Adaptive Price Zone Oscillator [QuantAlgo]Adaptive Price Zone Oscillator 🎯📊
The Adaptive Price Zone (APZ) Oscillator by QuantAlgo is an advanced technical indicator designed to identify market trends and reversals through adaptive price zones based on volatility-adjusted bands. This sophisticated system combines typical price analysis with dynamic volatility measurements to help traders and investors identify trend direction, potential reversals, and market volatility conditions. By evaluating both price action and volatility together, this tool enables users to make informed trading decisions while adapting to changing market conditions.
💫 Dynamic Zone Architecture
The APZ Oscillator provides a unique framework for assessing market trends through a blend of smoothed typical prices and volatility-based calculations. Unlike traditional oscillators that use fixed parameters, this system incorporates dynamic volatility measurements to adjust sensitivity automatically, helping users determine whether price movements are significant relative to current market conditions. By combining smoothed price trends with adaptive volatility zones, it evaluates both directional movement and market volatility, while the smoothing parameters ensure stable yet responsive signals. This adaptive approach allows users to identify trending conditions while remaining aware of volatility expansions and contractions, enhancing both trend-following and mean-reversion strategies.
📊 Indicator Components & Mechanics
The APZ Oscillator is composed of several technical components that create a dynamic trending system:
Typical Price: Utilizes HLC3 (High, Low, Close average) as a balanced price representation
Volatility Measurement: Computes exponential moving average of price changes to determine dynamic zones
Smoothed Calculations: Applies additional smoothing to reduce noise while maintaining responsiveness
Trend Detection: Evaluates price position relative to adaptive zones to determine market direction
📈 Key Indicators and Features
The APZ Oscillator utilizes typical price with customizable length and threshold parameters to adapt to different trading styles. Volatility calculations are applied to determine zone boundaries, providing context-aware levels for trend identification. The trend detection component evaluates price action relative to the adaptive zones, helping validate trends and identify potential reversals.
The indicator also incorporates multi-layered visualization with:
Color-coded trend representation (bullish/bearish)
Clear trend state indicators (+1/-1)
Mean reversion signals with distinct markers
Gradient fills for better visual clarity
Programmable alerts for trend changes
⚡️ Practical Applications and Examples
✅ Add the Indicator : Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
👀 Monitor Trend State : Watch the oscillator's position relative to the zero line to identify trend direction and potential reversals. The step-line visualization with diamonds makes trend changes clearly visible.
🎯 Track Signals : Pay attention to the mean reversion markers that appear above and below the price chart:
→ Upward triangles (⤻) signal potential bullish reversals
→ X crosses (↷) indicate potential bearish reversals
🔔 Set Alerts : Configure alerts for trend changes in both bullish and bearish directions, ensuring you can act on significant technical developments promptly.
🌟 Summary and Tips
The Adaptive Price Zone Oscillator by QuantAlgo is a versatile technical tool, designed to support both trend following and mean reversion strategies across different market environments. By combining smoothed typical price analysis with dynamic volatility-based zones, it helps traders and investors identify significant trend changes while measuring market volatility, providing reliable technical signals. The tool's adaptability through customizable length, threshold, and smoothing parameters makes it suitable for various trading timeframes and styles, allowing users to capture opportunities while maintaining awareness of changing market conditions.
Key parameters to optimize for your trading style:
APZ Length: Adjust for more or less sensitivity to price changes
Threshold: Fine-tune the volatility multiplier for wider or narrower zones
Smoothing: Balance noise reduction with signal responsiveness
Moving Averages
Granville Entry GuideThis indicator is designed to identify trade entry points using patterns 2 and 3 of the Granville's Law. It is compatible with version 6.
Determining Entry Points
・ Long Entry : When the medium-term moving average is rising, if the stock price falls close to or below the moving average and then begins to rise, with that bar being a bullish candle, it is determined as an entry point. At this time, a red circle will be displayed above the bar.
・ Short Entry : When the medium-term moving average is falling, if the stock price rises close to or above the moving average and then begins to fall, with that bar being a bearish candle, it is determined as an entry point. At this time, a blue circle will be displayed below the bar.
Trend Filter
Entry points will only be displayed if the following trend conditions are met:
・In an uptrend, the order of moving averages should be: short-term moving average, medium-term moving average, and long-term moving average from top to bottom. In a downtrend, the order should be: long-term moving average, medium-term moving average, and short-term moving average from top to bottom. The order of the short-term moving average is flexible.
・The medium-term and long-term moving averages should be inclined in the direction of the trend. The inclination of the short-term moving average is flexible.
Adjusting Parameters
・ Stock Selection : You can choose whether to use the stock price from candlesticks or the short-term moving average for determining entry points. Selecting candlesticks allows for quicker determination but increases noise, while selecting the short-term moving average slows down determination but reduces noise. The default value is the short-term moving average.
・ Determining Pullbacks or Retracements : This is determined by the number of bars on either side of the lowest point of the pullback. Increasing the number of bars reduces noise but may result in missed opportunities. The default values are 3 bars on the left and 1 bar on the right.
・ Use of Trend Filter : You can choose whether to use the trend filter. The default setting is to use it.
・ Conditions for Moving Average Inclination : You can choose whether to include the trend direction inclination in the trend filter conditions. The default setting is to include it.
・ Bar Background Color : The trend filter is displayed with the bar's background color, but it can also be set to not display.
このインジケーターは、グランビルの法則のパターン2とパターン3を利用して、トレードのエントリーポイントを見つけるためのものです。version6に対応しています。
エントリーポイントの判定方法
ロングエントリー :中期移動平均線が上昇しているとき、株価が移動平均線の近くまで落ちるか、割り込んだ後に上昇を始め、そのバーが陽線である場合にエントリーポイントと判定します。このとき、赤い丸がバーの上に表示されます。
ショートエントリー :中期移動平均線が下落しているとき、株価が移動平均線の近くまで上昇するか、上抜けた後に下落を始め、そのバーが陰線である場合にエントリーポイントと判定します。このとき、青い丸がバーの下に表示されます。
トレンドフィルター
エントリーポイントは、次のトレンド条件を満たす場合のみ表示されます。
・上昇トレンドの場合、移動平均線が上から中期移動平均線、長期移動平均線の順になっている。下降トレンドの場合、移動平均線が上から長期移動平均線、中期移動平均線の順になっている。なお短期移動平均線の順番は任意です。
・中期移動平均線と長期移動平均線がトレンド方向に傾いている。なお短期移動平均線の傾きは任意です。
パラメーターの調整方法
・ 株価の選択 : エントリーポイントの判定に使用する株価を、ローソク足か短期移動平均線から選べます。ローソク足を選ぶと判定が早くなりますがノイズが増え、短期移動平均線を選ぶと判定が遅くなりますがノイズが減ります。初期値は短期移動平均線です。
・ 押しや戻りの判定 : 押しの最下点の左右のバーの数で判定します。バーの数を増やすとノイズが減りますが、機会を逃すこともあります。初期値は左が3、右が1です。
・ トレンドフィルターの使用 : トレンドフィルターを使うかどうかを選べます。初期値は使用する設定です。
・ 移動平均線の傾きの条件 : トレンドフィルターのうち、トレンド方向の傾きを条件に入れるかどうかを選べます。初期値は条件に入れる設定です。
バーの背景色: トレンドフィルターはバーの背景色で表示されますが、非表示に設定することもできます。
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 🚀.
Gauti Market Maker Killzone EMA1. Identifying the Trend
Use Daily (1D) and Hourly (1H) Exponential Moving Averages (EMAs) to define the overall trend:
Bullish Trend: Both 1D and 1H EMAs are upward sloping, and the price is above these EMAs.
Bearish Trend: Both 1D and 1H EMAs are downward sloping, and the price is below these EMAs.
2. Confirmation with Higher Timeframes
Bullish Conditions:
Check 1D and 4H charts for price action above the EMA bands.
Look for price forming higher highs and higher lows or respecting support at the EMA bands.
Bearish Conditions:
Check 1D and 4H charts for price action below the EMA bands.
Look for price forming lower highs and lower lows or respecting resistance at the EMA bands.
Note: Crossover of EMAs on higher timeframes is an optional extra confirmation, but not mandatory for entry.
3. Entry Strategy
Use the 15-Minute (15M) timeframe for entries.
Entries are taken only during Killzones:
Killzones: London Open, New York Open, or other intraday key trading sessions. (Define the time ranges for these zones based on your trading hours.)
Wait for the price to touch or pull back to the EMA band during the Killzones in the direction of the overall trend:
In a bullish trend, enter long when the price touches the EMA band and shows signs of rejection or reversal.
In a bearish trend, enter short when the price touches the EMA band and shows signs of rejection or reversal.
4. Checklist for Entry
Confirm the following before entering:
1D Trend aligns with the 1H Trend.
Price Action in 1D and 4H supports the trend.
Killzone session is active.
Price is reacting to the EMA band on the 15M chart in the trend direction.
Multi-Indicator Signal with TableThis indicator is a versatile multi-indicator tool designed for traders who want to combine signals from various popular indicators into a single framework. It not only visualizes buy and sell signals but also provides a clear, easy-to-read table that summarizes the included indicators and their respective signal colors.
Key Features:
RSI (Relative Strength Index):
Buy Signal: RSI falls below the oversold level (default: 30).
Sell Signal: RSI rises above the overbought level (default: 70).
Signal Color: Green.
MACD (Moving Average Convergence Divergence):
Buy Signal: MACD line crosses above the signal line.
Sell Signal: MACD line crosses below the signal line.
Signal Color: Blue.
MA Crossover (Moving Average Crossover):
Buy Signal: Short EMA (default: 7) crosses above Long SMA (default: 14).
Sell Signal: Short EMA crosses below Long SMA.
Signal Color: Purple.
Stochastic Oscillator:
Buy Signal: Stochastic %K falls below 20 and crosses above %D.
Sell Signal: Stochastic %K rises above 80 and crosses below %D.
Signal Color: Yellow.
TSI (True Strength Index):
Buy Signal: TSI crosses above the zero line.
Sell Signal: TSI crosses below the zero line.
Signal Color: Red.
Dynamic Signal Table:
A clean, compact table displayed at the top-right corner of the chart, summarizing the indicators and their respective signal colors for quick reference.
Customization:
All indicator parameters are fully adjustable, allowing users to fine-tune settings to match their trading strategy.
Signal colors and table design ensure a visually intuitive experience.
Usage:
This tool is ideal for traders who prefer a multi-indicator approach for generating buy/sell signals.
The combination of different indicators helps to filter out noise and increase the accuracy of trade setups.
Notes:
Signals appear only after the confirmation of the current bar to avoid false triggers.
This indicator is designed for educational purposes and should be used in conjunction with proper risk management strategies.
Bitcoin: Mayer MultipleMayer Multiple Indicator
The Mayer Multiple is a powerful tool designed to help traders assess market conditions and identify optimal buying or selling opportunities. It calculates the ratio between the current price and its 200-day simple moving average (SMA), visualizing key thresholds that indicate value zones, caution areas, and overheated markets.
Key Features:
Dynamic Market Zones: Clearly marked levels like "Smash Buy," "Boost DCA," and "Extreme Euphoria" to guide your trading decisions.
Customizable Input: Adjust the SMA length to fit your strategy.
Color-Coded Signals: Intuitive visualization of market sentiment for quick analysis.
Comprehensive Thresholds: Historical insights into price behavior with plotted reference levels based on probabilities.
This indicator is ideal for traders aiming to enhance their long-term strategies and improve decision-making in volatile markets. Use it to gain an edge in identifying potential turning points and managing risk effectively.
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!
Candled LWMA (Loacally Weighted MA)The Locally Weighted Moving Average (LWMA) is a type of moving average that emphasizes recent data points by assigning them higher weights compared to older values. Unlike the Simple Moving Average (SMA), which treats all data points equally, or the Exponential Moving Average (EMA), which uses a fixed weighting factor, the LWMA applies a linear weighting scheme. This means that the most recent prices contribute more significantly to the average, making the LWMA more responsive to price changes while retaining a smooth curve.
In trading, the LWMA is particularly useful for identifying trends and detecting price reversals with reduced lag. By giving more importance to the latest prices, it provides a clearer picture of the current market dynamics. Traders often use the LWMA in combination with other indicators to confirm trends or spot potential entry and exit points. The adjustable length parameter allows for fine-tuning the indicator to match different market conditions and trading styles. Its ability to adapt to recent price behavior makes it a valuable tool for both short-term and long-term traders.
Adjustable Color Changing WMA by Slope Degree30 weighted moving average that changes colors based upon degree of slope. Consider it a green light for buying/selling pullbacks to the wma. You can adjust the colors and the threshold for the degree of slope.
Precision Trading Strategy: Golden EdgeThe PTS: Golden Edge strategy is designed for scalping Gold (XAU/USD) on lower timeframes, such as the 1-minute chart. It captures high-probability trade setups by aligning with strong trends and momentum, while filtering out low-quality trades during consolidation or low-volatility periods.
The strategy uses a combination of technical indicators to identify optimal entry points:
1. Exponential Moving Averages (EMAs): A fast EMA (3-period) and a slow EMA (33-period) are used to detect short-term trend reversals via crossover signals.
2. Hull Moving Average (HMA): A 66-period HMA acts as a higher-timeframe trend filter to ensure trades align with the overall market direction.
3. Relative Strength Index (RSI): A 12-period RSI identifies momentum. The strategy requires RSI > 55 for long trades and RSI < 45 for short trades, ensuring entries are backed by strong buying or selling pressure.
4. Average True Range (ATR): A 14-period ATR ensures trades occur only during volatile conditions, avoiding choppy or low-movement markets.
By combining these tools, the PTS: Golden Edge strategy creates a precise framework for scalping and offers a systematic approach to capitalize on Gold’s price movements efficiently.
Smoothed Source Weighted EMAThe Smoothed Source EMA is a tool designed to help traders identify potential buying and selling opportunities in the market. It combines two key elements: price smoothing (using standard deviation) and an Exponential Moving Average (EMA). The purpose is to filter out the day-to-day price fluctuations and create clearer buy and sell signals.
Key Concepts Behind the Indicator:
Price Smoothing (Standard Deviation):
To make the price action easier to follow, the indicator first "smooths" the price. This is done by looking at how much the price tends to move up and down (known as standard deviation).
It then creates two "bands" around the current price—one above and one below. These bands represent a smoothed version of the price and help filter out the noise caused by small, random price movements.
Exponential Moving Average (EMA):
The indicator also uses an Exponential Moving Average (EMA), which is a line that represents the average price over a certain period of time (but gives more weight to recent prices). The EMA helps capture the general trend of the price.
The indicator uses this EMA to compare the current price with the overall trend.
How Does the Indicator Work?
Once the indicator calculates the smoothed price bands and the EMA, it looks for specific conditions to trigger a buy or sell signal:
Long (Buy) Signal:
A buy signal happens when the smoothed price (the lower band) is above the EMA. In simple terms, the price is moving up, and the indicator is telling you it's a good time to buy.
The more "weight" or influence you give to the EMA, the slower this buy signal will appear, meaning it’ll only trigger when there’s a strong enough upward movement.
Short (Sell) Signal:
A sell signal occurs when the smoothed price (the upper band) is below the EMA. This suggests the price is moving down, and the indicator signals that it might be time to sell.
Again, the more "weight" you put on the EMA, the slower the sell signal will appear, as the indicator waits for a clearer downtrend.
Why is this Useful for Traders?
Smoothing the Price: Many traders struggle with the noise of price fluctuations, where the price moves up and down quickly without a clear trend. By smoothing the price, this indicator helps traders focus on the bigger picture and avoid reacting to every small movement.
Clear Buy and Sell Signals: The indicator generates easy-to-understand buy and sell signals based on the relationship between the smoothed price and the EMA. If the price is above the smoothed level and EMA, it’s a signal to buy. If it’s below, it’s a signal to sell.
Customizable Sensitivity: The indicator lets traders adjust how sensitive the buy and sell signals are. By changing certain settings, such as the smoothing length and the weight of the EMA, traders can make the indicator react faster or slower depending on how quickly they want to catch changes in the market.
How the Indicator Appears on the Chart:
EMA Line: A line that represents the trend of the price.
Upper and Lower Smoothed Bands: Two bands above and below the price that help identify when the price is moving up or down relative to the trend.
Buy and Sell Arrows: Small arrows on the chart show where the indicator suggests buying or selling.
Colored Bars: The bars on the chart may change color to visually indicate whether the indicator suggests a buy (green) or a sell (red).
In Summary:
The Smoothed Source EMA helps you identify trends by smoothing out price movements using standard deviation, then comparing these smoothed prices with the Exponential Moving Average (EMA).
When the smoothed price moves above or below the EMA, it gives you a signal: a buy when the smoothed price is above the EMA, and a sell when it’s below.
You can adjust how quickly or slowly these signals appear by modifying the settings, giving you control over how sensitive the indicator is to changes in the market.
This indicator is useful for traders who want to reduce noise and focus on the overall trend, using clear, visually simple signals to guide their trading decisions.
Optimal MA FinderIntroduction to the "Optimal MA Finder" Indicator
The "Optimal MA Finder" is a powerful and versatile tool designed to help traders optimize their moving average strategies. This script combines flexibility, precision, and automation to identify the most effective moving average (MA) length for your trading approach. Whether you're aiming to improve your long-only strategy or implement a buy-and-sell methodology, the "Optimal MA Finder" is your go-to solution for enhanced decision-making.
What Does It Do?
The script evaluates a wide range of moving average lengths, from 10 to 500, to determine which one produces the best results based on historical data. By calculating critical metrics such as the total number of trades and the profit factor for each MA length, it identifies the one that maximizes profitability. It supports both simple moving averages (SMA) and exponential moving averages (EMA), allowing you to tailor the analysis to your preferred method.
The logic works by backtesting each MA length against the price data and assessing the performance under two strategies:
Buy & Sell: Includes both long and short trades.
Long Only: Focuses solely on long positions for more conservative strategies.
Once the optimal MA length is identified, the script overlays it on the chart, highlighting periods when the price crosses over or under the optimal MA, helping traders identify potential entry and exit points.
Why Is It Useful?
This indicator stands out for its ability to automate a task that is often labor-intensive and subjective: finding the best MA length. By providing a clear, data-driven answer, it saves traders countless hours of manual testing while significantly enhancing the accuracy of their strategies. For example, instead of guessing whether a 50-period EMA is more effective than a 200-period SMA, the "Optimal MA Finder" will pinpoint the exact length and type of MA that has historically yielded the best results for your chosen strategy.
Key Benefits:
Precision: Identifies the MA length with the highest profit factor for maximum profitability.
Automation: Conducts thorough backtesting without manual effort.
Flexibility: Adapts to your preferred MA type (SMA or EMA) and trading strategy (Buy & Sell or Long Only).
Real-Time Feedback: Provides actionable insights by plotting the optimal MA directly on your chart and highlighting relevant trading periods.
Example of Use: Imagine you're trading a volatile stock and want to optimize your long-only strategy. By applying the "Optimal MA Finder," you discover that a 120-period EMA results in the highest profit factor. The indicator plots this EMA on your chart, showing you when to consider entering or exiting positions based on price movements relative to the EMA.
In short, the "Optimal MA Finder" empowers traders by delivering data-driven insights and improving the effectiveness of trading strategies. Its clear logic, combined with robust automation, makes it an invaluable tool for both novice and experienced traders seeking consistent results.
OBV + Custom MA StrategyFor a long time, the use of the OBV indicator has been relatively monotonous, with its expression and content lacking diversity. Therefore, I'm considering trying new ways of representation.
This "OBV + Custom MA Strategy" indicator combines the On-Balance Volume (OBV) with customizable moving averages (SMA, EMA, or WMA) to provide advanced insights into market trends. The indicator calculates OBV manually and overlays two moving averages: a short-term and a long-term MA. Key features include:
OBV plotted alongside short-term and long-term moving averages for better trend visualization.
Signals generated when OBV crosses the short-term MA or when the short-term MA crosses the long-term MA.
Alerts for bullish and bearish crossovers to help identify potential buy or sell opportunities.
This indicator is suitable for traders looking to incorporate volume dynamics into their strategy while customizing their moving average type and periods.
中文说明
此“OBV + 自定义均线策略”指标结合了成交量指标OBV与可定制的移动均线（SMA、EMA或WMA），为市场趋势分析提供了更多的视角。该指标手动计算OBV，并叠加短期与长期均线，主要特点包括：
绘制OBV以及短期和长期均线，以更清晰地观察趋势。
当OBV上穿/下穿短期均线或短期均线上穿/下穿长期均线时，生成买卖信号。
提供多种看涨和看跌信号的警报，帮助识别潜在的买入或卖出机会。
此指标适合希望将成交量动态纳入策略的交易者，并支持自定义均线类型和周期以满足个性化需求。
2-Year MA Multiplier [UAlgo]The 2-Year MA Multiplier is a technical analysis tool designed to assist traders and investors in identifying potential overbought and oversold conditions in the market. By plotting the 2-year moving average (MA) of an asset's closing price alongside an upper band set at five times this moving average, the indicator provides visual cues to assess long-term price trends and significant market movements.
🔶 Key Features
2-Year Moving Average (MA): Calculates the simple moving average of the asset's closing price over a 730-day period, representing approximately two years.
Visual Indicators: Plots the 2-year MA in forest green and the upper band in firebrick red for clear differentiation.
Fills the area between the 2-year MA and the upper band to highlight the normal trading range.
Uses color-coded fills to indicate overbought (tomato red) and oversold (cornflower blue) conditions based on the asset's closing price relative to the bands.
🔶 Idea
The concept behind the 2-Year MA Multiplier is rooted in the cyclical nature of markets, particularly in assets like Bitcoin. By analyzing long-term price movements, the indicator aims to identify periods of significant deviation from the norm, which may signal potential buying or selling opportunities.
2-year MA smooths out short-term volatility, providing a clearer view of the asset's long-term trend. This timeframe is substantial enough to capture major market cycles, making it a reliable baseline for analysis.
Multiplying the 2-year MA by five establishes an upper boundary that has historically correlated with market tops. When the asset's price exceeds this upper band, it may indicate overbought conditions, suggesting a potential for price correction. Conversely, when the price falls below the 2-year MA, it may signal oversold conditions, presenting potential buying opportunities.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
CauchyTrend [InvestorUnknown]The CauchyTrend is an experimental tool that leverages a Cauchy-weighted moving average combined with a modified Supertrend calculation. This unique approach provides traders with insight into trend direction, while also offering an optional ATR-based range analysis to understand how often the market closes within, above, or below a defined volatility band.
Core Concepts
Cauchy Distribution and Gamma Parameter
The Cauchy distribution is a probability distribution known for its heavy tails and lack of a defined mean or variance. It is characterized by two parameters: a location parameter (x0, often 0 in our usage) and a scale parameter (γ, "gamma").
Gamma (γ): Determines the "width" or scale of the distribution. Smaller gamma values produce a distribution more concentrated near the center, giving more weight to recent data points, while larger gamma values spread the weight more evenly across the sample.
In this indicator, gamma influences how much emphasis is placed on values closer to the current price versus those further away in time. This makes the resulting weighted average either more reactive or smoother, depending on gamma’s value.
// Cauchy PDF formula used for weighting:
// f(x; γ) = (1/(π*γ)) *
f_cauchyPDF(offset, gamma) =>
numerator = gamma * gamma
denominator = (offset * offset) + (gamma * gamma)
pdf = (1 / (math.pi * gamma)) * (numerator / denominator)
pdf
A chart showing different Cauchy PDFs with various gamma values, illustrating how gamma affects the weight distribution.
Cauchy-Weighted Moving Average (CWMA)
Using the Cauchy PDF, we calculate normalized weights to create a custom Weighted Moving Average. Each bar in the lookback period receives a weight according to the Cauchy PDF. The result is a Cauchy Weighted Average (cwm_avg) that differs from typical moving averages, potentially offering unique sensitivity to price movements.
// Summation of weighted prices using Cauchy distribution weights
cwm_avg = 0.0
for i = 0 to length - 1
w_norm = array.get(weights, i) / sum_w
cwm_avg += array.get(values, i) * w_norm
Supertrend with a Cauchy Twist
The indicator integrates a modified Supertrend calculation using the cwm_avg as its reference point. The Supertrend logic typically sets upper and lower bands based on volatility (ATR), and flips direction when price crosses these bands.
In this case, the Cauchy-based average replaces the usual baseline, aiming to capture trend direction via a different weighting mechanism.
When price closes above the upper band, the trend is considered bullish; closing below the lower band signals a bearish trend.
ATR Stats Range (Optional)
Beyond the fundamental trend detection, the indicator optionally computes ATR-based stats to understand price distribution relative to a volatility corridor centered on the cwm_avg line:
Volatility Range:
Defined as cwm_avg ± (ATR * atr_mult), this range creates upper and lower bands. Turning on atr_stats computes how often the daily close falls: Within the range, Above the upper ATR boundary, Below the lower ATR boundary, Within the range but above cwm_avg, Within the range but below cwm_avg
These statistics can help traders gauge how the market behaves relative to this volatility envelope and possibly identify if the market tends to revert to the mean or break out more often.
Backtesting and Performance Metrics
The code is integrated with a backtesting library that allows users to assess strategy performance historically:
Equity Curve Calculation: Compares CauchyTrend-based signals against the underlying asset.
Performance Metrics Table: Once enabled, displays key metrics such as mean returns, Sharpe Ratio, Sortino Ratio, and more, comparing the strategy to a simple Buy & Hold approach.
Alerts and Notifications
The indicator provides Alerts for key events:
Long Alert: Triggered when the trend flips bullish.
Short Alert: Triggered when the trend flips bearish.
Customization and Calibration
Important: The default parameters are not optimized for any specific instrument or time frame. Traders should:
Adjust the length and gamma parameters to influence how sharply or broadly the cwm_avg reacts to price changes.
Tune the atr_len and atr_mult for the Supertrend logic to better match the asset’s volatility characteristics.
Experiment with atr_stats on/off to see if that additional volatility distribution information provides helpful insights.
Traders may find certain sets of parameters that align better with their preferred trading style, risk tolerance, or asset volatility profile.
Disclaimer: This indicator is for educational and informational purposes only. Past performance in backtesting does not guarantee future results. Always perform due diligence, and consider consulting a qualified financial advisor before trading.
Force Volume GradientThis Pine Script is a technical indicator designed for trading platforms, specifically TradingView. It plots the Force Volume Gradient (FVG) and generates buy/sell signals based on the crossover of the FVG line and a signal line.
Key Components:
Force Index: Calculates the exponential moving average (EMA) of the product of the close price and volume.
Force Volume Gradient (FVG): Calculates the EMA of the Force Index.
Signal Line: A simple moving average (SMA) of the FVG.
Buy/Sell Signals: Generated when the FVG line crosses above/below the signal line.
How it Works:
The script calculates the Force Index, which measures the amount of energy or "force" behind price movements.
The FVG is then calculated by applying an EMA to the Force Index, smoothing out the values.
The signal line is a SMA of the FVG, providing a benchmark for buy/sell signals.
When the FVG line crosses above the signal line, a buy signal is generated. Conversely, when the FVG line crosses below the signal line, a sell signal is generated.
Trading Strategy:
This script can be used as a momentum indicator to identify potential buying or selling opportunities. Traders can use the buy/sell signals as entry/exit points, or combine the FVG with other indicators to create a more comprehensive trading strategy.
Customization:
Users can adjust the input parameters, such as the length of the Force Index and signal line, to suit their individual trading preferences.
Volume Weighted Jurik Moving AverageThe Jurik Moving Average (JMA) is a smoothing indicator that is designed to improve upon traditional moving averages by reducing lag while enhancing responsiveness to price movements. It was created by Jurik Research and is often used to track trends with greater accuracy and minimal delay. The JMA is based on a combination of **exponential smoothing** and **phase adjustments**, making it more adaptable to varying market conditions compared to standard moving averages like SMA (Simple Moving Average) or EMA (Exponential Moving Average).
The core advantage of the JMA lies in its ability to adjust to price changes without excessively lagging, which is a common issue with traditional moving averages. It incorporates a **phase parameter** that can be adjusted to smooth out the signal further or make it more responsive to recent price action. This phase adjustment allows traders to fine-tune the JMA's sensitivity to the market, optimizing it for different timeframes and trading strategies.
How JMA Works and Benefits of Adding Volume Weight
The JMA works by applying a **smoothing process** to price data while allowing for adjustments through its phase and power parameters. These parameters help control the degree of smoothness and responsiveness. The result is a curve that follows price trends closely but with less lag than traditional moving averages.
Adding **volume weighting** to the JMA enhances its ability to reflect market activity more accurately. Just like the **Volume-Weighted Moving Average (VWMA)**, volume-weighting adjusts the moving average based on the strength of trading volume, meaning that price movements with higher volume will have a greater influence on the JMA. This can help traders identify trends that are supported by significant market participation, making the moving average more reliable.
The benefit of a volume-weighted JMA is that it responds more effectively to price movements that occur during periods of high trading volume, which are often considered more significant. This can help traders avoid false signals that may occur during low-volume periods when price changes may not reflect true market sentiment. By incorporating volume into the calculation, the JMA becomes more aligned with real market conditions, enhancing its effectiveness for trend identification and decision-making.
Combined Zero Lag EMA with Crosses | ASHGCombined Zero Lag EMA with Crosses
This indicator combines the power of Zero Lag Exponential Moving Averages (EMAs) with the widely used Golden Cross and Death Cross signals. It provides an efficient and precise trend-following tool for traders.
Key Features:
Short and Long Zero Lag EMAs: The indicator uses two Zero Lag EMAs with customizable periods (Short and Long). The short EMA is typically more responsive to price changes, while the long EMA smooths out price data, providing a broader trend perspective.
Golden Cross and Death Cross signals: The Golden Cross occurs when the short EMA crosses above the long EMA, indicating a potential bullish trend. The Death Cross occurs when the short EMA crosses below the long EMA, signaling a possible bearish trend.
Combined Zero Lag EMA: The average of the Short and Long Zero Lag EMAs gives a balanced view of the market's overall direction.
Plotting and Alerts: The indicator plots both the short and long Zero Lag EMAs, as well as the combined EMA, with visual cues for Golden and Death Crosses. Alerts can be set for when these crosses occur.
Use this indicator for clearer entry and exit points, helping you stay ahead of market movements.
This indicator is based on Kıvanç ÖZBİLGİÇ's "Zero Lag EMA v2" indicator.
tr.tradingview.com
Birleştirilmiş Zero Lag EMA ve Cross (Kesişim) Sinyalleri
Bu gösterge, Zero Lag (Sıfır Gecikmeli) Üssel Hareketli Ortalamaların (EMA) gücünü, yaygın olarak kullanılan Golden Cross (Altın Kesişim) ve Death Cross (Ölüm Kesişimi) sinyalleriyle birleştirir. Yatırımcılar için verimli ve hassas bir trend takip aracıdır.
Öne Çıkan Özellikler:
Kısa ve Uzun Zero Lag EMA: Gösterge, özelleştirilebilir periyotlarla iki Zero Lag EMA kullanır (Kısa ve Uzun). Kısa EMA, fiyat değişimlerine daha hızlı tepki verirken, uzun EMA fiyat verilerini düzleştirerek daha geniş bir trend perspektifi sunar.
Golden Cross ve Death Cross sinyalleri: Golden Cross, kısa EMA'nın uzun EMA'yı yukarı doğru kesmesiyle oluşur ve potansiyel bir yükseliş trendine işaret eder. Death Cross ise, kısa EMA'nın uzun EMA'yı aşağı doğru kesmesiyle oluşur ve düşüş trendi sinyali verir.
Birleştirilmiş Zero Lag EMA: Kısa ve uzun Zero Lag EMA'larının ortalaması, piyasanın genel yönünü dengeli bir şekilde gösterir.
Grafik ve Uyarılar: Gösterge, kısa ve uzun Zero Lag EMA'ları ile birleştirilmiş EMA'yı çizerek Golden Cross ve Death Cross sinyalleri için görsel uyarılar sağlar. Bu kesişimler gerçekleştiğinde alarm kurabilirsiniz.
Bu göstergeleri kullanarak, piyasa hareketlerinden önce net giriş ve çıkış noktaları belirleyebilir, böylece daha bilinçli kararlar alabilirsiniz.
Bu indikatör Kıvanç ÖZBİLGİÇ'in "Zero Lag EMA v2" indikatörünü temel alarak hazırlanmıştır.
tr.tradingview.com
Volume Weighted TWAP (VW-TWAP)The Volume Weighted Time Weighted Average Price (VW-TWAP) is an indicator that combines the principles of price averaging with volume sensitivity. Unlike the traditional TWAP, which calculates a simple time-weighted average, VW-TWAP integrates volume into its computation, emphasizing price movements that occur during periods of higher trading activity. This makes it particularly effective for identifying realistic price levels influenced by significant market participation. It is computed by summing the volume-weighted prices over a specified period and dividing by the total volume, providing a more accurate reflection of the price participants value most.
The key benefits of VW-TWAP lie in its ability to guide both traders and investors with a data-driven perspective. By accounting for both time and volume, it highlights fair value zones where significant accumulation or distribution might occur. This can improve trade entries and exits by aligning decisions with zones of substantial market consensus. Furthermore, its adaptability to different timeframes enhances its utility in multi-timeframe analysis, making it suitable for intraday scalpers and long-term swing traders alike. The VW-TWAP's focus on volume sensitivity also minimizes noise from low-volume, erratic price movements, offering a clearer view of market dynamics.
Boltzmann Weighted Moving average ( BWMA )Overview:
Introducing the Boltzmann Weighted Moving Average (BWMA) – a novel approach that draws inspiration from statistical mechanics to emphasize recent market data more than older data. By applying an exponential decay governed by a “temperature” parameter, BWMA provides a unique perspective on price trends and enhances noise filtering. An EMA-based smoothing is then applied for an even cleaner, more stable signal.
Key Features:
Boltzmann Weighting: The BWMA assigns weights to each data point based on a Boltzmann-like formula, giving more influence to recent bars and reducing the impact of older ones. This creates a dynamic, adaptive moving average that can quickly respond to market changes.
Adaptive Temperature Control: Users can adjust the “Temperature” (T) parameter. A lower T puts a stronger emphasis on the most recent data, while a higher T makes the weight distribution more uniform across the chosen period.
EMA Smoothing: After computing the weighted average, an EMA is applied to smooth out short-term noise, resulting in a cleaner trend indication.
Color-Coded Trend Indicator: The BWMA line changes color depending on its slope, allowing traders to quickly identify bullish (green) or bearish (red) conditions at a glance.
Parameters:
Period: Defines the lookback window over which the Boltzmann weights are calculated.
Temperature (T): Controls the steepness of the weight decay. Lower T emphasizes recency, while higher T spreads weights more evenly.
Alpha (Energy Scale): Adjusts how quickly “Energy” (and thus weight decay) increases with older data points.
Smoothing Period: Determines the EMA length for reducing noise after weighting, providing a more stable signal.
How It Works:
The BWMA calculates a weighted average of recent prices, where the weight for each data point i is given by:
weight = math.exp(-energy / (k_B * T))
Energy_i: Increases as the data point is further back in time.
k_B: A scaling constant, set to 1 for simplicity.
T: "Temperature" parameter that controls how quickly the weights decay. A lower T emphasizes more recent data strongly, while a higher T spreads out the emphasis more evenly.
Visuals:
BWMA Line: Plotted as a smooth line that changes color based on trend direction.
Green: BWMA is rising (bullish trend).
Red: BWMA is falling (bearish trend).
Usage:
The BWMA can be used similarly to traditional moving averages but offers greater flexibility and adaptability:
Adjust T and Alpha: Fine-tune the weighting profile to match your trading style, whether you prefer rapid response to recent changes or a more balanced view.
Trend Confirmation: Use color changes to confirm bullish or bearish momentum.
Filtering Noise: The combination of Boltzmann weighting and EMA smoothing can help reduce the impact of sudden price spikes and yield clearer trend signals.
By blending the concepts of statistical mechanics with classic technical analysis techniques, the Boltzmann Weighted Moving Average provides traders with an innovative tool for revealing underlying market trends.
Ensemble Alerts█ OVERVIEW
This indicator creates highly customizable alert conditions and messages by combining several technical conditions into groups , which users can specify directly from the "Settings/Inputs" tab. It offers a flexible framework for building and testing complex alert conditions without requiring code modifications for each adjustment.
█ CONCEPTS
Ensemble analysis
Ensemble analysis is a form of data analysis that combines several "weaker" models to produce a potentially more robust model. In a trading context, one of the most prevalent forms of ensemble analysis is the aggregation (grouping) of several indicators to derive market insights and reinforce trading decisions. With this analysis, traders typically inspect multiple indicators, signaling trade actions when specific conditions or groups of conditions align.
Simplifying ensemble creation
Combining indicators into one or more ensembles can be challenging, especially for users without programming knowledge. It usually involves writing custom scripts to aggregate the indicators and trigger trading alerts based on the confluence of specific conditions. Making such scripts customizable via inputs poses an additional challenge, as it often involves complicated input menus and conditional logic.
This indicator addresses these challenges by providing a simple, flexible input menu where users can easily define alert criteria by listing groups of conditions from various technical indicators in simple text boxes . With this script, you can create complex alert conditions intuitively from the "Settings/Inputs" tab without ever writing or modifying a single line of code. This framework makes advanced alert setups more accessible to non-coders. Additionally, it can help Pine programmers save time and effort when testing various condition combinations.
█ FEATURES
Configurable alert direction
The "Direction" dropdown at the top of the "Settings/Inputs" tab specifies the allowed direction for the alert conditions. There are four possible options:
• Up only : The indicator only evaluates upward conditions.
• Down only : The indicator only evaluates downward conditions.
• Up and down (default): The indicator evaluates upward and downward conditions, creating alert triggers for both.
• Alternating : The indicator prevents alert triggers for consecutive conditions in the same direction. An upward condition must be the first occurrence after a downward condition to trigger an alert, and vice versa for downward conditions.
Flexible condition groups
This script features six text inputs where users can define distinct condition groups (ensembles) for their alerts. An alert trigger occurs if all the conditions in at least one group occur.
Each input accepts a comma-separated list of numbers with optional spaces (e.g., "1, 4, 8"). Each listed number, from 1 to 35, corresponds to a specific individual condition. Below are the conditions that the numbers represent:
1 — RSI above/below threshold
2 — RSI below/above threshold
3 — Stoch above/below threshold
4 — Stoch below/above threshold
5 — Stoch K over/under D
6 — Stoch K under/over D
7 — AO above/below threshold
8 — AO below/above threshold
9 — AO rising/falling
10 — AO falling/rising
11 — Supertrend up/down
12 — Supertrend down/up
13 — Close above/below MA
14 — Close below/above MA
15 — Close above/below open
16 — Close below/above open
17 — Close increase/decrease
18 — Close decrease/increase
19 — Close near Donchian top/bottom (Close > (Mid + HH) / 2)
20 — Close near Donchian bottom/top (Close < (Mid + LL) / 2)
21 — New Donchian high/low
22 — New Donchian low/high
23 — Rising volume
24 — Falling volume
25 — Volume above average (Volume > SMA(Volume, 20))
26 — Volume below average (Volume < SMA(Volume, 20))
27 — High body to range ratio (Abs(Close - Open) / (High - Low) > 0.5)
28 — Low body to range ratio (Abs(Close - Open) / (High - Low) < 0.5)
29 — High relative volatility (ATR(7) > ATR(40))
30 — Low relative volatility (ATR(7) < ATR(40))
31 — External condition 1
32 — External condition 2
33 — External condition 3
34 — External condition 4
35 — External condition 5
These constituent conditions fall into three distinct categories:
• Directional pairs : The numbers 1-22 correspond to pairs of opposing upward and downward conditions. For example, if one of the inputs includes "1" in the comma-separated list, that group uses the "RSI above/below threshold" condition pair. In this case, the RSI must be above a high threshold for the group to trigger an upward alert, and the RSI must be below a defined low threshold to trigger a downward alert.
• Non-directional filters : The numbers 23-30 correspond to conditions that do not represent directional information. These conditions act as filters for both upward and downward alerts. Traders often use non-directional conditions to refine trending or mean reversion signals. For instance, if one of the input lists includes "30", that group uses the "Low relative volatility" condition. The group can trigger an upward or downward alert only if the 7-period Average True Range (ATR) is below the 40-period ATR.
• External conditions : The numbers 31-35 correspond to external conditions based on the plots from other indicators on the chart. To set these conditions, use the source inputs in the "External conditions" section near the bottom of the "Settings/Inputs" tab. The external value can represent an upward, downward, or non-directional condition based on the following logic:
▫ Any value above 0 represents an upward condition.
▫ Any value below 0 represents a downward condition.
▫ If the checkbox next to the source input is selected, the condition becomes non-directional . Any group that uses the condition can trigger upward or downward alerts only if the source value is not 0.
To learn more about using plotted values from other indicators, see this article in our Help Center and the Source input section of our Pine Script™ User Manual.
Group markers
Each comma-separated list represents a distinct group , where all the listed conditions must occur to trigger an alert. This script assigns preset markers (names) to each condition group to make the active ensembles easily identifiable in the generated alert messages and labels. The markers assigned to each group use the format "M", where "M" is short for "Marker" and "x" is the group number. The titles of the inputs at the top of the "Settings/Inputs" tab show these markers for convenience.
For upward conditions, the labels and alert messages show group markers with upward triangles (e.g., "M1▲"). For downward conditions, they show markers with downward triangles (e.g., "M1▼").
NOTE: By default, this script populates the "M1" field with a pre-configured list for a mean reversion group ("2,18,24,28"). The other fields are empty. If any "M*" input does not contain a value, the indicator ignores it in the alert calculations.
Custom alert messages
By default, the indicator's alert message text contains the activated markers and their direction as a comma-separated list. Users can override this message for upward or downward alerts with the two text fields at the bottom of the "Settings/Inputs" tab. When the fields are not empty , the alerts use that text instead of the default marker list.
NOTE: This script generates alert triggers, not the alerts themselves. To set up an alert based on this script's conditions, open the "Create Alert" dialog box, then select the "Ensemble Alerts" and "Any alert() function call" options in the "Condition" tabs. See the Alerts FAQ in our Pine Script™ User Manual for more information.
Condition visualization
This script offers organized visualizations of its conditions, allowing users to inspect the behaviors of each condition alongside the specified groups. The key visual features include:
1) Conditional plots
• The indicator plots the history of each individual condition, excluding the external conditions, as circles at different levels. Opposite conditions appear at positive and negative levels with the same absolute value. The plots for each condition show values only on the bars where they occur.
• Each condition's plot is color-coded based on its type. Aqua and orange plots represent opposing directional conditions, and purple plots represent non-directional conditions. The titles of the plots also contain the condition numbers to which they apply.
• The plots in the separate pane can be turned on or off with the "Show plots in pane" checkbox near the top of the "Settings/Inputs" tab. This input only toggles the color-coded circles, which reduces the graphical load. If you deactivate these visuals, you can still inspect each condition from the script's status line and the Data Window.
• As a bonus, the indicator includes "Up alert" and "Down alert" plots in the Data Window, representing the combined upward and downward ensemble alert conditions. These plots are also usable in additional indicator-on-indicator calculations.
2) Dynamic labels
• The indicator draws a label on the main chart pane displaying the activated group markers (e.g., "M1▲") each time an alert condition occurs.
• The labels for upward alerts appear below chart bars. The labels for downward alerts appear above the bars.
NOTE: This indicator can display up to 500 labels because that is the maximum allowed for a single Pine script.
3) Background highlighting
• The indicator can highlight the main chart's background on bars where upward or downward condition groups activate. Use the "Highlight background" inputs in the "Settings/Inputs" tab to enable these highlights and customize their colors.
• Unlike the dynamic labels, these background highlights are available for all chart bars, irrespective of the number of condition occurrences.
█ NOTES
• This script uses Pine Script™ v6, the latest version of TradingView's programming language. See the Release notes and Migration guide to learn what's new in v6 and how to convert your scripts to this version.
• This script imports our new Alerts library, which features functions that provide high-level simplicity for working with complex compound conditions and alerts. We used the library's `compoundAlertMessage()` function in this indicator. It evaluates items from "bool" arrays in groups specified by an array of strings containing comma-separated index lists , returning a tuple of "string" values containing the marker of each activated group.
• The script imports the latest version of the ta library to calculate several technical indicators not included in the built-in `ta.*` namespace, including Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Fractal Adaptive Moving Average (FRAMA), Tilson T3, Awesome Oscillator (AO), Full Stochastic (%K and %D), SuperTrend, and Donchian Channels.
• The script uses the `force_overlay` parameter in the label.new() and bgcolor() calls to display the drawings and background colors in the main chart pane.
• The plots and hlines use the available `display.*` constants to determine whether the visuals appear in the separate pane.
Look first. Then leap.
Stage Market V4This script provides a comprehensive tool for identifying market stages based on exponential moving averages (EMAs), market performance metrics, and additional price statistics. Below is a summary of its functionality and instructions on how to use it:
1. Inputs and Configuration
Fast and Slow EMA:
Fast EMA Length: Determines the period for the fast EMA.
Slow EMA Length: Determines the period for the slow EMA.
Additional EMAs:
Enable or disable three additional EMAs (EMA 1, EMA 2, and EMA 3) with customizable lengths.
52-Week High Display:
Optionally display the percentage distance from the 52-week high.
2. Market Stages
The indicator identifies six market stages based on the relationship between the price, fast EMA, and slow EMA:
Recovery: Price is above the fast EMA, and the slow EMA is above both the price and the fast EMA.
Accumulation: Price is above both the fast EMA and slow EMA, but the slow EMA is still above the fast EMA.
Bull Market: Price, fast EMA, and slow EMA are all aligned in a rising trend.
Warning: Price is below the fast EMA, but still above the slow EMA, signaling potential weakness.
Distribution: Price is below both EMAs, but the slow EMA remains below the fast EMA.
Bear Market: Price, fast EMA, and slow EMA are all aligned in a falling trend.
The current stage is displayed in a table along with the number of bars spent in that stage.
3. Performance Metrics
The script calculates additional metrics to gauge the stock's performance:
30-Day Change: The percentage price change over the last 30 days.
90-Day Change: The percentage price change over the last 90 days.
Year-to-Date (YTD) Change: The percentage change from the year's first closing price.
Distance from 52-Week High (if enabled): The percentage difference between the current price and the highest price over the past 52 weeks.
These values are color-coded:
Green for positive changes.
Red for negative changes.
4. Table Display
The indicator uses a table in the bottom-right corner of the chart to show:
Current market stage and bars spent in the stage.
30-day, 90-day, and YTD changes.
Distance from the 52-week high (if enabled).
5. EMA Plotting
The script plots the following EMAs on the chart:
Fast EMA (default: 50-period) in yellow.
Slow EMA (default: 200-period) in orange.
Optional EMAs (EMA 1, EMA 2, and EMA 3) in blue, green, and purple, respectively.
6. Using the Indicator
Add the indicator to your chart via the Pine Editor in TradingView.
Customize the input parameters to fit your trading style or the asset's characteristics.
Use the table to quickly assess the current market stage and key performance metrics.
Observe the plotted EMAs to understand trend alignments and potential crossovers.
This script is particularly useful for identifying market trends, understanding price momentum, and aligning trading decisions with broader market conditions.
Heat Map Trend (VIDYA MA) [BigBeluga]The Heat Map Trend (VIDYA MA) - BigBeluga indicator is a multi-timeframe trend detection tool based on the Volumetric Variable Index Dynamic Average (VIDYA). This indicator calculates trends using volume momentum, or volatility if volume data is unavailable, and displays the trends across five customizable timeframes. It features a heat map to visualize trends, color-coded candles based on an average of the five timeframes, and a dashboard that shows the current trend direction for each timeframe. This tool helps traders identify trends while minimizing market noise and is particularly useful in detecting faster market changes in shorter timeframes.
🔵 KEY FEATURES & USAGE
◉ Volumetric Variable Index Dynamic Average (VIDYA):
The core of the indicator is the VIDYA moving average, which adjusts dynamically based on volume momentum. If volume data isn't available, the indicator uses volatility instead to smooth the moving average. This allows traders to assess the trend direction with more accuracy, using either volume or volatility, if volume data is not provided, as the basis for the trend calculation.
// VIDYA CALCULATION -----------------------------------------------------------------------------------------
// ATR (Average True Range) and volume calculation
bool volume_check = ta.cum(volume) <= 0
float atrVal = ta.atr(1)
float volVal = volume_check ? atrVal : volume // Use ATR if volume is not available
// @function: Calculate the VIDYA (Volumetric Variable Index Dynamic Average)
vidya(src, len, cmoLen) =>
float cmoVal = ta.sma(ta.cmo(volVal, cmoLen), 10) // Calculate the CMO and smooth it with an SMA
float absCmo = math.abs(cmoVal) // Absolute value of CMO
float alpha = 2 / (len + 1) // Alpha factor for smoothing
var float vidyaVal = 0.0 // Initialize VIDYA
vidyaVal := alpha * absCmo / 100 * src + (1 - alpha * absCmo / 100) * nz(vidyaVal ) // VIDYA formula
◉ Multi-Timeframe Trend Analysis with Heat Map Visualization:
The indicator calculates VIDYA across five customizable timeframes, allowing traders to analyze trends from multiple perspectives. The resulting trends are displayed as a heat map below the chart, where each timeframe is represented by a gradient color. The color intensity reflects the distance of the moving average (VIDYA) from the price, helping traders to identify trends on different timeframes visually. Shorter timeframes in the heat map are particularly useful for detecting faster market changes, while longer timeframes help to smooth out market noise and highlight the general trend.
Trend Direction:
Heat Map Reading:
◉ Dashboard for Multi-Timeframe Trend Directions:
The built-in dashboard displays the trend direction for each of the five timeframes, showing whether the trend is up or down. This quick overview provides traders with valuable insights into the current market conditions across multiple timeframes, helping them to assess whether the market is aligned or if there are conflicting trends. This allows for more informed decisions, especially during volatile periods.
◉ Color-Coded Candles Based on Multi-Timeframe Averages:
Candles are dynamically colored based on the average of the VIDYA across all five timeframes. When the price is in an uptrend, the candles are colored blue, while in a downtrend, they are colored red. If the VIDYA averages suggest a possible trend shift, the candles are displayed in orange to highlight a potential change in momentum. This color coding simplifies the process of identifying the dominant trend and spotting potential reversals.
BTC:
SP500:
◉ UP and DOWN Signals for Trend Direction Changes:
The indicator provides clear UP and DOWN signals to mark trend direction changes. When the average VIDYA crosses above a certain threshold, an UP signal is plotted, indicating a shift to an uptrend. Conversely, when it crosses below, a DOWN signal is shown, highlighting a transition to a downtrend. These signals help traders to quickly identify shifts in market direction and respond accordingly.
🔵 CUSTOMIZATION
VIDYA Length and Momentum Settings:
Adjust the length of the VIDYA moving average and the period for calculating volume momentum. These settings allow you to fine-tune how sensitive the indicator is to market changes, helping to match it with your preferred trading style.
Timeframe Selection:
Select five different timeframes to analyze trends simultaneously. This gives you the flexibility to focus on short-term trends, long-term trends, or a combination of both depending on your trading strategy.
Candle and Heat Map Color Customization:
Change the colors of the candles and heat map to fit your personal preferences. This customization allows you to align the visuals of the indicator with your overall chart setup, making it easier to analyze market conditions.
🔵 CONCLUSION
The Heat Trend (VIDYA MA) - BigBeluga indicator provides a comprehensive, multi-timeframe view of market trends, using VIDYA moving averages that adapt to volume momentum or volatility. Its heat map visualization, combined with a dashboard of trend directions and color-coded candles, makes it an invaluable tool for traders looking to understand both short-term market fluctuations and longer-term trends. By showing the overall market direction across multiple timeframes, it helps traders avoid market noise and focus on the bigger picture while being alert to faster shifts in shorter timeframes.
