ka66: Candle Range MarkThis is a simple trailing stop loss tool using bar ranges, to be used with some discretion and understanding of basic price action.
Given a configurable percentage value, e.g. 25%:
A bullish bar (close > open) will be marked at the lower 25%
A bearish bar (close < open) will be marked at the upper 25%
The idea is to move your stop loss after each completed bar in the direction of the trade, at the configured percentage value.
If you have an inside bar, or something very close to it, or a doji-type bar, don't trail that, because there is no clarity of what the bar means, we can only wait.
The chart shows an example use, with trailing at 10% of the bar, from the initial stop loss after entry, trailing till we get stopped out. Some things to note:
Because this example focuses on a short trade, we ignore the bullish candles, and keep our trailing stop at the last bearish candle.
We ignore doji-esque candles and inside bars, where the body is in the range of the prior candle. Some definitions of inside bars include the wicks as well. I don't have a strong opinion, and this example is just for illustration. Furthermore, the inside bar will likely be the opposite of the swing bars (e.g. bullish bar in a range of bearish bars), so our stop remains unchanged.
One could use this semi-systematic approach in scalping on any timeframe, for example to maximise gains, adjusting the bar percentage as needed.
Zmienność
Algorithmic Signal AnalyzerMeet Algorithmic Signal Analyzer (ASA) v1: A revolutionary tool that ushers in a new era of clarity and precision for both short-term and long-term market analysis, elevating your strategies to the next level.
ASA is an advanced TradingView indicator designed to filter out noise and enhance signal detection using mathematical models. By processing price movements within defined standard deviation ranges, ASA produces a smoothed analysis based on a Weighted Moving Average (WMA). The Volatility Filter ensures that only relevant price data is retained, removing outliers and improving analytical accuracy.
While ASA provides significant analytical advantages, it’s essential to understand its capabilities in both short-term and long-term use cases. For short-term trading, ASA excels at capturing swift opportunities by highlighting immediate trend changes. Conversely, in long-term trading, it reveals the overall direction of market trends, enabling traders to align their strategies with prevailing conditions.
Despite these benefits, traders must remember that ASA is not designed for precise trade execution systems where accuracy in timing and price levels is critical. Its focus is on analysis rather than order management. The distinction is crucial: ASA helps interpret price action effectively but may not account for real-time market factors such as slippage or execution delays.
Features and Functionality
ASA integrates multiple tools to enhance its analytical capabilities:
Customizable Moving Averages: SMA, EMA, and WMA options allow users to tailor the indicator to their trading style.
Signal Detection: Identifies bullish and bearish trends using the Relative Exponential Moving Average (REMA) and marks potential buy/sell opportunities.
Visual Aids: Color-coded trend lines (green for upward, red for downward) simplify interpretation.
Alert System: Notifications for trend swings and reversals enable timely decision-making.
Notes on Usage
ASA’s effectiveness depends on the context in which it is applied. Traders should carefully consider the trade-offs between analysis and execution.
Results may vary depending on market conditions and chart types. Backtesting with ASA on standard charts provides more reliable insights compared to non-standard chart types.
Short-term use focuses on rapid trend recognition, while long-term application emphasizes understanding broader market movements.
Takeaways
ASA is not a tool for precise trade execution but a powerful aid for interpreting price trends.
For short-term trading, ASA identifies quick opportunities, while for long-term strategies, it highlights trend directions.
Understanding ASA’s limitations and strengths is key to maximizing its utility.
ASA is a robust solution for traders seeking to filter noise, enhance analytical clarity, and align their strategies with market movements, whether for short bursts of activity or sustained trading goals.
[blackcat] L1 Extreme Shadows█ OVERVIEW
The Pine Script provided is an indicator designed to detect market volatility and extreme shadow conditions. It calculates various conditions based on simple moving averages (SMAs) and plots the results to help traders identify potential market extremes. The primary function of the script is to provide visual cues for extreme market conditions without generating explicit trading signals.
█ LOGICAL FRAMEWORK
Structure:
1 — Input Parameters:
• No user-defined input parameters are present in this script.
2 — Calculations:
• Calculate Extreme Shadow: Checks if the differences between certain SMAs and prices exceed predefined thresholds.
• Calculate Buy Extreme Shadow: Extends the logic by incorporating additional SMAs to identify stronger buy signals.
• Calculate Massive Bullish Sell: Detects massive bullish sell conditions using longer-term SMAs.
3 — Plotting:
• The script plots the calculated conditions using distinct colors to differentiate between various types of extreme shadows.
Data Flow:
• The close price is passed through each custom function.
• Each function computes its respective conditions based on specified SMAs and thresholds.
• The computed values are then summed and returned.
• Finally, the aggregated values are plotted on the chart using the plot function.
█ CUSTOM FUNCTIONS
1 — calculate_extreme_shadow(close)
• Purpose: Identify extreme shadow conditions based on 8-period and 14-period SMAs.
• Functionality: Computes the difference between the 8-period SMA and the close price, and the difference between the 14-period SMA and the 4-period SMA, relative to the 6-period SMA. Returns 2 if both conditions exceed 0.04; otherwise, returns 0.
• Parameters: close (price series)
• Return Value: Integer (0 or 2)
2 — calculate_buy_extreme_shadow(close)
• Purpose: Identify more robust buy signals by evaluating multiple SMAs.
• Functionality: Considers the 8-period SMA along with additional SMAs (21, 42, 63, 84, 105) and combines multiple conditions to provide a comprehensive buy signal.
• Parameters: close (price series)
• Return Value: Integer (sum of conditions, ranging from 0 to 14)
3 — calculate_massive_bullish_sell(close)
• Purpose: Detect massive bullish sell conditions using longer-term SMAs.
• Functionality: Evaluates conditions based on the 8-period SMA and longer-term SMAs (88, 44, 22, 11, 5), returning a sum of conditions meeting specified thresholds.
• Parameters: close (price series)
• Return Value: Integer (sum of conditions, ranging from 0 to 10)
█ KEY POINTS AND TECHNIQUES
• Advanced Pine Script Features:
• Multiple Nested Conditions: Uses nested conditions to assess complex market scenarios.
• Combination of Conditions: Combines multiple conditions to provide a more reliable signal.
• Optimization Techniques:
• Thresholds: Employs specific thresholds (0.04 and 0.03) to filter out noise and highlight significant market movements.
• SMA Comparisons: Compares multiple SMAs to identify trends and extreme conditions.
• Unique Approaches:
• Combining Multiple Time Frames: Incorporates multiple time frames to offer a holistic view of the market.
• Visual Distinction: Utilizes different colors and line widths to clearly differentiate between various extreme shadow conditions.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Potential Modifications:
• User-Defined Thresholds: Allow users to customize thresholds to align with personal trading strategies.
• Additional Indicators: Integrate other technical indicators like RSI or MACD to improve the detection of extreme market conditions.
• Entry and Exit Signals: Enhance the script to generate clear buy and sell signals based on identified extreme shadow conditions.
• Application Scenarios:
• Volatility Analysis: Analyze market volatility and pinpoint times of extreme price action.
• Trend Following: Pair with trend-following strategies to capitalize on significant market moves.
• Risk Management: Adjust position sizes or stop-loss levels based on detected extreme conditions.
• Related Pine Script Concepts:
• Custom Functions: Demonstrates how to create reusable functions for simplified and organized code.
• Plotting Techniques: Shows effective ways to visualize data using color and styling options.
• Multiple Time Frame Analysis: Highlights the benefits of analyzing multiple time frames for a broader market understanding.
Prediction Based on Linreg & Atr
We created this algorithm with the goal of predicting future prices 📊, specifically where the value of any asset will go in the next 20 periods ⏳. It uses linear regression based on past prices, calculating a slope and an intercept to forecast future behavior 🔮. This prediction is then adjusted according to market volatility, measured by the ATR 📉, and the direction of trend signals, which are based on the MACD and moving averages 📈.
How Does the Linreg & ATR Prediction Work?
1. Trend Calculation and Signals:
o Technical Indicators: We use short- and long-term exponential moving averages (EMA), RSI, MACD, and Bollinger Bands 📊 to assess market direction and sentiment (not visually presented in the script).
o Calculation Functions: These include functions to calculate slope, average, intercept, standard deviation, and Pearson's R, which are crucial for regression analysis 📉.
2. Predicting Future Prices:
o Linear Regression: The algorithm calculates the slope, average, and intercept of past prices to create a regression channel 📈, helping to predict the range of future prices 🔮.
o Standard Deviation and Pearson's R: These metrics determine the strength of the regression 🔍.
3. Adjusting the Prediction:
o The predicted value is adjusted by considering market volatility (ATR 📉) and the direction of trend signals 🔮, ensuring that the prediction is aligned with the current market environment 🌍.
4. Visualization:
o Prediction Lines and Bands: The algorithm plots lines that display the predicted future price along with a prediction range (upper and lower bounds) 📉📈.
5. EMA Cross Signals:
o EMA Conditions and Total Score: A bullish crossover signal is generated when the total score is positive and the short EMA crosses above the long EMA 📈. A bearish crossover signal is generated when the total score is negative and the short EMA crosses below the long EMA 📉.
6. Additional Considerations:
o Multi-Timeframe Regression Channel: The script calculates regression channels for different timeframes (5m, 15m, 30m, 4h) ⏳, helping determine the overall market direction 📊 (not visually presented).
Confidence Interpretation:
• High Confidence (close to 100%): Indicates strong alignment between timeframes with a clear trend (bullish or bearish) 🔥.
• Low Confidence (close to 0%): Shows disagreement or weak signals between timeframes ⚠️.
Confidence complements the interpretation of the prediction range and expected direction 🔮, aiding in decision-making for market entry or exit 🚀.
Español
Creamos este algoritmo con el objetivo de predecir los precios futuros 📊, específicamente hacia dónde irá el valor de cualquier activo en los próximos 20 períodos ⏳. Utiliza regresión lineal basada en los precios pasados, calculando una pendiente y una intersección para prever el comportamiento futuro 🔮. Esta predicción se ajusta según la volatilidad del mercado, medida por el ATR 📉, y la dirección de las señales de tendencia, que se basan en el MACD y las medias móviles 📈.
¿Cómo Funciona la Predicción con Linreg & ATR?
Cálculo de Tendencias y Señales:
Indicadores Técnicos: Usamos medias móviles exponenciales (EMA) a corto y largo plazo, RSI, MACD y Bandas de Bollinger 📊 para evaluar la dirección y el sentimiento del mercado (no presentados visualmente en el script).
Funciones de Cálculo: Incluye funciones para calcular pendiente, media, intersección, desviación estándar y el coeficiente de correlación de Pearson, esenciales para el análisis de regresión 📉.
Predicción de Precios Futuros:
Regresión Lineal: El algoritmo calcula la pendiente, la media y la intersección de los precios pasados para crear un canal de regresión 📈, ayudando a predecir el rango de precios futuros 🔮.
Desviación Estándar y Pearson's R: Estas métricas determinan la fuerza de la regresión 🔍.
Ajuste de la Predicción:
El valor predicho se ajusta considerando la volatilidad del mercado (ATR 📉) y la dirección de las señales de tendencia 🔮, asegurando que la predicción esté alineada con el entorno actual del mercado 🌍.
Visualización:
Líneas y Bandas de Predicción: El algoritmo traza líneas que muestran el precio futuro predicho, junto con un rango de predicción (límites superior e inferior) 📉📈.
Señales de Cruce de EMAs:
Condiciones de EMAs y Puntaje Total: Se genera una señal de cruce alcista cuando el puntaje total es positivo y la EMA corta cruza por encima de la EMA larga 📈. Se genera una señal de cruce bajista cuando el puntaje total es negativo y la EMA corta cruza por debajo de la EMA larga 📉.
Consideraciones Adicionales:
Canal de Regresión Multi-Timeframe: El script calcula canales de regresión para diferentes marcos de tiempo (5m, 15m, 30m, 4h) ⏳, ayudando a determinar la dirección general del mercado 📊 (no presentado visualmente).
Interpretación de la Confianza:
Alta Confianza (cerca del 100%): Indica una fuerte alineación entre los marcos temporales con una tendencia clara (alcista o bajista) 🔥.
Baja Confianza (cerca del 0%): Muestra desacuerdo o señales débiles entre los marcos temporales ⚠️.
La confianza complementa la interpretación del rango de predicción y la dirección esperada 🔮, ayudando en las decisiones de entrada o salida en el mercado 🚀.
The Dragons Maw [inspired by Kioseff Trading]The Dragon's Maw is a playful visualization tool that uses Monte Carlo simulation to create a dragon-like pattern on your chart. Although primarily intended for entertainment, it is also suitable for testing or falsifying the utility of this method's predictions.
What It Does:
- Generates multiple price path simulations that form the shape of a "fire-breathing" effect
- Shows upper and lower boundaries of all simulations as the dragon's "maw"
- Displays the dragon's "eye" and "ear" as a visual indicator of the historical data used
How It Works:
1. The indicator calculates returns from historical price data
2. Using Monte Carlo simulation with either normal distribution or bootstrap sampling, it generates multiple potential price paths
3. These paths are rendered with high transparency to create a fire/smoke effect showing the higher probability regions as denser color
4. It can be observed that the direction of the "fire" is influenced by recent price movement especially when set in relation to the "eye" position which indicates the limit of historical data used for the simulation
Educational Value:
Use the 'Move to the Left' parameter to position the dragon's head at different points in historical data. This feature serves as an excellent demonstration of the limitations of statistical price projections – you'll quickly see how the simulated paths diverge from what actually happened, highlighting why such projections should not be relied upon for trading decisions.
You might find, that it's not at all capable of 'predicting' sudden price movements but rather 'predicts' a continuation of the recent trend.
Features:
- Adjustable number of simulations (affects detail of the "fire" effect)
- Moveable dragon head (can be positioned at different points in price history)
- Customizable colors for the maw boundaries and fire effect
- Optional scale display for price levels
Note: This indicator is inspired by KioseffTrading's original work, with added features for visualization and positioning. While it uses statistical methods, it should be viewed as an artistic interpretation of price movement rather than a predictive tool.
Settings Guide:
- Upper/Lower Limit: Colors for the dragon's maw boundaries
- Fire Color: Color and transparency of the simulation paths
- Look Back: How far back to calculate the dragon's eye position
- Much Fire: Controls the density of simulation paths
- Length: Determines how far forward the simulation extends
The chart shows a clean view of the indicator's output, with the dragon's eye (o), ear, maw boundaries, and fire effect clearly visible on the right side of the chart by default.
VWAP Trend with Standard Deviation & MidlinesThis indicator is a sophisticated VWAP (Volume Weighted Average Price) tool with multiple features:
Core Functionality:
1. Calculates a primary VWAP line that changes color based on trend direction (green when rising, red when falling)
2. Creates multiple standard deviation bands around the VWAP at customizable distances
3. Resets calculations at either:
- New York session start time (configurable, default 9:30 AM)
- Daily start time
- Can be hidden on daily/weekly/monthly timeframes if desired
Band Structure:
- Band 1 (innermost): ±1 standard deviation
- Band 2 (middle): ±2 standard deviations
- Band 3 (outermost): ±3 standard deviations
- Midlines at 0.5σ intervals between bands
- All bands can be individually enabled/disabled
Customization Options:
1. Band calculation modes:
- Standard Deviation based
- Percentage based
2. Visual settings:
- Customizable colors for all elements
- Adjustable line widths
- Optional labels with configurable size
- Optional extension lines
- Label position adjustment
3. Source data selection (default: HLC3 - High, Low, Close average)
Common Uses:
- Identifying potential support/resistance levels
- Measuring price volatility
- Spotting mean reversion opportunities
- Trading range analysis
- Trend direction confirmation
The indicator essentially creates a dynamic support/resistance structure that adapts to market volatility and volume, making it useful for both intraday and swing trading strategies.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Implied Leverage Ratio Between Current Symbol and BTCThis script calculates and visualizes the implied leverage ratio between the current symbol and Bitcoin (BTC). The implied leverage ratio is computed by comparing the cumulative price changes of the two symbols over a defined number of candles. The results provide insights into how the current symbol performs relative to BTC in terms of bullish (upward) and bearish (downward) movements.
Features
Cumulative Up and Down Ratios:
The script calculates the cumulative price increase (up) and decrease (down) ratios for both the current symbol and BTC. These ratios are based on the percentage changes relative to each candle's opening price.
Implied Leverage Ratio:
For bullish movements, the cumulative up ratio of the current symbol is divided by BTC's cumulative up ratio.
For bearish movements, the cumulative down ratio of the current symbol is divided by BTC's cumulative down ratio.
These values reflect the implied leverage of the current symbol relative to BTC in both directions.
Customizable Comparison Symbol:
By default, the script compares the current symbol to BINANCE:BTCUSDT. However, you can specify any other symbol to tailor the analysis.
Interactive Visualization:
Green Line: Represents the ratio of cumulative up movements (current symbol vs. BTC).
Red Line: Represents the ratio of cumulative down movements (current symbol vs. BTC).
A horizontal zero line is included for reference, ensuring the chart always starts from zero.
How to Use
Add this script to your chart from the Pine Editor or the public library.
Customize the number of candles (t) to define the period over which cumulative changes are calculated.
If desired, replace the comparison symbol with another asset in the input settings.
Analyze the green and red lines to identify relative strength and implied leverage trends.
Who Can Benefit
Traders and Analysts: Gain insights into the relative performance of altcoins, stocks, or other instruments against BTC.
Leverage Seekers: Identify assets with higher or lower implied leverage compared to Bitcoin.
Market Comparisons: Understand how various assets react to market movements relative to BTC.
This tool is particularly useful for identifying potential outperformers or underperformers relative to Bitcoin and can guide strategic decisions in trading pairs or market analysis.
[blackcat] L1 Banker Move█ OVERVIEW
The Pine Script is an indicator designed to analyze market signals for institutional and short-term investors. It calculates and plots three main signals: Institutional Signal, Institutional Build, and Short-Term Investor Signal. The script uses a combination of price, volume, and moving average data to generate these signals, which can help traders identify potential buying or selling opportunities.
█ LOGICAL FRAMEWORK
The script is structured into several main sections:
1 — Input Parameters
The script does not explicitly define any input parameters, relying on default values for calculations.
2 — Custom Functions
• reference_value(values, length) : Retrieves the first non-NA value from a specified number of past values.
• calculate_institutional_and_short_term_signals(low, close, open, volume) : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
3 — Calculations
• Price and Volume Metrics: The script calculates various smoothed price changes, lowest and highest values over different periods, and volume-weighted prices.
• Moving Averages: It computes simple moving averages (SMA) and exponential moving averages (EMA) for different periods.
• RSI Calculation: The script calculates a custom RSI for different periods.
• Signal Generation: It generates the institutional and short-term investor signals based on the calculated metrics.
4 — Plotting
The script plots the three main signals on the chart using the plot function.
The flow of data and logic is as follows:
• The reference_value function is used to find reference values for calculations.
• The calculate_institutional_and_short_term_signals function performs the core calculations and returns the institutional and short-term investor signals.
• The main script calls this function and plots the results.
█ CUSTOM FUNCTIONS
1 — reference_value(values, length)
• Purpose : Retrieves the first non-NA value from a specified number of past values.
• Parameters :
• values: An array of values.
• length: The number of past values to consider.
• Return Value : The first non-NA value found or na if no valid value is found.
• Functionality : Iterates through the specified number of past values and returns the first non-NA value.
2 — calculate_institutional_and_short_term_signals(low, close, open, volume)
• Purpose : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
• Parameters :
• low: Low price series.
• close: Close price series.
• open: Open price series.
• volume: Volume series.
• Return Values :
• institutional_signal: The institutional signal.
• institutional_build: The institutional build signal.
• short_term_investor_signal: The short-term investor signal.
• Functionality :
• Computes various price and volume metrics.
• Calculates moving averages and volume-weighted prices.
• Generates the institutional and short-term investor signals based on these metrics.
█ KEY POINTS AND TECHNIQUES
1 — Advanced Pine Script Features
• Custom Functions: The script defines and uses custom functions to encapsulate complex logic.
• Conditional Statements: Extensive use of iff and if statements to control the flow of calculations.
• Looping Constructs: The for loop in reference_value function to iterate through past values.
• Exponential Moving Averages (EMA): Used to smooth out price and signal changes.
• Volume-Weighted Price (VWP): Calculated to factor in volume in price analysis.
• Custom RSI Calculation: A custom RSI formula is used, which differs from the standard RSI calculation.
2 — Optimization Techniques
• Efficient Data Handling: The reference_value function efficiently finds the first non-NA value without unnecessary computations.
• Smoothed Signals: Using EMAs to smooth out noisy signals for better trend identification.
3 — Unique Approaches
• Combination of Metrics: The script combines multiple metrics (price, volume, moving averages, and custom RSI) to generate comprehensive signals.
• Institutional Build Signal: A unique approach to detect institutional activity by comparing current price levels with historical lows and smoothed price changes.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
1 — Potential Modifications
• Input Parameters: Add input parameters to allow users to customize the lengths and thresholds used in the calculations.
• Strategy Version: Convert the indicator into a strategy by adding buy/sell signals based on the generated signals.
• Additional Indicators: Integrate other technical indicators (e.g., MACD, Bollinger Bands) to enhance the signal generation process.
2 — Similar Trading Scenarios
• Institutional Activity Analysis: Use similar techniques to analyze institutional activity in other markets or assets.
• Volume Analysis: Apply the volume-weighted price and volume analysis to identify significant price movements.
• Multi-Timeframe Analysis: Extend the script to analyze signals across multiple timeframes for a more robust trading strategy.
3 — Related Pine Script Concepts
• Pine Script Functions: Understanding how to define and use custom functions effectively.
• Conditional Logic: Mastering the use of iff and if statements for complex logic.
• Looping Constructs: Familiarity with for loops for iterating through data.
• Moving Averages: Knowledge of different types of moving averages and their applications.
• Volume Analysis: Techniques for incorporating volume data into price analysis.
Shannon Entropy Volatility AnalyzerThis algorithm aims to measure market uncertainty or volatility using a Shannon entropy-based approach. 🔄📊
Entropy is a measure of disorder or unpredictability, and here we use it to evaluate the structure of price returns within a defined range of periods (window length). 🧩⏳ Thus, the goal is to detect changes to identify conditions of high or low volatility. 🔍⚡
What we seek with Shannon's formula in this algorithm is to measure market uncertainty or volatility through dynamic entropy. This measure helps us understand how unpredictable price behavior is over a given period, which is key to making informed decisions. 📈🧠
Through this formula, we calculate the level of disorder or dispersion in price returns based on their probability of occurrence, enabling us to identify moments of high or low volatility. 💡💥
Shannon Entropy Calculation 📏
• Uses probabilities to measure uncertainty in returns. 🎲
• Entropy is normalized on a scale of 0 to 100, where:
o High Entropy: Unpredictable movements (high uncertainty). ⚠️💥
•
o Low Entropy: Structured movements (low uncertainty). 📉🔒
•
• With probabilities, we measure the level of dispersion or unpredictability of returns using Shannon's entropy formula. 📊🔍
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Indicator Usefulness 🛠️
• Identify High Volatility: When the market is unpredictable, the indicator signals "High Uncertainty." ⚡🔮
• Detect Market Stability: When the market is more predictable and structured, the indicator highlights "Low Uncertainty." 🔒🧘♂️
• Neutral Zones: Helps monitor markets without extreme conditions, enabling safer entry or exit opportunities. ⚖️🚶♂️
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Uncertainty Zones 🌀
1. High Uncertainty: When entropy exceeds the upper threshold. 🚨🔺
2. Low Uncertainty: When entropy is below the lower threshold. 🔻💡
3. Neutral: When entropy lies between both thresholds. ⚖️🔄
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What We Aim to Achieve with the Formula in Practice 🎯
1. Detection of Volatile Moments: Shannon’s formula helps us identify when the market is unpredictable. This is a good moment to take additional precautions, such as reducing position size or avoiding trading during high volatility phases. ⚠️📉
2. Trading Opportunities in Stable Markets: With low entropy, we can identify when the market is more predictable, favoring trend or momentum strategies with a higher chance of success. 🚀📈
3. Optimization of Risk Management: By measuring market volatility in real-time, we can adjust entry and exit strategies, tailoring risk based on the level of uncertainty detected. 🔄⚖️
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We hope this makes it easy to interpret and use. If you have any questions or comments, please feel free to reach out to us! 📬😊
Custom EMA (v4) [MacroGlide]Custom EMA (v4) is an easy-to-use tool designed for traders who want a clear and reliable way to analyze market trends. By using multiple Exponential Moving Averages (EMAs), this indicator helps you visualize the market's direction and momentum in a straightforward way. Whether you're tracking short-term movements or looking for long-term patterns, Custom EMA makes it simple to spot trends and trading opportunities.
Key Features:
• Multi-EMA System: Plots up to four EMAs on the chart with customizable lengths and colors, providing flexibility to analyze trends over different timeframes.
• Dynamic Trend Cloud: A visually intuitive cloud is generated between the fastest and slowest EMA. The cloud changes color based on market trends:
• Green Cloud: Indicates a bullish trend when shorter EMAs are above longer EMAs.
• Red Cloud: Indicates a bearish trend when shorter EMAs are below longer EMAs.
• Highlighting Zones: Background shading helps distinguish bullish and bearish conditions, further clarifying the prevailing trend in the market.
How to Use:
• Add the Indicator: Load the indicator onto your chart and customize the EMA lengths to suit your trading style.
• Interpret the Cloud: Observe the color of the trend cloud to identify bullish (green) or bearish (red) market conditions.
• Combine with Highlighting Zones: Use the background shading in conjunction with the cloud to confirm trend strength and direction.
• Customize to Fit Your Strategy: Adjust the lengths and colors of the EMAs to align with your preferred analysis timeframe.
Methodology:
This indicator leverages a layered EMA approach, using up to four EMAs to calculate the trend cloud and define market conditions. By comparing the relative positions of the EMAs, it identifies bullish and bearish trends and visually represents them with a color-coded cloud. The inclusion of highlighting zones enhances the trader's ability to quickly grasp market sentiment.
Originality and Usefulness:
Custom EMA (v4) sets itself apart by integrating a trend cloud that adapts dynamically to EMA positions, providing traders with a clean and intuitive way to visualize market trends. The combination of multi-EMA plotting, background shading, and trend cloud offers comprehensive insight into both short-term and long-term market movements.
Charts:
The indicator plots four customizable EMAs alongside a trend cloud that visually captures market direction. Whether you're monitoring short-term price action or identifying long-term trends, the Custom EMA (v4) provides clarity and simplicity for traders at all levels.
Enjoy the game!
Standard Deviation of Returns: DivergencePurpose:
The "Standard Deviation of Returns: Divergence" indicator is designed to help traders identify potential trend reversals or continuation signals by analyzing divergences between price action and the statistical volatility of returns. Divergences can signal weakening momentum in the prevailing trend, offering insight into potential buying or selling opportunities.
Key Components
1. Returns Calculation:
* The indicator uses logarithmic returns (log(close / close )) to measure relative price changes in a normalized manner.
* Log returns are more effective than simple price differences when analyzing data across varying price levels, as they account for percentage-based changes.
2. Standard Deviation of Returns:
* The script computes the standard deviation of returns over a user-defined lookback period (ta.stdev(returns, lookback)).
* Standard deviation measures the dispersion of returns around their average, effectively quantifying market volatility.
* A higher standard deviation indicates increased volatility, while lower standard deviation reflects a calmer market.
3. Price Action:
* Detects higher highs (new peaks in price) and lower lows (new troughs in price) over the lookback period.
* Price trends are compared to the behavior of the standard deviation.
4. Divergence Detection:
A divergence occurs when price action (higher highs or lower lows) is not confirmed by a corresponding movement in standard deviation:
Bullish Divergence: Price makes a lower low, but the standard deviation does not, signaling potential upward momentum.
Bearish Divergence: Price makes a higher high, but the standard deviation does not, signaling potential downward momentum.
5. Visual Cues:
The script highlights divergence regions directly on the chart:
Green Background: Indicates a bullish divergence (potential buy signal).
Red Background: Indicates a bearish divergence (potential sell signal).
How It Works
Inputs:
* The user specifies the lookback period (lookback) for calculating the standard deviation and detecting divergences.
Calculation:
* Each bar’s returns are computed and used to calculate the standard deviation over the specified lookback period.
* The indicator evaluates price highs/lows and compares these with the highest and lowest values of the standard deviation within the same lookback period.
Highlight of Divergences:
When divergences are detected:
Bullish Divergence: The background of the chart is shaded green.
Bearish Divergence: The background of the chart is shaded red.
Trading Application
Bullish Divergence:
* Occurs when the market is oversold, or downward momentum is weakening.
* Suggests a potential reversal to an uptrend, signaling a buying opportunity.
Bearish Divergence:
* Occurs when the market is overbought, or upward momentum is weakening.
* Suggests a potential reversal to a downtrend, signaling a selling opportunity.
Contextual Use:
* Use this indicator in conjunction with other technical tools like RSI, MACD, or moving averages to confirm signals.
* Effective in volatile or ranging markets to help anticipate shifts in momentum.
Summary
The "Standard Deviation of Returns: Divergence" indicator is a robust tool for spotting divergences that can signal weakening market trends. It combines statistical volatility with price action analysis to highlight key areas of potential reversals. By integrating this tool into your trading strategy, you can gain additional confirmation for entries or exits while keeping a close watch on momentum shifts.
Disclaimer: This is not a financial advise; please consult your financial advisor for personalized advice.
Relative PerformanceSimple relative performance of a token compared to BTC, with display of normalized performance velocity line.
Rolling VWAP with Optional Kalman FilterThis script provides an advanced and customizable Rolling VWAP (Volume-Weighted Average Price) indicator, designed for traders who want to refine their trend analysis and improve decision-making. With a unique option to apply a Kalman Filter, you can smooth out VWAP values to reduce noise in volatile markets, making it easier to identify actionable trends.
Key Features:
Dynamic Rolling VWAP:
Choose the rolling window size (number of bars) to match your trading style, whether you’re an intraday scalper or a swing trader.
Kalman Filter Toggle:
Enable the Kalman filter to smooth VWAP values and eliminate market noise.
Adjustable Kalman Gain to control the level of smoothing, making it suitable for both fast and slow markets.
Price Source Flexibility:
Use the Typical Price ((H+L+C)/3) or the Close Price as the basis for VWAP calculation.
Visual Enhancements:
Background shading highlights whether the price is above (bullish) or below (bearish) the VWAP, helping traders make quick visual assessments.
A legend dynamically updates the current VWAP value.
Dual View Option:
Compare the raw Rolling VWAP and the Kalman-filtered VWAP when the filter is enabled, giving you deeper insight into market trends.
Use Cases:
Intraday Traders: Identify key price levels for re-entry or exits using a short rolling window and responsive filtering.
Swing Traders: Analyze broader trends with a longer rolling window and smoother VWAP output.
Volatile Markets: Use the Kalman filter to reduce noise and avoid false signals during high market volatility.
How to Use:
Adjust the Rolling Window to set the number of bars for VWAP calculation.
Toggle Kalman Filter on/off depending on your preference for raw or smoothed VWAP values.
Fine-tune the Kalman Gain for the desired level of smoothing.
Use the shading to quickly assess whether the price is trading above or below the VWAP for potential entry/exit signals.
ATR SL Band (No-Repaint, Multi-Timeframe) + Risk per ContractThis indicator draws a non-repainting band for ATR-based Stoploss placement.
If used on Futures, it shows the distance + risk from the previous candle close, as well as from the current price.
The risk value is automatically calculated for the following symbols:
(Micro) ES (S&P 500)
(Micro) NQ (NASDAQ 100)
(Micro) YM (Dow Jones Industrial Average / US30)
The timeframe can be set individually. It is not recommended to use a lower timeframe than the chart timeframe as values differ from the actual timeframe's ATR SL in this case.
Visual ATR StopThis indicator uses the Average True Range (ATR) to display a visual range for stop placement. Two multiplier values (example, 1 and 3) can be set to create a filled area below the price. This area represents the range between the two ATR levels, adjusted by subtracting the current price, providing a simple way to visualize stop-loss placement based on volatility.
The indicator is customizable; for example, negative values can place the area above the price for short positions. The filled color can also be removed, which allows precise levels to be marked above and below.
[blackcat] L1 Abnormal Volume Monitor█ OVERVIEW
The script is an indicator designed to monitor abnormal volume patterns in the market. It calculates and plots moving average volumes, identifies triple volume bars, and detects potential large order entries based on specific conditions.
█ FEATURES
• Input Parameters: The script defines parameters M1, M2, and lbk which control the calculation of moving averages and the lookback period for detecting abnormal volume.
• Calculations: The script calculates two moving averages of volume (MAVOL1 and MAVOL2), a smoothed price level (mm), and identifies conditions for triple volume bars and large order entries.
• Plotting: The script plots volume histograms for up and down bars, moving average volumes, and highlights triple volume bars with and without large order entries.
• Conditional Statements: The script uses conditional statements to determine when to plot certain data points and labels based on the calculated conditions.
█ LOGICAL FRAMEWORK
• xfl(cond, lbk): This function checks if a condition (cond) has been true within a specified lookback period (lbk). It returns true if the condition has been met and false otherwise.
• Parameters: cond (condition to check), lbk (lookback period).
• Return Value: outb (boolean indicating if the condition was met within the lookback period).
• abnormal_vol_monitor(close, open, high, low, volume, M1, M2, lbk): This function calculates moving average volumes, identifies triple volume bars, and detects large order entries.
• Parameters: close, open, high, low, volume (price and volume data), M1, M2 (periods for moving averages), lbk (lookback period).
• Return Value: A tuple containing MAVOL1, MAVOL2, xa (large order entry condition), and tripleVolume (triple volume condition).
█ KEY POINTS AND TECHNIQUES
• Moving Averages: The script uses simple moving averages (sma) and exponential moving averages (ema) to smooth volume data.
• Volume Analysis: The script identifies triple volume bars and large order entries based on specific conditions, such as volume doubling and price increases.
• Lookback Period: The xfl function uses a lookback period to ensure the accuracy of the detected conditions.
• Plotting Techniques: The script uses different plot styles and colors to distinguish between up bars, down bars, moving averages, and abnormal volume patterns.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: The script could be modified to include additional conditions for detecting other types of abnormal volume patterns or to adjust the sensitivity of the detection.
• Extensions: Similar techniques could be applied to other financial instruments or timeframes to identify unusual trading activity.
• Related Concepts: The script utilizes concepts such as moving averages, exponential moving averages, and conditional plotting, which are fundamental in Pine Script and technical analysis.
Average Price Range Screener [KFB Quant]Average Price Range Screener
Overview:
The Average Price Range Screener is a technical analysis tool designed to provide insights into the average price volatility across multiple symbols over user-defined time periods. The indicator compares price ranges from different assets and displays them in a visual table and chart for easy reference. This can be especially helpful for traders looking to identify symbols with high or low volatility across various time frames.
Key Features:
Multiple Symbols Supported:
The script allows for analysis of up to 10 symbols, such as major cryptocurrencies and market indices. Symbols can be selected by the user and configured for tracking price volatility.
Dynamic Range Calculation:
The script calculates the average price range of each symbol over three distinct time periods (default are 30, 60, and 90 bars). The price range for each symbol is calculated as a percentage of the bar's high-to-low difference relative to its low value.
Range Visualization:
The results are visually represented using:
- A color-coded table showing the calculated average ranges of each symbol and the current chart symbol.
- A line plot that visually tracks the volatility for each symbol on the chart, with color gradients representing the range intensity from low (red/orange) to high (blue/green).
Customizable Inputs:
- Length Inputs: Users can define the time lengths (default are 30, 60, and 90 bars) for calculating average price ranges for each symbol.
- Symbol Inputs: 10 symbols can be tracked at once, with default values set to popular crypto pairs and indices.
- Color Inputs: Users can customize the color scheme for the range values displayed in the table and chart.
Real-Time Ranking:
The indicator ranks symbols by their average price range, providing a clear view of which assets are exhibiting higher volatility at any given time.
Each symbol's range value is color-coded based on its relative volatility within the selected symbols (using a gradient from low to high range).
Data Table:
The table shows the average range values for each symbol in real-time, allowing users to compare volatility across multiple assets at a glance. The table is dynamically updated as new data comes in.
Interactive Labels:
The indicator adds labels to the chart, showing the average range for each symbol. These labels adjust in real-time as the price range values change, giving users an immediate view of volatility rankings.
How to Use:
Set Time Periods: Adjust the time periods (lengths) to match your trading strategy's timeframe and volatility preference.
Symbol Selection: Add and track the price range for your preferred symbols (cryptocurrencies, stocks, indices).
Monitor Volatility: Use the visual table and plot to identify symbols with higher or lower volatility, and adjust your trading strategy accordingly.
Interpret the Table and Chart: Ranges that are color-coded from red/orange (lower volatility) to blue/green (higher volatility) allow you to quickly gauge which symbols are most volatile.
Disclaimer: This tool is provided for informational and educational purposes only and should not be considered as financial advice. Always conduct your own research and consult with a licensed financial advisor before making any investment decisions.
Volume Spike DetectorVolume Spike Detector
This script is designed to identify significant spikes in trading volume and visually represent them on the chart. It calculates the 20-period simple moving average (SMA) of the trading volume and multiplies it by a user-defined threshold to determine the spike threshold. When the current volume exceeds this threshold, the script detects and highlights a volume spike.
Key Features:
Dynamic Spike Threshold:
The script calculates the spike threshold dynamically based on the average trading volume. Users can customize the threshold multiplier using an input setting.
Example: A threshold multiplier of 2.0 means the current volume must be twice the 20-period SMA to trigger a detection.
Visual Representation:
The current volume is plotted in blue bars.
The spike threshold is plotted as a red line, making it easy to visually identify when the volume crosses the threshold.
Alert Notification:
When a volume spike is detected, an alert is triggered to notify the user.
This feature is useful for real-time monitoring and spotting potential trading opportunities.
Use Case:
Traders can use this tool to identify sudden increases in trading activity, which may indicate a significant market move or event. It’s suitable for all markets, including cryptocurrencies, stocks, and forex.
Linear Regression Intensity [AlgoAlpha]Introducing the Linear Regression Intensity indicator by AlgoAlpha, a sophisticated tool designed to measure and visualize the strength of market trends using linear regression analysis. This indicator not only identifies bullish and bearish trends with precision but also quantifies their intensity, providing traders with deeper insights into market dynamics. Whether you’re a novice trader seeking clearer trend signals or an experienced analyst looking for nuanced trend strength indicators, Linear Regression Intensity offers the clarity and detail you need to make informed trading decisions.
Key Features:
📊 Comprehensive Trend Analysis: Utilizes linear regression over customizable periods to assess and quantify trend strength.
🎨 Customizable Appearance: Choose your preferred colors for bullish and bearish trends to align with your trading style.
🔧 Flexible Parameters: Adjust the lookback period, range tolerance, and regression length to tailor the indicator to your specific strategy.
📉 Dynamic Bar Coloring: Instantly visualize trend states with color-coded bars—green for bullish, red for bearish, and gray for neutral.
🏷️ Intensity Labels: Displays dynamic labels that represent the intensity of the current trend, helping you gauge market momentum at a glance.
🔔 Alert Conditions: Set up alerts for strong bullish or bearish trends and trend neutrality to stay ahead of market movements without constant monitoring.
Quick Guide to Using Linear Regression Intensity:
🛠 Add the Indicator: Simply add Linear Regression Intensity to your TradingView chart from your favorites. Customize the settings such as lookback period, range tolerance, and regression length to fit your trading approach.
📈 Market Analysis: Observe the color-coded bars to quickly identify the current trend state. Use the intensity labels to understand the strength behind each trend, allowing for more strategic entry and exit points.
🔔 Set Up Alerts: Enable alerts for when strong bullish or bearish trends are detected or when the trend reaches a neutral zone. This ensures you never miss critical market movements, even when you’re away from the chart.
How It Works:
The Linear Regression Intensity indicator leverages linear regression to calculate the underlying trend of a selected price source over a specified length. By analyzing the consistency of the regression values within a defined lookback period, it determines the trend’s intensity based on a percentage tolerance. The indicator aggregates pairwise comparisons of regression values to assess whether the trend is predominantly upward or downward, assigning a state of bullish, bearish, or neutral accordingly. This state is then visually represented through dynamic bar colors and intensity labels, offering a clear and immediate understanding of market conditions. Additionally, the inclusion of Average True Range (ATR) ensures that the intensity visualization accounts for market volatility, providing a more robust and reliable trend assessment. With customizable settings and alert conditions, Linear Regression Intensity empowers traders to fine-tune their strategies and respond swiftly to evolving market trends.
Elevate your trading strategy with Linear Regression Intensity and gain unparalleled insights into market trends! 🌟📊
WhalenatorThis custom TradingView indicator combines multiple analytic techniques to help identify potential market trends, areas of support and resistance, and zones of heightened trading activity. It incorporates a SuperTrend-like line based on ATR, Keltner Channels for volatility-based price envelopes, and dynamic order blocks derived from significant volume and pivot points. Additionally, it highlights “whale” activities—periods of exceptionally large volume—along with an estimated volume profile level and approximate bid/ask volume distribution. Together, these features aim to offer traders a more comprehensive view of price structure, volatility, and institutional participation.
This custom TradingView indicator integrates multiple trading concepts into a single, visually descriptive tool. Its primary goal is to help traders identify directional bias, volatility levels, significant volume events, and potential support/resistance zones on a price chart. Below are the main components and their functionalities:
SuperTrend-Like Line (Trend Bias):
At the core of the indicator is a trend-following line inspired by the SuperTrend concept, which uses Average True Range (ATR) to adaptively set trailing stop levels. By comparing price to these levels, the line attempts to indicate when the market is in an uptrend (price above the line) or a downtrend (price below the line). The shifting levels can provide a dynamic sense of direction and help traders stay with the predominant trend until it shifts.
Keltner Channels (Volatility and Range):
Keltner Channels, based on an exponential moving average and Average True Range, form volatility-based envelopes around price. They help traders visualize whether price is extended (touching or moving outside the upper/lower band) or trading within a stable range. This can be useful in identifying low-volatility consolidations and high-volatility breakouts.
Dynamic Order Blocks (Approximations of Supply/Demand Zones):
By detecting pivot highs and lows under conditions of significant volume, the indicator approximates "order blocks." Order blocks are areas where institutional buying or selling may have occurred, potentially acting as future support or resistance zones. Although these approximations are not perfect, they offer a visual cue to areas on the chart where price might react strongly if revisited.
Volume Profile Proxy and Whale Detection:
The indicator highlights price levels associated with recent maximum volume activity, providing a rough "volume profile" reference. Such levels often become key points of price interaction.
"Whale" detection logic attempts to identify bars where exceptionally large volume occurs (beyond a defined threshold). By tracking these "whale bars," traders can infer where heavy participation—often from large traders or institutions—may influence market direction or create zones of interest.
Approximate Bid/Ask Volume and Dollar Volume Tracking:
The script estimates whether volume within each bar leans more towards the bid or the ask side, aiming to understand which participant (buyers or sellers) might have been more aggressive. Additionally, it calculates dollar volume (close price multiplied by volume) and provides an average to gauge the relative participation strength over time.
Labeling and Visual Aids:
Dynamic labels display Whale Frequency (the ratio of bars with exceptionally large volume), average dollar volume, and approximate ask/bid volume metrics. This gives traders at-a-glance insights into current market conditions, participation, and sentiment.
Strengths:
Multifaceted Analysis:
By combining trend, volatility, volume, and order block logic in one place, the indicator saves chart space and simplifies the analytical process. Traders gain a holistic view without flipping between multiple separate tools.
Adaptable to Market Conditions:
The use of ATR and Keltner Channels adapts to changing volatility conditions. The SuperTrend-like line helps keep traders aligned with the prevailing trend, avoiding constant whipsaws in choppy markets.
Volume-Based Insights:
Integrating whale detection and a crude volume profile proxy helps traders understand where large players might be interacting. This perspective can highlight critical levels that might not be evident from price action alone.
Convenient Visual Cues and Labels:
The indicator provides quick reference points and textual information about the underlying volume dynamics, making decision-making potentially faster and more informed.
Weaknesses:
Heuristic and Approximate Nature:
Many of the indicator’s features, like the "order blocks," "whale detection," and the approximate bid/ask volume, rely on heuristics and assumptions that may not always be accurate. Without actual Level II data or true volume profiles, the insights are best considered as supplementary, not definitive signals.
Lagging Components:
Indicators that rely on past data, like ATR-based trends or moving averages for Keltner Channels, inherently lag behind price. This can cause delayed signals, particularly in fast-moving markets, potentially missing some early opportunities or late in confirming market reversals.
No Guaranteed Predictive Power:
As with any technical tool, it does not forecast the future with certainty. Strong volume at a certain level or a bullish SuperTrend reading does not guarantee price will continue in that direction. Market conditions can change unexpectedly, and false signals will occur.
Complexity and Overreliance Risk:
With multiple signals combined, there’s a risk of information overload. Traders might feel compelled to rely too heavily on this one tool. Without complementary analysis (fundamentals, news, or additional technical confirmation), overreliance on the indicator could lead to misguided trades.
Conclusion:
This integrated indicator offers a comprehensive visual guide to market structure, volatility, and activity. Its strength lies in providing a multi-dimensional viewpoint in a single tool. However, traders should remain aware of its approximations, inherent lags, and the potential for conflicting signals. Sound risk management, position sizing, and the use of complementary analysis methods remain essential for trading success.
Risks Associated with Trading:
No indicator can guarantee profitable trades or accurately predict future price movements. Market conditions are inherently unpredictable, and reliance on any single tool or combination of tools carries the risk of financial loss. Traders should practice sound risk management, including the use of stop losses and position sizing, and should not trade with funds they cannot afford to lose. Ultimately, decisions should be guided by a thorough trading plan and possibly supplemented with other forms of market analysis or professional advice.
Risks and Important Considerations:
• Not a Standalone Tool:
• This indicator should not be used in isolation. It is essential to incorporate additional technical analysis tools, fundamental analysis, and market context when making trading decisions.
• Relying solely on this indicator may lead to incomplete assessments of market conditions.
• Market Volatility and False Signals:
• Financial markets can be highly volatile, and indicators based on historical data may not accurately predict future movements.
• The indicator may produce false signals due to sudden market changes, low liquidity, or atypical trading activity.
• Risk Management:
• Always employ robust risk management strategies, including setting stop-loss orders, diversifying your portfolio, and not over-leveraging positions.
• Understand that no indicator guarantees success, and losses are a natural part of trading.
• Emotional Discipline:
• Avoid making impulsive decisions based on indicator signals alone.
• Emotional trading can lead to significant financial losses; maintain discipline and adhere to a well-thought-out trading plan.
• Continuous Learning and Adaptation:
• Stay informed about market news, economic indicators, and global events that may impact trading conditions.
• Continuously evaluate and adjust your trading strategies as market dynamics evolve.
• Consultation with Professionals:
• Consider seeking advice from financial advisors or professional traders to understand better how this indicator can fit into your overall trading strategy.
• Professional guidance can provide personalized insights based on your financial goals and risk tolerance.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
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.
Adaptive ATR Trailing Stops█ Introduction
This script is based on the average true range (ATR) and has been improved with the HHV or LLV. The script supports the trader to have his stoploss trailed. In this case, the stoploss is dynamic and can be adjusted with each candleclose.
█ What Does This Indicator Do?
The ATR SL Trailing Indicator helps you dynamically adjust your stop-loss levels based on market movements. It uses market volatility to calculate trailing stop-loss levels, ensuring you can secure profits or minimize losses. The indicator creates two lines:
A green/red line for long positions (when you’re betting on prices going up).
A green/red line for short positions (when you’re betting on prices going down).
█ Key Concepts: How Does the Indicator Work?
The Average True Range (ATR) measures market volatility, showing how much the price moves over a specific period.
A high ATR indicates a volatile market (large price swings), while a low ATR indicates a quiet market (smaller price changes).
Why is ATR important? ATR helps dynamically adjust the distance between your stop-loss and the current price. In volatile markets, the stop-loss is placed further away to avoid being triggered by short-term fluctuations. In quieter markets, the stop-loss is set closer to the price.
The HHV is the highest price over a specific period. For long positions, the indicator uses the highest price minus an ATR-based value to determine the stop-loss level.
Why is HHV important? HHV ensures the stop-loss for long positions only moves up when the price reaches new highs. Once the price starts falling, the stop-loss remains unchanged to lock in profits or minimize losses.
The LLV is the lowest price over a specific period. For short positions, the indicator uses the lowest price plus an ATR-based value to determine the stop-loss level.
Why is LLV important? LLV ensures the stop-loss for short positions only moves down when the price reaches new lows. Once the price starts rising, the stop-loss remains unchanged to lock in profits or minimize losses.
█ How Does the Indicator Work?
For Long Positions:
The indicator sets the stop-loss below the current price, based on:
Market volatility (ATR).
The highest price over a specific period (HHV).
The line turns green when the current price is above the stop-loss.
The line turns red when the price drops below the stop-loss, signaling you may need to exit the trade.
For Short Positions:
The indicator sets the stop-loss above the current price, based on:
*Market volatility (ATR).
*The lowest price over a specific period (LLV).
*The line turns green when the current price is below the stop-loss.
*The line turns red when the price moves above the stop-loss, signaling you may need to exit the trade.
█ Advantages of the ATR SL Trailing Indicator
*Dynamic and adaptive: Automatically adjusts stop-loss levels based on market volatility.
*Visual clarity: Green and red lines clearly indicate whether your position is safe or at risk.
*Effective risk management: Helps you lock in profits and minimize losses without the need for constant manual adjustments.
█ When Should You Use This Indicator?
*If you practice trend-based trading and want your stop-losses to automatically adapt to market movements.
*In volatile markets, to avoid being stopped out by short-term fluctuations.
*When you want to implement efficient risk management without manually adjusting your positions.
█ Inputs
The user can set the indicator for both longs and shorts. This is particularly important because the calculation is different. The HHV is used for longs and the LLV for shorts. The user can therefore set the period/length for the ATR on the one hand and the HHV/LLV on the other. He also has a multiplier, which can also be customized. The multiplier multiplies the price change of each individual candle.
█ Color Change
If the SL is trailed and the price breaks a line, the color changes. In this case, it would have executed the SL on an open trade.
