a screener alert to actionable analysis. 3. Detailed Price Action Study Quickly identify key session timings, see how price reacts to news events at a specific time, or analyze intraday volume patterns with complete temporal clarity. Features & Customization The tool is designed to be lightweight, efficient, and fully customizable to match your charting environment. Timezone-Aware Accuracy: Automatically detects your chart's timezone for a perfect match between the label and the x-axis. Fully Customizable Position: Place the time display in any of nine screen positions (e.g., Top Left, Bottom Center) using a simple dropdown menu. Custom Colors: Easily set the background and text colors to blend seamlessly with your chart's theme.
Penunjuk Pine Script®
oleh ChiragPatnaik
ADX Phantom SniperADX Phantom Sniper is a precision trend-following tool that combines three powerful forces: 1. ADX & DI Crossover Trigger – Detects strong directional moves only when the trend strength exceeds a defined threshold. 2. Multi-Timeframe (MTF) Confirmation – Executes on the current chart timeframe (e.g., M15) only if the higher timeframe (H1) confirms the same trend direction. 3. Force Index Momentum Filter – Filters entries based on bullish/bearish momentum to avoid weak signals. Signal Logic: BUY: EMA14 > EMA100, price above EMA14, +DI crosses above -DI, ADX > threshold, Stochastic crosses above signal line in the bullish zone (>50), MTF trend aligned, Force Index > 0 (optional). SELL: EMA14 < EMA100, price below EMA14, -DI crosses above +DI, ADX > threshold, Stochastic crosses below signal line in the bearish zone (<50), MTF trend aligned, Force Index < 0 (optional). Features: Noise filtering with trend structure + higher timeframe alignment On-chart BUY/SELL labels for easy signal spotting Optional Force Index filter toggle Adjustable ADX threshold, EMA lengths, Stochastic settings, and higher timeframe choice Suitable for scalping and swing entries depending on timeframe Recommended Setup: Primary chart: M15 Higher timeframe confirmation: H1 Combine with your preferred risk management rules. Disclaimer: This tool is for educational purposes only and is not financial advice. Past performance does not guarantee future results. Use at your own risk.
Strategi Pine Script®
oleh togethertrader4
Key Levels ProThis indicator automatically plots important price levels from multiple timeframes and market sessions, such as opens, highs, lows, and midpoints . It dynamically tags each level as support or resistance based on current price position, so you instantly know how the market is reacting . When price touches a level, it’s highlighted with a subtle glow for easy visibility, and an optional alert can be triggered. This makes it easier to identify, track, and trade around high-probability zones without manually marking them yourself CME_MINI:NQ1! All credits to spacemanbtc for creating the original one and he inspired me do create this version for the TradingView community. I just improved what I thought it was missing like real-time alerts when price touches a new level.
Penunjuk Pine Script®
oleh edilsonpaca
Session Liquidity [TakingProphets]Session Liquidity Session Liquidity maps the intraday landscape that ICT/SMC traders care about: each session’s high/low prints, key opens (Midnight, True Day/6PM, 8:30), and prior period reference levels (Previous Week/Day and optional Mon/Tue/Wed). It auto-draws and extends clean horizontal levels, updates them live, and optionally preserves “mitigated” tags so you can review what price consumed. To keep charts readable, overlapping labels at the same price are merged into a single combined label (e.g., LON.H + PDH + PWH) with smart anti-overlap placement. What it does (at a glance) – Tracks Asia, London, NY AM, NY Lunch, and NY PM session highs/lows in your chosen timezone (default America/New_York). – Draws key opens: Midnight Open, True Day Open (6 PM), and 8:30 Open. – Plots Previous Week High/Low (PWH/PWL) and Previous Day High/Low (PDH/PDL) with optional Mon/Tue/Wed references. – Live extension: lines extend to the current bar; when a level is traded through you can either remove it or keep a left-anchored “mitigated” label. – Combined labels: when multiple levels share the same price, the script shows one label listing all tokens (e.g., LON.L + PWL). – Timeframe governor: a Timeframe Limit hides drawings on higher resolutions to avoid clutter (e.g., show on ≤ 30 min only). – Styling controls: per-feature colors, dotted/dashed/solid styles, and label size/position (session labels left/center/right logic handled via label types and offsets). How it works: – Sessions are defined with TradingView’s session input strings. While you are “in session,” the script updates running highs/lows and stores their bar indices. When the session closes, it freezes the prints and draws two horizontal lines: one at the session high (token “ASIA.H”, “LON.H”, “NYAM.H”, “NYLU.H”, “NYPM.H”) and one at the session low (“…L”). – Prior period levels come from higher-timeframe requests: Previous Week’s High/Low from W, Previous Day from D (plus Mon/Tue/Wed using simple daily offsets). New periods wipe and redraw lines/labels cleanly. – Key opens are stamped exactly when they occur (00:00 for Midnight, 18:00 for True Day, 08:30 for the print), then extended forward. – Mitigation logic: if price trades beyond a level, either remove it entirely (Show Mitigated Levels = off) or stop extending the line and drop a small, persistent left-justified label where mitigation occurred (Show Mitigated Levels = on). – Label combining: on each update, per-level labels are optionally cleared and replaced with one combined label per price level. The script groups by tick index, merges tokens (e.g., LON.H + PDH), and uses a small vertical offset loop to avoid label collisions at the same x-position. Inputs you control – Timeframe Limit: drawings will not appear on charts greater than or equal to this resolution. – Timezone: default America/New_York. – Label Settings – Show Labels / Show Session High/Low Levels. – Show Mitigated Levels: keep a small label where a level was traded through. – Combine overlapping level labels: merge tokens into one label if prices match. – Label sizes for levels and for session start/end text (sizes: Tiny/Small/Normal/Large). – Visual Settings – Colors for level lines and label text. – Styles (Solid/Dashed/Dotted) for Previous Week and Previous Day blocks. – Custom Labels – Rename tokens for each session print (e.g., ASIA.H, LON.L, NYAM.H, etc.) to match your playbook. – Key Opens – Toggle Midnight Open, True Day Open (6 PM), and 8:30 Open lines; customize colors. – Previous Week / Previous Day – Toggle PWH/PWL and PDH/PDL; optionally plot Mon/Tue/Wed reference prints. – Macro Sessions (toodegrees-style bracket) – Toggle two macro windows (9:45–10:15 and 10:45–11:15). – Choose bracket height in ticks, line style, label size/text, and optional price projection. – The bracket is dynamic during its window (extends across the window; top adapts to new highs + chosen height; label centers on completion). How to use it: Pick your Timeframe Limit (e.g., 30) so the map only shows where you execute. Enable the sessions you trade and keep the timezone aligned to your venue. Turn on the prior period levels you care about (PWH/PWL, PDH/PDL, Mon/Tue/Wed). Choose whether to preserve mitigated levels. If you journal, keeping mitigated tags helps with post-session review. Enable combined labels to reduce clutter and spotlight confluence (e.g., LON.H aligning with PDH). Use Macro windows for playbook timing (9:45–10:15, 10:45–11:15) to visualize typical volatility brackets. Practical notes – The indicator is a context and mapping tool; it does not produce signals. Use with your own bias, PD arrays, and execution model. – Very long lookbacks or many toggles can push object limits on lower-powered machines. Use Timeframe Limit and feature toggles to keep things light. – If you use custom sessions, ensure they do not overlap unexpectedly in your timezone. – “Combine labels” intentionally removes per-level labels in favor of one merged label per price level; mitigated labels are preserved by design. What’s unique here – A full intraday “session print” system (Asia/London/NY AM/NY Lunch/NY PM) with clean freezing at session close and live line extension. – True Day/Midnight/8:30 opens integrated into the same framework for a single, coherent liquidity map. – Prior period structure (week/day + optional Mon/Tue/Wed) and toodegrees-style macro windows in one tool. – Robust label merging by tick level with anti-overlap logic so multi-signal confluence is readable at a glance.
Penunjuk Pine Script®
oleh TakingProphets
Kelly Position Size CalculatorThis position sizing calculator implements the Kelly Criterion, developed by John L. Kelly Jr. at Bell Laboratories in 1956, to determine mathematically optimal position sizes for maximizing long-term wealth growth. Unlike arbitrary position sizing methods, this tool provides a scientifically solution based on your strategy's actual performance statistics and incorporates modern refinements from over six decades of academic research. The Kelly Criterion addresses a fundamental question in capital allocation: "What fraction of capital should be allocated to each opportunity to maximize growth while avoiding ruin?" This question has profound implications for financial markets, where traders and investors constantly face decisions about optimal capital allocation (Van Tharp, 2007). Theoretical Foundation The Kelly Criterion for binary outcomes is expressed as f* = (bp - q) / b, where f* represents the optimal fraction of capital to allocate, b denotes the risk-reward ratio, p indicates the probability of success, and q represents the probability of loss (Kelly, 1956). This formula maximizes the expected logarithm of wealth, ensuring maximum long-term growth rate while avoiding the risk of ruin. The mathematical elegance of Kelly's approach lies in its derivation from information theory. Kelly's original work was motivated by Claude Shannon's information theory (Shannon, 1948), recognizing that maximizing the logarithm of wealth is equivalent to maximizing the rate of information transmission. This connection between information theory and wealth accumulation provides a deep theoretical foundation for optimal position sizing. The logarithmic utility function underlying the Kelly Criterion naturally embodies several desirable properties for capital management. It exhibits decreasing marginal utility, penalizes large losses more severely than it rewards equivalent gains, and focuses on geometric rather than arithmetic mean returns, which is appropriate for compounding scenarios (Thorp, 2006). Scientific Implementation This calculator extends beyond basic Kelly implementation by incorporating state of the art refinements from academic research: Parameter Uncertainty Adjustment: Following Michaud (1989), the implementation applies Bayesian shrinkage to account for parameter estimation error inherent in small sample sizes. The adjustment formula f_adjusted = f_kelly × confidence_factor + f_conservative × (1 - confidence_factor) addresses the overconfidence bias documented by Baker and McHale (2012), where the confidence factor increases with sample size and the conservative estimate equals 0.25 (quarter Kelly). Sample Size Confidence: The reliability of Kelly calculations depends critically on sample size. Research by Browne and Whitt (1996) provides theoretical guidance on minimum sample requirements, suggesting that at least 30 independent observations are necessary for meaningful parameter estimates, with 100 or more trades providing reliable estimates for most trading strategies. Universal Asset Compatibility: The calculator employs intelligent asset detection using TradingView's built-in symbol information, automatically adapting calculations for different asset classes without manual configuration. ASSET SPECIFIC IMPLEMENTATION Equity Markets: For stocks and ETFs, position sizing follows the calculation Shares = floor(Kelly Fraction × Account Size / Share Price). This straightforward approach reflects whole share constraints while accommodating fractional share trading capabilities. Foreign Exchange Markets: Forex markets require lot-based calculations following Lot Size = Kelly Fraction × Account Size / (100,000 × Base Currency Value). The calculator automatically handles major currency pairs with appropriate pip value calculations, following industry standards described by Archer (2010). Futures Markets: Futures position sizing accounts for leverage and margin requirements through Contracts = floor(Kelly Fraction × Account Size / Margin Requirement). The calculator estimates margin requirements as a percentage of contract notional value, with specific adjustments for micro-futures contracts that have smaller sizes and reduced margin requirements (Kaufman, 2013). Index and Commodity Markets: These markets combine characteristics of both equity and futures markets. The calculator automatically detects whether instruments are cash-settled or futures-based, applying appropriate sizing methodologies with correct point value calculations. Risk Management Integration The calculator integrates sophisticated risk assessment through two primary modes: Stop Loss Integration: When fixed stop-loss levels are defined, risk calculation follows Risk per Trade = Position Size × Stop Loss Distance. This ensures that the Kelly fraction accounts for actual risk exposure rather than theoretical maximum loss, with stop-loss distance measured in appropriate units for each asset class. Strategy Drawdown Assessment: For discretionary exit strategies, risk estimation uses maximum historical drawdown through Risk per Trade = Position Value × (Maximum Drawdown / 100). This approach assumes that individual trade losses will not exceed the strategy's historical maximum drawdown, providing a reasonable estimate for strategies with well-defined risk characteristics. Fractional Kelly Approaches Pure Kelly sizing can produce substantial volatility, leading many practitioners to adopt fractional Kelly approaches. MacLean, Sanegre, Zhao, and Ziemba (2004) analyze the trade-offs between growth rate and volatility, demonstrating that half-Kelly typically reduces volatility by approximately 75% while sacrificing only 25% of the growth rate. The calculator provides three primary Kelly modes to accommodate different risk preferences and experience levels. Full Kelly maximizes growth rate while accepting higher volatility, making it suitable for experienced practitioners with strong risk tolerance and robust capital bases. Half Kelly offers a balanced approach popular among professional traders, providing optimal risk-return balance by reducing volatility significantly while maintaining substantial growth potential. Quarter Kelly implements a conservative approach with low volatility, recommended for risk-averse traders or those new to Kelly methodology who prefer gradual introduction to optimal position sizing principles. Empirical Validation and Performance Extensive academic research supports the theoretical advantages of Kelly sizing. Hakansson and Ziemba (1995) provide a comprehensive review of Kelly applications in finance, documenting superior long-term performance across various market conditions and asset classes. Estrada (2008) analyzes Kelly performance in international equity markets, finding that Kelly-based strategies consistently outperform fixed position sizing approaches over extended periods across 19 developed markets over a 30-year period. Several prominent investment firms have successfully implemented Kelly-based position sizing. Pabrai (2007) documents the application of Kelly principles at Berkshire Hathaway, noting Warren Buffett's concentrated portfolio approach aligns closely with Kelly optimal sizing for high-conviction investments. Quantitative hedge funds, including Renaissance Technologies and AQR, have incorporated Kelly-based risk management into their systematic trading strategies. Practical Implementation Guidelines Successful Kelly implementation requires systematic application with attention to several critical factors: Parameter Estimation: Accurate parameter estimation represents the greatest challenge in practical Kelly implementation. Brown (1976) notes that small errors in probability estimates can lead to significant deviations from optimal performance. The calculator addresses this through Bayesian adjustments and confidence measures. Sample Size Requirements: Users should begin with conservative fractional Kelly approaches until achieving sufficient historical data. Strategies with fewer than 30 trades may produce unreliable Kelly estimates, regardless of adjustments. Full confidence typically requires 100 or more independent trade observations. Market Regime Considerations: Parameters that accurately describe historical performance may not reflect future market conditions. Ziemba (2003) recommends regular parameter updates and conservative adjustments when market conditions change significantly. Professional Features and Customization The calculator provides comprehensive customization options for professional applications: Multiple Color Schemes: Eight professional color themes (Gold, EdgeTools, Behavioral, Quant, Ocean, Fire, Matrix, Arctic) with dark and light theme compatibility ensure optimal visibility across different trading environments. Flexible Display Options: Adjustable table size and position accommodate various chart layouts and user preferences, while maintaining analytical depth and clarity. Comprehensive Results: The results table presents essential information including asset specifications, strategy statistics, Kelly calculations, sample confidence measures, position values, risk assessments, and final position sizes in appropriate units for each asset class. Limitations and Considerations Like any analytical tool, the Kelly Criterion has important limitations that users must understand: Stationarity Assumption: The Kelly Criterion assumes that historical strategy statistics represent future performance characteristics. Non-stationary market conditions may invalidate this assumption, as noted by Lo and MacKinlay (1999). Independence Requirement: Each trade should be independent to avoid correlation effects. Many trading strategies exhibit serial correlation in returns, which can affect optimal position sizing and may require adjustments for portfolio applications. Parameter Sensitivity: Kelly calculations are sensitive to parameter accuracy. Regular calibration and conservative approaches are essential when parameter uncertainty is high. Transaction Costs: The implementation incorporates user-defined transaction costs but assumes these remain constant across different position sizes and market conditions, following Ziemba (2003). Advanced Applications and Extensions Multi-Asset Portfolio Considerations: While this calculator optimizes individual position sizes, portfolio-level applications require additional considerations for correlation effects and aggregate risk management. Simplified portfolio approaches include treating positions independently with correlation adjustments. Behavioral Factors: Behavioral finance research reveals systematic biases that can interfere with Kelly implementation. Kahneman and Tversky (1979) document loss aversion, overconfidence, and other cognitive biases that lead traders to deviate from optimal strategies. Successful implementation requires disciplined adherence to calculated recommendations. Time-Varying Parameters: Advanced implementations may incorporate time-varying parameter models that adjust Kelly recommendations based on changing market conditions, though these require sophisticated econometric techniques and substantial computational resources. Comprehensive Usage Instructions and Practical Examples Implementation begins with loading the calculator on your desired trading instrument's chart. The system automatically detects asset type across stocks, forex, futures, and cryptocurrency markets while extracting current price information. Navigation to the indicator settings allows input of your specific strategy parameters. Strategy statistics configuration requires careful attention to several key metrics. The win rate should be calculated from your backtest results using the formula of winning trades divided by total trades multiplied by 100. Average win represents the sum of all profitable trades divided by the number of winning trades, while average loss calculates the sum of all losing trades divided by the number of losing trades, entered as a positive number. The total historical trades parameter requires the complete number of trades in your backtest, with a minimum of 30 trades recommended for basic functionality and 100 or more trades optimal for statistical reliability. Account size should reflect your available trading capital, specifically the risk capital allocated for trading rather than total net worth. Risk management configuration adapts to your specific trading approach. The stop loss setting should be enabled if you employ fixed stop-loss exits, with the stop loss distance specified in appropriate units depending on the asset class. For stocks, this distance is measured in dollars, for forex in pips, and for futures in ticks. When stop losses are not used, the maximum strategy drawdown percentage from your backtest provides the risk assessment baseline. Kelly mode selection offers three primary approaches: Full Kelly for aggressive growth with higher volatility suitable for experienced practitioners, Half Kelly for balanced risk-return optimization popular among professional traders, and Quarter Kelly for conservative approaches with reduced volatility. Display customization ensures optimal integration with your trading environment. Eight professional color themes provide optimization for different chart backgrounds and personal preferences. Table position selection allows optimal placement within your chart layout, while table size adjustment ensures readability across different screen resolutions and viewing preferences. Detailed Practical Examples Example 1: SPY Swing Trading Strategy Consider a professionally developed swing trading strategy for SPY (S&P 500 ETF) with backtesting results spanning 166 total trades. The strategy achieved 110 winning trades, representing a 66.3% win rate, with an average winning trade of $2,200 and average losing trade of $862. The maximum drawdown reached 31.4% during the testing period, and the available trading capital amounts to $25,000. This strategy employs discretionary exits without fixed stop losses. Implementation requires loading the calculator on the SPY daily chart and configuring the parameters accordingly. The win rate input receives 66.3, while average win and loss inputs receive 2200 and 862 respectively. Total historical trades input requires 166, with account size set to 25000. The stop loss function remains disabled due to the discretionary exit approach, with maximum strategy drawdown set to 31.4%. Half Kelly mode provides the optimal balance between growth and risk management for this application. The calculator generates several key outputs for this scenario. The risk-reward ratio calculates automatically to 2.55, while the Kelly fraction reaches approximately 53% before scientific adjustments. Sample confidence achieves 100% given the 166 trades providing high statistical confidence. The recommended position settles at approximately 27% after Half Kelly and Bayesian adjustment factors. Position value reaches approximately $6,750, translating to 16 shares at a $420 SPY price. Risk per trade amounts to approximately $2,110, representing 31.4% of position value, with expected value per trade reaching approximately $1,466. This recommendation represents the mathematically optimal balance between growth potential and risk management for this specific strategy profile. Example 2: EURUSD Day Trading with Stop Losses A high-frequency EURUSD day trading strategy demonstrates different parameter requirements compared to swing trading approaches. This strategy encompasses 89 total trades with a 58% win rate, generating an average winning trade of $180 and average losing trade of $95. The maximum drawdown reached 12% during testing, with available capital of $10,000. The strategy employs fixed stop losses at 25 pips and take profit targets at 45 pips, providing clear risk-reward parameters. Implementation begins with loading the calculator on the EURUSD 1-hour chart for appropriate timeframe alignment. Parameter configuration includes win rate at 58, average win at 180, and average loss at 95. Total historical trades input receives 89, with account size set to 10000. The stop loss function is enabled with distance set to 25 pips, reflecting the fixed exit strategy. Quarter Kelly mode provides conservative positioning due to the smaller sample size compared to the previous example. Results demonstrate the impact of smaller sample sizes on Kelly calculations. The risk-reward ratio calculates to 1.89, while the Kelly fraction reaches approximately 32% before adjustments. Sample confidence achieves 89%, providing moderate statistical confidence given the 89 trades. The recommended position settles at approximately 7% after Quarter Kelly application and Bayesian shrinkage adjustment for the smaller sample. Position value amounts to approximately $700, translating to 0.07 standard lots. Risk per trade reaches approximately $175, calculated as 25 pips multiplied by lot size and pip value, with expected value per trade at approximately $49. This conservative position sizing reflects the smaller sample size, with position sizes expected to increase as trade count surpasses 100 and statistical confidence improves. Example 3: ES1! Futures Systematic Strategy Systematic futures trading presents unique considerations for Kelly criterion application, as demonstrated by an E-mini S&P 500 futures strategy encompassing 234 total trades. This systematic approach achieved a 45% win rate with an average winning trade of $1,850 and average losing trade of $720. The maximum drawdown reached 18% during the testing period, with available capital of $50,000. The strategy employs 15-tick stop losses with contract specifications of $50 per tick, providing precise risk control mechanisms. Implementation involves loading the calculator on the ES1! 15-minute chart to align with the systematic trading timeframe. Parameter configuration includes win rate at 45, average win at 1850, and average loss at 720. Total historical trades receives 234, providing robust statistical foundation, with account size set to 50000. The stop loss function is enabled with distance set to 15 ticks, reflecting the systematic exit methodology. Half Kelly mode balances growth potential with appropriate risk management for futures trading. Results illustrate how favorable risk-reward ratios can support meaningful position sizing despite lower win rates. The risk-reward ratio calculates to 2.57, while the Kelly fraction reaches approximately 16%, lower than previous examples due to the sub-50% win rate. Sample confidence achieves 100% given the 234 trades providing high statistical confidence. The recommended position settles at approximately 8% after Half Kelly adjustment. Estimated margin per contract amounts to approximately $2,500, resulting in a single contract allocation. Position value reaches approximately $2,500, with risk per trade at $750, calculated as 15 ticks multiplied by $50 per tick. Expected value per trade amounts to approximately $508. Despite the lower win rate, the favorable risk-reward ratio supports meaningful position sizing, with single contract allocation reflecting appropriate leverage management for futures trading. Example 4: MES1! Micro-Futures for Smaller Accounts Micro-futures contracts provide enhanced accessibility for smaller trading accounts while maintaining identical strategy characteristics. Using the same systematic strategy statistics from the previous example but with available capital of $15,000 and micro-futures specifications of $5 per tick with reduced margin requirements, the implementation demonstrates improved position sizing granularity. Kelly calculations remain identical to the full-sized contract example, maintaining the same risk-reward dynamics and statistical foundations. However, estimated margin per contract reduces to approximately $250 for micro-contracts, enabling allocation of 4-5 micro-contracts. Position value reaches approximately $1,200, while risk per trade calculates to $75, derived from 15 ticks multiplied by $5 per tick. This granularity advantage provides better position size precision for smaller accounts, enabling more accurate Kelly implementation without requiring large capital commitments. Example 5: Bitcoin Swing Trading Cryptocurrency markets present unique challenges requiring modified Kelly application approaches. A Bitcoin swing trading strategy on BTCUSD encompasses 67 total trades with a 71% win rate, generating average winning trades of $3,200 and average losing trades of $1,400. Maximum drawdown reached 28% during testing, with available capital of $30,000. The strategy employs technical analysis for exits without fixed stop losses, relying on price action and momentum indicators. Implementation requires conservative approaches due to cryptocurrency volatility characteristics. Quarter Kelly mode is recommended despite the high win rate to account for crypto market unpredictability. Expected position sizing remains reduced due to the limited sample size of 67 trades, requiring additional caution until statistical confidence improves. Regular parameter updates are strongly recommended due to cryptocurrency market evolution and changing volatility patterns that can significantly impact strategy performance characteristics. Advanced Usage Scenarios Portfolio position sizing requires sophisticated consideration when running multiple strategies simultaneously. Each strategy should have its Kelly fraction calculated independently to maintain mathematical integrity. However, correlation adjustments become necessary when strategies exhibit related performance patterns. Moderately correlated strategies should receive individual position size reductions of 10-20% to account for overlapping risk exposure. Aggregate portfolio risk monitoring ensures total exposure remains within acceptable limits across all active strategies. Professional practitioners often consider using lower fractional Kelly approaches, such as Quarter Kelly, when running multiple strategies simultaneously to provide additional safety margins. Parameter sensitivity analysis forms a critical component of professional Kelly implementation. Regular validation procedures should include monthly parameter updates using rolling 100-trade windows to capture evolving market conditions while maintaining statistical relevance. Sensitivity testing involves varying win rates by ±5% and average win/loss ratios by ±10% to assess recommendation stability under different parameter assumptions. Out-of-sample validation reserves 20% of historical data for parameter verification, ensuring that optimization doesn't create curve-fitted results. Regime change detection monitors actual performance against expected metrics, triggering parameter reassessment when significant deviations occur. Risk management integration requires professional overlay considerations beyond pure Kelly calculations. Daily loss limits should cease trading when daily losses exceed twice the calculated risk per trade, preventing emotional decision-making during adverse periods. Maximum position limits should never exceed 25% of account value in any single position regardless of Kelly recommendations, maintaining diversification principles. Correlation monitoring reduces position sizes when holding multiple correlated positions that move together during market stress. Volatility adjustments consider reducing position sizes during periods of elevated VIX above 25 for equity strategies, adapting to changing market conditions. Troubleshooting and Optimization Professional implementation often encounters specific challenges requiring systematic troubleshooting approaches. Zero position size displays typically result from insufficient capital for minimum position sizes, negative expected values, or extremely conservative Kelly calculations. Solutions include increasing account size, verifying strategy statistics for accuracy, considering Quarter Kelly mode for conservative approaches, or reassessing overall strategy viability when fundamental issues exist. Extremely high Kelly fractions exceeding 50% usually indicate underlying problems with parameter estimation. Common causes include unrealistic win rates, inflated risk-reward ratios, or curve-fitted backtest results that don't reflect genuine trading conditions. Solutions require verifying backtest methodology, including all transaction costs in calculations, testing strategies on out-of-sample data, and using conservative fractional Kelly approaches until parameter reliability improves. Low sample confidence below 50% reflects insufficient historical trades for reliable parameter estimation. This situation demands gathering additional trading data, using Quarter Kelly approaches until reaching 100 or more trades, applying extra conservatism in position sizing, and considering paper trading to build statistical foundations without capital risk. Inconsistent results across similar strategies often stem from parameter estimation differences, market regime changes, or strategy degradation over time. Professional solutions include standardizing backtest methodology across all strategies, updating parameters regularly to reflect current conditions, and monitoring live performance against expectations to identify deteriorating strategies. Position sizes that appear inappropriately large or small require careful validation against traditional risk management principles. Professional standards recommend never risking more than 2-3% per trade regardless of Kelly calculations. Calibration should begin with Quarter Kelly approaches, gradually increasing as comfort and confidence develop. Most institutional traders utilize 25-50% of full Kelly recommendations to balance growth with prudent risk management. Market condition adjustments require dynamic approaches to Kelly implementation. Trending markets may support full Kelly recommendations when directional momentum provides favorable conditions. Ranging or volatile markets typically warrant reducing to Half or Quarter Kelly to account for increased uncertainty. High correlation periods demand reducing individual position sizes when multiple positions move together, concentrating risk exposure. News and event periods often justify temporary position size reductions during high-impact releases that can create unpredictable market movements. Performance monitoring requires systematic protocols to ensure Kelly implementation remains effective over time. Weekly reviews should compare actual versus expected win rates and average win/loss ratios to identify parameter drift or strategy degradation. Position size efficiency and execution quality monitoring ensures that calculated recommendations translate effectively into actual trading results. Tracking correlation between calculated and realized risk helps identify discrepancies between theoretical and practical risk exposure. Monthly calibration provides more comprehensive parameter assessment using the most recent 100 trades to maintain statistical relevance while capturing current market conditions. Kelly mode appropriateness requires reassessment based on recent market volatility and performance characteristics, potentially shifting between Full, Half, and Quarter Kelly approaches as conditions change. Transaction cost evaluation ensures that commission structures, spreads, and slippage estimates remain accurate and current. Quarterly strategic reviews encompass comprehensive strategy performance analysis comparing long-term results against expectations and identifying trends in effectiveness. Market regime assessment evaluates parameter stability across different market conditions, determining whether strategy characteristics remain consistent or require fundamental adjustments. Strategic modifications to position sizing methodology may become necessary as markets evolve or trading approaches mature, ensuring that Kelly implementation continues supporting optimal capital allocation objectives. Professional Applications This calculator serves diverse professional applications across the financial industry. Quantitative hedge funds utilize the implementation for systematic position sizing within algorithmic trading frameworks, where mathematical precision and consistent application prove essential for institutional capital management. Professional discretionary traders benefit from optimized position management that removes emotional bias while maintaining flexibility for market-specific adjustments. Portfolio managers employ the calculator for developing risk-adjusted allocation strategies that enhance returns while maintaining prudent risk controls across diverse asset classes and investment strategies. Individual traders seeking mathematical optimization of capital allocation find the calculator provides institutional-grade methodology previously available only to professional money managers. The Kelly Criterion establishes theoretical foundation for optimal capital allocation across both single strategies and multiple trading systems, offering significant advantages over arbitrary position sizing methods that rely on intuition or fixed percentage approaches. Professional implementation ensures consistent application of mathematically sound principles while adapting to changing market conditions and strategy performance characteristics. Conclusion The Kelly Criterion represents one of the few mathematically optimal solutions to fundamental investment problems. When properly understood and carefully implemented, it provides significant competitive advantage in financial markets. This calculator implements modern refinements to Kelly's original formula while maintaining accessibility for practical trading applications. Success with Kelly requires ongoing learning, systematic application, and continuous refinement based on market feedback and evolving research. Users who master Kelly principles and implement them systematically can expect superior risk-adjusted returns and more consistent capital growth over extended periods. The extensive academic literature provides rich resources for deeper study, while practical experience builds the intuition necessary for effective implementation. Regular parameter updates, conservative approaches with limited data, and disciplined adherence to calculated recommendations are essential for optimal results. References Archer, M. D. (2010). Getting Started in Currency Trading: Winning in Today's Forex Market (3rd ed.). John Wiley & Sons. Baker, R. D., & McHale, I. G. (2012). An empirical Bayes approach to optimising betting strategies. Journal of the Royal Statistical Society: Series D (The Statistician), 61(1), 75-92. Breiman, L. (1961). Optimal gambling systems for favorable games. In J. Neyman (Ed.), Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability (pp. 65-78). University of California Press. Brown, D. B. (1976). Optimal portfolio growth: Logarithmic utility and the Kelly criterion. In W. T. Ziemba & R. G. Vickson (Eds.), Stochastic Optimization Models in Finance (pp. 1-23). Academic Press. Browne, S., & Whitt, W. (1996). Portfolio choice and the Bayesian Kelly criterion. Advances in Applied Probability, 28(4), 1145-1176. Estrada, J. (2008). Geometric mean maximization: An overlooked portfolio approach? The Journal of Investing, 17(4), 134-147. Hakansson, N. H., & Ziemba, W. T. (1995). Capital growth theory. In R. A. Jarrow, V. Maksimovic, & W. T. Ziemba (Eds.), Handbooks in Operations Research and Management Science (Vol. 9, pp. 65-86). Elsevier. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Kaufman, P. J. (2013). Trading Systems and Methods (5th ed.). John Wiley & Sons. Kelly Jr, J. L. (1956). A new interpretation of information rate. Bell System Technical Journal, 35(4), 917-926. Lo, A. W., & MacKinlay, A. C. (1999). A Non-Random Walk Down Wall Street. Princeton University Press. MacLean, L. C., Sanegre, E. O., Zhao, Y., & Ziemba, W. T. (2004). Capital growth with security. Journal of Economic Dynamics and Control, 28(4), 937-954. MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific. Michaud, R. O. (1989). The Markowitz optimization enigma: Is 'optimized' optimal? Financial Analysts Journal, 45(1), 31-42. Pabrai, M. (2007). The Dhandho Investor: The Low-Risk Value Method to High Returns. John Wiley & Sons. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423. Tharp, V. K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill. Thorp, E. O. (2006). The Kelly criterion in blackjack sports betting, and the stock market. In L. C. MacLean, E. O. Thorp, & W. T. Ziemba (Eds.), The Kelly Capital Growth Investment Criterion: Theory and Practice (pp. 789-832). World Scientific. Van Tharp, K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill Education. Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons. Vince, R., & Zhu, H. (2015). Optimal betting under parameter uncertainty. Journal of Statistical Planning and Inference, 161, 19-31. Ziemba, W. T. (2003). The Stochastic Programming Approach to Asset, Liability, and Wealth Management. The Research Foundation of AIMR. Further Reading For comprehensive understanding of Kelly Criterion applications and advanced implementations: MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific. Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons. Thorp, E. O. (2017). A Man for All Markets: From Las Vegas to Wall Street. Random House. Cover, T. M., & Thomas, J. A. (2006). Elements of Information Theory (2nd ed.). John Wiley & Sons. Ziemba, W. T., & Vickson, R. G. (Eds.). (2006). Stochastic Optimization Models in Finance. World Scientific.
Penunjuk Pine Script®
oleh EdgeTools
The Daily Bias Dashboard📜 Overview This indicator is a powerful statistical tool designed to provide traders with a probable Daily Bias based on historical price action. It is built upon the concepts of Quarterly Theory, which divides the 24-hour trading day into 4 distinct sessions to analyze market behavior. This tool analyzes how the market has behaved in the past to give you a statistical edge. It answers the question: "Based on the last X number of days, what is the most likely way the price will move during the Newyork AM & PM Sessions based on Asian & London Sessions?" ⚙️ How It Works The indicator divides the 24-hour day (based on the America/New_York timezone) into two 12-hour halves: First Half - 12 Hour Candle: The Accumulation/Manipulation or Asian/London Sessions (6 PM to 6 AM NY Time) This period covers the Asian session and the start of the London session. The indicator's only job here is to identify the highest high and lowest low of this 12-hour block, establishing the initial daily range. Second Half - 12 Hour Candle: The Distribution/Continuation or NY AM/PM Sessions (6 AM to 6 PM NY Time) This period covers the main London session and the full New York session. The indicator actively watches to see if, and in what order, the price breaks out of the range established in Session 1 (FIrst Half of the day). By tracking this behavior over hundreds of days, the indicator compiles statistics on four possible daily scenarios. 📊 The Four Scenarios & The Dashboard The indicator presents its findings in a clean, easy-to-read dashboard, calculating the historical probability of each of the following scenarios: ↓ Low, then ↑ High: The price first breaks the low of Session 1 (often a liquidity sweep or stop hunt) before reversing to break the high of Session 1. This suggests a "sweep and reverse" bullish day. ↑ High, then ↓ Low: The price first breaks the high of Session 1 before reversing to break the low of Session 1. This suggests a "sweep and reverse" bearish day. One-Sided Breakout: The price breaks only one of the boundaries (either the high or the low) and continues in that direction without taking the other side. This indicates a strong, trending day. No Breakout (Inside Bar): The price fails to break either the high or the low of Session 1, remaining contained within its range. This indicates a day of consolidation and low volatility. 🧠 How to Use This Indicator This is a confluence tool, not a standalone trading system. Its purpose is to help you frame a high-probability narrative for the trading day. Establish a Bias: Start checking the dashboard at 06:00 AM Newyork time, which is the start of next half day trading session. If one scenario has a significantly higher probability (e.g., "One-Sided Breakout" at 89%), you have a statistically-backed directional bias in the direction of Breakout. 🔧 Features & Settings Historical Days to Analyze: Set how many past days the indicator should use for its statistical analysis (default is 500). Session Timezone : The calculation is locked to America/New_York as it is central to the Quarterly Theory concept, but this setting ensures correct alignment. Dashboard Display: Fully customize the on-screen table, including its position and text size, or hide it completely. ⚠️ Important Notes For maximum accuracy, use this indicator on hourly (H1) or lower timeframes. The statistical probabilities are based on past performance and are not a guarantee of future results. This tool is designed to sharpen your analytical skills and provide a robust, data-driven framework for your daily trading decisions. Use it to build confidence in your directional bias and to better understand the rhythm of the market. Disclaimer: This indicator is for educational and informational purposes only and does not constitute financial advice. All trading involves risk.
Penunjuk Pine Script®
oleh traderprimez
Armand.trade47This indicator automatically identifies high-probability swing highs and swing lows (potential tops and bottoms) in the market. It uses a combination of price action analysis and volatility filters to highlight key levels where the market has shown strong reactions in the past. The detected levels can act as potential support or resistance zones, offering traders an objective reference for trade planning. When price approaches one of these levels, traders can look for confirmation signals (such as candlestick patterns, momentum shifts, or volume spikes) to enter high-quality trades with a favorable risk-to-reward ratio. Main Features: • Automatic detection of recent and historical swing highs/lows. • Clearly plotted levels that update in real time. • Adjustable sensitivity to control how frequently new levels appear. • Works on all timeframes and asset classes (forex, crypto, stocks, indices). • Designed to be used in combination with confirmation signals, not as a standalone entry trigger. How to Use: 1. Wait for price to approach a marked swing high or swing low. 2. Observe the price reaction and look for confirmation patterns (e.g., pin bars, engulfing candles, divergence). 3. Place trades in line with your strategy, using the plotted level as a reference for stop-loss and take-profit placement. ⸻ If you want, I can also prepare a shorter, marketing-style version that sounds more catchy for the TradingView description so it grabs traders’ attention faster. That works really well in the script marketplace.
Penunjuk Pine Script®
oleh armandtrade47
Ai buy and sell fundamental the Gk fundamental is a precision built market analysis tool designed yto help traders identify high probability it uses a combination of market structure analysis, volatility tracking, and multi time frame confirmation to highlight possible trade opportunities HOW IT WORKS analyses momentum shift and structure breaks on the 2h chart for clearer direction confirms potential entries by filtering market noise and using volatility directional filters HOW TO USE apply 2h chart for primary direction when signal appears allow 1 candle to close for confirmation drop to lower time frame to lower time frame to refine entry if desired always use proper risk management - no tool guarantees results
Penunjuk Pine Script®
oleh hgavin780
IU Indicators DashboardDESCRIPTION The IU Indicators Dashboard is a comprehensive multi-stock monitoring tool that provides real-time technical analysis for up to 10 different stocks simultaneously. This powerful indicator creates a customizable table overlay that displays the trend status of multiple technical indicators across your selected stocks, giving you an instant overview of market conditions without switching between charts. Perfect for portfolio monitoring, sector analysis, and quick market screening, this dashboard consolidates critical technical data into one easy-to-read interface with color-coded trend signals. USER INPUTS Stock Selection (10 Configurable Stocks): - Stock 1-10: Customize any symbols (Default: NSE:CDSL, NSE:RELIANCE, NSE:VEDL, NSE:TCS, NSE:BEL, NSE:BHEL, NSE:TATAPOWER, NSE:TATASTEEL, NSE:ITC, NSE:LT) Technical Indicator Parameters: - EMA 1 Length: First Exponential Moving Average period (Default: 20) - EMA 2 Length: Second Exponential Moving Average period (Default: 50) - EMA 3 Length: Third Exponential Moving Average period (Default: 200) - RSI Length: Relative Strength Index calculation period (Default: 14) - SuperTrend Length: SuperTrend indicator period (Default: 10) - SuperTrend Factor: SuperTrend multiplier factor (Default: 3.0) Visual Customization: - Table Size: Choose from Normal, Tiny, Small, or Large - Table Background Color: Customize dashboard background - Table Frame Color: Set frame border color - Table Border Color: Configure border styling - Text Color: Set text display color - Bullish Color: Color for positive/bullish signals (Default: Green) - Bearish Color: Color for negative/bearish signals (Default: Red) LOGIC OF THE INDICATOR The dashboard employs a multi-timeframe analysis approach using five key technical indicators: 1. Triple EMA Analysis - Compares current price against three different EMA periods (20, 50, 200) - Bullish Signal: Price above EMA level - Bearish Signal: Price below EMA level - Provides short-term, medium-term, and long-term trend perspective 2. RSI Momentum Analysis - Uses 14-period RSI with 50-level threshold - Bullish Signal: RSI > 50 (upward momentum) - Bearish Signal: RSI < 50 (downward momentum) - Identifies momentum strength and potential reversals 3. SuperTrend Direction - Utilizes SuperTrend with configurable length and factor - Bullish Signal: SuperTrend direction = -1 (uptrend) - Bearish Signal: SuperTrend direction = 1 (downtrend) - Provides clear trend direction with volatility-adjusted signals 4. MACD Histogram Analysis - Uses standard MACD (12, 26, 9) histogram values - Bullish Signal: Histogram > 0 (bullish momentum) - Bearish Signal: Histogram < 0 (bearish momentum) - Identifies momentum shifts and trend confirmations 5. Real-time Data Processing - Implements request.security() for multi-symbol data retrieval - Uses barstate.isrealtime logic for accurate live data - Processes data only on the last bar for optimal performance WHY IT IS UNIQUE Multi-Stock Monitoring - Monitor up to 10 different stocks simultaneously on a single chart - No need to switch between multiple charts or timeframes Highly Customizable Interface - Full color customization for personalized visual experience - Adjustable table size and positioning - Clean, professional dashboard design Real-time Analysis - Live data processing with proper real-time handling - Instant visual feedback through color-coded signals - Optimized performance with smart data retrieval Comprehensive Technical Coverage - Combines trend-following, momentum, and volatility indicators - Multiple timeframe perspective through different EMA periods - Balanced approach using both lagging and leading indicators Flexible Configuration - Easy symbol switching for different markets (NSE, BSE, NYSE, NASDAQ) - Adjustable indicator parameters for different trading styles - Suitable for both swing trading and position trading HOW USERS CAN BENEFIT FROM IT Portfolio Management - Quick Portfolio Health Check: Instantly assess the technical status of your entire stock portfolio - Diversification Analysis: Monitor stocks across different sectors to ensure balanced exposure - Risk Management: Identify which positions are showing bearish signals for potential exit strategies - Rebalancing Decisions: Spot strongest performers for potential position increases Market Screening and Analysis - Sector Rotation: Compare different sector stocks to identify rotation opportunities - Relative Strength Analysis: Quickly identify which stocks are outperforming or underperforming - Market Breadth Assessment: Gauge overall market sentiment by monitoring diverse stock selections - Trend Confirmation: Validate market trends by observing multiple stock behaviors Time-Efficient Trading - Single-Glance Analysis: Get complete technical overview without chart-hopping - Pre-Market Preparation: Quickly assess overnight changes across multiple positions - Intraday Monitoring: Track multiple opportunities simultaneously during trading hours - End-of-Day Review: Efficiently review all watched stocks for next-day planning Strategic Decision Making - Entry Point Identification: Spot stocks showing bullish alignment across multiple indicators - Exit Signal Recognition: Identify positions showing deteriorating technical conditions - Swing Trading Opportunities: Find stocks with favorable technical setups for swing trades - Long-term Investment Guidance: Use 200 EMA signals for long-term position decisions Educational Benefits - Pattern Recognition: Learn how different indicators behave across various market conditions - Correlation Analysis: Understand how stocks move relative to each other - Technical Analysis Learning: Observe multiple indicator interactions in real-time - Market Sentiment Understanding: Develop better market timing skills through multi-stock observation Workflow Optimization - Reduced Chart Clutter: Keep your main chart clean while monitoring multiple stocks - Faster Analysis: Complete technical analysis of 10 stocks in seconds instead of minutes - Consistent Methodology: Apply the same technical criteria across all monitored stocks - Alert Integration: Easy visual identification of stocks requiring immediate attention This indicator is designed for traders and investors who want to maximize their market awareness while minimizing analysis time. Whether you're managing a portfolio, screening for opportunities, or learning technical analysis, the IU Indicators Dashboard provides the comprehensive overview you need for better trading decisions. DISCLAIMER : This indicator is not financial advice, it's for educational purposes only highlighting the power of coding( pine script) in TradingView, I am not a SEBI-registered advisor. Trading and investing involve risk, and you should consult with a qualified financial advisor before making any trading decisions. I do not guarantee profits or take responsibility for any losses you may incur.
Penunjuk Pine Script®
oleh Shivam_Mandrai
4
Candle OpenDescription: The Candle Open indicator automatically plots horizontal lines at the opening price of user-defined times throughout the trading day. Supports up to 7 customizable times, each with independent color, line style, and visibility controls. Flexible time input (e.g., 09:15, 915, noon, midnight). Lines extend from the selected time to the current candle, with optional labels. Option to remove lines from previous days for a clean chart. Global controls for line width and label size. Works across different time zones. Disclaimer: This indicator is for educational and informational purposes only. It does not provide financial advice or trading signals. The author is not responsible for any trades, losses, or decisions made based on the use of this tool. Always do your own research and trade at your own risk.
Penunjuk Pine Script®
oleh Pinnacle_Trader
SulLaLuna — HTF M2 x Ultimate BB (Fusion) 🌕 **SulLaLuna — HTF M2 x Ultimate BB (Fusion)** 🚀💵 **By SulLaLuna Trading** (Portions of the Bollinger Band logic adapted with permission/credit from the *Ultimate Buy & Sell Indicator* by its original author — thank you for the brilliance!) --- 🧭 **What This Is** This is not just another price-following tool. This is **a macro liquidity detector** — a **Daily Higher Timeframe Hull Moving Average of the Global M2 Money Supply**, smoothed via lower timeframe candles (default 5m, 48 Hull length), overlaid with **Ultimate-style double Bollinger Bands** to reveal *over-extension & mean reversion zones*. It doesn’t chase candles. It watches the tides beneath the market — the **money supply currents** that have a **direct correlation** to asset price behavior. When liquidity expands → risk-on assets tend to rise. When liquidity contracts → risk-off waves hit. We ride those waves. --- 🔍 **What It Does** * **Tracks Global M2** across major economies, FX-adjusted, and scales it to your chart’s price. * **HTF Hull MA** (Daily, smoothed via 5m base) → gives you the macro liquidity trend. * **Ultimate BB logic** applied to the HTF M2 Hull → inner/outer bands for volatility envelopes. * **Pivot Labels** → ideal entry/exit zones on macro turns. * **Over-Extension Alerts** → when HTF M2 Hull pushes outside the outer bands. * **Re-Entry Alerts** → mean reversion triggers when liquidity moves back inside the range. * **Background Paint** from chart TF M2 slope → for confluence on your entry timeframe. --- 📜 **Suggested How-To** 1. **Choose your execution chart** — e.g., 1–15m for scalps, 1H–4H for swings. 2. **Use the background paint** as your *local tide check* (chart TF M2 slope). 3. **Trade in the direction of the HTF M2 Hull** — green line = liquidity rising, red line = liquidity falling. 4. **Watch pivot labels** — these are potential “macro inflection” points. 5. **Confluence stack** — pair with ZLSMA, WaveTrend divergences, VWAP volume, or your favorite price-action setups. 6. **Size down** when HTF M2 Hull is flat/gray (chop zone). 7. **Scale in/out** on over-extension + re-entry alerts for higher probability swings. --- ⚠️ **Important Note** This indicator **does not predict price** — it tracks macro liquidity flows that *influence* price. Think of it as your market’s **tide chart**: when the water’s coming in, you can swim out; when it’s going out, you’d better be ready for the undertow. --- 📢 **Alerts Available** * HTF Pivot HIGH / LOW * Over-Extension (HTF Hull outside outer BB) * Re-Entry (return from overbought/oversold) --- 🤝 **Join the SulLaLuna Tribe** If this indicator helps you capture better entries, follow & share so more traders can learn to trade *math, not emotion*. We rise together — **and we’ll meet you on the Moon** 🌕🚀💵.
Penunjuk Pine Script®
oleh Calzolaio
Unmitigated Imbalances [TakingProphets] (High Timeframe)Unmitigated Imbalances Unmitigated Imbalance is designed to automatically detect and display active Fair Value Gaps (FVGs) across multiple higher timeframes and your current chart. It only keeps the ones that remain unmitigated, helping you clearly see where price has “unfinished business” and potential liquidity draw areas. The tool extends these levels forward until they are tagged according to your chosen mitigation criteria, then removes them automatically. The indicator uses the classic 3-bar FVG structure: – Bearish FVG forms when the low of the third candle back is above the high of the first candle. – Bullish FVG forms when the high of the third candle back is below the low of the first candle. – Each detected gap must meet a minimum size threshold, which is determined automatically from the Sensitivity setting and adjusted for the symbol type. Higher timeframes (up to 4) can be plotted simultaneously with your current chart’s gaps. The script merges overlapping levels from different timeframes into one clean label, showing all the contributing timeframes together (for example: M15 + H1 + H4). This makes it easy to spot high-confluence levels without cluttering your chart. Key features – Multi-timeframe detection: up to 4 custom HTFs plus your current chart. – Automatic gap size filtering based on chosen Sensitivity (High, Medium, Low). – Choice of Wick or Close-based mitigation logic. – Lookback control: 1 Day, 1 Week, 1 Month, or Max. – Combined labels for overlapping gaps with clear timeframe tags. – Separate color and style settings for each timeframe’s bullish and bearish gaps. – Labels can be positioned Left, Right, or Center Above for maximum clarity. – Automatic line extension until mitigation or until they exceed the lookback period. How to use Select your desired higher timeframes in the HTF1–HTF4 settings. Choose the Sensitivity level to control the minimum gap size detected. Decide on Wick or Close mitigation according to your trading rules. Use the Lookback setting to limit how far back the script checks for gaps. Watch for levels where multiple timeframe labels are stacked — these can carry greater significance. Incorporate the levels into your existing strategy, using them as context rather than entry signals. Practical notes – Current timeframe gaps reset each trading day to keep the chart relevant to intraday bias. – Higher timeframe gaps remain until mitigated or until the lookback period expires. – Large lookback periods with multiple HTFs can increase chart load — adjust settings as needed. – This indicator is a mapping and context tool, not a signal generator. Always apply it alongside your own analysis.
Penunjuk Pine Script®
oleh TakingProphets
Bharat Jhunjhunwala - RSI Cross Trading SignalRSI Crossover Indicator This custom indicator uses the Relative Strength Index (RSI) to generate precise buy and sell signals based on momentum shifts. The strategy works as follows: Buy Signal: Triggered when: The Daily RSI is above 50, indicating bullish market conditions. The Hourly RSI crosses above 70, signaling a strong upward momentum. Sell Signal: Triggered when: The Daily RSI is below 50, indicating bearish market conditions. The Hourly RSI crosses below 30, signaling potential downward momentum. The indicator plots green up arrows for buy signals and red down arrows for sell signals, making it ideal for traders looking to trade momentum shifts with clarity.
Penunjuk Pine Script®
oleh BharatJhunjhunwala
Shubh Labh - Buy Sell Signal IndicatorThe Signal created from this Indicator is merely for educational and informational purposes. Should you decide to act upon the signals posted from this Indicator, you do so at your own risk. While the Indicator has been created & the outcome has been verified to the best of our abilities, we cannot guarantee that there are no mistakes or errors. It is not intended as a substitute for professional advice. Please seek the professional advise before taking any trading / investment decision.
Penunjuk Pine Script®
oleh ShubhLabhFinserve
Minimal S/R Zones with Volume StrengthHow it works Pivot Detection A pivot high is a candle whose high is greater than the highs of a certain number of candles before and after it. A pivot low is a candle whose low is lower than the lows of a certain number of candles before and after it. Parameters like Pivot Left Bars and Pivot Right Bars control how sensitive the pivots are. Zone Creation Pivot High → creates a Resistance zone. Pivot Low → creates a Support zone. Each zone is defined as a price range (top and bottom) and drawn horizontally for a given lookback length. Volume Strength Filter Volume Strength (%) = (Volume at Pivot / Volume SMA) × 100. If the strength is below the minimum threshold (Min Strength %), the zone is ignored. This ensures only pivots with significant trading activity create zones. Zone Management The indicator stores zones in arrays. Max Zones per side prevents too many zones from being displayed at once. Older zones are removed when new ones are added beyond the limit. Visuals Support zones → green label with Volume Strength %. Resistance zones → red label with Volume Strength %. Zones have semi-transparent boxes so price action remains visible.
Penunjuk Pine Script®
oleh tai239