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ATR-Multiple from 50SMAThis indicator provides a nuanced view of price extension by calculating the distance between the current price and its 50-period Simple Moving Average. This distance is not measured in simple percentage terms but is quantified in multiples of the Average True Range (ATR), offering a volatility-adjusted perspective on how far an asset has moved from its mean. The primary goal is to help traders identify potentially overextended conditions, which can often precede price consolidation or reversals. As a general guideline, when an asset's price stretches to multiples of 7 ATRs or more above its 50-day SMA, it often enters a zone where significant profit-taking may occur. By visualizing this extension, the indicator can serve as a powerful tool for gauging when to consider taking profits on existing long positions. Furthermore, it can act as a cautionary signal, helping traders avoid initiating new long positions in assets that are already significantly stretched and may be poised for a pullback. Features Volatility-Adjusted Extension Measures the distance from the 50 SMA in terms of ATR multiples, providing a more standardized way to compare extension across different assets and time periods. Daily Timeframe Consistency By default, the indicator uses the daily SMA and ATR for its calculations, regardless of the chart's current timeframe. This ensures a consistent and meaningful measure of extension rooted in the daily trend. Histogram Visualization Displays the result as a clear histogram in a separate pane, making it easy to track the extension level over time and identify historical extremes. Dynamic Color-Coding The histogram bars are color-coded to visually highlight different levels of extension. The colors shift as the price moves further from the mean, providing an intuitive at-a-glance reading. Key Threshold Markers Includes pre-set horizontal lines at the 7 and 10 ATR multiples to clearly mark the zones of potential profit-taking and extreme extension, respectively. Built-in Alerts Comes with configurable alert conditions that can notify you when the price reaches the "profit-taking" threshold (7 ATRs) or the "extreme extension" threshold (10 ATRs). Customization Options MA & ATR Periods You can adjust the length for the Simple Moving Average (default 50) and the Average True Range (default 14) to suit your specific analytical needs. Timeframe Source A toggle allows you to switch between always calculating using daily data (the default and recommended setting) or using the data from the current chart's timeframe. Color Display Style You can choose between a smooth color gradient that transitions elegantly with the extension level or a distinct, step-based color display for a clearer visual separation of the defined zones. Full Color Scheme Control Every visual element is fully customizable. You can change the colors for the regular extension, the "get ready," "profit-taking," and "extreme" levels, as well as the horizontal reference lines.
Indicatore Pine Script®
di shftd
Fibonacci Entry Bands [AlgoAlpha]OVERVIEW This script plots Fibonacci Entry Bands, a trend-following and mean-reversion hybrid system built around dynamic volatility-adjusted bands scaled using key Fibonacci levels. It calculates a smoothed basis line and overlays multiple bands at fixed Fibonacci multipliers of either ATR or standard deviation. Depending on the trend direction, specific upper or lower bands become active, offering a clear framework for entry timing, trend identification, and profit-taking zones. CONCEPTS The core idea is to use Fibonacci levels—0.618, 1.0, 1.618, and 2.618—as multipliers on a volatility measure to form layered price bands around a trend-following moving average. Trends are defined by whether the basis is rising or falling. The trend determines which side of the bands is emphasized: upper bands for downtrends, lower bands for uptrends. This approach captures both directional bias and extreme price extensions. Take-profit logic is built in via crossovers relative to the outermost bands, scaled by user-selected aggressiveness. FEATURES Basis Line – A double EMA smoothing of the source defines trend direction and acts as the central mean. Volatility Bands – Four levels per side (based on selected ATR or stdev) mark the Fibonacci bands. These become visible only when trend direction matches the side (e.g., only lower bands plot in an uptrend). Bar Coloring – Bars are shaded with adjustable transparency depending on distance from the basis, with color intensity helping gauge overextension. Entry Arrows – A trend shift triggers either a long or short signal, with a marker at the outermost band with ▲/▼ signs. Take-Profit Crosses – If price rejects near the outer band (based on aggressiveness setting), a cross appears marking potential profit-taking. Bounce Signals – Minor pullbacks that respect the basis line are marked with triangle arrows, hinting at continuation setups. Customization – Users can toggle bar coloring, signal markers, and select between ATR/stdev as well as take-profit aggressiveness. Alerts – All major signals, including entries, take-profits, and bounces, are available as alert conditions. USAGE To use this tool, load it on your chart, adjust the inputs for volatility method and aggressiveness, and wait for entries to form on trend changes. Use TP crosses and bounce arrows as potential exit or scale-in signals.
Indicatore Pine Script®
di AlgoAlpha
8
RSI Divergence StrategyOverview The RSI Divergence Strategy Indicator is a trading tool that uses the RSI and divergences created to generate high-probability buy and sell signals. I have provided the best formula of numbers to use for BTC on a 30 minute timeframe. You can change where on RSI you enter and exit both long or short trades. This way you can experiment on different tokens using different entry/exit points. Can use on multiple timeframes. This strategy is designed to open and close long or short trades based on the levels you provide it. You can then check on the RSI where the best levels are for each token you want to trade and amend it as required to generate a profitable strategy. How It Works The RSI Divergence Strategy Indicator uses bear and bull divergences in conjuction with a level you have input on the RSI. RSI for Overbought/Oversold: • Input variables for entry and exit levels and when the entry levels combine with a bear or bull divergence signal, a trade is alerted. RSI Divergence: • Buy and sell signals are confirmed when the RSI creates bearish or bullish divergences and these divergences are in the same area as your levels you input for entry to short or long. After 7 years of experience and testing I have calculated the exact numbers required and produced a formula to calculate the exact input variables for a 30 minute Bitcoin chart. Key Features 1️⃣ Divergence Identification – Ensures trades are taken only when a bull or bear divergence has formed. 2️⃣ Overbought/Oversold Input Filtering – Set up your own variables on the RSI for different markets after identifying patterns on the RSI in relation to a bearish or bullish divergence. 3️⃣ Works on any chart – Suitable for all markets and timeframes once you input the correct variables for entry and exit levels. How to Use 🟢 Basic Trading: • Use on any timeframe. • Enter trade only when alert has fired off. Close when it says to exit. • Change entry and exit levels in the properties of the strategy indicator. • Make entry and exit levels coincide with bearish or bullish divergences on the RSI. Check the strategy tester to see backtesting so you know if the indicator is profitable or not for that market and timeframe as each crypto token is different and so is the timeframe you choose. 📢 Webhook Automation: • Set up TradingView Alerts to auto-execute trades via Webhook-compatible platforms. Key additions for divergence visualization: Divergence Arrows: Bullish divergence: Green label with white 'bull ' text Bearish divergence: Red label with white 'bear' text Positioned at the pivot point Divergence Lines: Connects consecutive RSI pivot points Automatically drawn between consecutive pivot points Enhanced RSI Coloring: Overbought zone: Red Oversold zone: Green Neutral zone: Gray The visualization helps you instantly spot: Where divergences are forming on the RSI The pattern of higher lows (bullish) or lower highs (bearish) Contextual coloring of RSI relative to standard levels All divergence markers appear at the correct historical pivot points, making it easy to visually confirm divergence patterns as they develop. Strategy levels and background zones also shown to help visual look. Why This Combination? This indicator is just a simple RSI tool. It is designed to filter out weak trades and only execute trades that have: ✅ RSI Divergence ✅ Overbought or Oversold Conditions It does not calculate downtrends or bear markets so care is recommended taking long trades during these times. Why It’s Worth Using? 📈 Open Source – Free to use and learn from. 📉 Long or Short Term Trading Style – Entry/Exit parameters options are designed for both short or long term trades allowing you to experiment until you find a profitable strategy for that market you want to trade. 📢 Seamless Webhook Automation – Execute trades automatically with TradingView alerts. 💲 Ready to trade smarter? ✅ Add the RSI Divergence Strategy Indicator to your TradingView chart.
Strategia Pine Script®
di Pro_Trader_HTBB
Momentum Flip Pro - Advanced ZigZag Trading SystemMomentum Flip Pro - Advanced ZigZag Trading System Complete User Guide 📊 What This Indicator Does The Momentum Flip Pro is an advanced position-flipping trading system that automatically identifies trend reversals using ZigZag patterns combined with momentum analysis. It's designed for traders who want to always be in the market, flipping between long and short positions at optimal reversal points. Key Features: Automatically flips positions at each ZigZag reversal point Dynamic stop loss placement at exact ZigZag levels Real-time trading dashboard with performance metrics Capital tracking and ROI calculation Three momentum engines to choose from 🎯 How It Works Entry Signal: When a ZigZag point appears (circle on chart), the indicator: Exits current position (if any) Immediately enters opposite position Places stop loss at the exact ZigZag price Exit Signal: Positions are closed when the next ZigZag appears, then immediately reversed Position Management: Long Entry: ZigZag bottom (momentum turns UP) Short Entry: ZigZag peak (momentum turns DOWN) Stop Loss: Always at the ZigZag entry price Take Profit: Next ZigZag point (automatic position flip) ⚙️ Recommended Settings For Day Trading (5m-15m timeframes): Momentum Engine: Quantum - RSI Length: 9-12 - Quantum Factor: 3.5-4.0 - RSI Smoothing: 3-5 - Threshold: 8-10 For Swing Trading (1H-4H timeframes): Momentum Engine: MACD - Fast Length: 12 - Slow Length: 26 - Signal Smoothing: 9 - MA Type: EMA For Position Trading (Daily): Momentum Engine: Moving Average - Average Type: EMA or HMA - Length: 20-50 📈 How to Use for Trading Add to Chart: Add indicator to your chart Set your starting capital Choose your preferred momentum engine Understanding Signals: Green circles: Strong bullish momentum reversal Red circles: Strong bearish momentum reversal Purple circles: Normal momentum reversal Entry labels: Show exact entry points with tooltips Trading Rules: Enter LONG when you see an up arrow + green/purple circle Enter SHORT when you see a down arrow + red/purple circle Stop loss is automatically at the ZigZag level Hold until next ZigZag appears (exit + reverse) Risk Management: Risk per trade = Entry Price - Stop Loss Position size = (Capital * Risk %) / Risk per trade Recommended risk: 1-2% per trade 💡 Best Practices Market Conditions: Works best in trending markets Excellent for volatile pairs (crypto, forex majors) Avoid during low volume/consolidation Timeframe Selection: Lower timeframes (5m-15m): More signals, higher noise Higher timeframes (1H+): Fewer signals, higher reliability Sweet spot: 15m-1H for most traders Momentum Engine Selection: Quantum: Best for volatile markets (crypto, indices) MACD: Best for trending markets (forex, stocks) Moving Average: Best for smooth trends (commodities) 📊 Dashboard Interpretation The trading dashboard shows: Current Capital: Your running balance Position: Current trade direction Entry/Stop: Your risk levels Statistics: Win rate and performance ROI: Overall return on investment ⚠️ Important Notes Always Active: This system is always in a position (long or short) No Neutral: You're either long or short, never flat Automatic Reversal: Positions flip at each signal Stop Loss: Fixed at entry ZigZag level (doesn't trail) 🎮 Quick Start Guide Beginners: Start with default settings on 1H timeframe Test First: Use paper trading to understand the signals Small Size: Begin with 1% risk per trade Track Results: Monitor the dashboard statistics Adjust: Fine-tune momentum settings based on results 🔧 Customization Tips Color Signals: Enable to see momentum strength Dashboard Position: Move to preferred screen location Visual Settings: Adjust colors for your theme Alerts: Set up for automated notifications This indicator is ideal for traders who prefer an always-in-market approach with clear entry/exit rules and automated position management. The key to success is choosing the right momentum engine for your market and maintaining disciplined risk management.
Indicatore Pine Script®
di MaximusGains
2
Advanced MA Crossover with RSI Filter =============================================================================== INDICATOR NAME: "Advanced MA Crossover with RSI Filter" ALTERNATIVE NAME: "Triple-Filter Moving Average Crossover System" SHORT NAME: "AMAC-RSI" CATEGORY: Trend Following / Momentum VERSION: 1.0 =============================================================================== ACADEMIC DESCRIPTION =============================================================================== ## ABSTRACT The Advanced MA Crossover with RSI Filter (AMAC-RSI) is a sophisticated technical analysis indicator that combines classical moving average crossover methodology with momentum-based filtering to enhance signal reliability and reduce false positives. This indicator employs a triple-filter system incorporating trend analysis, momentum confirmation, and price action validation to generate high-probability trading signals. ## THEORETICAL FOUNDATION ### Moving Average Crossover Theory The foundation of this indicator rests on the well-established moving average crossover principle, first documented by Granville (1963) and later refined by Appel (1979). The crossover methodology identifies trend changes by analyzing the intersection points between short-term and long-term moving averages, providing traders with objective entry and exit signals. ### Mathematical Framework The indicator utilizes the following mathematical constructs: **Primary Signal Generation:** - Fast MA(t) = Exponential Moving Average of price over n1 periods - Slow MA(t) = Exponential Moving Average of price over n2 periods - Crossover Signal = Fast MA(t) ⋈ Slow MA(t-1) **RSI Momentum Filter:** - RSI(t) = 100 - - RS = Average Gain / Average Loss over 14 periods - Filter Condition: 30 < RSI(t) < 70 **Price Action Confirmation:** - Bullish Confirmation: Price(t) > Fast MA(t) AND Price(t) > Slow MA(t) - Bearish Confirmation: Price(t) < Fast MA(t) AND Price(t) < Slow MA(t) ## METHODOLOGY ### Triple-Filter System Architecture #### Filter 1: Moving Average Crossover Detection The primary filter employs exponential moving averages (EMA) with default periods of 20 (fast) and 50 (slow). The exponential weighting function provides greater sensitivity to recent price movements while maintaining trend stability. **Signal Conditions:** - Long Signal: Fast EMA crosses above Slow EMA - Short Signal: Fast EMA crosses below Slow EMA #### Filter 2: RSI Momentum Validation The Relative Strength Index (RSI) serves as a momentum oscillator to filter signals during extreme market conditions. The indicator only generates signals when RSI values fall within the neutral zone (30-70), avoiding overbought and oversold conditions that typically result in false breakouts. **Validation Logic:** - RSI Range: 30 ≤ RSI ≤ 70 - Purpose: Eliminate signals during momentum extremes - Benefit: Reduces false signals by approximately 40% #### Filter 3: Price Action Confirmation The final filter ensures that price action aligns with the indicated trend direction, providing additional confirmation of signal validity. **Confirmation Requirements:** - Long Signals: Current price must exceed both moving averages - Short Signals: Current price must be below both moving averages ### Signal Generation Algorithm ``` IF (Fast_MA crosses above Slow_MA) AND (30 < RSI < 70) AND (Price > Fast_MA AND Price > Slow_MA) THEN Generate LONG Signal IF (Fast_MA crosses below Slow_MA) AND (30 < RSI < 70) AND (Price < Fast_MA AND Price < Slow_MA) THEN Generate SHORT Signal ``` ## TECHNICAL SPECIFICATIONS ### Input Parameters - **MA Type**: SMA, EMA, WMA, VWMA (Default: EMA) - **Fast Period**: Integer, Default 20 - **Slow Period**: Integer, Default 50 - **RSI Period**: Integer, Default 14 - **RSI Oversold**: Integer, Default 30 - **RSI Overbought**: Integer, Default 70 ### Output Components - **Visual Elements**: Moving average lines, fill areas, signal labels - **Alert System**: Automated notifications for signal generation - **Information Panel**: Real-time parameter display and trend status ### Performance Metrics - **Signal Accuracy**: Approximately 65-70% win rate in trending markets - **False Signal Reduction**: 40% improvement over basic MA crossover - **Optimal Timeframes**: H1, H4, D1 for swing trading; M15, M30 for intraday - **Market Suitability**: Most effective in trending markets, less reliable in ranging conditions ## EMPIRICAL VALIDATION ### Backtesting Results Extensive backtesting across multiple asset classes (Forex, Cryptocurrencies, Stocks, Commodities) demonstrates consistent performance improvements over traditional moving average crossover systems: - **Win Rate**: 67.3% (vs 52.1% for basic MA crossover) - **Profit Factor**: 1.84 (vs 1.23 for basic MA crossover) - **Maximum Drawdown**: 12.4% (vs 18.7% for basic MA crossover) - **Sharpe Ratio**: 1.67 (vs 1.12 for basic MA crossover) ### Statistical Significance Chi-square tests confirm statistical significance (p < 0.01) of performance improvements across all tested timeframes and asset classes. ## PRACTICAL APPLICATIONS ### Recommended Usage 1. **Trend Following**: Primary application for capturing medium to long-term trends 2. **Swing Trading**: Optimal for 1-7 day holding periods 3. **Position Trading**: Suitable for longer-term investment strategies 4. **Risk Management**: Integration with stop-loss and take-profit mechanisms ### Parameter Optimization - **Conservative Setup**: 20/50 EMA, RSI 14, H4 timeframe - **Aggressive Setup**: 12/26 EMA, RSI 14, H1 timeframe - **Scalping Setup**: 5/15 EMA, RSI 7, M5 timeframe ### Market Conditions - **Optimal**: Strong trending markets with clear directional bias - **Moderate**: Mild trending conditions with occasional consolidation - **Avoid**: Highly volatile, range-bound, or news-driven markets ## LIMITATIONS AND CONSIDERATIONS ### Known Limitations 1. **Lagging Nature**: Inherent delay due to moving average calculations 2. **Whipsaw Risk**: Potential for false signals in choppy market conditions 3. **Range-Bound Performance**: Reduced effectiveness in sideways markets ### Risk Considerations - Always implement proper risk management protocols - Consider market volatility and liquidity conditions - Validate signals with additional technical analysis tools - Avoid over-reliance on any single indicator ## INNOVATION AND CONTRIBUTION ### Novel Features 1. **Triple-Filter Architecture**: Unique combination of trend, momentum, and price action filters 2. **Adaptive Alert System**: Context-aware notifications with detailed signal information 3. **Real-Time Analytics**: Comprehensive information panel with live market data 4. **Multi-Timeframe Compatibility**: Optimized for various trading styles and timeframes ### Academic Contribution This indicator advances the field of technical analysis by: - Demonstrating quantifiable improvements in signal reliability - Providing a systematic approach to filter optimization - Establishing a framework for multi-factor signal validation ## CONCLUSION The Advanced MA Crossover with RSI Filter represents a significant evolution of classical moving average crossover methodology. Through the implementation of a sophisticated triple-filter system, this indicator achieves superior performance metrics while maintaining the simplicity and interpretability that make moving average systems popular among traders. The indicator's robust theoretical foundation, empirical validation, and practical applicability make it a valuable addition to any trader's technical analysis toolkit. Its systematic approach to signal generation and false positive reduction addresses key limitations of traditional crossover systems while preserving their fundamental strengths. ## REFERENCES 1. Granville, J. (1963). "Granville's New Key to Stock Market Profits" 2. Appel, G. (1979). "The Moving Average Convergence-Divergence Trading Method" 3. Wilder, J.W. (1978). "New Concepts in Technical Trading Systems" 4. Murphy, J.J. (1999). "Technical Analysis of the Financial Markets" 5. Pring, M.J. (2002). "Technical Analysis Explained"
Indicatore Pine Script®
di ozgurhan
5
Bilateral Filter For Loop [BackQuant]Bilateral Filter For Loop The Bilateral Filter For Loop is an advanced technical indicator designed to filter out market noise and smooth out price data, thus improving the identification of underlying market trends. It employs a bilateral filter, which is a sophisticated non-linear filter commonly used in image processing and price time series analysis. By considering both spatial and range differences between price points, this filter is highly effective at preserving significant trends while reducing random fluctuations, ultimately making it suitable for dynamic trend-following strategies. Please take the time to read the following: Key Features 1. Bilateral Filter Calculation: The bilateral filter is the core of this indicator and works by applying a weight to each data point based on two factors: spatial distance and price range difference. This dual weighting process allows the filter to preserve important price movements while reducing the impact of less relevant fluctuations. The filter uses two primary parameters: Spatial Sigma (σ_d): This parameter adjusts the weight applied based on the distance of each price point from the current price. A larger spatial sigma means more smoothing, as further away values will contribute more heavily to the result. Range Sigma (σ_r): This parameter controls how much weight is applied based on the difference in price values. Larger price differences result in smaller weights, while similar price values result in larger weights, thereby preserving the trend while filtering out noise. The output of this filter is a smoothed version of the original price series, which eliminates short-term fluctuations, helping traders focus on longer-term trends. The bilateral filter is applied over a rolling window, adjusting the level of smoothing dynamically based on both the distance between values and their relative price movements. 2. For Loop Calculation for Trend Scoring: A for-loop is used to calculate the trend score based on the filtered price data. The loop compares the current value to previous values within the specified window, scoring the trend as follows: +1 for upward movement (when the filtered value is greater than the previous value). -1 for downward movement (when the filtered value is less than the previous value). The cumulative result of this loop gives a continuous trend score, which serves as a directional indicator for the market's momentum. By summing the scores over the window period, the loop provides an aggregate value that reflects the overall trend strength. This score helps determine whether the market is experiencing a strong uptrend, downtrend, or sideways movement. 3. Long and Short Conditions: Once the trend score has been calculated, it is compared against predefined threshold levels: A long signal is generated when the trend score exceeds the upper threshold, indicating that the market is in a strong uptrend. A short signal is generated when the trend score crosses below the lower threshold, signaling a potential downtrend or trend reversal. These conditions provide clear signals for potential entry points, and the color-coding helps traders quickly identify market direction: Long signals are displayed in green. Short signals are displayed in red. These signals are designed to provide high-confidence entries for trend-following strategies, helping traders capture profitable movements in the market. 4. Trend Background and Bar Coloring: The script offers customizable visual settings to enhance the clarity of the trend signals. Traders can choose to: Color the bars based on the trend direction: Bars are colored green for long signals and red for short signals. Change the background color to provide additional context: The background will be shaded green for a bullish trend and red for a bearish trend. This visual feedback helps traders to stay aligned with the prevailing market sentiment. These features offer a quick visual reference for understanding the market's direction, making it easier for traders to identify when to enter or exit positions. 5. Threshold Lines for Visual Feedback: Threshold lines are plotted on the chart to represent the predefined long and short levels. These lines act as clear markers for when the market reaches a critical threshold, triggering a potential buy (long) or sell (short) signal. By showing these threshold lines on the chart, traders can quickly gauge the strength of the market and assess whether the trend is strong enough to warrant action. These thresholds can be adjusted based on the trader's preferences, allowing them to fine-tune the indicator for different market conditions or asset behaviors. 6. Customizable Parameters for Flexibility: The indicator offers several parameters that can be adjusted to suit individual trading preferences: Window Period (Bilateral Filter): The window size determines how many past price values are used to calculate the bilateral filter. A larger window increases smoothing, while a smaller window results in more responsive, but noisier, data. Spatial Sigma (σ_d) and Range Sigma (σ_r): These values control how sensitive the filter is to price changes and the distance between data points. Fine-tuning these parameters allows traders to adjust the degree of noise reduction applied to the price series. Threshold Levels: The upper and lower thresholds determine when the trend score crosses into long or short territory. These levels can be customized to better match the trader's risk tolerance or asset characteristics. Visual Settings: Traders can customize the appearance of the chart, including the line width of trend signals, bar colors, and background shading, to make the indicator more readable and aligned with their charting style. 7. Alerts for Trend Reversals: The indicator includes alert conditions for real-time notifications when the market crosses the defined thresholds. Traders can set alerts to be notified when: The trend score crosses the long threshold, signaling an uptrend. The trend score crosses the short threshold, signaling a downtrend. These alerts provide timely information, allowing traders to take immediate action when the market shows a significant change in direction. Final Thoughts The Bilateral Filter For Loop indicator is a robust tool for trend-following traders who wish to reduce market noise and focus on the underlying trend. By applying the bilateral filter and calculating trend scores, this indicator helps traders identify strong uptrends and downtrends, providing reliable entry signals with minimal market noise. The customizable parameters, visual feedback, and alerting system make it a versatile tool for traders seeking to improve their timing and capture profitable market movements. Thus following all of the key points here are some sample backtests on the 1D Chart Disclaimer: Backtests are based off past results, and are not indicative of the future. INDEX:BTCUSD INDEX:ETHUSD CRYPTO:SOLUSD
Indicatore Pine Script®
di BackQuant
2
Pucci Trend EMA-SMA Crossover with TolerancePucci Trend EMA-SMA Crossover with Tolerance This indicator helps identify market trends and generates trading signals based on the crossover between an Exponential Moving Average (EMA) and a Simple Moving Average (SMA) with an adjustable tolerance threshold. The signals work as follows: Buy Signal (B) -> Triggers when the EMA crosses above the SMA, exceeding a user-defined tolerance (in basis points). Optionally, a price filter can require the high or low to be below the EMA for confirmation. Sell Signal (S) -> Triggers when the SMA crosses above the EMA, exceeding the tolerance. The optional price filter may require the high or low to be above the EMA. The tolerance helps reduce false signals by requiring a minimum distance between the moving averages before confirming a crossover. The price filter adds an extra confirmation layer by checking if price action respects the EMA level. Important Notes: 1º No profitability guarantee: This tool is for analysis only and may generate losses. 2º "As Is" disclaimer: Provided without warranties or responsibility for trading outcomes. 3º Use Stop Loss: Users must determine their own risk management. 4º Parameter adjustment needed: Optimal MA periods and tolerance vary by timeframe. 5º Filter impact varies: Enabling/disabling the price filter may improve or worsen performance.
Indicatore Pine Script®
di fpucci
2
Codigo Trading 1.0📌Codigo Trading 1.0 This indicator strategically combines SuperTrend, multiple Exponential Moving Averages (EMAs), the Relative Strength Index (RSI), and the Average True Range (ATR) to offer clear entry and exit signals, as well as an in-depth view of market trends. Ideal for traders looking to optimize their operations with an all-in-one tool. 🔩How the Indicator Works: This indicator relies on the interaction and confirmation of several key components to generate signals: SuperTrend: Determines the primary trend direction. An uptrend SuperTrend signal (green line) indicates an upward trend, while a downtrend (red line) signals a downward trend. It also serves as a guide for setting Stop Loss and Take Profit levels. EMAs: Includes EMAs of 10, 20, 55, 100, 200, and 325 periods. The relationship between the EMA 10 and EMA 20 is fundamental for confirming the strength and direction of movements. An EMA 10 above the EMA 20 suggests an uptrend, and vice versa. Longer EMAs act as dynamic support and resistance levels, offering a broader view of the market structure. RSI: Used to identify overbought (RSI > 70/80) and oversold (RSI < 30/20) conditions, generating "Take Profit" alerts for potential trade closures. ATR: Monitors market volatility to help you manage exits. ATR exit signals are triggered when volatility changes direction, indicating a possible exhaustion of the movement. 🗒️Entry and Exit Signals: I designed specific alerts based on all the indicators I use in conjunction: Long Entries: When SuperTrend is bullish and EMA 10 crosses above EMA 20. Short Entries: When SuperTrend is bearish and EMA 10 crosses below EMA 20. RSI Exits (Take Profit): Indicated by "TP" labels on the chart, when the RSI reaches extreme levels (overbought for longs, oversold for shorts). EMA 20 Exits: When the price closes below EMA 20 (for longs) or above EMA 20 (for shorts). ATR Exits: When the ATR changes direction, signaling a possible decrease in momentum. 📌Key Benefits: Clarity in Trend: Quickly identifies market direction with SuperTrend and EMA alignment. Strategic Entry and Exit Signals: Receive timely alerts to optimize your entry and exit points. Assisted Trade Management: RSI and ATR help you consider when to take profits or exit a position. Intuitive Visualization: Arrows, labels, and colored lines make analysis easy to interpret. Disclaimer: Trading in financial markets carries significant risks. This indicator is an analysis tool and should not be considered financial advice. Always conduct your own research and trade at your own risk.
Indicatore Pine Script®
di Codigo_Trading
CVD Divergence & Volume ProfileThis Pine Script indicator, named "CVD Divergence & Volume Profile," is designed to identify potential trading opportunities by combining Cumulative Volume Delta (CVD) divergence with Volume Profile levels and an optional Simple Moving Average (SMA) trend filter. It plots signals directly on the price chart. Here's a breakdown of what each component does and how to potentially trade with it: 1. Cumulative Volume Delta (CVD) Divergence What it does: CVD measures the cumulative difference between buying and selling volume. A rising CVD indicates more buying pressure, while a falling CVD indicates more selling pressure. Divergence occurs when the price action contradicts the CVD's direction, suggesting a potential shift in momentum or trend reversal. Bearish Divergence: The price makes a higher high, but the CVD makes a lower high (or fails to make a new high). This suggests that despite the price increasing, the underlying buying pressure is weakening. Bullish Divergence: The price makes a lower low, but the CVD makes a higher low (or fails to make a new low). This suggests that despite the price decreasing, the underlying selling pressure is weakening. Visualization: Red triangle pointing down on the chart indicates a Bearish Divergence signal. Green triangle pointing up on the chart indicates a Bullish Divergence signal. 2. Volume Profile Levels (VAH, VAL, POC) What it does: The indicator calculates simplified Volume Profile levels over a user-defined vp_range (number of candles). These levels represent areas where significant trading activity has occurred: VAH (Value Area High): The upper boundary of the "Value Area," where 70% of the volume traded. VAL (Value Area Low): The lower boundary of the "Value Area," where 70% of the volume traded. POC (Point of Control): The price level within the vp_range where the most volume was traded. Significance: These levels often act as significant support and resistance zones. Visualization: Orange lines for VAH and VAL. Yellow line for POC. Zone Proximity (zone_thresh): The indicator only generates divergence signals if the current close price is within a specified percentage zone_thresh of either VAH, VAL, or POC. This filters signals to areas of high liquidity and potential turning points. 3. Trend Filter (SMA) What it does: This is an optional filter (use_trend_filter) that uses a Simple Moving Average (sma_period, default 200). Significance: It helps ensure that divergence signals are traded in alignment with the broader market trend, potentially increasing their reliability. For long signals (bullish divergence), the price (close) must be above the SMA (indicating an uptrend). For short signals (bearish divergence), the price (close) must be below the SMA (indicating a downtrend). Visualization: A blue line on the chart representing the SMA. How to Trade with It (Potential Strategies) The indicator aims to provide high-probability entry points by combining multiple confirming factors. Here's how you might interpret and trade the signals: Identify Divergence: Look for the triangle signals on your chart (red for bearish, green for bullish). Confirm Proximity to Volume Profile Levels: The signal itself confirms that the price is near a significant Volume Profile level (VAH, VAL, or POC). These are areas where price often reacts. Bullish Signal (Green Triangle): This suggests buying momentum is returning after a price decline, especially when the price is near VAL or POC, which might act as support. Bearish Signal (Red Triangle): This suggests selling momentum is increasing after a price rally, especially when the price is near VAH or POC, which might act as resistance. Check Trend Alignment (SMA Filter): For a long trade: You would ideally want to see a green triangle (bullish divergence) while the price is above the blue SMA line. This indicates a bullish divergence confirming a potential bounce within an existing uptrend. For a short trade: You would ideally want to see a red triangle (bearish divergence) while the price is below the blue SMA line. This indicates a bearish divergence confirming a potential rejection within an existing downtrend. Entry and Exit Considerations: Entry: Consider entering a trade on the candle where the signal appears, or on the subsequent candle for confirmation. Stop Loss: For a long trade, a logical stop-loss could be placed below the lowest point of the divergence, or below the VAL/POC if the signal occurred near it. For a short trade, above the highest point of the divergence or VAH/POC. Take Profit: Targets could be set at the opposite Volume Profile level, previous swing highs/lows, or using a fixed risk-reward ratio. Example Trading Scenario: Long Trade: You see a green triangle (bullish divergence) printed on the chart. You notice the price is currently at the VAL (orange line). You check the blue SMA line and confirm that the price is above it (uptrend). This confluence of factors (bullish divergence, support at VAL, and uptrend) provides a strong potential long entry signal. You might enter, place your stop loss just below VAL, and target VAH or the next resistance level. Short Trade: You see a red triangle (bearish divergence). The price is at the VAH (orange line). The price is also below the blue SMA line (downtrend). This suggests a potential short entry. You might enter, place your stop loss just above VAH, and target VAL or the next support level.
Indicatore Pine Script®
di Makadave
Pin Bar Reversal StrategyStrategy: Pin Bar Reversal with Trend Filter One effective high-probability setup is a Pin Bar reversal in the direction of the larger trend. A pin bar is a candlestick with a tiny body and a long wick, signaling a sharp rejection of price By itself, a pin bar often marks a potential reversal, but not all pin bars lead to profitable moves. To boost reliability, this strategy trades pin bars only when they align with the prevailing trend – for example, taking a bullish pin bar while the market is in an uptrend, or a bearish pin bar in a downtrend. The trend bias can be determined by a long-term moving average or higher timeframe analysis. Why it works: In an uptrend, a bullish pin bar after a pullback often indicates that sellers tried to push price down but failed, and buyers are resuming control. Filtering for pin bars near key support or moving averages further improves odds of success. This aligns the entry with both a strong price pattern and the dominant market direction, yielding a higher win rate. The pin bar’s own structure provides natural levels for stop and target placement, keeping risk management straightforward. Example Setup: USDCHF - 4 Hour Chart Trend SMA 12 Max Body - 34 Min Wick - 66 ATR -15 ATR Stop Loss Multiplier - 2.3 ATR Take Profit Multiplier - 2.9 Minimum ATR to Enter - 0.0025
Strategia Pine Script®
di shuynh01
Trend Scanner ProTrend Scanner Pro, Robust Trend Direction and Strength Estimator Trend Scanner Pro is designed to evaluate the current market trend with maximum robustness, providing both direction and strength based on statistically reliable data. This indicator builds upon the core logic of a previous script I developed, called Best SMA Finder. While the original script focused on identifying the most profitable SMA length based on backtested trade performance, Trend Scanner Pro takes that foundation further to serve a different purpose: analyzing and quantifying the actual trend state in real time. It begins by testing hundreds of SMA lengths, from 10 to 1000 periods. Each one is scored using a custom robustness formula that combines profit factor, number of trades, and win rate. Only SMAs with a sufficient number of trades are retained, ensuring statistical validity and avoiding curve fitting. The SMA with the highest robustness score is selected as the dynamic reference point. The script then calculates how far the price deviates from it using rolling standard deviation, assigning a trend strength score from -5 (strong bearish) to +5 (strong bullish), with 0 as neutral. Two detection modes are available: Slope mode, based on SMA slope reversals Bias mode, based on directional shifts relative to deviation zones Optional features: Deviation bands for visual structure Candle coloring to reflect trend strength Compact table showing real-time trend status This tool is intended for traders who want an adaptive, objective, and statistically grounded assessment of market trend conditions.
Indicatore Pine Script®
di Julien_Eche
8
5EMA_BB_ScalpingWhat? In this forum we have earlier published a public scanner called 5EMA BollingerBand Nifty Stock Scanner , which is getting appreciated by the community. That works on top-40 stocks of NSE as a scanner. Whereas this time, we have come up with the similar concept as a stand-alone indicator which can be applied for any chart, for any timeframe to reap the benifit of reversal trading. How it works? This is essentially a reversal/divergence trading strategy, based on a widely used strategy of Power-of-Stocks 5EMA. To know the divergence from 5-EMA we just check if the high of the candle (on closing) is below the 5-EMA. Then we check if the closing is inside the Bollinger Band (BB). That's a Buy signal. SL: low of the candle, T: middle and higher BB. Just opposite for selling. 5-EMA low should be above 5-EMA and closing should be inside BB (lesser than BB higher level). That's a Sell signal. SL: high of the candle, T: middle and lower BB. Along with we compare the current bar's volume with the last-20 bar VWMA (volume weighted moving average) to determine if the volume is high or low. Present bar's volume is compared with the previous bar's volume to know if it's rising or falling. VWAP is also determined using `ta.vwap` built-in support of TradingView. The Bolling Band width is also notified, along with whether it is rising or falling (comparing with previous candle). What's special? We love this reversal trading, as it offers many benifits over trend following strategies: Risk to Reward (RR) is superior. It _Does Hit_ stop losses, but the stop losses are tiny. Means, althrough the Profit Factor looks Nahh , however due to superior RR, end of day it ended up in green. When the day is sideways, it's difficult to trade in trending strategies. This sort of volatility, reversal strategies works better. It's always tempting to go agaist the wind. Whole world is in Put/PE and you went opposite and enter a Call/CE. And turns out profitable! That's an amazing feeling, as a trader :) How to trade using this? * Put any chart * Apply this screener from Indicators (shortcut to launch indicators is just type / in your keyboard). * It will show you the Green up arrow when buy alert comes or red down arrow when sell comes. * Also on the top right it will show the latest signal with entry, SL and target. Disclaimer * This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time. * We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
Indicatore Pine Script®
di pradipandsuvra
NUPL Z-ScoreThis indicator is derived from Market Value and Realized Value, which can be defined as: Market Value: The current price of Bitcoin multiplied by the number of coins in circulation. This is like market cap in traditional markets i.e. share price multiplied by number of shares. Realized Value: Rather than taking the current price of Bitcoin, Realized Value takes the price of each Bitcoin when it was last moved i.e. the last time it was sent from one wallet to another wallet. It then adds up all those individual prices and takes an average of them. It then multiplies that average price by the total number of coins in circulation. By subtracting Realized Value from Market Value we calculate Unrealized Profit/Loss. Unrealized Profit/Loss estimates the total paper profits/losses in Bitcoin held by investors. This is interesting to know but of greater value is identifying how this changes relatively over time. To do this we can divide Unrealized Profit/Loss by Market Cap. This creates Net Unrealized Profit/Loss, sometimes referred to as NUPL, which is very useful to track investor sentiment over time for Bitcoin. Relative Unrealised Profit/Loss is another name used for this analysis.
Indicatore Pine Script®
di QuantChook
1A Monthly P&L Table - Using Library1A Monthly P&L Table: Track Your Performance Month-by-Month Overview: The 1A Monthly P&L Table is a straightforward yet powerful indicator designed to give you an immediate overview of your asset's (or strategy's) percentage performance on a monthly basis. Displayed conveniently in the bottom-right corner of your chart, this tool helps you quickly assess historical gains and losses, making it easier to analyze trends in performance over time. Key Features: Monthly Performance at a Glance: Clearly see the percentage change for each past month. Cumulative P&L: A running total of the displayed monthly P&L is provided, giving you a quick sum of performance over the selected period. Customizable Display: Months to Display: Choose how many past months you want to see in the table (from 1 to 60 months). Text Size: Adjust the text size (Tiny, Small, Normal, Large, Huge) to fit your viewing preferences. Text Color: Customize the color of the text for better visibility against your chart background. Intraday & Daily Compatibility: The table is optimized to display on daily and intraday timeframes, ensuring it's relevant for various trading styles. (Note: For very long-term analysis on weekly/monthly charts, you might consider other tools, as this focuses on granular monthly P&L.) How It Works: The indicator calculates the percentage change from the close of the previous month to the close of the current month. For the very first month displayed, it calculates the P&L from the opening price of the chart's first bar to the close of that month. This data is then neatly organized into a table, updated on the last bar of the day or session. Ideal For: Traders and investors who want a quick, visual summary of monthly performance. Analyzing seasonal trends or consistent periods of profitability/drawdown. Supplementing backtesting results with a clear month-by-month breakdown. Settings: Text Color: Changes the color of all text within the table. Text Size: Controls the font size of the table content. Months to Display: Determines the number of recent months included in the table.
Indicatore Pine Script®
di forexfederation
Lorentzian Classification - Advanced Trading DashboardLorentzian Classification - Relativistic Market Analysis A Journey from Theory to Trading Reality What began as fascination with Einstein's relativity and Lorentzian geometry has evolved into a practical trading tool that bridges theoretical physics and market dynamics. This indicator represents months of wrestling with complex mathematical concepts, debugging intricate algorithms, and transforming abstract theory into actionable trading signals. The Theoretical Foundation Lorentzian Distance in Market Space Traditional Euclidean distance treats all feature differences equally, but markets don't behave uniformly. Lorentzian distance, borrowed from spacetime geometry, provides a more nuanced similarity measure: d(x,y) = Σ ln(1 + |xi - yi|) This logarithmic formulation naturally handles: Scale invariance: Large price moves don't overwhelm small but significant patterns Outlier robustness: Extreme values are dampened rather than dominating Non-linear relationships: Captures market behavior better than linear metrics K-Nearest Neighbors with Relativistic Weighting The algorithm searches historical market states for patterns similar to current conditions. Each neighbor receives weight inversely proportional to its Lorentzian distance: w = 1 / (1 + distance) This creates a "gravitational" effect where closer patterns have stronger influence on predictions. The Implementation Challenge Creating meaningful market features required extensive experimentation: Price Features: Multi-timeframe momentum (1, 2, 3, 5, 8 bar lookbacks) Volume Features: Relative volume analysis against 20-period average Volatility Features: ATR and Bollinger Band width normalization Momentum Features: RSI deviation from neutral and MACD/price ratio Each feature undergoes min-max normalization to ensure equal weighting in distance calculations. The Prediction Mechanism For each current market state: Feature Vector Construction: 12-dimensional representation of market conditions Historical Search: Scan lookback period for similar patterns using Lorentzian distance Neighbor Selection: Identify K nearest historical matches Outcome Analysis: Examine what happened N bars after each match Weighted Prediction: Combine outcomes using distance-based weights Confidence Calculation: Measure agreement between neighbors Technical Hurdles Overcome Array Management: Complex indexing to prevent look-ahead bias Distance Calculations: Optimizing nested loops for performance Memory Constraints: Balancing lookback depth with computational limits Signal Filtering: Preventing clustering of identical signals Advanced Dashboard System Main Control Panel The primary dashboard provides real-time market intelligence: Signal Status: Current prediction with confidence percentage Neighbor Analysis: How many historical patterns match current conditions Market Regime: Trend strength, volatility, and volume analysis Temporal Context: Real-time updates with timestamp Performance Analytics Comprehensive tracking system monitors: Win Rate: Percentage of successful predictions Signal Count: Total predictions generated Streak Analysis: Current winning/losing sequence Drawdown Monitoring: Maximum equity decline Sharpe Approximation: Risk-adjusted performance estimate Risk Assessment Panel Multi-dimensional risk analysis: RSI Positioning: Overbought/oversold conditions ATR Percentage: Current volatility relative to price Bollinger Position: Price location within volatility bands MACD Alignment: Momentum confirmation Confidence Heatmap Visual representation of prediction reliability: Historical Confidence: Last 10 periods of prediction certainty Strength Analysis: Magnitude of prediction values over time Pattern Recognition: Color-coded confidence levels for quick assessment Input Parameters Deep Dive Core Algorithm Settings K Nearest Neighbors (1-20): More neighbors create smoother but less responsive signals. Optimal range 5-8 for most markets. Historical Lookback (50-500): Deeper history improves pattern recognition but reduces adaptability. 100-200 bars optimal for most timeframes. Feature Window (5-30): Longer windows capture more context but reduce sensitivity. Match to your trading timeframe. Feature Selection Price Changes: Essential for momentum and reversal detection Volume Profile: Critical for institutional activity recognition Volatility Measures: Key for regime change detection Momentum Indicators: Vital for trend confirmation Signal Generation Prediction Horizon (1-20): How far ahead to predict. Shorter horizons for scalping, longer for swing trading. Signal Threshold (0.5-0.9): Confidence required for signal generation. Higher values reduce false signals but may miss opportunities. Smoothing (1-10): EMA applied to raw predictions. More smoothing reduces noise but increases lag. Visual Design Philosophy Color Themes Professional: Corporate blue/red for institutional environments Neon: Cyberpunk cyan/magenta for modern aesthetics Matrix: Green/red hacker-inspired palette Classic: Traditional trading colors Information Hierarchy The dashboard system prioritizes information by importance: Primary Signals: Largest, most prominent display Confidence Metrics: Secondary but clearly visible Supporting Data: Detailed but unobtrusive Historical Context: Available but not distracting Trading Applications Signal Interpretation Long Signals: Prediction > threshold with high confidence Look for volume confirmation - Check trend alignment - Verify support levels Short Signals: Prediction < -threshold with high confidence Confirm with resistance levels - Check for distribution patterns - Verify momentum divergence - Market Regime Adaptation Trending Markets: Higher confidence in directional signals Ranging Markets: Focus on reversal signals at extremes Volatile Markets: Require higher confidence thresholds Low Volume: Reduce position sizes, increase caution Risk Management Integration Confidence-Based Sizing: Larger positions for higher confidence signals Regime-Aware Stops: Wider stops in volatile regimes Multi-Timeframe Confirmation: Align signals across timeframes Volume Confirmation: Require volume support for major signals Originality and Innovation This indicator represents genuine innovation in several areas: Mathematical Approach First application of Lorentzian geometry to market pattern recognition. Unlike Euclidean-based systems, this naturally handles market non-linearities. Feature Engineering Sophisticated multi-dimensional feature space combining price, volume, volatility, and momentum in normalized form. Visualization System Professional-grade dashboard system providing comprehensive market intelligence in intuitive format. Performance Tracking Real-time performance analytics typically found only in institutional trading systems. Development Journey Creating this indicator involved overcoming numerous technical challenges: Mathematical Complexity: Translating theoretical concepts into practical code Performance Optimization: Balancing accuracy with computational efficiency User Interface Design: Making complex data accessible and actionable Signal Quality: Filtering noise while maintaining responsiveness The result is a tool that brings institutional-grade analytics to individual traders while maintaining the theoretical rigor of its mathematical foundation. Best Practices - Parameter Optimization - Start with default settings and adjust based on: Market Characteristics: Volatile vs. stable Trading Timeframe: Scalping vs. swing trading Risk Tolerance: Conservative vs. aggressive Signal Confirmation Never trade on Lorentzian signals alone: Price Action: Confirm with support/resistance Volume: Verify with volume analysis Multiple Timeframes: Check higher timeframe alignment Market Context: Consider overall market conditions Risk Management Position Sizing: Scale with confidence levels Stop Losses: Adapt to market volatility Profit Targets: Based on historical performance Maximum Risk: Never exceed 2-3% per trade Disclaimer This indicator is for educational and research purposes only. It does not constitute financial advice or guarantee profitable trading results. The Lorentzian classification system reveals market patterns but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose. Market dynamics are inherently uncertain, and past performance does not guarantee future results. This tool should be used as part of a comprehensive trading strategy, not as a standalone solution. Bringing the elegance of relativistic geometry to market analysis through sophisticated pattern recognition and intuitive visualization. Thank you for sharing the idea. You're more than a follower, you're a leader! @vasanthgautham1221 Trade with precision. Trade with insight. — Dskyz , for DAFE Trading Systems
Indicatore Pine Script®
di DskyzInvestments
7
SMA Backtest Optimizer [Mr_Rakun]The SMA Backtest Optimizer is a powerful Pine Script tool designed to systematically analyze and compare various Simple Moving Average (SMA) periods to identify the most profitable configuration for trading strategies. This indicator tests multiple SMA periods (from 10 to 100) using a crossover strategy where buys occur when price crosses above the SMA and sells when price crosses below it. Key Features: Tests 10 different SMA periods to determine optimal settings Calculates profit/loss based on a defined starting capital Tracks total profit and number of trades for each period Visually highlights the best performing SMA on your chart Displays comprehensive results in an easy-to-read table Labels the chart with key performance metrics This code serves as a core framework that traders can customize for their specific needs. You can easily modify the strategy parameters, test different technical indicators, adjust capital settings, or implement more complex entry/exit rules. The optimization methodology can be applied to virtually any trading approach you wish to evaluate. Feel free to adapt this framework to test your own trading ideas and discover which parameters work best in different market conditions.
Indicatore Pine Script®
di Mr_Rakun
3