Cryptocurrrency — אינדיקטורים ואסטרטגיות

Lakshmi - Low Volatility Range Breakout (LVRB)⚡️ Overview The Low Volatility Range Breakout (LVRB) indicator is designed to identify consolidation phases characterized by suppressed volatility and generate actionable signals when price breaks out of these ranges. The underlying premise is rooted in the market principle that periods of low volatility often precede significant directional moves—volatility contraction leads to expansion. Important Note on Optimization: The default parameter settings of this indicator have been specifically optimized for BTCUSDT on the 2-hour (2H) timeframe. While the indicator can be applied to other instruments and timeframes, users are encouraged to adjust the parameters accordingly to suit different trading conditions and asset characteristics. This indicator automates the detection of "quiet" accumulation/distribution zones and provides clear visual cues and alerts when a breakout occurs. ⚡️ How to Use 1. Add the indicator to your chart. Default settings are optimized for BTCUSDT 2H. 2. Wait for a gray box to appear—this indicates a qualified low-volatility range is forming. 3. Monitor for breakout signals: • LONG (green triangle below bar): Price broke above the range. Consider entering a long position. • SHORT (red triangle above bar): Price broke below the range. Consider entering a short position. 4. Set alerts using "LVRB LONG" or "LVRB SHORT" to receive notifications on confirmed breakouts. 5. Adjust parameters as needed for different instruments or timeframes. Tip: Combine with volume analysis or trend filters for higher-probability setups. ⚡️ How It Works 1. Low Volatility Bar Detection A bar is classified as "low volatility" when it meets the following criteria: • True Range (TR) is at or below the average TR (Simple Moving Average) multiplied by a user-defined threshold. • (Optional) Candle Body is at or below the average body size multiplied by a separate threshold. This dual-filter approach helps isolate bars that exhibit genuine compression in both range and directional commitment. 2. Range Box Formation When consecutive low-volatility bars are detected, the indicator begins constructing a consolidation box: • The box expands to encompass the high and low of qualifying bars. • A minimum number of bars and a minimum fraction of low-volatility bars are required for the box to become "qualified" (active). • A configurable tolerance allows for a limited number of consecutive non-low-vol bars within the sequence, accommodating minor noise without invalidating the range. • If the box height exceeds a maximum threshold (defined as a multiple of the base ATR at sequence start), the range is invalidated. 3. Breakout Detection Once a qualified range is established, the indicator monitors for breakouts: • Wick Mode: Requires both a wick pierce beyond the range boundary AND a close outside the range. • Close Mode: Requires only a close beyond the range boundary. • (Optional) Breakout Body Filter: The breakout candle's body must exceed a multiple of the average body size at range formation. • (Optional) Candle Direction Filter: Bullish breakouts require a green candle; bearish breakouts require a red candle. Signals are displayed in real-time and confirmed upon bar close. ⚡️ Inputs & Parameters • Volatility Window: Lookback period for calculating average TR and average body size. • TR Multiplier: A bar's TR must be ≤ avgTR × this value to qualify as low-vol. • Body Multiplier: A bar's body must be ≤ avgBody × this value (if body filter is enabled). • Use Body Filter: Toggle the body size filter on/off. • Min Bars in Box: Minimum number of bars required for a range to become qualified. • Min Low-Vol Fraction: Minimum proportion of bars in the sequence that must be low-vol. • Allowed Consecutive Non-Low-Vol Bars: Tolerance for consecutive bars that do not meet low-vol criteria. • Max Box Height: Maximum allowed range height as a multiple of the base ATR. • Breakout Mode: Choose between "Wick" (pierce + close) or "Close" (close only). • Breakout Body Multiplier: Require breakout candle body ≥ avgBody × this value (1.0 = OFF). • Require Candle Direction: Enforce green candle for LONG, red candle for SHORT. ⚡️ Visual Features • Consolidation Boxes: Displayed in neutral (gray) color during formation. Upon a confirmed breakout, the box is colored green for bullish breakouts or red for bearish breakouts. • Breakout Signals: • LONG: Green upward triangle displayed below the price bar with "LONG" label. • SHORT: Red downward triangle displayed above the price bar with "SHORT" label. • Range Levels: Optional horizontal plots for the active range's high and low. • Invalidated Boxes: Optionally retained in neutral (gray) color or deleted from the chart. • Full Customization: Colors, transparency, and border width are all adjustable. ⚡️ Alerts Two alert conditions are available: • LVRB LONG: Triggered on a confirmed bullish breakout (bar close). • LVRB SHORT: Triggered on a confirmed bearish breakout (bar close). ⚡️ Use Cases • Breakout Trading: Enter positions when price escapes a well-defined low-volatility range. • Volatility Expansion Plays: Anticipate increased volatility following periods of compression. • Filtering Choppy Markets: Avoid trading during extended consolidation; wait for confirmed breakouts. • Multi-Timeframe Analysis: Use on higher timeframes to identify major consolidation zones. ⚡️ Notes • Best used in conjunction with volume analysis, trend context, or support/resistance levels for confirmation. • Performance varies across instruments and timeframes; backtesting and parameter optimization are recommended. ⚡️ Credits Developed by Lakshmi. Inspired by volatility contraction principles and range breakout methodologies. ⚡️ Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profits. Trading financial instruments involves substantial risk, and you may lose more than your initial investment. Past performance, whether indicated by backtesting or historical analysis, does not guarantee future results. The use of this indicator does not ensure or promise any profits or protection against losses. Users are solely responsible for their own trading decisions and should conduct their own research and/or consult with a qualified financial advisor before making any investment decisions. By using this indicator, you acknowledge and accept that you bear full responsibility for any trading outcomes.

ADX Forecast Colorful [DiFlip]ADX Forecast Colorful Introducing one of the most advanced ADX indicators available — a fully customizable analytical tool that integrates forward-looking forecasting capabilities. ADX Forecast Colorful is a scientific evolution of the classic ADX, designed to anticipate future trend strength using linear regression. Instead of merely reacting to historical data, this indicator projects the future behavior of the ADX, giving traders a strategic edge in trend analysis. ⯁ Real-Time ADX Forecasting For the first time, a public ADX indicator incorporates linear regression (least squares method) to forecast the future behavior of ADX. This breakthrough approach enables traders to anticipate trend strength changes based on historical momentum. By applying linear regression to the ADX, the indicator plots a projected trendline n periods ahead — helping users make more accurate and timely trading decisions. ⯁ Highly Customizable The indicator adapts seamlessly to any trading style. It offers a total of 26 long entry conditions and 26 short entry conditions, making it one of the most configurable ADX tools on TradingView. Each condition is fully adjustable, enabling the creation of statistical, quantitative, and automated strategies. You maintain full control over the signals to align perfectly with your system. ⯁ Innovative and Science-Based This is the first public ADX indicator to apply least-squares predictive modeling to ADX dynamics. Technically, it embeds machine learning logic into a traditional trend-strength indicator. Using linear regression as a predictive engine adds powerful statistical rigor to the ADX, turning it into an intelligent, forward-looking signal generator. ⯁ Scientific Foundation: Linear Regression Linear regression is a fundamental method in statistics and machine learning used to model the relationship between a dependent variable y and one or more independent variables x. The basic formula for simple linear regression is: y = β₀ + β₁x + ε Where: y = predicted value (e.g., future ADX) x = explanatory variable (e.g., bar index or time) β₀ = intercept β₁ = slope (rate of change) ε = random error term The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the ADX projection based on recent trends. ⯁ Least Squares Estimation To minimize the error, the regression coefficients are calculated as: β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²) β₀ = ȳ - β₁x̄ Where: Σ = summation x̄ and ȳ = means of x and y i ranges from 1 to n (number of data points) These formulas provide the best linear unbiased estimator under Gauss-Markov conditions — assuming constant variance and linearity. ⯁ Linear Regression in Machine Learning Linear regression is a foundational algorithm in supervised learning. Its power in producing quantitative predictions makes it essential in AI systems, predictive analytics, time-series forecasting, and automated trading. Applying it to the ADX essentially places an intelligent forecasting engine inside a classic trend tool. ⯁ Visual Interpretation Imagine an ADX time series like this: Time → ADX → The regression line smooths these values and projects them n periods forward, creating a predictive trajectory. This forecasted ADX line can intersect with the actual ADX, offering smarter buy and sell signals. ⯁ Summary of Scientific Concepts Linear Regression: Models variable relationships with a straight line. Least Squares: Minimizes prediction errors for best fit. Time-Series Forecasting: Predicts future values using historical data. Supervised Learning: Trains models to predict outcomes from inputs. Statistical Smoothing: Reduces noise and highlights underlying trends. ⯁ Why This Indicator Is Revolutionary Scientifically grounded: Based on rigorous statistical theory. Unprecedented: First public ADX using least-squares forecast modeling. Smart: Uses machine learning logic. Forward-Looking: Generates predictive, not just reactive, signals. Customizable: Flexible for any strategy or timeframe. ⯁ Conclusion By merging ADX and linear regression, this indicator enables traders to predict market momentum rather than merely follow it. ADX Forecast Colorful is not just another indicator — it’s a scientific leap forward in technical analysis. With 26 fully configurable entry conditions and smart forecasting, this open-source tool is built for creating cutting-edge quantitative strategies. ⯁ Example of simple linear regression with one independent variable This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables. ⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x) This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component. ⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models. ⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model. ⯁ Result of fitting a set of data points with a quadratic function This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line. ⯁ What is the ADX? The Average Directional Index (ADX) is a technical analysis indicator developed by J. Welles Wilder. It measures the strength of a trend in a market, regardless of whether the trend is up or down. The ADX is an integral part of the Directional Movement System, which also includes the Plus Directional Indicator (+DI) and the Minus Directional Indicator (-DI). By combining these components, the ADX provides a comprehensive view of market trend strength. ⯁ How to use the ADX? The ADX is calculated based on the moving average of the price range expansion over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and has three main zones: Strong Trend: When the ADX is above 25, indicating a strong trend. Weak Trend: When the ADX is below 20, indicating a weak or non-existent trend. Neutral Zone: Between 20 and 25, where the trend strength is unclear. ⯁ Entry Conditions Each condition below is fully configurable and can be combined to build precise trading logic. 📈 BUY 🅰️ Signal Validity: The signal will remain valid for X bars . 🅰️ Signal Sequence: Configurable as AND or OR . 🅰️ +DI > -DI 🅰️ +DI < -DI 🅰️ +DI > ADX 🅰️ +DI < ADX 🅰️ -DI > ADX 🅰️ -DI < ADX 🅰️ ADX > Threshold 🅰️ ADX < Threshold 🅰️ +DI > Threshold 🅰️ +DI < Threshold 🅰️ -DI > Threshold 🅰️ -DI < Threshold 🅰️ +DI (Crossover) -DI 🅰️ +DI (Crossunder) -DI 🅰️ +DI (Crossover) ADX 🅰️ +DI (Crossunder) ADX 🅰️ +DI (Crossover) Threshold 🅰️ +DI (Crossunder) Threshold 🅰️ -DI (Crossover) ADX 🅰️ -DI (Crossunder) ADX 🅰️ -DI (Crossover) Threshold 🅰️ -DI (Crossunder) Threshold 🔮 +DI (Crossover) -DI Forecast 🔮 +DI (Crossunder) -DI Forecast 🔮 ADX (Crossover) +DI Forecast 🔮 ADX (Crossunder) +DI Forecast 📉 SELL 🅰️ Signal Validity: The signal will remain valid for X bars . 🅰️ Signal Sequence: Configurable as AND or OR . 🅰️ +DI > -DI 🅰️ +DI < -DI 🅰️ +DI > ADX 🅰️ +DI < ADX 🅰️ -DI > ADX 🅰️ -DI < ADX 🅰️ ADX > Threshold 🅰️ ADX < Threshold 🅰️ +DI > Threshold 🅰️ +DI < Threshold 🅰️ -DI > Threshold 🅰️ -DI < Threshold 🅰️ +DI (Crossover) -DI 🅰️ +DI (Crossunder) -DI 🅰️ +DI (Crossover) ADX 🅰️ +DI (Crossunder) ADX 🅰️ +DI (Crossover) Threshold 🅰️ +DI (Crossunder) Threshold 🅰️ -DI (Crossover) ADX 🅰️ -DI (Crossunder) ADX 🅰️ -DI (Crossover) Threshold 🅰️ -DI (Crossunder) Threshold 🔮 +DI (Crossover) -DI Forecast 🔮 +DI (Crossunder) -DI Forecast 🔮 ADX (Crossover) +DI Forecast 🔮 ADX (Crossunder) +DI Forecast 🤖 Automation All BUY and SELL conditions are compatible with TradingView alerts, making them ideal for fully or semi-automated systems. ⯁ Unique Features Linear Regression: (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Condition Table: BUY/SELL Condition Labels: BUY/SELL Plot Labels in the Graph Above: BUY/SELL Automate and Monitor Signals/Alerts: BUY/SELL Background Colors: "bgcolor" Background Colors: "fill" Linear Regression (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Table of Conditions: BUY/SELL Conditions Label: BUY/SELL Plot Labels in the graph above: BUY/SELL Automate & Monitor Signals/Alerts: BUY/SELL Background Colors: "bgcolor" Background Colors: "fill"

Crowding model ║ BullVision 🔬 Overview The Crypto Crowding Model Pro is a sophisticated analytical tool designed to visualize and quantify market conditions across multiple cryptocurrencies. By leveraging Relative Strength Index (RSI) and Z-score calculations, this indicator provides traders with an intuitive and detailed snapshot of current crypto market dynamics, highlighting areas of extreme momentum, crowded trades, and potential reversal points. ⚙️ Key Concepts 📊 RSI and Z-Score Analysis RSI (Relative Strength Index) evaluates the momentum and strength of each cryptocurrency, identifying overbought or oversold conditions. Z-Score Normalization measures each asset's current price deviation relative to its historical average, identifying statistically significant extremes. 🎯 Crowding Analytics An integrated analytics panel provides real-time crowding metrics, quantifying market sentiment into four distinct categories: 🔥 FOMO (Fear of Missing Out): High momentum, potential exhaustion. ❄️ Fear: Low momentum, potential reversal or consolidation. 📈 Recovery: Moderate upward momentum after a downward trend. 💪 Strength: Stable bullish conditions with sustained momentum. 🖥️ Visual Scatter Plot Assets are plotted on a dynamic scatter plot, positioning each cryptocurrency according to its RSI and Z-score. Color coding, symbol shapes, and sizes help quickly identify main market segments (BTC, ETH, TOTAL, OTHERS) and individual asset conditions. 🧩 Quadrant Classification Assets are categorized into four quadrants based on their momentum and deviation: Overbought Extended: High RSI and positive Z-score. Recovery Phase: Low RSI but positive Z-score. Oversold Compressed: Low RSI and negative Z-score. Strong Consolidation: High RSI but negative Z-score. 🔧 User Customization 🎨 Visual Settings Bar Scale: Adjust the scatter plot visual scale. Asset Visibility: Optionally display key market benchmarks (TOTAL, BTC, ETH, OTHERS). Gradient Background: Enhances visual interpretation of asset clusters. Crowding Analytics Panel: Toggle the analytics panel on/off. 📊 Indicator Parameters RSI Length: Defines the calculation period for RSI. Z-score Lookback: Historical lookback period for normalization. Crowding Alert Threshold: Sets alert sensitivity for crowded market conditions. 🎯 Zone Settings Quadrant Labels: Displays descriptive labels for each quadrant. Danger Zones: Highlights extreme RSI levels indicative of heightened market risk. 📈 Visual Output Dynamic Scatter Plot: Visualizes asset positioning clearly and intuitively. Gradient and Grid: Professional gridlines and subtle gradient backgrounds assist visual assessment. Danger Zone Highlights: Visually indicates RSI extremes to warn of potential market turning points. Crowding Analytics Panel: Real-time summary of market sentiment and asset distribution. 🔍 Use Cases This indicator is particularly beneficial for traders and analysts looking to: Identify crowded trades and potential reversal points. Quickly assess overall market sentiment and individual asset strength. Integrate a robust momentum analysis into broader technical or fundamental strategies. Enhance market timing and improve risk management decisions. ⚠️ Important Notes This indicator does not provide explicit buy or sell signals. It is intended solely for informational, analytical, and educational purposes. Past performance and signals are not indicative of future market results. Always combine with additional tools and analysis as part of comprehensive decision-making.