Power Core MAThe Power Core MA indicator is a powerful tool designed to identify the most significant moving average (MA) in a given price chart. This indicator analyzes a wide range of moving averages, from 50 to 400 periods, to determine which one has the strongest influence on the current price action.
The blue line plotted on the chart represents the "Current Core MA," which is the moving average that is most closely aligned with other nearby moving averages. This line indicates the current trend and potential support or resistance levels.
The table displayed on the chart provides two important pieces of information. The "Current Core MA" value shows the length of the moving average that is currently most influential. The "Historical Core MA" value represents the average length of the most influential moving averages over time.
This indicator is particularly useful for traders and analysts who want to identify the most relevant moving average for their analysis. By focusing on the moving average that has the strongest historical significance, users can make more informed decisions about trend direction, support and resistance levels, and potential entry or exit points.
The Power Core MA is an excellent tool for those interested in finding the strongest moving average in the price history. It simplifies the process of analyzing multiple moving averages by automatically identifying the most influential one, saving time and providing valuable insights into market dynamics.
By combining current and historical data, this indicator offers a comprehensive view of the market's behavior, helping traders to adapt their strategies to the most relevant timeframes and trend strengths.
Cycles
No Trade Zone Indicator [CHE]No Trade Zone Indicator
The "No Trade Zone Indicator " is a powerful tool designed to help traders identify periods when the market may not present favorable trading opportunities. By analyzing the percentage change in the 20-period Simple Moving Average (SMA20) relative to a dynamically adjusted threshold based on market volatility, this indicator highlights times when it's prudent to stay out of the market.
Why Knowing When Not to Trade Is Important
Understanding when not to trade is just as crucial as knowing when to enter or exit a position. Trading during periods of low volatility or uncertain market direction can lead to unnecessary risks and potential losses. By recognizing these "No Trade Zones," you can:
- Avoid Low-Probability Trades: Reduce the chances of entering trades with unfavorable risk-to-reward ratios.
- Preserve Capital: Protect your investment from unpredictable market movements.
- Enhance Focus: Concentrate on high-quality trading opportunities that align with your strategy.
How the Indicator Works
- SMA20 Calculation: Computes the 20-period Simple Moving Average of closing prices to identify the market's short-term trend.
- ATR Measurement: Calculates the Average True Range (ATR) over a user-defined period (default is 14) to assess market volatility.
- Dynamic Threshold: Determines an adjusted threshold by multiplying the ATR percentage by a Threshold Adjustment Factor (default is 0.05).
- Trend Analysis: Compares the percentage change of the SMA20 against the adjusted threshold to evaluate market momentum.
- Status Identification:
- Long: Indicates a rising SMA20 above the threshold—suggesting a potential upward trend.
- Short: Indicates a falling SMA20 above the threshold—suggesting a potential downward trend.
- No Trade: Signals when the SMA20 change is below the threshold, marking a period of low volatility or indecision.
Features
- Customizable Settings: Adjust the ATR period and Threshold Adjustment Factor to suit different trading styles and market conditions.
- Visual Indicators: Colored columns represent market status—green for "Long," red for "Short," and gray for "No Trade."
- On-Chart Table: An optional table displays the current market status directly on your chart for quick reference.
- Alerts: Set up alerts to receive notifications when the market enters a "No Trade Zone," helping you stay informed without constant monitoring.
How to Use the Indicator
1. Add to Chart: Apply the "No Trade Zone Indicator " to your preferred trading chart on TradingView.
2. Configure Settings: Customize the ATR period and Threshold Adjustment Factor based on your analysis and risk tolerance.
3. Interpret Signals:
- Green Columns: Consider looking for buying opportunities as the market shows upward momentum.
- Red Columns: Consider looking for selling opportunities as the market shows downward momentum.
- Gray Columns: Refrain from trading as the market lacks clear direction.
4. Monitor Alerts: Use the alert feature to get notified when the market status changes, allowing you to make timely decisions.
Conclusion
Incorporating the "No Trade Zone Indicator " into your trading toolkit can enhance your decision-making process by clearly indicating when the market may not be conducive to trading. By focusing on periods with favorable conditions and avoiding low-volatility times, you can improve your trading performance and achieve better results over the long term.
*Trade wisely, and remember—the best trade can sometimes be no trade at all.*
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
best regards
Chervolino
Auto HTF atrautohtf atr helps to idenify cycles and swings with indicaion of strong demand and need to identify the trend with the fundamentals posiive cashflow
Enhanced Market Analyzer with Adaptive Cognitive LearningThe "Enhanced Market Analyzer with Advanced Features and Adaptive Cognitive Learning" is an advanced, multi-dimensional trading indicator that leverages sophisticated algorithms to analyze market trends and generate predictive trading signals. This indicator is designed to merge traditional technical analysis with modern machine learning techniques, incorporating features such as adaptive learning, Monte Carlo simulations, and probabilistic modeling. It is ideal for traders who seek deeper market insights, adaptive strategies, and reliable buy/sell signals.
Key Features:
Adaptive Cognitive Learning:
Utilizes Monte Carlo simulations, reinforcement learning, and memory feedback to adapt to changing market conditions.
Adjusts the weighting and learning rate of signals dynamically to optimize predictions based on historical and real-time data.
Hybrid Technical Indicators:
Custom RSI Calculation: An RSI that adapts its length based on recursive learning and error adjustments, making it responsive to varying market conditions.
VIDYA with CMO Smoothing: An advanced moving average that incorporates Chander Momentum Oscillator for adaptive smoothing.
Hamming Windowed VWMA: A volume-weighted moving average that applies a Hamming window for smoother calculations.
FRAMA: A fractal adaptive moving average that responds dynamically to price movements.
Advanced Statistical Analysis:
Skewness and Kurtosis: Provides insights into the distribution and potential risk of market trends.
Z-Score Calculations: Identifies extreme market conditions and adjusts trading thresholds dynamically.
Probabilistic Monte Carlo Simulation:
Runs thousands of simulations to assess potential price movements based on momentum, volatility, and volume factors.
Integrates the results into a probabilistic signal that informs trading decisions.
Feature Extraction:
Calculates a variety of market metrics, including price change, momentum, volatility, volume change, and ATR.
Normalizes and adapts these features for use in machine learning algorithms, enhancing signal accuracy.
Ensemble Learning:
Combines signals from different technical indicators, such as RSI, MACD, Bollinger Bands, Stochastic Oscillator, and statistical features.
Weights each signal based on cumulative performance and learning feedback to create a robust ensemble signal.
Recursive Memory and Feedback:
Stores and averages past RSI calculations in a memory array to provide historical context and improve future predictions.
Adaptive memory factor adjusts the influence of past data based on current market conditions.
Multi-Factor Dynamic Length Calculation:
Determines the length of moving averages based on volume, volatility, momentum, and rate of change (ROC).
Adapts to various market conditions, ensuring that the indicator is responsive to both high and low volatility environments.
Adaptive Learning Rate:
The learning rate can be adjusted based on market volatility, allowing the system to adapt its speed of learning and sensitivity to changes.
Enhances the system's ability to react to different market regimes.
Monte Carlo Simulation Engine:
Simulates thousands of random outcomes to model potential future price movements.
Weights and aggregates these simulations to produce a final probabilistic signal, providing a comprehensive risk assessment.
RSI with Dynamic Adjustments:
The initial RSI length is adjusted recursively based on calculated errors between true RSI and predicted RSI.
The adaptive RSI calculation ensures that the indicator remains effective across various market phases.
Hybrid Moving Averages:
Short-Term and Long-Term Averages: Combines FRAMA, VIDYA, and Hamming VWMA with specific weights for a unique hybrid moving average.
Weighted Gradient: Applies a color gradient to indicate trend strength and direction, improving visual clarity.
Signal Generation:
Generates buy and sell signals based on the ensemble model and multi-factor analysis.
Uses percentile-based thresholds to determine overbought and oversold conditions, factoring in historical data for context.
Optional settings to enable adaptation to volume and volatility, ensuring the indicator remains effective under different market conditions.
Monte Carlo and Learning Parameters:
Users can customize the number of Monte Carlo simulations, learning rate, memory factor, and reward decay for tailored performance.
Applications:
Scalping and Day Trading:
The fast response of the adaptive RSI and ensemble learning model makes this indicator suitable for short-term trading strategies.
Swing Trading:
The combination of long-term moving averages and probabilistic models provides reliable signals for medium-term trends.
Volatility Analysis:
The ATR, Bollinger Bands, and adaptive moving averages offer insights into market volatility, helping traders adjust their strategies accordingly.
EMA Touch Alertit shows when price is touching with 10 ema,it is useful if u dont want to zoom in on price
Enhanced Chaikin Money FlowEnhanced Chaikin Money Flow (CMF) with Normalized Distribution
The Enhanced Chaikin Money Flow (CMF) is a sophisticated version of Marc Chaikin's classic volume-weighted indicator that measures buying and selling pressure. This version incorporates statistical normalization and advanced smoothing techniques to provide more reliable signals.
Key Features
Normalized distribution (z-score) for better historical comparison
Multiple smoothing options (SMA, EMA, WMA, RMA) for noise reduction
Standard deviation bands (1σ and 2σ) to identify extreme readings
Adjustable parameters for customization
Alert system for extreme readings
Interpretation
Values represent standard deviations from the mean
Above 0: Indicates net buying pressure
Below 0: Indicates net selling pressure
Outside ±2σ bands: Suggests extreme market conditions
Crossovers of standard deviation bands may signal potential reversals
Technical Details
The indicator combines volume with price location within a bar to determine buying/selling pressure, then normalizes these values using a rolling z-score calculation. This normalization allows for better historical comparison and more reliable overbought/oversold signals.
Best used in conjunction with price action and other indicators for confirmation of potential market turns or trend strength.
Expanded Keltner Channel with Forecast The entire code aims to display market dynamics on the chart based on two indicators: the Keltner Channel and volume. This allows traders to identify potential reversal points (when the price touches the Keltner bands) and areas where there is increased market activity (changes in volume). With this information, traders can make more informed decisions about opening or closing positions.
The code generates forecasts based on the touches of the bands, and the yellow line acts as an additional volume indicator, suggesting important market changes.
Cruce de Medias AvanzadoLa estrategia es muy simple, es cruce de medias móviles, por defecto la rápida es 50 y la lenta 200 pero se pueden personalizar, es una estrategia a largo plazo que ha demostrado ser muy rentable en cualquiera de sus medias con índices en gráficos diarios.
Se pueden elegir distintos tipos de medias móviles existentes y ajustar la rentabilidad de cada una y ajustar sus medias móviles a para aumentar la rentabilidad.
Aquí tienes una descripción de las medias móviles añadidas al script y sus características:
Simple SMA (Media Móvil Simple):
Calcula el promedio simple de los precios de cierre durante un período específico.
Es la más básica y fácil de interpretar, pero puede ser lenta para reaccionar a los cambios bruscos en el precio.
Exponencial EMA (Media Móvil Exponencial):
Da más peso a los precios recientes, lo que la hace más sensible a los cambios de precio.
Responde más rápidamente a las fluctuaciones del mercado en comparación con la SMA, lo que ayuda a detectar cambios de tendencia más temprano.
Ponderada WMA (Media Móvil Ponderada):
Asigna más peso a los datos más recientes de forma lineal.
Proporciona un balance entre la sensibilidad de la EMA y la suavidad de la SMA, siendo útil para seguir tendencias a corto plazo.
Volumen Ponderada VWMA (Media Móvil Ponderada por Volumen):
Pondera los precios según el volumen de negociación, dándole más importancia a los precios con mayor volumen.
Es útil para analizar si los movimientos de precio están respaldados por un volumen alto, lo que indica mayor relevancia.
Hull HMA (Media Móvil de Hull):
Diseñada para minimizar el retraso y aumentar la sensibilidad al mismo tiempo.
Combina el suavizado y la rápida respuesta al precio, lo que la hace adecuada para traders que necesitan detectar cambios de tendencia rápidamente.
Media Suavizada RMA (Media Móvil Suavizada):
Es similar a la EMA pero con un suavizado diferente, proporcionando un promedio que filtra de forma más efectiva el ruido de precios.
Suele usarse para análisis de tendencias a medio plazo.
Media de Arnaud Legoux ALMA (Media Móvil ALMA):
Utiliza un algoritmo especial de suavizado con control de sesgo para reducir el ruido y mejorar la detección de tendencias.
Permite ajustar los parámetros de sesgo y suavizado para adaptarse a diferentes necesidades de trading.
Es conocida por su capacidad de mantener una respuesta rápida al precio al tiempo que suprime el ruido.
Estas medias móviles ofrecen diferentes enfoques para seguir y analizar las tendencias en los precios. Dependiendo de tu estrategia de trading, puedes elegir la media móvil que mejor se adapte a tus necesidades: desde una respuesta rápida con la HMA o EMA, hasta un enfoque más estable y menos reactivo con la SMA o RMA.
Bolvoman by Dragon.3 Chiến lược giao dịch t là một hệ thống khá phức tạp, kết hợp nhiều chỉ báo và điều kiện khác nhau để xác định tín hiệu mua và bán. Dưới đây là phần giải thích chi tiết từng phần:
EMA (Exponential Moving Averages)
Mã sử dụng ba đường EMA:
Signal EMA là EMA chu kỳ ngắn, thường là 21 hoặc 10.
Trend EMA là EMA 55, dùng để xác định xu hướng chính.
Supper Trend EMA là EMA dùng để hỗ trợ xác định xu hướng, tương tự như trailing stop.
Màu sắc và Điều kiện xu hướng
Khi Signal EMA nằm trên Trend EMA, mã sẽ hiển thị màu xanh để báo hiệu xu hướng tăng.
Khi Signal EMA nằm dưới Trend EMA, mã sẽ hiển thị màu đỏ báo hiệu xu hướng giảm.
Keltner Channel
Keltner Channel được tạo bằng cách sử dụng ATR (Average True Range) làm độ rộng kênh, nhằm xác định các vùng mua và bán.
Kênh trên (upperKC) và kênh dưới (lowerKC) được hiển thị khi người dùng bật Show KC.
Phân tích Mô Hình Nến và Khối Lượng
Mã xác định các mô hình nến như Bullish Engulfing, Bearish Engulfing, Bullish Pinbar, và Bearish Pinbar.
Nếu một trong các mô hình này xuất hiện trong điều kiện xu hướng tăng/giảm (EMA cắt lên/xuống), và khối lượng lớn hơn khối lượng trung bình của 14 phiên trước đó, thì tín hiệu mua hoặc bán sẽ được đưa ra.
Dynamic Levels Breakout
Mã có thể xác định các mức kháng cự và hỗ trợ động dựa trên các điểm pivot, dùng Pivot Point Period và ATR Factor.
Các mức kháng cự và hỗ trợ động sẽ giúp xác định điểm vào lệnh tiềm năng khi giá phá vỡ các mức này.
SuperTrend AI Dựa Trên Machine Learning
Phần này của mã nhằm phân tích và phân loại các vùng biến động cao, trung bình, và thấp dựa trên ATR.
Dựa trên AI Supper Trend, mã tính toán các trung tâm cụm dữ liệu và tạo các dải SuperTrend để chỉ ra sự biến động, hỗ trợ trader trong việc nắm bắt cơ hội giao dịch trong các điều kiện thị trường khác nhau.
Đường Zigzag và Double Bottom/Double Top
Mã có tích hợp đường zigzag để hiển thị các đỉnh và đáy, từ đó giúp xác định các mô hình đảo chiều như Double Bottom hoặc Double Top.
Điều kiện Mua/Bán chính
Mua khi Signal EMA cắt lên Trend EMA, xuất hiện Bullish Engulfing hoặc Bullish Pinbar, và giá đóng cửa trên Signal EMA kèm khối lượng lớn hơn trung bình 14 phiên.
Bán khi Signal EMA cắt xuống Trend EMA, xuất hiện Bearish Engulfing hoặc Bearish Pinbar, và giá đóng cửa dưới Signal EMA kèm khối lượng lớn hơn trung bình 14 phiên.
Chiến lược này hướng đến việc kết hợp các chỉ báo kỹ thuật và mô hình nến để tăng độ chính xác cho tín hiệu giao dịch. Với các chỉ báo như EMA, Keltner Channel, SuperTrend AI, và phân tích khối lượng, mã cho phép các trader nhận diện các cơ hội giao dịch tốt trong xu hướng và các điểm phá vỡ quan trọng.
My System Tradding . Dragon.R3 StrategyChiến luojc following, với sonic R với tỷ lệ lợi nhuận trên 50%
High Frequency Trend Following - Single Trade ActiveHigh Frequency Trend Following - Single Trade Active Strategy
Overview
This TradingView strategy script is designed for high-frequency trading on shorter timeframes, leveraging exponential moving averages (EMAs) and the Relative Strength Index (RSI) to identify potential trade entries and exits. It ensures only one active trade at a time by closing the current position when an opposing signal is detected. This clean, visually appealing strategy is suited for day traders looking to follow short-term trends with minimal chart clutter.
How It Works
The strategy combines three main indicators:
EMA Cross: The script uses two EMAs (20-period and 50-period) to capture trend direction. A cross of the shorter EMA (20) above the longer EMA (50) indicates a bullish trend, while a cross below signals a bearish trend.
RSI Confirmation: RSI levels are used to confirm entries, filtering out trades in overbought or oversold conditions. For long entries, the RSI must be below 40, indicating a potential reversal from oversold conditions. For short entries, the RSI must be above 60, signaling a potential reversal from overbought conditions.
ATR-Based Exits: This script incorporates the Average True Range (ATR) to dynamically adjust stop loss and take profit levels based on market volatility, although exits in this version are based on opposite signals.
Best Use
This strategy is best suited for fast-moving markets and shorter timeframes, such as 5- or 15-minute charts, where it can capture frequent trend reversals. It can be applied to cryptocurrencies, forex, and other high-volatility assets.
Set Timeframe: This strategy performs best on intraday timeframes (e.g., 5-minute or 15-minute) where trend reversals are frequent.
Pair with High Volatility Assets: Ideal for assets like cryptocurrency pairs or forex where short-term trends and reversals are common.
Variables and Parameters
EMA Periods:
ema_short_length: The length of the short-term EMA (default is 20). This captures the faster-moving trend.
ema_long_length: The length of the long-term EMA (default is 50), representing the slower trend.
RSI Settings:
rsi_length: The period for the RSI (default is 14).
rsi_overbought: RSI level above which the market is considered overbought (default is 60).
rsi_oversold: RSI level below which the market is considered oversold (default is 40).
ATR Settings:
atr_length: Period for calculating ATR (default is 14).
atr_multiplier: Multiplier to adjust stop loss distance relative to ATR (default is 1.1).
take_profit_multiplier: Multiplier to adjust take profit distance relative to ATR (default is 1.5).
Interpretation
Entry Signals:
Long Entry: When the 20 EMA crosses above the 50 EMA (indicating an uptrend) and the RSI is below the rsi_oversold threshold (default 40), the script opens a long position.
Short Entry: When the 20 EMA crosses below the 50 EMA (indicating a downtrend) and the RSI is above the rsi_overbought threshold (default 60), the script opens a short position.
Exit Signals:
The strategy closes a long position when a short entry signal is generated, and vice versa. This ensures only one active trade at a time.
Visuals:
EMA Lines: The 20 EMA is green, and the 50 EMA is red. Crosses between these lines indicate potential trend shifts.
Background Colors: The background color changes faintly to green when a long position is active and to red when a short position is active, providing a clear visual representation of the current trade direction.
Entry and Exit Arrows: Small green arrows indicate long entries and exits from short positions, while red arrows mark short entries and exits from long positions.
Additional Notes
Customizability: Users can adjust the EMA and RSI parameters to suit their specific asset or timeframe. For example, decreasing the EMA lengths (e.g., 10 and 30) can make the strategy more sensitive to short-term trends.
Trading Environment: This strategy is ideal for high-volatility environments, where price reversals are common and where high-frequency trading can capture small but frequent gains.
Disclaimer
This strategy is intended for educational purposes and should be backtested and adjusted according to the specific asset and market conditions. Always use risk management and trade responsibly.
Keltner Channel with Forecast It is recommended to use the 15-minute chart along with Heikin Ashi candles. The two blue lines represent the 15-minute Keltner Channel, while the green lines represent the 1-hour Keltner Channel. This setup provides a clearer view of both short-term and longer-term market trends, helping traders make more informed decisions based on the combined insights from the 15-minute and 1-hour timeframes.
The entire code aims to display market dynamics on the chart based on two indicators: the Keltner Channel and volume. This allows traders to identify potential reversal points (when the price touches the Keltner bands) and areas where there is increased market activity (changes in volume). With this information, traders can make more informed decisions about opening or closing positions.
The code generates forecasts based on the touches of the bands, and the yellow line acts as an additional volume indicator, suggesting important market changes.
Average Monthly Closing Direction StrategyEstrategia que diseñé, que combina patrones históricos y filtros técnicos para mejorar las probabilidades de éxito en trading. La idea es simple: he identificado ciertos días específicos del mes que, según los datos históricos, tienen tendencia a cerrar en positivo (suben) o en negativo (bajan).
Enhanced 1-Hour Strategy for Maximized ReturnsEnhanced 1-Hour Strategy for Maximized Returns
Overview
This is a trend-following and volatility-based breakout strategy designed for trading on the one-hour timeframe. It combines moving average crossovers, RSI for momentum, and Bollinger Bands as a volatility filter to confirm entries and exits. With a focus on maximizing returns, this strategy is tuned to work with leveraged trading and dynamically allocates position sizes based on available equity.
How the Strategy Works
Trend Detection: The strategy uses two moving averages—a short-term and a long-term—to detect trends.
A crossover of the short moving average above the long moving average indicates a potential upward trend.
Conversely, a crossover of the short moving average below the long moving average suggests a downward trend.
Momentum Confirmation with RSI: To avoid entering trades in low-momentum conditions, the strategy employs the Relative Strength Index (RSI).
A long (buy) trade is considered only when RSI is above a set threshold, indicating upward momentum.
A short (sell) trade is considered only when RSI is below a set threshold, indicating downward momentum.
Volatility Filter with Bollinger Bands: Bollinger Bands act as a filter to ensure the strategy enters trades only during periods of higher volatility.
For a long trade, the price must be above the lower Bollinger Band.
For a short trade, the price must be below the upper Bollinger Band.
ATR-Based Stop-Loss and Take-Profit: The strategy uses the Average True Range (ATR) to set stop-loss and take-profit levels dynamically based on market volatility.
The stop-loss level is set at a certain multiplier of the ATR below (for long trades) or above (for short trades) the entry price.
The take-profit level is set at a larger ATR multiplier, allowing the strategy to capture larger movements.
Position Sizing with Leverage: The position size is calculated as a percentage of equity, leveraging it to maximize returns as the account balance grows.
Key Variables and Adjustable Parameters
Here are the adjustable inputs in the strategy, allowing traders to tailor it to their preferences:
Moving Averages:
Short MA Length (shortMaLength): Length of the short-term moving average (default: 14).
Long MA Length (longMaLength): Length of the long-term moving average (default: 50).
These lengths can be adjusted to make the moving average crossovers more or less sensitive.
RSI Settings:
RSI Length (rsiLength): Length of the RSI calculation (default: 14).
RSI Upper Threshold (rsiUpperThreshold): Minimum RSI value required for long trades (default: 60).
RSI Lower Threshold (rsiLowerThreshold): Maximum RSI value allowed for short trades (default: 40).
Adjusting these thresholds can help control the momentum conditions required for trades.
ATR Multipliers for Stop-Loss and Take-Profit:
ATR Stop-Loss Multiplier (atrMultiplierStopLoss): Multiplier for the ATR to set the stop-loss level (default: 1.5).
ATR Take-Profit Multiplier (atrMultiplierTakeProfit): Multiplier for the ATR to set the take-profit level (default: 3.0).
Tuning these multipliers can help in balancing risk and reward, depending on market volatility.
Bollinger Bands Settings:
Deviation (dev): The standard deviation multiplier for Bollinger Bands (default: 2).
Bollinger Bands provide a volatility filter, and this multiplier affects the width of the bands.
Position Sizing and Leverage:
Leverage (leverage): The leverage applied to the position (default: 10).
Allocation Percent (allocationPercent): The percentage of equity allocated to each trade (default: 0.1 or 10%).
Adjusting these settings can increase or decrease the position size relative to your equity, helping control risk exposure.
ViganThe Vigan is a range bound momentum oscillator. This is designed to display the advance location of the close compared to the high/low range over a user defined number of periods. Typically, this is used for three things; Identifying overbought and oversold levels, spotting divergences and also identifying bull and bear set ups or signals.
Highlight 9:15 AM to 3:30 PM ISTindian share market time. this time frame you can used with cryptotrading session, dow jones
Nami Bands with Future Projection [FXSMARTLAB]The Nami Bands ( Inspired by "Nami", meaning "wave" in Japanese) are two dynamic bands around price data: an upper band and a lower band. These bands are calculated based on an Asymmetric Linear Weighted Moving Average of price and a similarly asymmetric weighted standard deviation. This weighting method emphasizes recent data without overreacting to short-term price changes, thus smoothing the bands in line with prevailing market conditions.
Advantages and Benefits of Using the Indicator
* Volatility Analysis: The bands expand and contract with market volatility, helping traders assess periods of high and low volatility. Narrow bands indicate low volatility and potential consolidation, while wide bands suggest increased volatility and potential price movement.
* Dynamic Support and Resistance Levels: By adapting to recent trends, the bands serve as dynamic support (lower band) and resistance (upper band) levels, which traders can use for entry and exit signals.
* Overbought and Oversold Conditions: When prices reach or cross the bands’ outer limits, it may signal overbought (upper band) or oversold (lower band) conditions, suggesting possible reversals or trend slowdowns.
* Trend Confirmation and Continuation: The slope of the central moving average confirms trend direction. An upward slope generally indicates a bullish trend, while a downward slope suggests a bearish trend.
* Anticipating Breakouts and Reversals: The projected bands help identify where price movements may head, allowing traders to anticipate potential breakouts or reversals based on projected support and resistance.
Indicator Parameters
Source (src): The price data used for calculations, by default set to the average of high, low, and close (hlc3).
Length: The period over which calculations are made, defaulted to 50 periods.
Projection Length: The length for future band projection, defaulted to 20 periods.
StdDev Multiplier (mult): A multiplier for the standard deviation, defaulted to 2.0.
Internal Calculations
1. Asymmetric Linear Weighted Moving Average of Price
The indicator uses an Asymmetric Linear Weighted Moving Average (ALWMA) to calculate a central value for the price.
Asymmetric Weighting: This weighting technique assigns the highest weight to the most recent value, with weights decreasing linearly as the data points become older. This structure provides a nuanced focus on recent price trends, while still reflecting historical price levels.
2. Asymmetric Weighted Standard Deviation
The standard deviation in this indicator is also calculated using asymmetric weighting:
Purpose of Asymmetric Weighted Standard Deviation: Rather than aiming for high sensitivity to recent data, this standard deviation measure smooths out volatility by integrating weighted values across the length period, stabilizing the overall measurement of price variability.
This approach yields a balanced view of volatility, capturing broader market trends without being overly reactive to short-lived changes.
3. Upper and Lower Bands
The upper and lower bands are created by adding and subtracting the asymmetric weighted standard deviation from the asymmetric weighted average of price. This creates a dynamic envelope that adjusts to both recent price trends and the smoothed volatility measure:
These bands represent adaptable support and resistance levels that shift with recent market volatility.
Future Band Projection
The indicator provides a projection of the bands based on their current slope.
1. Calculating the Slope of the Bands
The slope for each band is derived from the difference between the current and previous values of each band.
2. Projecting the Bands into the Future
For each period into the future, up to the defined Projection Length, the bands are projected using the current slope.
This feature offers an anticipated view of where support and resistance levels may move, providing insight for future market behavior based on current trends.
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