Commencez

Bandes et canaux

Wahrscheinlichkeits-OszillatorWhat the Indicator Measures (Short Version) The indicator measures, over several different time windows (eight different historyLength values), the probability that the current indicator value (here, a 14-period SMA of the closing price) is higher than past values in that window. These probabilities (named prob1 … prob8) are expressed as percentages (0–100). The arithmetic mean of these eight percentages is avgLine. Additionally, there are smoothings (SMMA) and a baseline (SMA of avgLine), similar to Bollinger Bands. Step-by-Step: How the Values Are Calculated Source: sma_val = ta.sma(close, 14) → This is the 14-period simple moving average of the closing price. This smoothed price is used as the "current comparison value" (instead of raw close) to reduce noise. Historical Array & Counting (Function calculateProbability) For each probX, the function maintains an array of the most recently stored current values (up to historicalLength entries). For the current sma_val, it counts how many entries in the historical array are smaller than current. Then this number is divided by the total number of historical entries → result is a decimal between 0 and 1. Multiplying by 100 gives probX in percent. Mathematical (Pseudo): ini Kopieren Bearbeiten prob = (1 / total) * sum_{i=0}^{total-1} [ current > historical ] * 100 → This is equivalent to the empirical percentile/rank position of the current value within the history. Eight Windows / Ensemble: prob1 … prob8 are calculated with different historyLength values (400, 350, 175, 130, 83, 42, 21, 15). Longer windows measure “long-term” trend strength; shorter windows measure short-term relative strength/momentum. avgLine: ini Kopieren Bearbeiten avgLine = (prob1 + ... + prob8) / 8 → Ensemble average of all eight percentiles. Useful for smoothing extreme values from individual windows. Smoothing (SMMA): SMMA on prob1 and SMMA1 on avgLine reduce short-term fluctuations and make signals more stable. Baseline & “Bands”: Finally, basis = ta.sma(avgLine, length) and dev = mult * ta.stdev(avgLine, length) are calculated — this is exactly the baseline + band logic of a Bollinger-style representation, applied to avgLine. Why It’s Meaningful Percentiles/ranks are robust to scale changes. Instead of absolute price differences, the indicator answers: “Is the current (smoothed) price higher than usual over the last N periods?” The ensemble of multiple window lengths captures different market regimes: short windows react quickly to momentum, long windows provide context and reduce false signals. Smoothing (SMA/SMMA) reduces noise, making signals less sensitive to intraday jitter. Interpretation: When Is the Market “Overheated” / “Not Overheated”? High values (e.g., avgLine ≈ 80–100 or individual probX > 90): The current SMA is higher than almost all previous values in the considered window → strong bullish dominance. This can indicate a strong rally (momentum), but also potential overbought conditions, especially if: Volume growth is slowing, or avgLine has remained very high for several periods (overextension). Low values (e.g., avgLine ≈ 0–20): The current SMA is below most of the historical values → market is under pressure or potentially oversold. Short-term reversal/recovery opportunities are more likely, especially if multiple windows are simultaneously low. Values around ~50: Neutral — the current value is typical, in the middle of its historical distribution. Concrete Rule (Your Specification): Buy / Sell Buy Signal: When all eight lines (prob1 … prob8) are below lowerLine (e.g., lowerLine = 20). → Meaning: In all short- to long-term windows, the current SMA is below most historical values → strong, broadly confirmed undervaluation signal (potential rebound or end of correction). Recommendation: Strong convergent long signal, especially if accompanied by volume increase or support confirmation. Sell Signal: When all eight lines are above upperLine (e.g., upperLine = 90). → Meaning: In all windows, the current SMA is higher than almost all historical values → broadly confirmed overbought / overheating. Recommendation: Strong convergent short/take-profit signal, especially if coinciding with divergences, weakening volume, or resistance areas. Important Limitations & Risks (Pay Attention!) Trend vs. Mean-Reversion: In a strong trend, all windows can stay high for a long time (trend continuation risk). An “all below lower → buy” signal can continue to fall in a strong downtrend → use stop-loss and trend filter (higher TF). Historical Length & Sampling: Chosen historyLength values determine sensitivity. Very long windows make the indicator slower; very short windows increase noise. Statistical Stationarity: Percentile signals assume the distribution remains comparable — in crashes/news events, distributions can break. Smoothing / Lag: SMMA reduces false breakouts but adds delay — trade entries may occur later. Practical Examples (Concrete) Example Buy: prob1..prob8 = , lowerLine = 20 → all below 20 → strong long signal. Example Sell: prob1..prob8 = , upperLine = 90 → all above 90 → take-profit / short signal. Conclusion (Short) Your indicator is a percentile/ranking oscillator over multiple windows — a robust ensemble measuring the relative position of the (smoothed) price to its own history. Overheated = high, broadly confirmed prob values (e.g., all > upperLine). Oversold = low, broadly confirmed prob values (e.g., all < lowerLine) → your rule: all below lowerLine = buy, all above upperLine = sell. Never trade blindly — always use risk management and confirmation (volume, higher timeframes, structure).
Indicateur Pine Script®
par kultr
Auto-Anchored MA with Deviation BandsAuto-Anchored MA with Deviation Bands ✨ Features 📈 Auto-Anchored MA: Calculates moving averages (EMA, SMA, EWMA, WMA, VWAP, TEMA) anchored to user-defined periods (Hour, Day, Week, etc.).📏 Deviation Bands: Plots upper/lower bands using Percentage or Standard Deviation modes for volatility analysis.⚙️ Customizable Timeframes: Choose anchor periods from Hour to Year for flexible trend analysis.🎨 Visuals: Displays MA and bands with gradient fills, customizable colors, and adjustable display bars.⏱️ Countdown Table: Shows bars since the last anchor for easy tracking.🛠️ Smoothing: Applies smoothing to bands for cleaner visuals. 🛠️ How to Use Add to Chart: Apply the indicator on TradingView. Configure Inputs: Anchor Settings: Select anchor period (e.g., Day, Week). MA Settings: Choose MA type (e.g., VWAP, TEMA). Deviation Settings: Set deviation mode (Percentage/Std Dev) and multipliers. Display Settings: Adjust bars to display, colors, and gradient fill. Analyze: View MA, deviation bands, and countdown table on the chart. Track Trends: Use bands as dynamic support/resistance and monitor anchor resets. 🎯 Why Use It? Dynamic Analysis: Auto-anchors MA to key timeframes for adaptive trend tracking. Volatility Insight: Deviation bands highlight potential breakouts or reversals. Customizable: Tailor MA type, timeframe, and visuals to your trading style. User-Friendly: Clear visuals and countdown table simplify analysis. 📝 Notes Ensure sufficient bars for accurate MA and deviation calculations. Gradient fill enhances readability but can be disabled for simplicity. Best used with complementary indicators like RSI or Bollinger Bands for robust strategies. Happy trading! 🚀📈
Indicateur Pine Script®
par AlchimistOfCrypto
SMC + FVG + EMA + TrendlinesSMC + FVG + EMA + Trendlines legRange = math.abs(structureHigh - structureLow) // <-- เปลี่ยนชื่อจาก range -> legRange if showCurrentStruct and not na(structureHigh) and not na(structureLow) if na(curHighLine) == false line.delete(curHighLine) if na(curLowLine) == false line.delete(curLowLine) curHighLine := line.new(sHighIdx, structureHigh, bar_index, structureHigh, xloc.bar_index, color=currentStructColor, style=currentStructStyle, width=currentStructWidth) curLowLine := line.new(sLowIdx, structureLow, bar_index, structureLow, xloc.bar_index, color=currentStructColor, style=currentStructStyle, width=currentStructWidth) // ---------- Fibonacci on current leg ---------- if showFibo and legRange > 0 for k = 0 to array.size(fLevels) - 1 lvl = array.get(fLevels, k) price = sDir == 1 ? structureHigh - (legRange - legRange * lvl) : structureLow + (legRange - legRange * lvl) l = line.new(sDir == 1 ? sHighIdx : sLowIdx, price, bar_index, price, xloc.bar_index, color=fiboColorMain, style=fiboStyle, width=fiboWidth) label.new(bar_index + 10, price, str.tostring(lvl) + " (" + str.tostring(price) + ")", style=label.style_none, textcolor=fiboColorMain)
Indicateur Pine Script®
par bxztty
PCV (Darren.L-V2)Description: This indicator combines Bollinger Bands, CCI, and RVI to help identify high-probability zones on M15 charts. Features: Bollinger Bands (BB) – displayed on the main chart in light gray. Helps visualize overbought and oversold price levels. CCI ±100 levels + RVI – displayed in a separate sub-window: CCI only shows the ±100 reference lines. RVI displays a cyan main line and a red signal line. Valid Zone Detection: Candle closes outside the Bollinger Bands. RVI crosses above +100 or below -100 (CCI level reference). Candle closes back inside the BB, confirming a price rebound. Requires two touches in the same direction to confirm the zone. Only zones within 20–30 pips range are considered valid. Usage: Helps traders spot reversal or bounce zones with clear visual signals. Suitable for all indices, Forex, and crypto on M15 timeframe.
Indicateur Pine Script®
par lawwaikean
Hilly's Advanced Crypto Scalping Strategy - 5 Min ChartTo determine the "best" input parameters for the Advanced Crypto Scalping Strategy on a 5-minute chart, we need to consider the goals of optimizing for profitability, minimizing false signals, and adapting to the volatile nature of cryptocurrencies. The default parameters in the script are a starting point, but the optimal values depend on the specific cryptocurrency pair, market conditions, and your risk tolerance. Below, I'll provide recommended input values based on common practices in crypto scalping, along with reasoning for each parameter. I’ll also suggest how to fine-tune them using TradingView’s backtesting and optimization tools. Recommended Input Parameters These values are tailored for a 5-minute chart for liquid cryptocurrencies like BTC/USD or ETH/USD on exchanges like Binance or Coinbase. They aim to balance signal frequency and accuracy for day trading. Fast EMA Length (emaFastLen): 9 Reasoning: A 9-period EMA is commonly used in scalping to capture short-term price movements while remaining sensitive to recent price action. It reacts faster than the default 10, aligning with the 5-minute timeframe. Slow EMA Length (emaSlowLen): 21 Reasoning: A 21-period EMA provides a good balance for identifying the broader trend on a 5-minute chart. It’s slightly longer than the default 20 to reduce noise while confirming the trend direction. RSI Length (rsiLen): 14 Reasoning: The default 14-period RSI is a standard choice for momentum analysis. It works well for detecting overbought/oversold conditions without being too sensitive on short timeframes. RSI Overbought (rsiOverbought): 75 Reasoning: Raising the overbought threshold to 75 (from 70) reduces false sell signals in strong bullish trends, which are common in crypto markets. RSI Oversold (rsiOversold): 25 Reasoning: Lowering the oversold threshold to 25 (from 30) filters out weaker buy signals, ensuring entries occur during stronger reversals. MACD Fast Length (macdFast): 12 Reasoning: The default 12-period fast EMA for MACD is effective for capturing short-term momentum shifts in crypto, aligning with scalping goals. MACD Slow Length (macdSlow): 26 Reasoning: The default 26-period slow EMA is a standard setting that works well for confirming momentum trends without lagging too much. MACD Signal Smoothing (macdSignal): 9 Reasoning: The default 9-period signal line is widely used and provides a good balance for smoothing MACD crossovers on a 5-minute chart. Bollinger Bands Length (bbLen): 20 Reasoning: The default 20-period Bollinger Bands are effective for identifying volatility breakouts, which are key for scalping in crypto markets. Bollinger Bands Multiplier (bbMult): 2.0 Reasoning: A 2.0 multiplier is standard and captures most price action within the bands. Increasing it to 2.5 could reduce signals but improve accuracy in highly volatile markets. Stop Loss % (slPerc): 0.8% Reasoning: A tighter stop loss of 0.8% (from 1.0%) suits the high volatility of crypto, helping to limit losses on false breakouts while keeping risk manageable. Take Profit % (tpPerc): 1.5% Reasoning: A 1.5% take-profit target (from 2.0%) aligns with scalping’s goal of capturing small, frequent gains. Crypto markets often see quick reversals, so a smaller target increases the likelihood of hitting profits. Use Candlestick Patterns (useCandlePatterns): True Reasoning: Enabling candlestick patterns (e.g., engulfing, hammer) adds confirmation to signals, reducing false entries in choppy markets. Use Volume Filter (useVolumeFilter): True Reasoning: The volume filter ensures signals occur during high-volume breakouts, which are more likely to sustain in crypto markets. Signal Arrow Size (signalSize): 2.0 Reasoning: Increasing the arrow size to 2.0 (from 1.5) makes buy/sell signals more visible on the chart, especially on smaller screens or volatile price action. Background Highlight Transparency (bgTransparency): 85 Reasoning: A slightly higher transparency (85 from 80) keeps the background highlights subtle but visible, avoiding chart clutter. How to Apply These Parameters Copy the Script: Use the Pine Script provided in the previous response. Paste in TradingView: Open TradingView, go to the Pine Editor, paste the code, and click "Add to Chart." Set Parameters: In the strategy settings, manually input the recommended values above or adjust them via the input fields. Test on a 5-Minute Chart: Apply the strategy to a liquid crypto pair (e.g., BTC/USDT, ETH/USDT) on a 5-minute chart. Fine-Tuning for Optimal Performance To find the absolute best parameters for your specific trading pair and market conditions, use TradingView’s Strategy Tester and optimization features: Backtesting: Run the strategy on historical data for your chosen pair (e.g., BTC/USDT on Binance). Check metrics like Net Profit, Profit Factor, Win Rate, and Max Drawdown in the Strategy Tester. Focus on a sample period of at least 1–3 months to capture various market conditions (bull, bear, sideways). Parameter Optimization: In the Strategy Tester, click the settings gear next to the strategy name. Enable optimization for key inputs like emaFastLen (test range: 7–12), emaSlowLen (15–25), slPerc (0.5–1.5), and tpPerc (1.0–3.0). Run the optimization to find the combination with the highest net profit or best Sharpe ratio, but avoid over-optimization (curve-fitting) by testing on out-of-sample data. Market-Specific Adjustments: Volatile Pairs (e.g., DOGE/USDT): Use tighter stop losses (e.g., 0.5–0.7%) and smaller take-profit targets (e.g., 1.0–1.2%) to account for rapid price swings. Stable Pairs (e.g., BTC/USDT): Slightly wider stop losses (e.g., 1.0–1.2%) and take-profit targets (e.g., 1.8–2.5%) may work better. Trending Markets: Increase emaSlowLen (e.g., to 25–30) to follow stronger trends. Choppy Markets: Tighten bbMult (e.g., to 1.8) and lower rsiOverbought/rsiOversold (e.g., to 70/30) to filter noise. Forward Testing: After backtesting, run the strategy in real-time on a demo account for 1–2 weeks to validate performance under current market conditions. Important Notes No Universal "Best" Numbers: Optimal parameters vary by crypto pair, exchange, and market conditions (e.g., bull vs. bear market). The suggested values are a starting point based on common scalping practices. Risk Management: Never risk more than 1–2% of your account per trade. Adjust position sizing in TradingView’s strategy settings to align with your risk tolerance. Market Volatility: Crypto markets are highly volatile. Test the strategy on your specific pair and adjust parameters if signals are too frequent or too rare. Not Financial Advice: This is an educational tool. Backtest thoroughly and use a demo account before trading with real funds. If you want me to generate a chart showing backtest performance for specific parameters or to tweak the script further (e.g., adding more indicators or adjusting signal logic), let me know!can you add clear buy ans sell signs above the candles in this codeTo add clear buy and sell signals above the candles in the provided Pine Script, I'll modify the existing code to include prominent text labels directly above (for sell signals) and below (for buy signals) the candles. These labels will be larger, color-coded, and positioned to avoid clutter, ensuring they are easily visible on the chart. The core strategy logic (EMA, RSI, MACD, Bollinger Bands, candlestick patterns, and volume filter) will remain unchanged, and I'll reuse the same artifact_id since this is an update to the previous script.AdvancedCryptoScalpingStrategy.pinex-pine
Stratégie Pine Script®
par Hilly1976
On-Chain Metrics & Z-Mode SelectionThis indicator provides an on-chain metric analysis framework for cryptocurrencies (currently limited to) BTC and ETH; allowing users to select from popular metrics such as SOPR, Profit Addresses %, NUPL, or MVRV. It enables various analyses on the chosen metric to capture momentum and rate of change dynamics over time. Analyses include: Normalization techniques utilizing Mean or Median with standard deviation, as well as a 'Robust' method using interquartile range-based Z-scoring to accommodate skewed distributions, or raw values without normalization. An optional differential calculation that highlights the rate of change (first derivative) of the metric. Moving average smoothing with up to two passes, supporting EMA, SMA, or WMA types. Optional sigmoid-based compression that scales and centers the indicator output, improving interpretability, mitigating extreme outliers, and allowing the user to scale the output so that the step size or increment of the long and short thresholds remains within a workable range. Buy and sell signals are generated based on configurable long and short thresholds applied to the processed output. Visual components such as trend colouring, threshold lines, background shading, and labels make it simple for traders to identify entry signals. This indicator is suitable for those looking to integrate blockchain behavioral insights into their trading decisions. Overall, this script transforms complex on-chain data into actionable trade signals by combining adaptive normalization and smoothing techniques. Its versatility and multi-metric support make it a valuable tool for both market monitoring and strategy development. No financial decisions should be made based solely on this indicator. Always conduct your own research. . Acknowledgements Inspiration drawn from: CipherDecoded
Indicateur Pine Script®
par Conradious
Adaptive Open InterestThis indicator analyzes Bitcoin open interest to identify overbought and oversold conditions that historically precede major price moves. Unlike static levels, it automatically adapts to current market conditions by analyzing the last 320 bars (user adjustable). How It Works Adaptive Algorithm: -Analyzes the last 320 bars of open interest data -Combines percentile analysis (90th, 80th, 20th, 10th percentiles) with statistical analysis (standard deviations) -Creates dynamic zones that adjust as market conditions change Four Key Zones: 🔴 Extreme Overbought (Red) - Major crash risk territory 🟠 Overbought (Orange) - Correction risk territory 🔵 Oversold (Blue) - Opportunity territory 🟢 Extreme Oversold (Green) - Major opportunity territory For Risk Management: -When OI enters red zones → Consider reducing long positions, major crash risk -When OI enters orange zones → Caution, correction likely incoming For Opportunities: -When OI enters blue zones → Look for long opportunities -When OI enters green zones → Strong buying opportunity, major bounce potential The Table Shows: -Current status (which zone OI is in) -Range position (where current OI sits as % of 320-bar range) -320-bar high/low levels for context Why It's Effective: -Adaptive Nature: What's "high" OI in a bear market differs from bull market - the indicator knows the difference and adjusts automatically. -Proven Approach: Combines multiple statistical methods for robust signals that work across different market cycles. -Alert System: Optional alerts notify you when OI crosses critical thresholds, so you don't miss important signals. -The indicator essentially tells you when the futures market is getting "too crowded" (danger) or "too empty" (opportunity) relative to recent history.
Indicateur Pine Script®
par s3raphic333