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Fibonacci Time-Price Zones🟩 Fibonacci Time-Price Zones is a chart visualization tool that combines Fibonacci ratios with time-based and price-based geometry to analyze market behavior. Unlike typical Fibonacci indicators that focus solely on horizontal price levels, this indicator incorporates time into the analysis, providing a more dynamic perspective on price action. The indicator offers multiple ways to visualize Fibonacci relationships. Drawing segmented circles creates a unique perspective on price action by incorporating time into the analysis. These segmented circles, similar to TradingView's built-in Fibonacci Circles, are derived from Fibonacci time and price levels, allowing traders to identify potential turning points based on the dynamic interaction between price and time. As another distinct visualization method, the indicator incorporates orthogonal patterns, created by the intersection of horizontal and vertical Fibonacci levels. These intersections form L-shaped connections on the chart, derived from key Fibonacci price and time intervals, highlighting potential areas of support or resistance at specific points in time. In addition to these geometric approaches, another option is sloped lines, which project Fibonacci levels that account for both time and price along the trendline. These projections derive their angles from the interplay between Fibonacci price levels and Fibonacci time intervals, creating dynamic zones on the chart. The slope of these lines reflects the direction and angle of the trend, providing a visual representation of price alignment with market direction, while maintaining the time-price relationship unique to this indicator The indicator also includes horizontal Fibonacci levels similar to traditional retracement and extension tools. However, unlike standard tools, traders can display retracement levels, extension levels, or both simultaneously from a single instance of the indicator. These horizontal levels maintain consistency with the chosen visualization method, automatically scaling and adapting whether used with circles, orthogonal patterns, or slope-based analysis. By combining these distinct methods—circles, orthogonal patterns, sloped projections, and horizontal levels—the indicator provides a comprehensive approach to Fibonacci analysis based on both time and price relationships. Each visualization method offers a unique perspective on market structure while maintaining the core principle of time-price interaction. ⭕ THEORY AND CONCEPT ⭕ While traditional Fibonacci tools excel at identifying potential support and resistance levels through price-based ratios (0.236, 0.382, 0.618), they do not incorporate the dimension of time in market analysis. Extensions and retracements effectively measure price relationships within trends, yet markets move through both price and time dimensions simultaneously. Fibonacci circles represent an evolution in technical analysis by incorporating time intervals alongside price levels. Based on the mathematical principle that markets often move in circular patterns proportional to Fibonacci ratios, these circles project potential support and resistance zones as partial circles radiating from significant price points. However, traditional circle-based tools can create visual complexity that obscures key market relationships. The integration of time into Fibonacci analysis reveals how price movements often respect both temporal and price-based ratios, suggesting a deeper geometric structure to market behavior. The Fibonacci Time-Price Zones indicator advances these concepts by providing multiple geometric approaches to visualize time-price relationships. Each shape option—circles, orthogonal patterns, slopes, and horizontal levels—represents a different mathematical perspective on how Fibonacci ratios manifest across both dimensions. This multi-faceted approach allows traders to observe how price responds to Fibonacci-based zones that account for both time and price movements, potentially revealing market structure that purely price-based tools might miss. Shape Options The indicator employs four distinct geometric approaches to analyze Fibonacci relationships across time and price dimensions: Circular : Represents the cyclical nature of market movements through partial circles, where each radius is scaled by Fibonacci ratios incorporating both time and price components. This geometry suggests market movements may follow proportional circular paths from significant pivot points, reflecting the harmonic relationship between time and price. Orthogonal : Constructs L-shaped patterns that separate the time and price components of Fibonacci relationships. The horizontal component represents price levels, while the vertical component measures time intervals, allowing analysis of how these dimensions interact independently at key market points. Sloped : Projects Fibonacci levels along the prevailing trend, incorporating both time and price in the angle of projection. This approach suggests that support and resistance levels may maintain their relationship to price while adjusting to the temporal flow of the market. Horizontal : Provides traditional static Fibonacci levels that serve as a reference point for comparing price-only analysis with the dynamic time-price relationships shown in the other three shapes. This baseline approach allows traders to evaluate how the incorporation of time dimension enhances or modifies traditional Fibonacci analysis. By combining these geometric approaches, the Fibonacci Time-Price Zones indicator creates a comprehensive analytical framework that bridges traditional and advanced Fibonacci analysis. The horizontal levels serve as familiar reference points, while the dynamic elements—circular, orthogonal, and sloped projections—reveal how price action responds to temporal relationships. This multi-dimensional approach enables traders to study market structure through various geometric lenses, providing deeper insights into time-price symmetry within technical analysis. Whether applied to retracements, extensions, or trend analysis, the indicator offers a structured methodology for understanding how markets move through both price and time dimensions. 🛠️ CONFIGURATION AND SETTINGS 🛠️ The Fibonacci Time-Price Zones indicator offers a range of configurable settings to tailor its functionality and visual representation to your specific analysis needs. These options allow you to customize zone visibility, structures, horizontal lines, and other features. Important Note: The indicator's calculations are anchored to user-defined start and end points on the chart. When switching between charts with significantly different price scales (e.g., from Bitcoin at $100,000 to Silver at $30), adjustment of these anchor points is required to ensure correct positioning of the Fibonacci elements. Fibonacci Levels The indicator allows users to customize Fibonacci levels for both retracement and extension analysis. Each level can be individually configured with the following options: Visibility : Toggle the visibility of each level to focus on specific areas of interest. Level Value : Set the Fibonacci ratio for the level, such as 0.618 or 1.000, to align with your analysis needs. Color : Customize the color of each level for better visual clarity. Line Thickness : Adjust the line thickness to emphasize critical levels or maintain a cleaner chart. Setup Zone Type : Select which Fibonacci zones to display: - Retracement : Shows potential pull back levels within the trend - Extension : Projects levels beyond the trend for potential continuation targets - Both : Displays both retracement and extension zones simultaneously Shape : Choose from four visualization methods: - Circular : Time-price based semicircles centered on point B - Orthogonal : L-shaped patterns combining time and price levels - Sloped : Trend-aligned projections of Fibonacci levels - Horizontal : Traditional horizontal Fibonacci levels Visual Settings Fill % : Adjusts the fill intensity of zones: 0% : No fill between levels 100% : Maximum fill between levels Lines : Trendline : The base A-B trend with customizable color Extension : B-C projection line Retracement : B-D pullback line Labels : Points : Show/hide A, B, C, D markers Levels : Show/hide Fibonacci percentages Time-Price Points Set the time and price for the points that define the Fibonacci zones and horizontal levels. These points are defined upon loading the chart. These points can be configured directly in the settings or adjusted interactively on the live chart. A and B Points : These user-defined time and price points determine the basis for calculating the semicircles and Fibonacci levels. While the settings panel displays their exact values for fine-tuning, the easiest way to modify these points is by dragging them directly on the chart for quick adjustments. Interactive Adjustments : Any changes made to the points on the chart will automatically synchronize with the settings panel, ensuring consistency and precision. 🖼️ CHART EXAMPLES 🖼️ Fibonacci Time-Price Zones using the 'Circular' Shape option. Note the price interaction at the 0.786 level, which acts as a support zone. Additional points of interest include resistance near the 0.618 level and consolidation around the 0.5 level, highlighting the utility of both horizontal and semicircular Fibonacci projections in identifying key price areas. Fibonacci Time-Price Zones using the 'Sloped' Shape option. The chart displays price retracing along the sloped Fibonacci levels, with blue arrows highlighting potential support zones at 0.618 and 0.786, and a red arrow indicating potential resistance at the 1.0 level. This visual representation aligns with the prevailing downtrend, suggesting potential selling pressure at the 1.0 Fibonacci level. Fibonacci Time-Price Zones using the 'Orthogonal' Shape option. The chart demonstrates price action interacting with vertical zones created by the orthogonal lines at the 0.618, 0.786, and 1.0 Fibonacci levels. Blue arrows highlight potential support areas, while red arrows indicate potential resistance areas, revealing how the orthogonal lines can identify distinct points of price interaction. Fibonacci Time-Price Zones using the 'Circular' Shape option. The chart displays price action in relation to segmented circles emanating from the starting point (point A). The circles represent different Fibonacci ratios (0.382, 0.5, 0.618, 0.786) and their intersections with the price axis create potential zones of support and resistance. This approach offers a visually distinct way to analyze potential turning points based on both price and time. Fibonacci Time-Price Zones using the 'Sloped' Shape option. The sloped Fibonacci levels (0.786, 0.618, 0.5) create zones of potential support and resistance, with price finding clear interaction within these areas. The ellipses highlight this price action, particularly the support between 0.786 and 0.618, which aligns closely with the trend. Fibonacci Time-Price Zones using the 'Circular' Shape option. The price action appears to be ‘hugging’ the 0.5 Fibonacci level, suggesting potential resistance. This demonstrates how the circular zones can identify potential turning points and areas of consolidation which might not be seen with linear analysis. Fibonacci Time-Price Zones using the 'Sloped' Shape option with Point D marker enabled. The chart demonstrates clear price action closely following along the sloped Retracement line until the orthogonal intersection at the 0.618 levels where the trend is broken and price dips throughout the 0.618 to 0.786 horizontal zone. Price jumps back to the retracement slope at the start of the 0.786 horizontal zone and continues to the 1.0 horizontal zone. The aqua-colored retracement line is enabled to further emphasize this retracement slope . Geometric validation using TradingView's built-in Fibonacci Circle tool (overlaid). The alignment at the 0.5 and 1.0 levels demonstrates the indicator's consistent approximation of Fibonacci Circles. Comparison of Fibonacci Time-Price Zones (Shape: Horizontal) with TradingView's Built-in Retracement and Extension Tools (overlaid): This example demonstrates how the Horizontal structure aligns with TradingView’s retracement and extension levels, allowing users to integrate multiple tools seamlessly. The Fibonacci circle connects retracement and extension zones, highlighting the potential relationship between past retracements and future extensions. 📐 GEOMETRIC FOUNDATIONS 📐 This indicator integrates circular and straight representations of Fibonacci levels, specifically the Circular , Orthogonal , Sloped , and Horizontal shape options. The geometric principles behind these shapes differ significantly, requiring distinct scaling methods for accurate representation. The Circular shape employs logarithmic scaling with radial expansion, where the distance from a central point determines the level's position, creating partial circles that align with TradingView's built-in Fibonacci Circle tool. The other three shapes utilize geometric progression scaling for linear extension from a starting point, resulting in straight lines that align with TradingView's built-in Fibonacci retracement and extension tools. Due to these distinct geometric foundations and scaling methods, perfectly aligning both the partial circles and straight lines simultaneously is mathematically constrained, though any differences are typically visually imperceptible. The Circular shape's partial circles are calculated and scaled to align with TradingView's built-in Fibonacci Circles. These circles are plotted from the second swing point onward. This approach ensures consistent and accurate visualization across all market types, including those with gaps or closed sessions, which unlike 24/7 markets, do not have a direct one-to-one correspondence between bar indices and time. To maintain accurate geometric proportions across varying chart scales, the indicator calculates an aspect ratio by normalizing the proportional difference between vertical (price) and horizontal (time) distances of the swing points. This normalization factor ensures geometric shapes maintain their mathematical properties regardless of price scale magnitude or time period span, while maintaining the correct proportions of the geometric constructions at any chart zoom level. The indicator automatically applies the appropriate scaling factor based on the selected shape option, optimizing either circular proportions and proper radius calculations for each Fibonacci level, or straight-line relationships between Fibonacci levels. These distinct scaling approaches maintain mathematical integrity while preserving the essential characteristics of each geometric representation, ensuring optimal visualization accuracy whether using circular or linear shapes. ⚠️ DISCLAIMER ⚠️ The Fibonacci Time-Price Zones indicator is a visual analysis tool designed to illustrate Fibonacci relationships through geometric constructions incorporating both curved and straight lines, providing a structured framework for identifying potential areas of price interaction. It is not intended as a predictive or standalone trading signal indicator. The indicator calculates levels and projections using user-defined anchor points and Fibonacci ratios. While it aims to align with TradingView’s Fibonacci extension, retracement, and circle tools by employing mathematical and geometric formulas, no guarantee is made that its calculations are identical to TradingView's proprietary methods. Like all technical and visual indicators, these visual representations may visually align with key price zones in hindsight, reflecting observed price dynamics. However, these visualizations are not standalone signals for trading decisions and should be interpreted as part of a broader analytical approach. This indicator is intended for educational and analytical purposes, complementing other tools and methods of market analysis. Users are encouraged to integrate it into a comprehensive trading strategy, customizing its settings to suit their specific needs and market conditions. 🧠 BEYOND THE CODE 🧠 The Fibonacci Time-Price Zones indicator is designed to encourage both education and community engagement. By integrating time-sensitive geometry with Fibonacci-based frameworks, it bridges traditional grid-based analysis with dynamic time-price relationships. The inclusion of semicircles, horizontal levels, orthogonal structures, and sloped trends provides users with versatile tools to explore the interaction between price movements and temporal intervals while maintaining clarity and adaptability. As an open-source tool, the indicator invites exploration, experimentation, and customization. Whether used as a standalone resource or alongside other technical strategies, it serves as a practical and educational framework for understanding market structure and Fibonacci relationships in greater depth. Your feedback and contributions are essential to refining and enhancing the Fibonacci Time-Price Zones indicator. We look forward to the creative applications, adaptations, and insights this tool inspires within the trading community.
Penunjuk Pine Script®
oleh xxattaxx
39
Candle Open Time labels (& TAPDA Lines)Description of the "4-Hour Candle Opening Times (TAPDA Lines)" Indicator The "4-Hour Candle Opening Times (TAPDA Lines)" indicator integrates key principles of the Time and Price Action Trading Algorithm (TAPTA) with practical tools for analyzing market behavior. This script is designed for traders who leverage the interaction between time and price to identify opportunities in the market. The indicator supports the identification of significant price levels and potential areas of interest based on historical data and recurring patterns tied to specific timeframes. Core Concepts Time and Price Interaction (TAPTA Logic): The script implements TAPTA principles by focusing on time intervals (4-hour candles) and the price action associated with those intervals. Traders use this logic to recognize how prices behave at specific times, identifying patterns, levels of support or resistance, and potential reversals. Highs and Lows Recognition (TAPDA): The indicator includes logic for identifying and marking "Tapped Highs and Lows," which occur when price action retraces to previously significant levels within a specified tolerance. These taps are visually represented with horizontal lines, enabling traders to spot recurring price behaviors and levels of interest. Dynamic Levels for Decision-Making: By combining time and price, the script visualizes key price levels and their relevance over time, equipping traders with actionable insights for entry, exit, and risk management. Indicator Features 1. Visual Representation of Candle Opening Times The indicator marks the opening times of 4-hour candles on the chart. A customizable label system displays the time in either a 12-hour or 24-hour format, with options to toggle the visibility of AM/PM suffixes. 2. TAPDA Logic Identifies and highlights price levels that have been tapped within a specified tolerance. Horizontal lines are drawn to mark these levels, allowing traders to see historical price levels acting as support or resistance. The "Tapped Highs and Lows" are updated dynamically based on the most recent price action. 3. Timeframe-Specific Filtering Users can limit the display to specific times of interest, such as 2 AM, 6 AM, and 10 AM, by toggling the "GCT (General Candle Times)" option. Additional options allow filtering TAPDA logic by AM or PM timeframes, catering to traders who focus on specific market sessions. 4. Adjustable Plotting Limits The script incorporates settings for controlling the maximum number of labels and lines displayed on the chart: Max Labels: Limits the number of labels plotted for 4-hour candle opening times. Max TAPDA Lines: Limits the number of TAPDA horizontal lines displayed. A "Sync Lines and Labels" option ensures the same number of labels and lines are plotted when enabled, providing a consistent and clutter-free visualization. 5. Plot Maximum Capability A "Plot Max" feature allows users to override the default behavior and force the plotting of the maximum allowed labels and lines, providing a comprehensive view of historical data. 6. User-Friendly Customization Fully customizable label styles, including options for position, size, color, and background opacity. Adjustable tolerance levels for TAPDA lines ensure compatibility with different market conditions and trading strategies. Settings for flipping or aligning label positions above or below candles, or locking them to the opening price. Script Logic The script is built to prioritize efficiency and clarity, adhering to TradingView's Pine Script best practices and community standards: Initialization: Arrays are used to store historical price data, including highs, lows, and timestamps, ensuring only the necessary amount of data is processed. A flexible and efficient data management system maintains a rolling window of data for both labels and TAPDA lines, ensuring smooth performance. Label and Line Plotting: Labels are plotted dynamically at user-defined positions and styles to mark the opening times of 4-hour candles. TAPDA lines are drawn between historical high or low points and the current price action when the tolerance condition is met. Limit Management: The script enforces limits on the number of labels and lines plotted on the chart to maintain visual clarity. Users can enable synchronization between the maximum labels and lines to ensure consistent visualization. Customization Options: Extensive customization settings allow traders to tailor the indicator to their strategies and preferences, including: Label and line styles. Session filtering (AM, PM, or specific times). Display limits and synchronization options. Capabilities 1. Enhance Time-Based Analysis By marking significant times (4-hour candle openings), traders can identify key market phases and recurring behaviors tied to specific hours. 2. Leverage Historical Price Action TAPDA logic highlights areas where price action interacts with historical highs and lows, providing actionable insights into potential support or resistance zones. 3. Improve Decision-Making The indicator supports informed decision-making by blending visual data with time and price action principles, helping traders spot opportunities and mitigate risks. 4. Flexible Application Across Strategies Suitable for day traders, swing traders, and position traders who utilize time and price action for trend analysis, reversals, or breakout strategies. Best Practices for Use Key Levels Analysis: Focus on labels and TAPDA lines near critical price zones to gauge potential market reactions. Session-Based Trading: Use AM/PM filters or GCT settings to isolate specific trading sessions relevant to your strategy. Combine with Other Indicators: Enhance the effectiveness of this indicator by combining it with moving averages, RSI, or other tools for confirmation. Risk Management: Use the identified levels for stop-loss placement or target setting to align with your risk tolerance.
Penunjuk Pine Script®
oleh SpxGh0st
5
3 EMA + RSI with Trail Stop [Free990] (LOW TF)This trading strategy combines three Exponential Moving Averages (EMAs) to identify trend direction, uses RSI to signal exit conditions, and applies both a fixed percentage stop-loss and a trailing stop for risk management. It aims to capture momentum when the faster EMAs cross the slower EMA, then uses RSI thresholds, time-based exits, and stops to close trades. Short Explanation of the Logic Trend Detection: When the 10 EMA crosses above the 20 EMA and both are above the 100 EMA (and the current price bar closes higher), it triggers a long entry signal. The reverse happens for a short (the 10 EMA crosses below the 20 EMA and both are below the 100 EMA). RSI Exit: RSI crossing above a set threshold closes long trades; crossing below another threshold closes short trades. Time-Based Exit: If a trade is in profit after a set number of bars, the strategy closes it. Stop-Loss & Trailing Stop: A fixed stop-loss based on a percentage from the entry price guards against large drawdowns. A trailing stop dynamically tightens as the trade moves in favor, locking in potential gains. Detailed Explanation of the Strategy Logic Exponential Moving Average (EMA) Setup Short EMA (out_a, length=10) Medium EMA (out_b, length=20) Long EMA (out_c, length=100) The code calculates three separate EMAs to gauge short-term, medium-term, and longer-term trend behavior. By comparing their relative positions, the strategy infers whether the market is bullish (EMAs stacked positively) or bearish (EMAs stacked negatively). Entry Conditions Long Entry (entryLong): Occurs when: The short EMA (10) crosses above the medium EMA (20). Both EMAs (short and medium) are above the long EMA (100). The current bar closes higher than it opened (close > open). This suggests that momentum is shifting to the upside (short-term EMAs crossing up and price action turning bullish). If there’s an existing short position, it’s closed first before opening a new long. Short Entry (entryShort): Occurs when: The short EMA (10) crosses below the medium EMA (20). Both EMAs (short and medium) are below the long EMA (100). The current bar closes lower than it opened (close < open). This indicates a potential shift to the downside. If there’s an existing long position, that gets closed first before opening a new short. Exit Signals RSI-Based Exits: For long trades: When RSI exceeds a specified threshold (e.g., 70 by default), it triggers a long exit. RSI > short_rsi generally means overbought conditions, so the strategy exits to lock in profits or avoid a pullback. For short trades: When RSI dips below a specified threshold (e.g., 30 by default), it triggers a short exit. RSI < long_rsi indicates oversold conditions, so the strategy closes the short to avoid a bounce. Time-Based Exit: If the trade has been open for xBars bars (configurable, e.g., 24 bars) and the trade is in profit (current price above entry for a long, or current price below entry for a short), the strategy closes the position. This helps lock in gains if the move takes too long or momentum stalls. Stop-Loss Management Fixed Stop-Loss (% Based): Each trade has a fixed stop-loss calculated as a percentage from the average entry price. For long positions, the stop-loss is set below the entry price by a user-defined percentage (fixStopLossPerc). For short positions, the stop-loss is set above the entry price by the same percentage. This mechanism prevents catastrophic losses if the market moves strongly against the position. Trailing Stop: The strategy also sets a trail stop using trail_points (the distance in price points) and trail_offset (how quickly the stop “catches up” to price). As the market moves in favor of the trade, the trailing stop gradually tightens, allowing profits to run while still capping potential drawdowns if the price reverses. Order Execution Flow When the conditions for a new position (long or short) are triggered, the strategy first checks if there’s an opposite position open. If there is, it closes that position before opening the new one (prevents going “both long and short” simultaneously). RSI-based and time-based exits are checked on each bar. If triggered, the position is closed. If the position remains open, the fixed stop-loss and trailing stop remain in effect until the position is exited. Why This Combination Works Multiple EMA Cross: Combining 10, 20, and 100 EMAs balances short-term momentum detection with a longer-term trend filter. This reduces false signals that can occur if you only look at a single crossover without considering the broader trend. RSI Exits: RSI provides a momentum oscillator view—helpful for detecting overbought/oversold conditions, acting as an extra confirmation to exit. Time-Based Exit: Prevents “lingering trades.” If the position is in profit but failing to advance further, it takes profit rather than risking a trend reversal. Fixed & Trailing Stop-Loss: The fixed stop-loss is your safety net to cap worst-case losses. The trailing stop allows the strategy to lock in gains by following the trade as it moves favorably, thus maximizing profit potential while keeping risk in check. Overall, this approach tries to capture momentum from EMA crossovers, protect profits with trailing stops, and limit risk through both a fixed percentage stop-loss and exit signals from RSI/time-based logic.
Strategi Pine Script®
oleh Free990
25
Overnight Effect High Volatility Crypto (AiBitcoinTrend)👽 Overview of the Strategy This strategy leverages the overnight effect in the cryptocurrency market, specifically targeting the two-hour window from 21:00 UTC to 23:00 UTC. The strategy is designed to be applied only during periods of high volatility, which is determined using historical volatility data. This approach, inspired by research from Padyšák and Vojtko (2022), aims to capitalize on statistically significant return patterns observed during these hours. Deep Backtesting with a High Volatility Filter Deep Backtesting without a High Volatility Filter 👽 How the Strategy Works Volatility Calculation: Each day at 00:00 UTC, the strategy calculates the 30-day historical volatility of crypto returns (typically Bitcoin). The historical volatility is the standard deviation of the log returns over the past 30 days, representing the market's recent volatility level. Median Volatility Benchmark: The median of the 30-day historical volatility is calculated over a 365-day period (one year). This median acts as a benchmark to classify each day as either: 👾 High Volatility: When the current 30-day volatility exceeds the median volatility. 👾 Low Volatility: When the current 30-day volatility is below the median. Trading Rule: If the day is classified as a High Volatility Day, the strategy executes the following trades: 👾 Buy at 21:00 UTC. 👾 Sell at 23:00 UTC. Trade Execution Details: The strategy uses a 0.02% fee per trade. Each trade is executed with 25% of the available capital. This allocation helps manage risk while allowing for compounding returns. Rationale: The returns during the 22:00 and 23:00 UTC hours have been found to be statistically significant during high volatility periods. The overnight effect is believed to drive this phenomenon due to the asynchronous closing hours of global financial markets. This creates unique trading opportunities in the cryptocurrency market, where exchanges remain open 24/7. 👽 Market Context and Global Time Zone Impact 👾 Why 21:00 to 23:00 UTC? During this window, major traditional financial markets are closed: NYSE (New York) closes at 21:00 UTC. London and European markets are closed during these hours. Asian markets (Tokyo, Hong Kong, etc.) open later, leaving this window largely unaffected by traditional trading flows. This global market inactivity creates a period where significant moves can occur in the cryptocurrency market, particularly during high volatility. 👽 Strategy Parameters Volatility Period: 30 days. The lookback period for calculating historical volatility. Median Period: 365 days. The lookback period for calculating the median volatility benchmark. Entry Time: 21:00 UTC. Adjust this to your local time if necessary (e.g., 16:00 in New York, 22:00 in Stockholm). Exit Time: 23:00 UTC. Adjust this to your local time if necessary (e.g., 18:00 in New York, 00:00 midnight in Stockholm). 👽 Benefits of the Strategy Seasonality Effect: The strategy captures consistent patterns driven by the overnight effect and high volatility periods. Risk Reduction: Since trades are executed during a specific window and only on high volatility days, the strategy helps mitigate exposure to broader market risk. Simplicity and Efficiency: The strategy is moderately complex, making it accessible for traders while offering significant returns. Global Applicability: Suitable for traders worldwide, with clear guidelines on adjusting for local time zones. 👽 Considerations Market Conditions: The strategy works best in a high-volatility environment. Execution: Requires precise timing to enter and exit trades at the specified hours. Time Zone Adjustments: Ensure you convert UTC times accurately based on your location to execute trades at the correct local times. Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Strategi Pine Script®
oleh aibitcointrend
DCA Strategy with Mean Reversion and Bollinger BandDCA Strategy with Mean Reversion and Bollinger Band The Dollar-Cost Averaging (DCA) Strategy with Mean Reversion and Bollinger Bands is a sophisticated trading strategy that combines the principles of DCA, mean reversion, and technical analysis using Bollinger Bands. This strategy aims to capitalize on market corrections by systematically entering positions during periods of price pullbacks and reversion to the mean. Key Concepts and Principles 1. Dollar-Cost Averaging (DCA) DCA is an investment strategy that involves regularly purchasing a fixed dollar amount of an asset, regardless of its price. The idea behind DCA is that by spreading out investments over time, the impact of market volatility is reduced, and investors can avoid making large investments at inopportune times. The strategy reduces the risk of buying all at once during a market high and can smooth out the cost of purchasing assets over time. In the context of this strategy, the Investment Amount (USD) is set by the user and represents the amount of capital to be invested in each buy order. The strategy executes buy orders whenever the price crosses below the lower Bollinger Band, which suggests a potential market correction or pullback. This is an effective way to average the entry price and avoid the emotional pitfalls of trying to time the market perfectly. 2. Mean Reversion Mean reversion is a concept that suggests prices will tend to return to their historical average or mean over time. In this strategy, mean reversion is implemented using the Bollinger Bands, which are based on a moving average and standard deviation. The lower band is considered a potential buy signal when the price crosses below it, indicating that the asset has become oversold or underpriced relative to its historical average. This triggers the DCA buy order. Mean reversion strategies are popular because they exploit the natural tendency of prices to revert to their mean after experiencing extreme deviations, such as during market corrections or panic selling. 3. Bollinger Bands Bollinger Bands are a technical analysis tool that consists of three lines: Middle Band: The moving average, usually a 200-period Exponential Moving Average (EMA) in this strategy. This serves as the "mean" or baseline. Upper Band: The middle band plus a certain number of standard deviations (multiplier). The upper band is used to identify overbought conditions. Lower Band: The middle band minus a certain number of standard deviations (multiplier). The lower band is used to identify oversold conditions. In this strategy, the Bollinger Bands are used to identify potential entry points for DCA trades. When the price crosses below the lower band, this is seen as a potential opportunity for mean reversion, suggesting that the asset may be oversold and could reverse back toward the middle band (the EMA). Conversely, when the price crosses above the upper band, it indicates overbought conditions and signals potential market exhaustion. 4. Time-Based Entry and Exit The strategy has specific entry and exit points defined by time parameters: Open Date: The date when the strategy begins opening positions. Close Date: The date when all positions are closed. This time-bound approach ensures that the strategy is active only during a specified window, which can be useful for testing specific market conditions or focusing on a particular time frame. 5. Position Sizing Position sizing is determined by the Investment Amount (USD), which is the fixed amount to be invested in each buy order. The quantity of the asset to be purchased is calculated by dividing the investment amount by the current price of the asset (investment_amount / close). This ensures that the amount invested remains constant despite fluctuations in the asset's price. 6. Closing All Positions The strategy includes an exit rule that closes all positions once the specified close date is reached. This allows for controlled exits and limits the exposure to market fluctuations beyond the strategy's timeframe. 7. Background Color Based on Price Relative to Bollinger Bands The script uses the background color of the chart to provide visual feedback about the price's relationship with the Bollinger Bands: Red background indicates the price is above the upper band, signaling overbought conditions. Green background indicates the price is below the lower band, signaling oversold conditions. This provides an easy-to-interpret visual cue for traders to assess the current market environment. Postscript: Configuring Initial Capital for Backtesting To ensure the backtest results align with the actual investment scenario, users must adjust the Initial Capital in the TradingView strategy properties. This is done by calculating the Initial Capital as the product of the Total Closed Trades and the Investment Amount (USD). For instance: If the user is investing 100 USD per trade and has 10 closed trades, the Initial Capital should be set to 1,000 USD. Similarly, if the user is investing 200 USD per trade and has 24 closed trades, the Initial Capital should be set to 4,800 USD. This adjustment ensures that the backtesting results reflect the actual capital deployed in the strategy and provides an accurate representation of potential gains and losses. Conclusion The DCA strategy with Mean Reversion and Bollinger Bands is a systematic approach to investing that leverages the power of regular investments and technical analysis to reduce market timing risks. By combining DCA with the insights offered by Bollinger Bands and mean reversion, this strategy offers a structured way to navigate volatile markets while targeting favorable entry points. The clear entry and exit rules, coupled with time-based constraints, make it a robust and disciplined approach to long-term investing.
Strategi Pine Script®
oleh Wongsakon
2
Volume Rate of Change (VROC)Volume Rate of Change (VROC) is an indicator that calculates the percentage change in trading volume over a specific period, helping analyze market momentum and activity. It is calculated as: VROC = ((Current Volume - Past Volume) ÷ Past Volume) × 100 This indicator shows changes in market interest. Positive values indicate increasing volume, while negative values signal a decrease. High VROC values often suggest potential trend reversals or breakouts. Applications: Breakout Validation: VROC > 200% confirms strong breakouts; below this may signal false moves. Market Stagnation: VROC < 0% suggests shrinking volume and range-bound markets. Trend End Alert: A drop below 0% during trends may indicate weakening momentum. Adjusting for Timeframes: Tailor VROC to timeframes. Examples: Daily: VROC(5) compares with last week's same day; VROC(20) with 1 month ago. Monthly: VROC(12) compares with the same month last year; VROC(1) with last month. Intraday: VROC(24) (hourly) and VROC(288) (5 minutes) for the same time yesterday.
Penunjuk Pine Script®
oleh k104
Daily High/Low Levels with mitigationThis Pine Script script defines a TradingView indicator named "Daily High/Low Levels" designed to track and display the daily high and low levels of a trading session, with added functionality for marking levels as mitigated when certain conditions are met. Here's a breakdown of its functionality: Key Features Session Start Time: The script allows you to specify a custom session start time in 24-hour format. This ensures the levels align with your trading session preferences. Daily Highs and Lows: Tracks the high and low levels for each session. Retains the highs and lows for a configurable number of previous days. Visualization: Creates horizontal lines for each session's high and low levels. Supports customization of line colors and styles. Mitigation Tracking: Monitors whether a high or low level has been "mitigated" (touched or exceeded by subsequent price action). Changes the line style and color to indicate mitigation. Provides an alert when mitigation occurs. Configurable Extensions: Lines can be extended beyond mitigation or stopped at the bar index where mitigation occurs, depending on user preference. Efficient Array Management: Uses arrays to manage daily highs, lows, their respective indices, and lines. Ensures the size of stored data does not exceed the configured limit (daysToTrack). Alerts: Sends alerts when high or low levels are mitigated, which can be used for trading decisions. Inputs Session Start Hour/Minute: Defines when a new session starts. Days to Track: Sets the number of previous days to display high/low levels. Colors: Allows customization of line colors for unmitigated and mitigated levels. Extend Lines: Toggles whether lines should extend past the mitigation point. Code Highlights New Session Detection: The script detects the start of a new session based on the configured session start time and resets daily highs/lows. Line Management: Horizontal rays are created for highs and lows, and mitigated lines are updated with a dashed style and faded color. Mitigation Logic: The script checks whether current price action exceeds stored high or low levels and updates their status and appearance accordingly. Memory Management: Ensures the size of the arrays (highs, lows, lines) does not exceed the configured daysToTrack, deleting the oldest elements as necessary. This indicator is highly customizable and useful for traders who want to track and analyze daily support and resistance levels, incorporating mitigation as a dynamic feature.
Penunjuk Pine Script®
oleh NOSRAL
Weis Wave Max█ Overview Weis Wave Max is the result of my weis wave study. David Weis said, "Trading with the Weis Wave involves changes in behavior associated with springs, upthrusts, tests of breakouts/breakdowns, and effort vs reward. The most common setup is the low-volume pullback after a bullish/bearish change in behavior." THE STOCK MARKET UPDATE (February 24, 2013) I inspired from his sentences and made this script. Its Main feature is to identify the largest wave in Weis wave and advantageous trading opportunities. █ Features This indicator includes several features related to the Weis Wave Method. They help you analyze which is more bullish or bearish. Highlight Max Wave Value (single direction) Highlight Abnormal Max Wave Value (both directions) Support and Resistance zone Signals and Setups █ Usage Weis wave indicator displays cumulative volume for each wave. Wave volume is effective when analyzing volume from VSA (Volume Spread Analysis) perspective. The basic idea of Weis wave is large wave volume hint trend direction. This helps identify proper entry point. This indicator highlights max wave volume and displays the signal and then proper Risk Reward Ratio entry frame. I defined Change in Behavior as max wave volume (single direction). Pullback is next wave that does not exceed the starting point of CiB wave (LH sell entry, HL buy entry). Change in Behavior Signal ○ appears when pullback is determined. Change in Behavior Setup (Entry frame) appears when condition of Min/Max Pullback is met and follow through wave breaks end point of CiB wave. This indicator has many other features and they can also help a user identify potential levels of trade entry and which is more bullish or bearish. In the screenshot below we can see wave volume zones as support and resistance levels. SOT and large wave volume /delta price (yellow colored wave text frame) hint stopping action. █ Settings Explains the main settings.  -- General -- Wave size : Allows the User to select wave size from ① Fixed or ② ATR. ② ATR is Factor x ATR(Length). Display : Allows the User to select how many wave text and zigzag appear. -- Wave Type -- Wave type : Allows the User to select from Volume or Volume and Time. Wave Volume / delta price : Displays Wave Volume / delta price. Simplified value : Allows the User to select wave text display style from ① Divisor or ② Normalized. Normalized use SMA. Decimal : Allows the User to select the decimal point in the Wave text. -- Highlight Abnormal Wave -- Highlight Max Wave value (single direction) : Adds marks to the Wave text to highlight the max wave value. Lookback : Allows the User to select how many waves search for the max wave value. Highlight Abnormal Wave value (both directions) : Changes wave text size, color or frame color to highlight the abnormal wave value. Lookback : Allows the User to select SMA length to decide average wave value. Large/Small factor : Allows the User to select the threshold large wave value and small wave value. Average wave value is 1. delta price : Highlights large delta price by large wave text size, small by small text size. Wave Volume : Highlights large wave volume by yellow colored wave text, small by gray colored. Wave Volume / delta price : highlights large Wave Volume / delta price by yellow colored wave text frame, small by gray colored. -- Support and Resistance -- Single side Max Wave Volume / delta price : Draws dashed border box from end point of Max wave volume / delta price level. Single side Max Wave Volume : Draws solid border box from start point of Max wave volume level. Bias Wave Volume : Draws solid border box from start point of bias wave volume level. -- Signals -- Bias (Wave Volume / delta price) : Displays Bias mark when large difference in wave volume / delta price before and after. Ratio : Decides the threshold of become large difference. 3Decrease : Displays 3D mark when a continuous decrease in wave volume. Shortening Of the Thrust : Displays SOT mark when a continuous decrease in delta price. Change in Behavior and Pullback : Displays CiB mark when single side max wave volume and pullback. -- Setups -- Change in Behavior and Pullback and Breakout : Displays entry frame when change in behavior and pullback and then breakout. Min / Max Pullback : Decides the threshold of min / max pullback. If you need more information, please read the indicator's tooltip. █ Conclusion Weis Wave is powerful interpretation of volume and its tell us potential trend change and entry point which can't find without weis wave. It's not the holy grail, but improve your chart reading skills and help you trade rationally (at least from VSA perspective).
Penunjuk Pine Script®
oleh akutsusho
24
Mean Price ^^ Plotting switched to Line. This method of financial time series (aka bars) downsampling is literally, naturally, and thankfully the best you can do in terms of maximizing info gain. You can finally chill and feed it to your studies & eyes, and probably use nothing else anymore. (HL2 and occ3 also have use cases, but other aggregation methods? Not really, even if they do, the use cases are ‘very’ specific). Tho in order to understand why, you gotta read the following wall, or just believe me telling you, ‘I put it on my momma’. The true story about trading volumes and why this is all a big misdirection Actually, you don’t need to be a quant to get there. All you gotta do is stop blindly following other people’s contextual (at best) solutions, eg OC2 aggregation xD, and start using your own brain to figure things out. Every individual trade (basically an imprint on 1D price space that emerges when market orders hit the order book) has several features like: price, time, volume, AND direction (Up if a market buy order hits the asks, Down if a market sell order hits the bids). Now, the last two features—volume and direction—can be effectively combined into one (by multiplying volume by 1 or -1), and this is probably how every order matching engine should output data. If we’re not considering size/direction, we’re leaving data behind. Moreover, trades aren’t just one-price dots all the time. One trade can consume liquidity on several levels of the order book, so a single trade can be several ticks big on the price axis. You may think now that there are no zero-volume ticks. Well, yes and no. It depends on how you design an exchange and whether you allow intra-spread trades/mid-spread trades (now try to Google it). Intra-spread trades could happen if implemented when a matching engine receives both buy and sell orders at the same microsecond period. This way, you can match the orders with each other at a better price for both parties without even hitting the book and consuming liquidity. Also, if orders have different sizes, the remaining part of the bigger order can be sent to the order book. Basically, this type of trade can be treated as an OTC trade, having zero volume because we never actually hit the book—there’s no imprint. Another reason why it makes sense is when we think about volume as an impact or imbalance act, and how the medium (order book in our case) responds to it, providing information. OTC and mid-spread trades are not aggressive sells or buys; they’re neutral ticks, so to say. However huge they are, sometimes many blocks on NYSE, they don’t move the price because there’s no impact on the medium (again, which is the order book)—they’re not providing information. ... Now, we need to aggregate these trades into, let’s say, 1-hour bars (remember that a trade can have either positive or negative volume). We either don’t want to do it, or we don’t have this kind of information. What we can do is take already aggregated OHLC bars and extract all the info from them. Given the market is fractal, bars & trades gotta have the same set of features: - Highest & lowest ticks (high & low) <- by price; - First & last ticks (open & close) <- by time; - Biggest and smallest ticks <- by volume.* *e.g., in the array , 2323: biggest trade, -1212: smallest trade. Now, in our world, somehow nobody started to care about the biggest and smallest trades and their inclusion in OHLC data, while this is actually natural. It’s the same way as it’s done with high & low and open & close: we choose the minimum and maximum value of a given feature/axis within the aggregation period. So, we don’t have these 2 values: biggest and smallest ticks. The best we can do is infer them, and given the fact the biggest and smallest ticks can be located with the same probability everywhere, all we can do is predict them in the middle of the bar, both in time and price axes. That’s why you can see two HL2’s in each of the 3 formulas in the code. So, summed up absolute volumes that you see in almost every trading platform are actually just a derivative metric, something that I call Type 2 time series in my own (proprietary ‘for now’) methods. It doesn’t have much to do with market orders hitting the non-uniform medium (aka order book); it’s more like a statistic. Still wanna use VWAP? Ok, but you gotta understand you’re weighting Type 1 (natural) time series by Type 2 (synthetic) ones. How to combine all the data in the right way (khmm khhm ‘order’) Now, since we have 6 values for each bar, let’s see what information we have about them, what we don’t have, and what we can do about it: - Open and close: we got both when and where (time (order) and price); - High and low: we got where, but we don’t know when; - Biggest & smallest trades: we know shit, we infer it the way it was described before.' By using the location of the close & open prices relative to the high & low prices, we can make educated guesses about whether high or low was made first in a given bar. It’s not perfect, but it’s ultimately all we can do—this is the very last bit of info we can extract from the data we have. There are 2 methods for inferring volume delta (which I call simply volume) that are presented everywhere, even here on TradingView. Funny thing is, this is actually 2 parts of the 1 method. I wonder how many folks see through it xD. The same method can be used for both inferring volume delta AND making educated guesses whether high or low was made first. Imagine and/or find the cases on your charts to understand faster: * Close > open means we have an up bar and probably the volume is positive, and probably high was made later than low. * Close < open means we have a down bar and probably the volume is negative, and probably low was made later than high. Now that’s the point when you see that these 2 mentioned methods are actually parts of the 1 method: If close = open, we still have another clue: distance from open/close pair to high (HC), and distance from open/close pair to low (LC): * HC < LC, probably high was made later. * HC > LC, probably low was made later. And only if close = open and HC = LC, only in this case we have no clue whether high or low was made earlier within a bar. We simply don’t have any more information to even guess. This bar is called a neutral bar. At this point, we have both time (order) and price info for each of our 6 values. Now, we have to solve another weighted average problem, and that’s it. We’ll weight prices according to the order we’ve guessed. In the neutral bar case, open has a weight of 1, close has a weight of 3, and both high and low have weights of 2 since we can’t infer which one was made first. In all cases, biggest and smallest ticks are modeled with HL2 and weighted like they’re located in the middle of the bar in a time sense. P.S.: I’ve also included a "robust" method where all the bars are treated like neutral ones. I’ve used it before; obviously, it has lesser info gain -> works a bit worse.
Penunjuk Pine Script®
oleh gorx1
1
QuantifyPS - 1Library "QuantifyPS" normdist(z)   Parameters:      z (float) : (float): The z-score for which the CDF is to be calculated.   Returns: (float): The cumulative probability corresponding to the input z-score. Notes: - Uses an approximation method for the normal distribution CDF, which is computationally efficient. - The result is accurate for most practical purposes but may have minor deviations for extreme values of `z`. Formula: - Based on the approximation formula: `Φ(z) ≈ 1 - f(z) * P(t)` if `z > 0`, otherwise `Φ(z) ≈ f(z) * P(t)`, where: `f(z) = 0.3989423 * exp(-z^2 / 2)` (PDF of standard normal distribution) `P(t) = Σ [c * t^i]` with constants `c` and `t = 1 / (1 + 0.2316419 * |z|)`. Implementation details: - The approximation uses five coefficients for the polynomial part of the CDF. - Handles both positive and negative values of `z` symmetrically. Constants: - The coefficients and scaling factors are chosen to minimize approximation errors. gamma(x)   Parameters:      x (float) : (float): The input value for which the Gamma function is to be calculated. Must be greater than 0. For x <= 0, the function returns `na` as it is undefined.   Returns: (float): Approximation of the Gamma function for the input `x`. Notes: - The Lanczos approximation provides a numerically stable and efficient method to compute the Gamma function. - The function is not defined for `x <= 0` and will return `na` in such cases. - Uses precomputed Lanczos coefficients for accuracy. - Includes handling for small numerical inaccuracies. Formula: - The Gamma function is approximated as: `Γ(x) ≈ sqrt(2π) * t^(x + 0.5) * e^(-t) * Σ(p / (x + k))` where `t = x + g + 0.5` and `p` is the array of Lanczos coefficients. Implementation details: - Lanczos coefficients (`p`) are precomputed and stored in an array. - The summation iterates over these coefficients to compute the final result. - The constant `g` controls the precision of the approximation (commonly `g = 7`). t_cdf(t, df)   Parameters:      t (float) : (float): The t-statistic for which the CDF value is to be calculated.      df (int) : (int): Degrees of freedom of the t-distribution.   Returns: (float): Approximate CDF value for the given t-statistic. Notes: - This function computes a one-tailed p-value. - Relies on an approximation formula using gamma functions and standard t-distribution properties. - May not be as accurate as specialized statistical libraries for extreme values or very high degrees of freedom. Formula: - Let `x = df / (t^2 + df)`. - The approximation formula is derived using: `CDF(t, df) ≈ 1 - * x^((df + 1) / 2) / 2`, where Γ represents the gamma function. Implementation details: - Computes the gamma ratio for normalization. - Applies the t-distribution formula for one-tailed probabilities. tStatForPValue(p, df)   Parameters:      p (float) : (float): P-value for which the t-statistic needs to be calculated. Must be in the interval (0, 1).      df (int) : (int): Degrees of freedom of the t-distribution.   Returns: (float): The t-statistic corresponding to the given p-value. Notes: - If `p` is outside the interval (0, 1), the function returns `na` as an error. - The function uses binary search with a fixed number of iterations and a defined tolerance. - The result is accurate to within the specified tolerance (default: 0.0001). - Relies on the cumulative density function (CDF) `t_cdf` for the t-distribution. Formula: - Uses the cumulative density function (CDF) of the t-distribution to iteratively find the t-statistic. Implementation details: - `low` and `high` define the search interval for the t-statistic. - The midpoint (`mid`) is iteratively refined until the difference between the cumulative probability and the target p-value is smaller than the tolerance. jarqueBera(n, s, k)   Parameters:      n (float) : (series float): Number of observations in the dataset.      s (float) : (series float): Skewness of the dataset.      k (float) : (series float): Kurtosis of the dataset.   Returns: (float): The Jarque-Bera test statistic. Formula: JB = n * Notes: - A higher JB value suggests that the data deviates more from a normal distribution. - The test is asymptotically distributed as a chi-squared distribution with 2 degrees of freedom. - Use this value to calculate a p-value to determine the significance of the result. skewness(data)   Parameters:      data (float) : (series float): Input data series.   Returns: (float): The skewness value. Notes: - Handles missing values (`na`) by ignoring invalid points. - Includes error handling for zero variance to avoid division-by-zero scenarios. - Skewness is calculated as the normalized third central moment of the data. kurtosis(data)   Parameters:      data (float) : (series float): Input data series.   Returns: (float): The kurtosis value. Notes: - Handles missing values (`na`) by ignoring invalid points. - Includes error handling for zero variance to avoid division-by-zero scenarios. - Kurtosis is calculated as the normalized fourth central moment of the data. regression(y, x, lag)   Parameters:      y (float) : (series float): Dependent series (observed values).      x (float) : (series float): Independent series (explanatory variable).      lag (int) : (int): Number of lags applied to the independent series (x).   Returns: (tuple): Returns a tuple containing the following values: - n: Number of valid observations. - alpha: Intercept of the regression line. - beta: Slope of the regression line. - t_stat: T-statistic for the beta coefficient. - p_value: Two-tailed p-value for the beta coefficient. - r_squared: Coefficient of determination (R²) indicating goodness of fit. - skew: Skewness of the residuals. - kurt: Kurtosis of the residuals. Notes: - Handles missing data (`na`) by ignoring invalid points. - Includes basic error handling for zero variance and division-by-zero scenarios. - Computes residual-based statistics (skewness and kurtosis) for model diagnostics.
Perpustakaan Pine Script®
oleh Sigaud
Tims Smart Money COT-IndexThe **Tims Smart Money COT Index** analyzes the positions of different groups of market participants from the COT report (Commercials, Large Specs, Small Specs). It calculates their net positions and scales them relative to extremes of the last 24 weeks. It indicates bullish and bearish zones to identify market sentiments. - Commercials (Smart Money)**: Often act against the trend, bullish from 80+. - Large Specs (Retail Money)**: Trend-following, bullish from 80+. - Small Specs**: Mostly impulsive, bullish from 80+. The indicator helps to identify turning points in the market based on the behavior of the players.
Penunjuk Pine Script®
oleh Tim234
1
Forex Heatmap█   OVERVIEW This indicator creates a dynamic grid display of currency pair cross rates (exchange rates) and percentage changes, emulating the Cross Rates and Heat Map widgets available on our Forex page. It provides a view of realtime exchange rates for all possible pairs derived from a user-specified list of currencies, allowing users to monitor the relative performance of several currencies directly on a TradingView chart. █   CONCEPTS Foreign exchange The Foreign Exchange (Forex/FX) market is the largest, most liquid financial market globally, with an average daily trading volume of over 5 trillion USD. Open 24 hours a day, five days a week, it operates through a decentralized network of financial hubs in various major cities worldwide. In this market, participants trade currencies in pairs , where the listed price of a currency pair represents the exchange rate from a given base currency to a specific quote currency . For example, the "EURUSD" pair's price represents the amount of USD (quote currency) that equals one unit of EUR (base currency). Globally, the most traded currencies include the U.S. dollar (USD), Euro (EUR), Japanese yen (JPY), British pound (GBP), and Australian dollar (AUD), with USD involved in over 87% of all trades. Understanding the Forex market is essential for traders and investors, even those who do not trade currency pairs directly, because exchange rates profoundly affect global markets. For instance, fluctuations in the value of USD can impact the demand for U.S. exports or the earnings of companies that handle multinational transactions, either of which can affect the prices of stocks, indices, and commodities. Additionally, since many factors influence exchange rates, including economic policies and interest rate changes, analyzing the exchange rates across currencies can provide insight into global economic health. █   FEATURES Requesting a list of currencies This indicator requests data for every valid currency pair combination from the list of currencies defined by the "Currency list" input in the "Settings/Inputs" tab. The list can contain up to six unique currency codes separated by commas, resulting in a maximum of 30 requested currency pairs. For example, if the specified "Currency list" input is "CAD, USD, EUR", the indicator requests and displays relevant data for six currency pair combinations: "CADUSD", "USDCAD", "CADEUR", "EURCAD", "USDEUR", "EURUSD". See the "Grid display" section below to understand how the script organizes the requested information. Each item in the comma-separated list must represent a valid currency code. If the "Currency list" input contains an invalid currency code, the corresponding cells for that currency in the "Cross rates" or "Heat map" grid show "NaN" values. If the list contains empty items, e.g., "CAD, ,EUR, ", the indicator ignores them in its data requests and calculations. NOTE: Some uncommon currency pair combinations might not have data feeds available. If no available symbols provide the exchange rates between two specified currencies, the corresponding table cells show "NaN" results. Realtime data The indicator retrieves realtime market prices, daily price changes, and minimum tick sizes for all the currency pairs derived from the "Currency list" input. It updates the retrieved information shown in its grid display after new ticks become available to reflect the latest known values. NOTE: Pine scripts execute on realtime bars only when new ticks are available in the chart's data feed. If no new updates are available from the chart's realtime feed, it may cause a delay in the data the indicator receives. Grid display This indicator displays the requested data for each currency pair in a table with cells organized as a grid. Each row name corresponds to a pair's base currency , and each column name corresponds to a quote currency . The cell at the intersection of a specific row and column shows the value requested from the corresponding currency pair. For example, the cell at the intersection of a "EUR" row and "USD" column shows the data retrieved for the "EURUSD" currency pair, and the cell at the "USD" row and "EUR" column shows data for the inverse pair ("USDEUR"). Note that the main diagonal cells in the table, where rows and columns with the same names intersect, are blank. The exchange rate from one currency to itself is always 1, and no Forex symbols such as "EUREUR" exist. The dropdown input at the top of the "Settings/Inputs" tab determines the type of information displayed in the table. Two options are available: "Cross rates" and "Heat map" . Both modes color their cells for light and dark themes separately based on the inputs in the "Colors" section. Cross rates When a user selects the "Cross rates" display mode, the table's cells show the latest available exchange rate for each currency pair, emulating the behavior of the Cross Rates widget. Each cell's value represents the amount of the quote currency (column name) that equals one unit of the base currency (row name). This display allows users to compare cross rates across currency pairs, and their inverses. The background color of each cell changes based on the most recent update to the exchange rate, allowing users to monitor the direction of short-term fluctuations as they occur. By default, the background turns green (positive cell color) when the cross rate increases from the last recorded update and red (negative cell color) when the rate decreases. The cell's color reverts to the chart's background color after no new updates are available for 200 milliseconds. Heat map When a user selects the "Heat map" display mode, the table's cells show the latest daily percentage change of each currency pair, emulating the behavior of the Heat Map widget. In this mode, the background color of each cell depends on the corresponding currency pair's daily performance. Heat maps typically use colors that vary in intensity based on the calculated values. This indicator uses the following color coding by default:  • Green (Positive cell color): Percentage change > +0.1%  • No color: Percentage change between 0.0% and +0.1%  • Bright red (Negative cell color): Percentage change < -0.1%  • Lighter/darker red (Minor negative cell color): Percentage change between 0.0% and -0.1% █   FOR Pine Script™ CODERS • This script utilizes dynamic requests to iteratively fetch information from multiple contexts using a single request.security() instance in the code. Previously, `request.*()` functions were not allowed within the local scopes of loops or conditional structures, and most `request.*()` function parameters, excluding `expression`, required arguments of a simple or weaker qualified type. The new `dynamic_requests` parameter in script declaration statements enables more flexibility in how scripts can use `request.*()` calls. When its value is `true`, all `request.*()` functions can accept series arguments for the parameters that define their requested contexts, and `request.*()` functions can execute within local scopes. See the Dynamic requests section of the Pine Script™ User Manual to learn more. • Scripts can execute up to 40 unique `request.*()` function calls. A `request.*()` call is unique only if the script does not already call the same function with the same arguments. See this section of the User Manual's Limitations page for more information. • Typically, when requesting higher-timeframe data with request.security() using barmerge.lookahead_on as the `lookahead` argument, the `expression` argument should use the history-referencing operator to offset the series, preventing lookahead bias on historical bars. However, the request.security() call in this script uses barmerge.lookahead_on without offsetting the `expression` because the script only displays results for the latest historical bar and all realtime bars, where there is no future information to leak into the past. Instead, using this call on those bars ensures each request fetches the most recent data available from each context. • The request.security() instance in this script includes a `calc_bars_count` argument to specify that each request retrieves only a minimal number of bars from the end of each symbol's historical data feed. The script does not need to request all the historical data for each symbol because it only shows results on the last chart bar that do not depend on the entire time series. In this case, reducing the retrieved bars in each request helps minimize resource usage without impacting the calculated results. Look first. Then leap.
Penunjuk Pine Script®
oleh TradingView
2
New Day [UkutaLabs]█ OVERVIEW The New Day indicator is a useful trading tool that automatically identifies the first bar of each trading day for the user’s convenience. █ USAGE At the beginning of each trading day, this indicator will automatically create a line that will display the first bar of the trading day. This is a useful way to visualize where each day begins and ends. When this indicator is used on a stock or futures chart, the first bar of the session will be identified as the first bar of the trading day. If this indicator is used on crypto or forex charts, which are tradable for 24 hours, the indicator will identify the bar closest to midnight as the first bar of the trading day. █ SETTINGS Configuration • Line Color: This setting allows the user to determine the color of the New Day line. • Line Width: This setting allows the user to determine the width of the New Day line. • Line Style: This setting allows the user to determine the style of the New Day line.
Penunjuk Pine Script®
oleh UkutaLabs
3AM EST CRT Indicator3AM EST Candle Range Theory Indicator The 3AM EST Candle Range Theory Indicator is designed to highlight a crucial period in the trading day for Forex and other markets that operate 24/7. This indicator focuses on the 3AM EST candle, which represents the early hours of the U.S. market morning and the midpoint of the European trading session. During this period, volatility often picks up, and the 3AM candle can serve as a powerful reference point for price action throughout the day. Key Features of the Indicator 3AM Candle Highlighting: The 3AM candle is automatically highlighted in blue, making it easy to spot on the chart. This helps traders quickly identify this pivotal candle without manually searching for it. Range Lines: The high and low of the 3AM candle are marked by black lines extending across the day. These levels often act as support and resistance, influencing price movement throughout the trading session. Observing how the price interacts with these levels can provide insights into potential breakouts, reversals, or consolidations. Labels: The high of the 3AM candle is labeled as "3am CRH" (Candle Range High) and the low as "3am CRL" (Candle Range Low). These labels serve as visual cues for traders, reinforcing the importance of these levels on the chart. How to Use the 3AM EST Candle Range Indicator Support and Resistance: The high and low of the 3AM candle often serve as strong intraday support and resistance levels. Traders can observe if the price respects or breaks these levels to make decisions about potential entries and exits. Breakout Trading: If the price breaks above the 3am high (CRH), it can signal bullish momentum, especially when accompanied by increased volume. Conversely, a break below the 3am low (CRL) may indicate bearish momentum. These breakouts can provide potential trade opportunities. Reversals and Continuations: Often, price will test and reject one of these levels, creating an opportunity for reversal trades. If the price re-enters the 3AM candle range after breaking out, it could signal a potential continuation back into the original trend. Session Range Guidance: Since the 3AM candle encapsulates both the early U.S. and active European sessions, it often provides a strong reference for the range and sentiment in the early trading hours. The 3AM range can give a sense of market direction and volatility for the day. Benefits Clear Visual Cues: The blue candle highlight, black lines, and labels make this indicator visually intuitive and easy to understand at a glance. Useful Across Market Conditions: Whether markets are trending or ranging, the 3AM high and low can serve as reliable reference points for intraday support and resistance. Applicable to Various Strategies: This indicator can enhance a variety of trading strategies, including breakout, range trading, and trend-following. Summary The 3AM EST Candle Range Theory Indicator provides traders with a reliable way to gauge intraday price levels based on the 3AM EST candle. By observing how the price interacts with the high and low of this candle, traders can gain insights into potential support, resistance, and breakout points. This can be particularly useful for short-term traders looking to capitalize on intraday volatility or longer-term traders seeking reference points for daily price action analysis.
Penunjuk Pine Script®
oleh jwongyt999
1
Performance Summary and Shading (Offset Version)Modified "Recession and Crisis Shading" Indicator by @haribotagada (Original Link: ) The updated indicator accepts a days offset (positive or negative) to calculate performance between the offset date and the input date. Potential uses include identifying performance one week after company earnings or an FOMC meeting. This feature simplifies input by enabling standardized offset dates, while still allowing flexibility to adjust ranges by overriding inputs as needed. Summary of added features and indicator notes: Inputs both positive and negative offset. By default, the script calculates performance from the close of the input date to the close of the date at (input date + offset) for positive offsets, and from the close of (input date - offset) to the close of the input date for negative offsets. For example, with an input date of November 1, 2024, an offset of 7 calculates performance from the close on November 1 to the close on November 8, while an offset of -7 calculates from the close on October 25 to the close on November 1. Allows user to perform the calculation using the open price on the input date instead of close price The input format has been modified to allow overrides for the default duration, while retaining the original capabilities of the indicator. The calculation shows both the average change and the average annualized change. For bar-wise calculations, annualization assumes 252 trading days per year. For date-wise calculations, it assumes 365 days for annualization. Carries over all previous inputs to retain functionality of the previous script. Changes a few small settings: Calculates start to end date performance by default instead of peak to trough performance. Updates visuals of label text to make it easier to read and less transparent. Changed stat box color scheme to make the text easier to read Updated default input data to new format of input with offsets Changed default duration statistic to number of days instead of number of bars with an option to select number of bars. Potential Features to Add: Import dataset from CSV files or by plugging into TradingView calendar Example Input Datasets: Recessions: 2020-02-01,COVID-19,59 2007-12-01,Subprime mortgages,547 2001-03-01,Dot-com,243 1990-07-01,Oil shock,243 1981-07-01,US unemployment,788 1980-01-01,Volker,182 1973-11-01,OPEC,485 Japan Revolving Door Elections 2006-09-26, Shinzo Abe 2007-09-26, Yasuo Fukuda 2008-09-24, Taro Aso 2009-09-16, Yukio Hatoyama 2010-07-08, Naoto Kan 2011-09-02, Yoshihiko Noda Hope you find the modified indicator useful and let me know if you would like any features to be added!
Penunjuk Pine Script®
oleh mintdotfinance
Dema Percentile Standard DeviationDema Percentile Standard Deviation The Dema Percentile Standard Deviation indicator is a robust tool designed to identify and follow trends in financial markets. How it works? This code is straightforward and simple: The price is smoothed using a DEMA (Double Exponential Moving Average). Percentiles are then calculated on that DEMA. When the closing price is below the lower percentile, it signals a potential short. When the closing price is above the upper percentile and the Standard Deviation of the lower percentile, it signals a potential long. Settings Dema/Percentile/SD/EMA Length's: Defines the period over which calculations are made. Dema Source: The source of the price data used in calculations. Percentiles: Selects the type of percentile used in calculations (options include 60/40, 60/45, 55/40, 55/45). In these settings, 60 and 55 determine percentile for long signals, while 45 and 40 determine percentile for short signals. Features Fully Customizable Fully Customizable: Customize colors to display for long/short signals. Display Options: Choose to show long/short signals as a background color, as a line on price action, or as trend momentum in a separate window. EMA for Confluence: An EMA can be used for early entries/exits for added signal confirmation, but it may introduce noise—use with caution! Built-in Alerts. Indicator on Diffrent Assets INDEX:BTCUSD 1D Chart (6 high 56 27 60/45 14) CRYPTO:SOLUSD 1D Chart (24 open 31 20 60/40 14) CRYPTO:RUNEUSD 1D Chart (10 close 56 14 60/40 14) Remember no indicator would on all assets with default setting so FAFO with setting to get your desired signal.
Penunjuk Pine Script®
oleh Patito_1
5
CMF and Scaled EFI OverlayCMF and Scaled EFI Overlay Indicator Overview The CMF and Scaled EFI Overlay indicator combines the Chaikin Money Flow (CMF) and a scaled version of the Elder Force Index (EFI) into a single chart. This allows traders to analyze both indicators simultaneously, facilitating better insights into market momentum and volume dynamics , specifically focusing on buying/selling pressure and momentum , without compromising the integrity of either indicator. Purpose Chaikin Money Flow (CMF): Measures buying and selling pressure by evaluating price and volume over a specified period. It indicates accumulation (buying pressure) when values are positive and distribution (selling pressure) when values are negative. Elder Force Index (EFI): Combines price changes and volume to assess the momentum behind market moves. Positive values indicate upward momentum (prices rising with strong volume), while negative values indicate downward momentum (prices falling with strong volume). By scaling the EFI to match the amplitude of the CMF, this indicator enables a direct comparison between pressure and momentum , preserving their shapes and zero crossings. Traders can observe the relationship between price movements, volume, and momentum more effectively, aiding in decision-making. Understanding Pressure vs. Momentum Chaikin Money Flow (CMF): - Indicates the level of demand (buying pressure) or supply (selling pressure) in the market based on volume and price movements. - Accumulation: When institutional or large investors are buying significant amounts of an asset, leading to an increase in buying pressure. - Distribution: When these investors are selling off their holdings, increasing selling pressure. Elder Force Index (EFI): - Measures the strength and speed of price movements, indicating how forceful the current trend is. - Positive Momentum: Prices are rising quickly, indicating a strong uptrend. - Negative Momentum: Prices are falling rapidly, indicating a strong downtrend. Understanding the difference between pressure and momentum is crucial. For example, a market may exhibit strong buying pressure (positive CMF) but weak momentum (low EFI), suggesting accumulation without significant price movement yet. Features Overlay of CMF and Scaled EFI: Both indicators are plotted on the same chart for easy comparison of pressure and momentum dynamics. Customizable Parameters: Adjust lengths for CMF and EFI calculations and fine-tune the scaling factor for optimal alignment. Preserved Indicator Integrity: The scaling method preserves the shape and zero crossings of the EFI, ensuring accurate analysis. How It Works CMF Calculation: - Calculates the Money Flow Multiplier (MFM) and Money Flow Volume (MFV) to assess buying and selling pressure. - CMF is computed by summing the MFV over the specified length and dividing by the sum of volume over the same period: CMF = (Sum of MFV over n periods) / (Sum of Volume over n periods) EFI Calculation: - Calculates the EFI using the Exponential Moving Average (EMA) of the price change multiplied by volume: EFI = EMA(n, Change in Close * Volume) Scaling the EFI: - The EFI is scaled by multiplying it with a user-defined scaling factor to match the CMF's amplitude. Plotting: - Both the CMF and the scaled EFI are plotted on the same chart. - A zero line is included for reference, aiding in identifying crossovers and divergences. Indicator Settings Inputs CMF Length (`cmf_length`): - Default: 20 - Description: The number of periods over which the CMF is calculated. A higher value smooths the indicator but may delay signals. EFI Length (`efi_length`): - Default: 13 - Description: The EMA length for the EFI calculation. Adjusting this value affects the sensitivity of the EFI to price changes. EFI Scaling Factor (`efi_scaling_factor`): - Default: 0.000001 - Description: A constant used to scale the EFI to match the CMF's amplitude. Fine-tuning this value ensures the indicators align visually. How to Adjust the EFI Scaling Factor Start with the Default Value: - Begin with the default scaling factor of `0.000001`. Visual Inspection: - Observe the plotted indicators. If the EFI appears too large or small compared to the CMF, proceed to adjust the scaling factor. Fine-Tune the Scaling Factor: - Increase or decrease the scaling factor incrementally (e.g., `0.000005`, `0.00001`, `0.00005`) until the amplitudes of the CMF and EFI visually align. - The optimal scaling factor may vary depending on the asset and timeframe. Verify Alignment: - Ensure that the scaled EFI preserves the shape and zero crossings of the original EFI. - Overlay the original EFI (if desired) to confirm alignment. How to Use the Indicator Analyze Buying/Selling Pressure and Momentum: - Positive CMF (>0): Indicates accumulation (buying pressure). - Negative CMF (<0): Indicates distribution (selling pressure). - Positive EFI: Indicates positive momentum (prices rising with strong volume). - Negative EFI: Indicates negative momentum (prices falling with strong volume). Look for Indicator Alignment: - Both CMF and EFI Positive: - Suggests strong bullish conditions with both buying pressure and upward momentum. - Both CMF and EFI Negative: - Indicates strong bearish conditions with selling pressure and downward momentum. Identify Divergences: - CMF Positive, EFI Negative: - Buying pressure exists, but momentum is negative; potential for a bullish reversal if momentum shifts. - CMF Negative, EFI Positive: - Selling pressure exists despite rising prices; caution advised as it may indicate a potential bearish reversal. Confirm Signals with Other Analysis: - Use this indicator in conjunction with other technical analysis tools (e.g., trend lines, support/resistance levels) to confirm trading decisions. Example Usage Scenario 1: Bullish Alignment - CMF Positive: Indicates accumulation (buying pressure). - EFI Positive and Increasing: Shows strengthening upward momentum. - Interpretation: - Strong bullish signal suggesting that buyers are active, and the price is likely to continue rising. - Action: - Consider entering a long position or adding to existing ones. Scenario 2: Bearish Divergence - CMF Negative: Indicates distribution (selling pressure). - EFI Positive but Decreasing: Momentum is positive but weakening. - Interpretation: - Potential bearish reversal; price may be rising but underlying selling pressure suggests caution. - Action: - Be cautious with long positions; consider tightening stop-losses or preparing for a possible trend reversal. Tips Adjust for Different Assets: - The optimal scaling factor may differ across assets due to varying price and volume characteristics. - Always adjust the scaling factor when analyzing a new asset. Monitor Indicator Crossovers: - Crossings above or below the zero line can signal potential trend changes. Watch for Divergences: - Divergences between the CMF and EFI can provide early warning signs of trend reversals. Combine with Other Indicators: - Enhance your analysis by combining this overlay with other indicators like moving averages, RSI, or Ichimoku Cloud. Limitations Scaling Factor Sensitivity: - An incorrect scaling factor may misalign the indicators, leading to inaccurate interpretations. - Regular adjustments may be necessary when switching between different assets or timeframes. Not a Standalone Indicator: - Should be used as part of a comprehensive trading strategy. - Always consider other market factors and indicators before making trading decisions. Disclaimer No Guarantee of Performance: - Past performance is not indicative of future results. - Trading involves risk, and losses can exceed deposits. Use at Your Own Risk: - This indicator is provided for educational purposes. - The author is not responsible for any financial losses incurred while using this indicator. Code Summary //@version=5 indicator(title="CMF and Scaled EFI Overlay", shorttitle="CMF & Scaled EFI", overlay=false) cmf_length = input.int(20, minval=1, title="CMF Length") efi_length = input.int(13, minval=1, title="EFI Length") efi_scaling_factor = input.float(0.000001, title="EFI Scaling Factor", minval=0.0, step=0.000001) // --- CMF Calculation --- ad = high != low ? ((2 * close - low - high) / (high - low)) * volume : 0 mf = math.sum(ad, cmf_length) / math.sum(volume, cmf_length) // --- EFI Calculation --- efi_raw = ta.ema(ta.change(close) * volume, efi_length) // --- Scale EFI --- efi_scaled = efi_raw * efi_scaling_factor // --- Plotting --- plot(mf, color=color.green, title="CMF", linewidth=2) plot(efi_scaled, color=color.red, title="EFI (Scaled)", linewidth=2) hline(0, color=color.gray, title="Zero Line", linestyle=hline.style_dashed) - Lines 4-6: Define input parameters for CMF length, EFI length, and EFI scaling factor. - Lines 9-11: Calculate the CMF. - Lines 14-16: Calculate the EFI. - Line 19: Scale the EFI by the scaling factor. - Lines 22-24: Plot the CMF, scaled EFI, and zero line. Feedback and Support Suggestions: If you have ideas for improvements or additional features, please share your feedback. Support: For assistance or questions regarding this indicator, feel free to contact the author through TradingView. --- By combining the CMF and scaled EFI into a single overlay, this indicator provides a powerful tool for traders to analyze market dynamics more comprehensively. Adjust the parameters to suit your trading style, and always practice sound risk management.
Penunjuk Pine Script®
oleh Rashino
Divergence for Many Indicators v4 Screener▋ INTRODUCTION: The “Divergence for Many Indicators v4 Screener” is developed to provide an advanced monitoring solution for up to 24 symbols simultaneously. It efficiently collects signals from multiple symbols based on the “ Divergence for Many Indicators v4 ” and presents the output in an organized table. The table includes essential details starting with the symbol name, signal price, corresponding divergence indicator, and signal time. _______________________ ▋ CREDIT: The divergence formula adapted from the “ Divergence for Many Indicators v4 ” script, originally created by @LonesomeTheBlue . Full credit to his work. _______________________ ▋ OVERVIEW: The chart image can be considered an example of a recorded divergence signal that occurred in $BTCUSDT. _______________________ ▋ APPEARANCE: The table can be displayed in three formats: 1. Full indicator name. 2. First letter of the indicator name. 3. Total number of divergences. _______________________ ▋ SIGNAL CONFIRMATION: The table distinguishes signal confirmation by using three different colors: 1. Not-Confirmed (Orange): The signal is not confirmed yet, as the bar is still open. 2. Freshly Confirmed (Green): The signal was confirmed 1 or 2 bars ago. 3. Confirmed (Gray): The signal was confirmed 3 or more bars ago. _______________________ ▋ INDICATOR SETTINGS: Section(1): Table Settings (1) Table location on the chart. (2) Table’s cells size. (3) Chart’s timezone. (4) Sorting table.            - Signal: Sorts the table by the latest signals.            - None: Sorts the table based on the input order. (5) Table’s colors. (6) Signal Confirmation type color. Explained above in the SIGNAL CONFIRMATION section Section(2): Divergence for Many Indicators v4 Settings As seen on the Divergence for Many Indicators v4 * Explained above in the APPEARANCE section Section(3): Symbols (1) Enable/disable symbol in the screener. (2) Entering a symbol. _______________________ ▋ FINAL COMMENTS: For best performance, add the Screener indicator to an active symbol chart, such as QQQ, SPY, AAPL, BTCUSDT, ES, EURUSD, etc., and avoid mixing symbols from different market allocations. The Divergence for Many Indicators v4 Screener indicator is not a primary tool for making trading decisions.
Penunjuk Pine Script®
oleh MUQWISHI
15
Adaptive MA Scalping StrategyAdaptive MA Scalping Strategy The Adaptive MA Scalping Strategy is an innovative trading approach that merges the strengths of the Kaufman's Adaptive Moving Average (KAMA) with the Moving Average Convergence Divergence (MACD) histogram. This combination results in a momentum-adaptive moving average that dynamically adjusts to market conditions, providing traders with timely and reliable signals. How It Works Kaufman's Adaptive Moving Average (KAMA): Unlike traditional moving averages, KAMA adjusts its sensitivity based on market volatility. It becomes more responsive during trending markets and less sensitive during periods of consolidation, effectively filtering out market noise. MACD Histogram Integration: The strategy incorporates the MACD histogram, a momentum indicator that measures the difference between a fast and a slow exponential moving average (EMA). By adding the MACD histogram values to the KAMA, the strategy creates a new line—the momentum-adaptive moving average (MOMA)—which captures both trend direction and momentum. Signal Generation: Long Entry: The strategy enters a long position when the closing price crosses above the MOMA. This indicates a potential upward momentum shift. Exit Position: The position is closed when the closing price crosses below the MOMA, signaling a potential decline in momentum. Cloud Calculation Detail The MOMA is calculated by adding the MACD histogram value to the KAMA of the price. This addition effectively adjusts the KAMA based on the momentum indicated by the MACD histogram. When momentum is strong, the MACD histogram will have higher values, causing the MOMA to adjust accordingly and provide earlier entry or exit signals. Performance on Stocks This strategy has demonstrated excellent performance on stocks when applied to the 1-hour timeframe. Its adaptive nature allows it to respond swiftly to market changes, capturing profitable trends while minimizing the impact of false signals caused by market noise. The combination of KAMA's adaptability and MACD's momentum detection makes it particularly effective in volatile market conditions commonly seen in stock trading. Key Parameters KAMA Length (malen): Determines the sensitivity of the KAMA. A length of 100 is used to balance responsiveness with noise reduction. MACD Fast Length (fast): Sets the period for the fast EMA in the MACD calculation. A value of 24 helps in capturing short-term momentum changes. MACD Slow Length (slow): Sets the period for the slow EMA in the MACD calculation. A value of 52 smooths out longer-term trends. MACD Signal Length (signal): Determines the period for the signal line in the MACD calculation. An 18-period signal line is used for timely crossovers. Advantages of the Strategy Adaptive to Market Conditions: By adjusting to both volatility and momentum, the strategy remains effective across different market phases. Enhanced Signal Accuracy: The fusion of KAMA and MACD reduces false signals, improving the accuracy of trade entries and exits. Simplicity in Execution: With straightforward entry and exit rules based on price crossovers, the strategy is user-friendly for traders at all experience levels
Strategi Pine Script®
oleh UnknownUnicorn13336802
Commitment of Trader %R StrategyThis Pine Script strategy utilizes the Commitment of Traders (COT) data to inform trading decisions based on the Williams %R indicator. The script operates in TradingView and includes various functionalities that allow users to customize their trading parameters. Here’s a breakdown of its key components: COT Data Import: The script imports the COT library from TradingView to access historical COT data related to different trader groups (commercial hedgers, large traders, and small traders). User Inputs: COT data selection mode (e.g., Auto, Root, Base currency). Whether to include futures, options, or both. The trader group to analyze. The lookback period for calculating the Williams %R. Upper and lower thresholds for triggering trades. An option to enable or disable a Simple Moving Average (SMA) filter. Williams %R Calculation: The script calculates the Williams %R value, which is a momentum indicator that measures overbought or oversold levels based on the highest and lowest prices over a specified period. SMA Filter: An optional SMA filter allows users to limit trades to conditions where the price is above or below the SMA, depending on the configuration. Trade Logic: The strategy enters long positions when the Williams %R value exceeds the upper threshold and exits when the value falls below it. Conversely, it enters short positions when the Williams %R value is below the lower threshold and exits when the value rises above it. Visual Elements: The script visually indicates the Williams %R values and thresholds on the chart, with the option to plot the SMA if enabled. Commitment of Traders (COT) Data The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides a breakdown of open interest positions held by different types of traders in the U.S. futures markets. It is widely used by traders and analysts to gauge market sentiment and potential price movements. Data Collection: The COT data is collected from futures commission merchants and is published every Friday, reflecting positions as of the previous Tuesday. The report categorizes traders into three main groups: Commercial Traders: These are typically hedgers (like producers and processors) who use futures to mitigate risk. Non-Commercial Traders: Often referred to as speculators, these traders do not have a commercial interest in the underlying commodity but seek to profit from price changes. Non-reportable Positions: Small traders who do not meet the reporting threshold set by the CFTC. Interpretation: Market Sentiment: By analyzing the positions of different trader groups, market participants can gauge sentiment. For instance, if commercial traders are heavily short, it may suggest they expect prices to decline. Extreme Positions: Some traders look for extreme positions among non-commercial traders as potential reversal signals. For example, if speculators are overwhelmingly long, it might indicate an overbought condition. Statistical Insights: COT data is often used in conjunction with technical analysis to inform trading decisions. Studies have shown that analyzing COT data can provide valuable insights into future price movements (Lund, 2018; Hurst et al., 2017). Scientific References Lund, J. (2018). Understanding the COT Report: An Analysis of Speculative Trading Strategies. Journal of Derivatives and Hedge Funds, 24(1), 41-52. DOI:10.1057/s41260-018-00107-3 Hurst, B., O'Neill, R., & Roulston, M. (2017). The Impact of COT Reports on Futures Market Prices: An Empirical Analysis. Journal of Futures Markets, 37(8), 763-785. DOI:10.1002/fut.21849 Commodity Futures Trading Commission (CFTC). (2024). Commitment of Traders. Retrieved from CFTC Official Website.
Strategi Pine Script®
oleh EdgeTools
Pivot Points LIVE [CHE]Title: Pivot Points LIVE Indicator Subtitle: Advanced Pivot Point Analysis for Real-Time Trading Presented by: Chervolino Date: September 24, 2024 Introduction What are Pivot Points? Definition: Pivot Points are technical analysis indicators used to determine potential support and resistance levels in financial markets. Purpose: They help traders identify possible price reversal points and make informed trading decisions. Overview of Pivot Points LIVE : A comprehensive indicator designed for real-time pivot point analysis. Offers advanced features for enhanced trading strategies. Key Features Pivot Points LIVE Includes: Dynamic Pivot Highs and Lows: Automatically detects and plots pivot high (HH, LH) and pivot low (HL, LL) points. Customizable Visualization: Multiple options to display markers, price labels, and support/resistance levels. Fractal Breakouts: Identifies and marks breakout and breakdown events with symbols. Line Connection Modes: Choose between "All Separate" or "Sequential" modes for connecting pivot points. Pivot Extension Lines: Extends lines from the latest pivot point to the current bar for trend analysis. Alerts: Configurable alerts for breakout and breakdown events. Inputs and Configuration Grouping Inputs for Easy Customization: Source / Length Left / Length Right: Pivot High Source: High price by default. Pivot Low Source: Low price by default. Left and Right Lengths: Define the number of bars to the left and right for pivot detection. Colors: Customizable colors for pivot high and low markers. Options: Display Settings: Show HH, LL, LH, HL markers and price labels. Display support/resistance level extensions. Option to show levels as a fractal chaos channel. Enable fractal breakout/down symbols. Line Connection Mode: Choose between "All Separate" or "Sequential" for connecting lines. Line Management: Set maximum number of lines to display. Customize line colors, widths, and styles. Pivot Extension Line: Visibility: Toggle the display of the last pivot extension line. Customization: Colors, styles, and width for extension lines. How It Works - Calculating Pivot Points Pivot High and Pivot Low Detection: Pivot High (PH): Identified when a high price is higher than a specified number of bars to its left and right. Pivot Low (PL): Identified when a low price is lower than a specified number of bars to its left and right. Higher Highs, Lower Highs, Higher Lows, Lower Lows: Higher High (HH): Current PH is higher than the previous PH. Lower High (LH): Current PH is lower than the previous PH. Higher Low (HL): Current PL is higher than the previous PL. Lower Low (LL): Current PL is lower than the previous PL. Visual Elements Markers and Labels: Shapes: HH and LH: Downward triangles above the bar. HL and LL: Upward triangles below the bar. Labels: Optionally display the price levels of HH, LH, HL, and LL on the chart. Support and Resistance Levels: Extensions: Lines extending from pivot points to indicate potential support and resistance zones. Chaos Channels: Display levels as a fractal chaos channel for enhanced trend analysis. Fractal Breakout Symbols: Buy Signals: Upward triangles below the bar. Sell Signals: Downward triangles above the bar. Slide 7: Line Connection Modes All Separate Mode: Description: Connects pivot highs with pivot highs and pivot lows with pivot lows separately. Use Case: Ideal for traders who want to analyze highs and lows independently. Sequential Mode: Description: Connects all pivot points in the order they occur, regardless of being high or low. Use Case: Suitable for identifying overall trend direction and momentum. Pivot Extension Lines Purpose: Trend Continuation: Visualize the continuation of the latest pivot point's price level. Customization: Colors: Differentiate between bullish and bearish extensions. Styles: Solid, dashed, or dotted lines based on user preference. Width: Adjustable line thickness for better visibility. Dynamic Updates: The extension line updates in real-time as new bars form, providing ongoing trend insights. Alerts and Notifications Configurable Alerts: Fractal Break Arrow: Triggered when a breakout or breakdown occurs. Long and Short Signals: Specific alerts for bullish breakouts (Long) and bearish breakdowns (Short). Benefits: Timely Notifications: Stay informed of critical market movements without constant monitoring. Automated Trading Strategies: Integrate with trading bots or automated systems for executing trades based on alerts. Customization and Optimization User-Friendly Inputs: Adjustable Parameters: Tailor pivot detection sensitivity with left and right lengths. Color and Style Settings: Match the indicator aesthetics to personal or platform preferences. Line Management: Maximum Lines Displayed: Prevent chart clutter by limiting the number of lines. Dynamic Line Handling: Automatically manage and delete old lines to maintain chart clarity. Flexibility: Adapt to Different Markets: Suitable for various financial instruments including stocks, forex, and cryptocurrencies. Scalability: Efficiently handles up to 500 labels and 100 lines for comprehensive analysis. Practical Use Cases Identifying Key Support and Resistance: Entry and Exit Points: Use pivot levels to determine optimal trade entry and exit points. Trend Confirmation: Validate market trends through the connection of pivot points. Breakout and Breakdown Strategies: Trading Breakouts: Enter long positions when price breaks above pivot highs. Trading Breakdowns: Enter short positions when price breaks below pivot lows. Risk Management: Setting Stop-Loss and Take-Profit Levels: Utilize pivot levels to place strategic stop-loss and take-profit orders. Slide 12: Benefits for Traders Real-Time Analysis: Provides up-to-date pivot points for timely decision-making. Enhanced Visualization: Clear markers and lines improve chart readability and analysis efficiency. Customizable and Flexible: Adapt the indicator to fit various trading styles and strategies. Automated Alerts: Stay ahead with instant notifications on key market events. Comprehensive Toolset: Combines pivot points with fractal analysis for deeper market insights. Conclusion Pivot Points LIVE is a robust and versatile indicator designed to enhance your trading strategy through real-time pivot point analysis. With its advanced features, customizable settings, and automated alerts, it equips traders with the tools needed to identify key market levels, execute timely trades, and manage risks effectively. Ready to Elevate Your Trading? Explore Pivot Points LIVE and integrate it into your trading toolkit today! Q&A Questions? Feel free to ask any questions or request further demonstrations of the Pivot Points LIVE indicator.
Penunjuk Pine Script®
oleh chervolino
3
Nifty Dashboard//@version=5 //Author @GODvMarkets indicator("GOD NSE Nifty Dashboard", "Nifty Dashboard") i_timeframe = input.timeframe("D", "Timeframe") // if not timeframe.isdaily // runtime.error("Please switch timeframe to Daily") i_text_size = input.string(size.auto, "Text Size", ) //-----------------------Functions----------------------------------------------------- f_oi_buildup(price_chg_, oi_chg_) => switch price_chg_ > 0 and oi_chg_ > 0 => price_chg_ > 0 and oi_chg_ < 0 => price_chg_ < 0 and oi_chg_ > 0 => price_chg_ < 0 and oi_chg_ < 0 => => f_color(val_) => val_ > 0 ? color.green : val_ < 0 ? color.red : color.gray f_bg_color(val_) => val_ > 0 ? color.new(color.green,80) : val_ < 0 ? color.new(color.red,80) : color.new(color.black,80) f_bg_color_price(val_) => fg_color_ = f_color(val_) abs_val_ = math.abs(val_) transp_ = switch abs_val_ > .03 => 40 abs_val_ > .02 => 50 abs_val_ > .01 => 60 => 80 color.new(fg_color_, transp_) f_bg_color_oi(val_) => fg_color_ = f_color(val_) abs_val_ = math.abs(val_) transp_ = switch abs_val_ > .10 => 40 abs_val_ > .05 => 50 abs_val_ > .025 => 60 => 80 color.new(fg_color_, transp_) f_day_of_week(time_=time) => switch dayofweek(time_) 1 => "Sun" 2 => "Mon" 3 => "Tue" 4 => "Wed" 5 => "Thu" 6 => "Fri" 7 => "Sat" //------------------------------------------------------------------------------------- var table table_ = table.new(position.middle_center, 22, 20, border_width = 1) var cols_ = 0 var text_color_ = color.white var bg_color_ = color.rgb(1, 5, 19) f_symbol(idx_, symbol_) => symbol_nse_ = "NSE" + ":" + symbol_ fut_cur_ = "NSE" + ":" + symbol_ + "1!" fut_next_ = "NSE" + ":" + symbol_ + "2!" = request.security(symbol_nse_, i_timeframe, [close, close-close , close/close -1, volume], ignore_invalid_symbol = true, lookahead = barmerge.lookahead_on) = request.security(fut_cur_, i_timeframe, , ignore_invalid_symbol = true, lookahead = barmerge.lookahead_on) = request.security(fut_next_, i_timeframe, , ignore_invalid_symbol = true, lookahead = barmerge.lookahead_on) = request.security(fut_cur_ + "_OI", i_timeframe, [close, close-close ], ignore_invalid_symbol = true, lookahead = barmerge.lookahead_on) = request.security(fut_next_ + "_OI", i_timeframe, [close, close-close ], ignore_invalid_symbol = true, lookahead = barmerge.lookahead_on) stk_vol_ = stk_vol_nse_ fut_vol_ = fut_cur_vol_ + fut_next_vol_ fut_oi_ = fut_cur_oi_ + fut_next_oi_ fut_oi_chg_ = fut_cur_oi_chg_ + fut_next_oi_chg_ fut_oi_chg_pct_ = fut_oi_chg_ / fut_oi_ fut_stk_vol_x_ = fut_vol_ / stk_vol_ fut_vol_oi_action_ = fut_vol_ / math.abs(fut_oi_chg_) = f_oi_buildup(chg_pct_, fut_oi_chg_pct_) close_color_ = fut_cur_close_ > fut_vwap_ ? color.green : fut_cur_close_ < fut_vwap_ ? color.red : text_color_ if barstate.isfirst row_ = 0, col_ = 0 table.cell(table_, col_, row_, "Symbol", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "Close", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "VWAP", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "Pts", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "Stk Vol", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "Fut Vol", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "Fut/Stk Vol", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "OI Cur", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "OI Next", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "OI Cur Chg", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "OI Next Chg", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "COI ", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "COI Chg", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "Vol/OI Chg", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "COI Chg%", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "Pr.Chg%", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 table.cell(table_, col_, row_, "OI Buildup", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size), col_ += 1 cell_color_ = color.white cell_bg_color_ = color.rgb(1, 7, 24) if barstate.islast row_ = idx_, col_ = 0 table.cell(table_, col_, row_, str.format("{0}", symbol_), text_color = f_color(chg_pct_), bgcolor = f_bg_color_price(chg_pct_), text_size = i_text_size, text_halign = text.align_left), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#.00}", fut_cur_close_), text_color = close_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#.00}", fut_vwap_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,0.00}", chg_pts_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#,###}", stk_vol_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#,###}", fut_vol_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,0.00}", fut_stk_vol_x_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#,###}", fut_cur_oi_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#,###}", fut_next_oi_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#,###}", fut_cur_oi_chg_), text_color = f_color(fut_cur_oi_chg_), bgcolor = f_bg_color(fut_cur_oi_chg_), text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#,###}", fut_next_oi_chg_), text_color = f_color(fut_next_oi_chg_), bgcolor = f_bg_color(fut_next_oi_chg_), text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#,###}", fut_oi_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,#,###}", fut_oi_chg_), text_color = f_color(fut_oi_chg_), bgcolor = f_bg_color(fut_oi_chg_), text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,0.00}", fut_vol_oi_action_), text_color = cell_color_, bgcolor = cell_bg_color_, text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,0.00%}", fut_oi_chg_pct_), text_color = f_color(fut_oi_chg_pct_), bgcolor = f_bg_color_oi(fut_oi_chg_pct_), text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0,number,0.00%}", chg_pct_), text_color = f_color(chg_pct_), bgcolor = f_bg_color_price(chg_pct_), text_size = i_text_size, text_halign = text.align_right), col_ += 1 table.cell(table_, col_, row_, str.format("{0}", oi_buildup_), text_color = oi_buildup_color_, bgcolor = color.new(oi_buildup_color_,80), text_size = i_text_size, text_halign = text.align_left), col_ += 1 idx_ = 1 f_symbol(idx_, "BANKNIFTY"), idx_ += 1 f_symbol(idx_, "NIFTY"), idx_ += 1 f_symbol(idx_, "CNXFINANCE"), idx_ += 1 f_symbol(idx_, "RELIANCE"), idx_ += 1 f_symbol(idx_, "HDFC"), idx_ += 1 f_symbol(idx_, "ITC"), idx_ += 1 f_symbol(idx_, "HINDUNILVR"), idx_ += 1 f_symbol(idx_, "INFY"), idx_ += 1
Penunjuk Pine Script®
oleh RAJAGOPAL1979
1
Volume Analysis - Heatmap and Volume ProfileHello All! I have a new toy for you! Volume Analysis - Heatmap and Volume Profile . Honestly I started to work to develop Volume Heatmap then I decided to improve it and add more features such Volume profile, volume, difference in Buy/Sell volumes etc. I tried to put my abilities into this script and tried to use some new Pine Language™ features ( method, force_overlay, enum etc features ). I hope the usage of these new features would be an example for Pine Programmers. Lets talk about how it works: - It gets number of Rows/Columns from the user for each candle to create heatmap - It calculates the number of the candles to analyze. Number of the candles may change by number of Rows/columns or if any volume / difference in volumes / volume profile is enabled - It gets Closing/Opening price, Volume and Time info from lower time frame for each candle ( it can be up to 100K for each candle ) - After getting the data it calculates lower time frame to analyze - Then it calculates how closing price moves, how much volume on each move and create boxes by the volume/move in each box - The colors for each box calculated by volume info and closing price movements in the lower time frame - It shows the boxes on Absolute places or Zero Line optionally - it shows Volume, Cumulative volume, Difference between Buy/Sell volume for each column - it changes empty box color by Chart background color, also you can change transparency - At this time it creates Volume Profile with up to 25 rows - As a new Pine Language™ feature, it can show Volume Profile in the indicator window or in Main chart, shows Value Area, Value Area High (VAH), Value Area Low (VAL), and draw it and POC (Point Of Control) in the indicator window and/or in the main chart - Honestly the feature I like is that: For the markets that are not open 24/7, it combines the data from the lower time period without any gaps. For example, if you work for a market that is closed on Saturdays and Sundays, it ensures data integrity by omitting weekends and holidays. so for example if the data is like "ABC---DEF-X---YL-Z" then it makes this data like "ABCDEFXYLZ". In this way, there will be no data breaks in the displayed boxes, there will be no empty colons, and it will appear as if data is coming in at any time. - Finally it shows Info Panel to give info, its background color automatically changes by the Chart background color - Important! You should set your "Plan" accordingly, your plan is "Premium or Higher" or "Lower tier". so the script can understand the minimum time frame it can get data!! I tried to share many screenshots below to explain it much better How it looks? it shows Highest Buy/Sell volumes brighter, move volume -> brighter Volume Profile ( up to 25 row s) ( number of contained candles should be more than 1 ) Volume Profile can be shown in the main chart optionally How the main chart looks: Closing price shown and you can enable it, change colors & line width Can include many candles according to Row&Column number you set Optionally it can show cumulative volume for each candle Closing prices from lower time frame Shows Candle Body by changing background colors It can shows all included candles on Zero line You can change the colors of many things You can set Empty box and border transparency Table, Empty box Colors adjustment done automatically by chart background color Sometimes we can not get data from some historical candles if time frame is high such 2days, 1 week etc, and it looks like: It also checks if Chart time frame and Chart type is suitable Enjoy!
Penunjuk Pine Script®
oleh LonesomeTheBlue
42