Bidirectional Trend Reversal StrategyBidirectional Trend Reversal Strategy
This strategy aims to identify potential trend reversals and execute trades accordingly, focusing on both long and short positions. It uses a crossover of the Simple Moving Average (SMA) with price action as a key signal. When the price crosses above the SMA and the previous period was bearish (closed lower than it opened), the script opens a long position ("o-Long"). The exit ("e-Long") occurs when the target or stop-loss levels are hit, which are dynamically set using the ATR (Average True Range).
For short trades, when the price crosses below the SMA and the previous period was bullish (closed higher than it opened), the script opens a short position ("o-Short"). The exit ("e-Short") follows the same ATR-based logic for stop-loss and take-profit.
All settings, including SMA and ATR parameters, are fully customizable, allowing users to adapt the strategy to different market conditions and personal trading preferences.
This approach provides a systematic way to capture trend reversals and manage trades with clear entry and exit signals based on market momentum and volatility.
Example Setup:
Market: Forex
Pair: USD/GBP
Order size: 100,000 Contracts (1 Lot)
Timeframe: 15 minutes
SMA: 93
ATR Length: 15
Stop-Loss (ATR Multiplier): 7
Take-Profit Multiplier: 2
Experiment with different settings to achieve the best results for your trading style and market conditions.
波动率
VIX Composite MeterThe VIX Composite Meter is a custom trading indicator designed to help identify potential buy and sell signals based on market volatility, specifically through VIX options. The VIX, also known as the "fear gauge," measures market expectations of future volatility. This meter combines several factors — the VIX-to-SPX ratio, moving average deviation, Z-score, and momentum oscillators — to create a single, easy-to-read score that guides trading decisions.
How It Works
Composite Score: The meter calculates a composite score that ranges from 0 to 1 by weighing four metrics:
VIX/SPX Ratio: Indicates relative volatility compared to the S&P 500.
Moving Average Deviation: Shows how far the VIX is from its typical range.
Z-Score: Measures how extreme the current VIX value is relative to its historical average.
Momentum Oscillator (RSI): Helps identify overbought or oversold conditions in the VIX.
Color-Coded Signals:
Green Background: If the score drops below 0.3, the meter suggests buying VIX calls, indicating a low-volatility environment with potential for increase.
Red Background: If the score rises above 0.7, the meter suggests buying VIX puts, indicating a high-volatility environment likely to decrease.
Use Cases
Buy VIX Calls: When the meter turns green, signaling potential future volatility spikes.
Buy VIX Puts: When the meter turns red, suggesting current high volatility is expected to revert lower.
By using the VIX Composite Meter, traders can better time their entries and exits in VIX options, aligning with market conditions for potential profits in periods of changing volatility.
Hedge Fund D. Multiple | viResearchHedge Fund D. Multiple | viResearch
Conceptual Foundation and Innovation
The "Hedge Fund D. Multiple" indicator from viResearch is designed as a comprehensive tool for trend analysis and volatility synchronization across multiple market components. Central to this tool is the D. Multiple, a unique multiplier that simultaneously controls various moving averages, smoothing factors, and volatility measures, ensuring all components remain synchronized. By adjusting this single multiplier, traders can modify the indicator’s sensitivity and adaptability across different market conditions. This cohesive control system streamlines market analysis, making the tool highly effective in professional settings, such as hedge fund environments where swift adjustments are essential.
This indicator was developed as part of a final project study during my time working at a hedge fund, where precision, flexibility, and the ability to control multiple variables in sync were key. The D. Multiple provides a streamlined mechanism to harmonize various elements, allowing for precise yet adaptable market analysis.
Technical Composition and Calculation
The "Hedge Fund D. Multiple" script utilizes the D. Multiple to influence the behavior of several key components, including the Double Hull Moving Average (DHMA), Double Exponential Moving Average (DEMA), standard deviation, and percentile-based median. By applying the D. Multiple across these components, the script ensures that their calculations and sensitivities are synchronized, creating a unified approach to market trend and volatility analysis.
The DHMA and DEMA, which filter market noise while responding quickly to price changes, are both smoothed using lengths dictated by the D. Multiple. The DEMA's smoothing is further applied to generate a dynamic median based on percentiles, providing a clearer central value from which trend deviations are measured. This dynamic median helps traders spot significant price movements that deviate from normal market behavior, aiding in identifying trend reversals.
The D. Multiple also governs the length of the standard deviation calculations, ensuring that the volatility measurements adjust in step with the trend detection methods. This ensures that the volatility-adjusted boundaries reflect real-time market conditions, providing clear thresholds for price action. The D. Multiple controls all of these elements in sync, ensuring the system operates cohesively across trend, volatility, and smoothing components.
Features and User Inputs
The "Hedge Fund D. Multiple" script is built around the D. Multiple input, which allows traders to control the sensitivity of all components at once. By adjusting this multiplier, users can modify the behavior of the DHMA, DEMA, standard deviation ranges, and percentile-based calculations. Additionally, the script provides custom thresholds for defining trend detection and volatility boundaries, enabling traders to tailor the indicator to their specific trading strategies and market conditions.
Practical Applications
The "Hedge Fund D. Multiple" indicator is particularly valuable for professional traders and hedge fund managers who require an efficient yet powerful tool for analyzing market trends and volatility. The D. Multiple simplifies the process of adjusting multiple parameters simultaneously, giving traders greater control over their analysis. This makes the indicator especially effective for:
Adjusting Sensitivity to Market Conditions: The D. Multiple allows traders to fine-tune the entire system’s sensitivity with a single input, enabling them to switch between short-term and long-term analysis easily.
Trend Detection and Reversal Signals: The dynamic median and volatility-adjusted boundaries help provide clear signals when the market is overbought or oversold, improving the accuracy of trend reversal detection.
Managing Volatility in Sync: The D. Multiple controls the volatility measurements and ensures they are synchronized with the trend detection methods, giving traders a clearer view of the market’s risk profile and helping them time their entries and exits more effectively.
Advantages and Strategic Value
The "Hedge Fund D. Multiple" script offers significant advantages by integrating multiple layers of analysis into a single, adaptable tool. The D. Multiple reduces the complexity of adjusting various moving averages, smoothing processes, and volatility measures, offering traders increased precision and control. This synchronization of components makes the indicator a versatile tool that reacts cohesively to market conditions. Developed during a hedge fund project, this tool reflects the adaptability and precision required in professional trading environments. The ability to control multiple components through a single multiplier makes this script particularly effective for hedge fund managers and professional traders looking for a sophisticated yet manageable system for market analysis.
Alerts and Visual Cues
The script includes built-in alert conditions that notify traders when significant trend shifts occur. The "Hedge Fund D. Multiple Long" alert is triggered when an uptrend is detected, while the "Hedge Fund D. Multiple Short" alert signals a potential downtrend. Visual cues, including color changes and shaded volatility zones on the chart, help traders quickly assess market conditions and make timely decisions.
Summary and Usage Tips
The "Hedge Fund D. Multiple | viResearch" indicator provides a streamlined solution for market analysis by integrating trend detection, volatility management, and dynamic smoothing through the use of the D. Multiple. By incorporating this script into your trading strategy, you can adjust multiple components simultaneously, improving your ability to detect trend reversals and manage risk effectively. The "Hedge Fund D. Multiple" offers a powerful, customizable tool that is particularly suited to professional traders who need precision and adaptability in volatile market environments.
Note: Backtests are based on past results and are not indicative of future performance.
Bollinger Bands ForLoopBollinger Bands ForLoop
OVERVIEW
BB ForLoop is an improved version of Bollinger Bands it is designed to calculate an array of values 1 or -1 depending if soruce for calculations is above or below basis.
It takes avereage of values over a range of lengths, providing trend signals smothed based on various moving averages in order to get rid of noise.
It offers flexibility with different signal modes and visual customizations.
TYPE OF SIGNALS
-FAST (MA > MA or MA > 0.99)
-SLOW (MA > 0)
-THRESHOLD CROSSING (when cross above/below treshold set independently for both directions)
-FAST THRESHOLD (when there's change in signal by set margin e.g (0.4 -> 0.2) means bearsih when FT is set to 0.1, when MA is > 0.99 it will signal bullish, when MA < -0.99 it will signal bearish)
Generaly Lime color of line indicates Bullish, Fuchsia indicates Bearish.
This colors are not set in stone so you can change them in settings.
-Bullish Trend, line color is lime
-Bearish Trend, line color is fuchsia
Credit
Idea for this script was from one of indicators created by www.tradingview.com
Warning
Be careful when using this indicator especialy combining DEMA with FT (Fast Treshold).
This indicator can be really noisy depending on the settings, signal mode so it should be used preferably as a part of an strategy not as a stand alone indicator
Remember the lower the timeframe you use the more noise there is.
No single indicator should be used alone when making investment decisions.
EMA-BAND-PIVOT-VCPThis indicator is named "EMA-BAND-PIVOT-VCP" and integrates multiple elements such as moving averages, volume, volatility contraction patterns (VCP), pivot points, and a table to display key market metrics.
Key Features:
Moving Averages: ( 4 - EMA) default settings 20 , 50 ,144 , 200 . Can be changed in settings.
Pivot Highs and Lows:
The script detects pivot highs and pivot lows using customizable left and right lengths and plots labels to mark these points on the chart.
TIG BAND : This is setting of 2 sma - with the high and low of 90 day average which forms like a band . Its a very strong indicator of trend . Buying is suggestable above this .This has to be tested on your own to knowhow it works wonders ( price magnet). Works on all timeframes . (credit : Bhushan Sir from TIG ) .These are the best buy areas.
Volatility Contraction :
It identifies specific price contraction pattern .
vc marked - used 4 candles - first candle is the mother bar ., 2,3 and 4th candles complete range ( high to low ) is within the range of mother candle.
lc marked -here the closing is considered not the wicks. used 8 candles., the 7 candles closing is within the range of motherbar. Crosses are plotted on the last candle
Table Display:
A table is displayed on the chart with data such as EMA values, relative volume (RVol), Average Daily Range (ADR), and volume ratios. This gives a comprehensive overview of current market conditions.(RVol) compared to the 50-period volume SMA, percentage volume change, and other metrics is also displayed.
Smart Signals Assistant [AlgoAlpha]Introduction
The Smart Signals Assistant, developed by AlgoAlpha, is a robust trading tool designed to empower traders of all levels with a flexible, customizable overlay indicator. Built on proprietary logic, this tool can integrate seamlessly with other indicators or be used as a standalone tool and offers powerful market insights, enabling users to tailor their trading strategy by combining different components for unique strategies. Whether you focus on trend-following or mean-reversion strategies, the Smart Signals Assistant is optimized to support you across various market conditions.
Core Features
1. Trend Cipher Component (Trend Identification and Bar Coloring):
The Trend Cipher is the core feature of the Smart Signals Assistant. It offers an intuitive method to detect trends by displaying clear visual signals, such as arrows ("▲" for bullish trends and "▼" for bearish trends). Additionally, signal strength indications are also included where the arrows will have a '+' sign to signify a strong trend, a strong signal is determined when the volatility of prices are increasing. the candlesticks are color-coded to reflect market conditions—green for bullish, red for bearish, and gray when the market is ranging, ranging markets are marked when the prices end up retracing in the opposite direction after a signal is sent, indicating that buyers/sellers are not ready to continue the trend yet. These added layers of confluence allows users to judge if signals provided by the Trend Cipher are high probability signals.
- Exit Signals : "X" marks indicate potential take-profit points when momentum is waning. Users can set a maximum number of exit signals, allowing for greater control over trade management and predictable exit strategies.
- Customization : Users can adjust the period length for the Trend Cipher to suit different market conditions and strategies. For example, a shorter period is more sensitive and responsive to quick shifts in trends, while a longer period offers more stable signals for long-term traders.(longer periods shown below)
2. Trend Bias Component (Long-term Trend Filter and Confirmation):
The Trend Bias acts as a trend confirmation tool. It comes in the form of a smooth band that reflects the central tendency of price movements. It provides a more comprehensive view of whether the price is trend up or down, as well as whether the price is trending strongly or not. It does so by checking if the current momentum of price is stronger relative to the average momentum over a period of time.
As mentioned earlier, the Trend Bias can also act as a marker of central tendency, meaning that users can use the Trend Bias as a dynamic take-profit zone when executing reversal trades.
- When aligned with the Trend Cipher, the Trend Bias helps traders differentiate between strong and weak trends. Bright colors signify a robust trend, while subdued colors signal weakening momentum. This helps users avoid false signals and enter high-probability trades.
3. Fair Value Trail (Entry Optimization):
The Fair Value Trail is a zone-based component that helps users capture optimal entry points, such as when the market is overbought or oversold. By waiting for price retracements into the Fair Value Trail, traders can achieve better pricing and potentially maximize their profits. The Fair Value Trail is unique in the sense that it dynamically adjusts its width according to the market volatility so that the optimal entry area remains as relevant.
- This feature works in conjunction with the Trend Cipher by allowing users to wait for retracement before entering the trade, thus improving their risk-reward ratio.
4. Trend Spine (Range Detection and Filter):
The Trend Spine helps identify periods of price consolidation by flattening the price action into a rigid line. This helps traders avoid entering trades in choppy or directionless markets. The Trend Spine’s values remain unchanged during consolidations, alerting users when to refrain from trading due to a lack of trend direction.
- This feature integrates with other components, providing clearer signals for trading in trending markets while filtering out trades in ranging or consolidating markets.
5. Firmament Cloud (Reversal Zones):
The Firmament Cloud defines zones on the price chart that are considered extreme, indicating overbought or oversold conditions. Price reaching these zones suggests potential reversal points, giving traders additional confirmation to enter or exit trades. The separation of the upper and lower clouds as well of the width of each respective cloud are dynamically adjusted based on the aggressiveness of price movements coupled with user defined settings for some base parameters such as multipliers for separation and width.
- This component works well for traders using a mean-reversion strategy or those looking for early exits during overextended price movements.
Usage and Customization
The Smart Signals Assistant offers a flexible interface, making it simple to adjust settings such as indicator lengths, noise reduction factors, and display options. Key components, such as the Trend Cipher, Trend Bias, and Fair Value Trail, are highly customizable, allowing traders to create a unique trading system tailored to their specific needs. Tooltips accompany most inputs to help users quickly understand how to adjust the tool effectively.
Combining Components for Synergy
1. Trend Cipher and Trend Bias:
By combining the Trend Cipher with the Trend Bias, users receive both short-term and long-term trend confirmations. A bullish signal from the Trend Cipher, when aligned with an upward-trending Trend Bias, significantly enhances the likelihood of a profitable trade, minimizing the chances of acting on premature signals.
2. Fair Value Trail for Entry Optimization:
Rather than immediately acting on a Trend Cipher signal, users can wait for the price to enter the Fair Value Trail. This strategy ensures better entries at premium or discounted prices, maximizing potential returns.
3. Trend Spine for Range Detection:
The Trend Spine works alongside the Trend Cipher to keep traders out of consolidating markets. When the Trend Spine remains flat, it signals a ranging market, advising users to avoid trades during such periods.
4. Firmament Cloud for Reversal Points:
The Firmament Cloud identifies extreme market conditions, marking zones where traders should be cautious about entering trades. When combined with Trend Cipher signals, this component helps users pinpoint overbought or oversold markets, allowing for strategic entries and exits.
Conclusion
The Smart Signals Assistant is more than just a collection of individual indicators. It offers a comprehensive, multi-layered system that provides a deeper understanding of market dynamics, ranging from trend detection to reversal opportunities. The flexibility in customizing its various components allows traders to craft a strategy suited to their style, whether they prefer trend-following or mean-reversion methods. With this tool, traders can enhance decision-making, optimize entries and exits, and navigate both trending and ranging markets more effectively.
Dynamic ALMA with signalsEnhanced ALMA with Signals
This TradingView indicator is designed to enhance your trading strategy by utilizing the Arnaud Legoux Moving Average (ALMA), a unique moving average that provides smoother price action while minimizing lag. The script not only plots the ALMA line but also dynamically adjusts its parameters based on market volatility to adapt to different trading conditions. Additionally, it highlights potential bounce points off the line, as well as breakout points, giving traders clear signals for potential support, resistance levels, and breakouts.
Key Features:
Dynamic ALMA Line with Glow Effect:
The core of this indicator is the ALMA line, which is dynamically adjusted to market volatility, providing more accurate signals in varying conditions. The line adapts to both trending and consolidating markets by adjusting its sensitivity in real time. A glow effect is created by plotting the ALMA line multiple times with increasing transparency, making it visually distinct.
Bounce Detection Signals with Volatility Filter:
The script detects and labels potential support and resistance bounces based on the crossover and crossunder of the price with the ALMA line, further filtered by a volatility condition. This helps in filtering out false signals during low-volatility conditions, making the signals more reliable.
Visual Enhancements:
Custom glow effects and labels for bounce detection enhance chart readability and help traders quickly identify key levels.
Inputs:
Base Window Size: Sets the number of bars used in calculating the ALMA, allowing traders to adjust the sensitivity of the moving average. This parameter is dynamically adjusted based on current market volatility.
Offset: Determines the position of the ALMA curve. Higher values move the curve further away from the price. This value remains constant for stability.
Sigma: Controls the smoothness of the ALMA curve; a higher sigma results in a smoother curve. This value also remains constant.
ATR Period and Threshold Multiplier: Used to calculate the Average True Range (ATR) for the volatility filter, which determines whether the market conditions are sufficiently volatile to consider bounce signals.
How It Works:
Dynamic ALMA Calculation:
The script calculates the ALMA (Arnaud Legoux Moving Average) using the ta.alma function, dynamically adjusting the window size based on market volatility measured by the ATR (Average True Range). This ensures that the ALMA line remains responsive in high-volatility environments and smooth in low-volatility conditions.
Glow Effect:
To create a glow effect around the ALMA line, the script plots the ALMA multiple times with varying degrees of transparency. This visual enhancement helps the ALMA line stand out on the chart.
Bounce Detection with Volatility Filter:
The script uses two conditions to detect potential bounces:
Support Bounce: Detected when the low of the bar crosses above the ALMA line (ta.crossover(low, alma)) and the close is above the ALMA, while the volatility filter confirms sufficient market activity. This suggests potential support at the ALMA line.
Resistance Bounce: Detected when the high of the bar crosses below the ALMA line (ta.crossunder(high, alma)) and the close is below the ALMA, while the volatility filter confirms sufficient market activity. This indicates potential resistance at the ALMA line.
Labeling Bounce Points:
When a bounce is detected, the script labels it on the chart:
Support Bounces (S): Labeled with a blue "S" below the bar where a support bounce is detected.
Resistance Bounces (R): Labeled with a white "R" above the bar where a resistance bounce is detected.
Usage:
This enhanced indicator helps traders visualize key support and resistance levels more effectively by dynamically adjusting the ALMA moving average to market conditions. By detecting and labeling potential bounce points and filtering these signals based on volatility, traders can better identify entry and exit points in their trading strategy. The dynamic adjustments and visual enhancements make it easier to spot critical levels quickly and adapt to changing market conditions.
Customize the inputs to fit your trading style, and use this enhanced ALMA indicator to gain a more refined understanding of market trends, potential reversals, and breakouts.
[ROC3] Rate of Change Candle ColorROC is a statistical indicator which tracks how much a security's price has changed over a certain period, showing whether momentum is picking up or slowing down. It’s a handy tool because it helps traders spot trend changes and understand how strong a trend is.
My ROC3 indicator will color the candlesticks based on the Rate of Change (ROC) and its Exponential Moving Average (EMA). This indicator helps traders visually identify bullish and bearish trends by applying color to the candles, making it easier to spot momentum shifts and trend changes.
How It Works:
Rate of Change (ROC): Calculates the percentage change in the price over a specified number of bars. This indicator measures the speed at which price changes.
EMA of ROC: Applies an Exponential Moving Average to the ROC values to provide a smoothed benchmark. The EMA helps to reduce noise and make trend identification more reliable.
Coloring Logic:
Bullish Candles (Green): When the current ROC is higher than the EMA of the ROC.
Bearish Candles (Red): When the current ROC is lower than the EMA of the ROC.
Settings:
ROC Length (Default: 60): The number of bars used to calculate the Rate of Change. Adjust this parameter to change the sensitivity of the ROC calculation.
ROC EMA Length (Default: 7): The number of bars used to calculate the Exponential Moving Average of the ROC. This length determines how smooth the EMA is. A shorter length reacts faster to price changes, while a longer length provides a smoother, slower response.
How to Use:
Apply the Indicator: Add the Rate of Change Candle Color indicator to your TradingView chart.
Interpret the Colors:
Green Candles: Indicate bullish momentum. The current ROC is greater than its EMA, suggesting upward pressure.
Red Candles: Indicate bearish momentum. The current ROC is less than its EMA, suggesting downward pressure.
Adjust Settings: Customize the ROC Length and ROC EMA Length based on your trading strategy. Shorter ROC lengths may capture more short-term trends, while longer lengths provide a broader view.
Combine with Other Indicators: Use the in conjunction with other technical indicators or chart patterns to enhance your trading analysis.
Example Use Case:
Trend Confirmation: Use the color changes to confirm bullish or bearish trends. Green candles can confirm uptrends, while red candles may signal downtrends or potential reversals.
Momentum Analysis: Monitor how frequently the ROC crosses above or below its EMA to gauge momentum strength and make informed trading decisions.
Note:
This indicator is designed to assist with trend analysis and should be used as part of a broader trading strategy. Always conduct your own research and analysis before making trading decisions.
Cherio...
Sinc Bollinger BandsKaiser Windowed Sinc Bollinger Bands Indicator
The Kaiser Windowed Sinc Bollinger Bands indicator combines the advanced filtering capabilities of the Kaiser Windowed Sinc Moving Average with the volatility measurement of Bollinger Bands. This indicator represents a sophisticated approach to trend identification and volatility analysis in financial markets.
Core Components
At the heart of this indicator is the Kaiser Windowed Sinc Moving Average, which utilizes the sinc function as an ideal low-pass filter, windowed by the Kaiser function. This combination allows for precise control over the frequency response of the moving average, effectively separating trend from noise in price data.
The sinc function, representing an ideal low-pass filter, provides the foundation for the moving average calculation. By using the sinc function, analysts can independently control two critical parameters: the cutoff frequency and the number of samples used. The cutoff frequency determines which price movements are considered significant (low frequency) and which are treated as noise (high frequency). The number of samples influences the filter's accuracy and steepness, allowing for a more precise approximation of the ideal low-pass filter without altering its fundamental frequency response characteristics.
The Kaiser window is applied to the sinc function to create a practical, finite-length filter while minimizing unwanted oscillations in the frequency domain. The alpha parameter of the Kaiser window allows users to fine-tune the trade-off between the main-lobe width and side-lobe levels in the frequency response.
Bollinger Bands Implementation
Building upon the Kaiser Windowed Sinc Moving Average, this indicator adds Bollinger Bands to provide a measure of price volatility. The bands are calculated by adding and subtracting a multiple of the standard deviation from the moving average.
Advanced Centered Standard Deviation Calculation
A unique feature of this indicator is its specialized standard deviation calculation for the centered mode. This method employs the Kaiser window to create a smooth deviation that serves as an highly effective envelope, even though it's always based on past data.
The centered standard deviation calculation works as follows:
It determines the effective sample size of the Kaiser window.
The window size is then adjusted to reflect the target sample size.
The source data is offset in the calculation to allow for proper centering.
This approach results in a highly accurate and smooth volatility estimation. The centered standard deviation provides a more refined and responsive measure of price volatility compared to traditional methods, particularly useful for historical analysis and backtesting.
Operational Modes
The indicator offers two operational modes:
Non-Centered (Real-time) Mode: Uses half of the windowed sinc function and a traditional standard deviation calculation. This mode is suitable for real-time analysis and current market conditions.
Centered Mode: Utilizes the full windowed sinc function and the specialized Kaiser window-based standard deviation calculation. While this mode introduces a delay, it offers the most accurate trend and volatility identification for historical analysis.
Customizable Parameters
The Kaiser Windowed Sinc Bollinger Bands indicator provides several key parameters for customization:
Cutoff: Controls the filter's cutoff frequency, determining the divide between trends and noise.
Number of Samples: Sets the number of samples used in the FIR filter calculation, affecting the filter's accuracy and computational complexity.
Alpha: Influences the shape of the Kaiser window, allowing for fine-tuning of the filter's frequency response characteristics.
Standard Deviation Length: Determines the period over which volatility is calculated.
Multiplier: Sets the number of standard deviations used for the Bollinger Bands.
Centered Alpha: Specific to the centered mode, this parameter affects the Kaiser window used in the specialized standard deviation calculation.
Visualization Features
To enhance the analytical value of the indicator, several visualization options are included:
Gradient Coloring: Offers a range of color schemes to represent trend direction and strength for the moving average line.
Glow Effect: An optional visual enhancement for improved line visibility.
Background Fill: Highlights the area between the Bollinger Bands, aiding in volatility visualization.
Applications in Technical Analysis
The Kaiser Windowed Sinc Bollinger Bands indicator is particularly useful for:
Precise trend identification with reduced noise influence
Advanced volatility analysis, especially in the centered mode
Identifying potential overbought and oversold conditions
Recognizing periods of price consolidation and potential breakouts
Compared to traditional Bollinger Bands, this indicator offers superior frequency response characteristics in its moving average and a more refined volatility measurement, especially in centered mode. These features allow for a more nuanced analysis of price trends and volatility patterns across various market conditions and timeframes.
Conclusion
The Kaiser Windowed Sinc Bollinger Bands indicator represents a significant advancement in technical analysis tools. By combining the ideal low-pass filter characteristics of the sinc function, the practical benefits of Kaiser windowing, and an innovative approach to volatility measurement, this indicator provides traders and analysts with a sophisticated instrument for examining price trends and market volatility.
Its implementation in Pine Script contributes to the TradingView community by making advanced signal processing and statistical techniques accessible for experimentation and further development in technical analysis. This indicator serves not only as a practical tool for market analysis but also as an educational resource for those interested in the intersection of signal processing, statistics, and financial markets.
Related:
Sma Standard Deviation | viResearchSma Standard Deviation | viResearch
Conceptual Foundation and Innovation
The "Sma Standard Deviation" indicator from viResearch combines the benefits of Simple Moving Average (SMA) smoothing with Standard Deviation (SD) analysis, offering traders a powerful tool for understanding price trends and volatility. The SMA provides a straightforward approach to trend detection by calculating the average price over a defined period, while the SD component adds insight into the market's volatility by measuring the variation of prices around the SMA. This combination helps traders identify whether the price is moving within a typical range or deviating significantly, which can signal potential trend shifts or periods of increased volatility. By using both SMA and SD together, this indicator enhances the trader's ability to detect not only the trend direction but also how strongly the market is deviating from that trend, offering more informed decision-making.
Technical Composition and Calculation
The "Sma Standard Deviation" script uses two key elements: the Simple Moving Average (SMA) and Standard Deviation (SD). The SMA is calculated over a user-defined length and represents the smoothed average price over this period. The script also incorporates DEMA smoothing applied to different price sources, providing further refinement to the trend analysis. The SD is calculated by measuring the deviation of the price from the SMA over a separate user-defined length, showing how volatile the price is relative to its average. The script generates upper and lower SD boundaries by adding and subtracting the SD from the SMA, creating a volatility-adjusted range for the price. This allows traders to visualize whether the price is moving within expected bounds or breaking out of its typical range. The script monitors crossovers between the DEMA, SMA, and SD boundaries, generating trend signals based on these interactions.
Features and User Inputs
The "Sma Standard Deviation" script offers several customizable inputs, allowing traders to adjust the indicator to their specific strategies. The SMA Length controls the period for which the moving average is calculated, while the SD Length defines how long the period is for measuring price deviation. Additionally, the DEMA smoothing length can be adjusted for both the trend and standard deviation calculations, giving traders control over how responsive or smooth they want the indicator to be. The script also includes alert conditions that notify traders when trend shifts occur, either to the upside or downside.
Practical Applications
The "Sma Standard Deviation" indicator is designed for traders who want to analyze both market trends and volatility in a unified tool. The combination of the SMA and SD helps traders identify potential trend reversals, as large deviations from the SMA can indicate periods of increased volatility that precede significant price moves. This makes the indicator particularly effective for identifying trend reversals, managing volatility, and improving trend-following strategies. By analyzing when the price moves outside the volatility-adjusted range defined by the SD, traders can detect early signals of potential trend reversals. The SD component helps traders understand how volatile the market is relative to its average price, allowing for more informed decisions in both trending and volatile market conditions. The dual use of DEMA and SMA smoothing allows for a clearer trend signal, helping traders stay aligned with the prevailing market direction while managing the noise caused by short-term volatility.
Advantages and Strategic Value
The "Sma Standard Deviation" script offers significant value by integrating both trend detection and volatility analysis into a single tool. The use of SMA for smoothing price trends, combined with the SD for assessing price volatility, provides a more comprehensive view of the market. This dual approach helps traders filter out false signals caused by short-term fluctuations while identifying potential trend changes driven by increased volatility. This makes the "Sma Standard Deviation" indicator ideal for traders seeking a balance between trend-following and volatility management.
Alerts and Visual Cues
The script includes alert conditions that notify traders when significant trend shifts occur based on price crossovers with the SMA and SD boundaries. The "Sma Standard Deviation Long" alert is triggered when the price crosses above the upper volatility boundary, indicating a potential upward trend. Conversely, the "Sma Standard Deviation Short" alert signals a possible downward trend when the price crosses below the lower boundary. Visual cues, such as changes in the color of the SMA line, help traders quickly identify trend shifts and act accordingly.
Summary and Usage Tips
The "Sma Standard Deviation | viResearch" indicator provides traders with a robust tool for analyzing market trends and volatility. By combining the benefits of SMA smoothing with SD analysis, this script offers a comprehensive approach to detecting trend changes and managing risk. Incorporating this indicator into your trading strategy can help improve your ability to spot trend reversals, understand market volatility, and stay aligned with the broader market direction. The "Sma Standard Deviation" is a reliable and customizable solution for traders looking to enhance their technical analysis in both trending and volatile markets.
Note: Backtests are based on past results and are not indicative of future performance.
[DarkTrader] Strong High LowThe Strong High Low indicator calculates strong high and low pivots based on price action and the Average True Range (ATR). The calculation for both the high and low pivots involves analyzing recent candle behavior to identify significant levels where price reversal is likely. Specifically, it looks for consecutive bearish or bullish candles to determine whether a strong high or low has been established.
Indicator In Use :
For strong highs, the indicator checks if three consecutive candles are bearish, meaning their closing price is lower than their opening price. It further examines prior candles to confirm that they followed a specific pattern where a reversal could occur. If one of these earlier candles closed higher than it opened, the indicator assumes that this was a strong high, and it records either the high of the second or third candle from the pattern, depending on their relationship to each other.
Similarly, for strong lows, the indicator searches for three consecutive bullish candles where the close is higher than the open. The algorithm then reviews prior candles in the sequence to ensure that the market condition supports a potential low pivot. If an earlier candle closes lower than it opens, it marks this as a strong low. The final low point for the pivot is chosen based on a comparison between the second and third candles of the pattern.
Once the high and low pivots are determined, the indicator adjusts these levels using the ATR value. The ATR is added to the strong high pivot and subtracted from the strong low pivot to create slightly modified levels. This helps accommodate market volatility by widening the range of the high and low pivots, making the levels more reliable in reflecting potential reversal zones.
Finally, the strong high and low pivot lines are drawn on the chart, extending both to the left and right of the current price, based on the user-defined offset values. These lines give a visual cue of where key resistance and support levels exist, with labels marking the exact pivot values for easy reference.
Volume Adjusted CandlesTraditional candlestick charts are invaluable for visualizing price movements over time. However, they often lack an explicit representation of trading volume, a key factor that can significantly influence price action. Our Volume Adjusted Candles Indicator fills this gap by incorporating volume directly into the candlesticks, allowing for a more comprehensive analysis.
How Candles are Calculated
Each candlestick in this indicator is adjusted based on the volume of trades that occurred during its timeframe. The process involves segmenting the price range of the trading session into equal parts, known as 'bins'. Each bin represents a segment of the price range, and the volume of trades within each bin influences the final shape and position of the candlestick.
The Formula: The volume adjusted position of each part of the candle (high, low, and close) is calculated using a weighted average formula where each price point is weighted by the volume of trades at that price. This results in a volume-weighted price for each segment of the candle, making it easy to see where the most trading activity occurred and how it impacted price movements.
Gaussian Acceleration ArrayIndicators play a role in analyzing price action, trends, and potential reversals. Among many of these, velocity and acceleration have held a significant place due to their ability to provide insight into momentum and rate of change. This indicator takes the old calculation and tweaks it with gaussian smoothing and logarithmic function to ensure proper scaling.
A Brief on Velocity and Acceleration: The concept of velocity in trading refers to the speed at which price changes over time, while acceleration is the rate of change(ROC) of velocity. Early momentum indicators like the RSI and MACD laid foundation for understanding price velocity. However, as markets evolve so do we as technical analysts, we seek the most advanced tools.
The Acceleration/Deceleration Oscillator, introduced by Bill Williams, was one of the early attempts to measure acceleration. It helped gauge whether the market was gaining or losing momentum. Over time more specific tools like the "Awesome Oscillator"(AO) emerged, which has a set length on the datasets measured.
Gaussian Functions: Named after the mathematician Carl Friedrich Gauss, the Gaussian function describes a bell-shaped curve, often referred to as the "normal distribution." In trading these functions are applied to smooth data and reduce noise, focusing on underlying patterns.
The Gaussian Acceleration Array leverages this function to create a smoothed representation of market acceleration.
How does it work?
This indicator calculates acceleration based the highs and lows of each dataset
Once the weighted average for velocity is determined, its rate of change essentially becomes the acceleration
It then plots multiple lines with customizable variance from the primary selected length
Practical Tips:
The Gaussian Acceleration Array offers various customizable parameters, including the sample period, smoothing function, and array variance. Experiment with these settings to tailor it to preferred timeframes and styles.
The color-coded lines and background zones make it easier to interpret the indicator at a glance. The backgrounds indicate increasing or decreasing momentum simply as a visual aid while the lines state how the velocity average is performing. Combining this with other tools can signal shifts in market dynamics.
Super Trend ReversalsMain Concept
The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, but just before it shifts direction based on the triggered Supertrend signals. This approach helps traders engage with the market right as the reversal momentum builds up, allowing for entry just as conditions become favorable and exit before momentum wanes.
How It Works
The Super Trend Reversals uses multiple Supertrend calculations, each with different period and multiplier settings, to form a comprehensive view of the trend. The total trend score from these calculations is then analyzed using the Relative Strength Index (RSI) and Exponential Moving Averages (EMA) to gauge the strength and sustainability of the trend.
A key feature of this indicator is the isCurrentRangeSmaller() function, which evaluates if the current price range is lower than the average over the recent period. This function is critical as it helps determine the stability of the market environment, reducing the likelihood of entering or exiting trades based on erratic price movements that could lead to false signals.
ATR+Order Block IndicatorThe ATR+Order Block Indicator is a unique and comprehensive tool designed to combine volatility-based analysis with key price action levels to provide traders with reliable entry and exit points. This indicator merges the Average True Range (ATR) for dynamic trailing stop calculation with order block detection to identify significant support and resistance zones on the chart. This combination offers traders a powerful blend of trend-following and price level analysis for improved trading decisions.
How the Components Work Together:
1. ATR-Based Trailing Stop:
• The Average True Range (ATR) is a widely used volatility indicator that measures the degree of price movement over a specified period. In this indicator, the ATR is used to create a trailing stop that dynamically adjusts to market conditions.
• How It Works: The ATR value is multiplied by a user-defined multiplier (ATR Multiplier) to set the distance of the trailing stop from the current price. This trailing stop moves with the price:
• If the price moves upwards, the trailing stop adjusts higher, ensuring it only moves in the direction of the trade.
• If the price moves downwards, the trailing stop adjusts lower accordingly.
• Purpose: This trailing stop helps traders manage risk by automatically adjusting to market volatility, ensuring that stops are not too tight in volatile conditions or too wide in quieter markets. It also helps lock in profits while maintaining a position in the market’s direction.
2. Order Block Detection:
• Order blocks are areas on the chart where significant buying (accumulation) or selling (distribution) has occurred. These zones often act as potential support or resistance levels due to the presence of unfilled buy or sell orders by large institutions or traders.
• How It Works: The indicator identifies the highest high (seller order block) and the lowest low (buyer order block) within a user-defined lookback period. These are plotted on the chart:
• Buyer Order Block: Represents a potential support area where buying interest is likely to reappear.
• Seller Order Block: Represents a potential resistance area where selling interest may reemerge.
• Purpose: By identifying these order blocks, traders can anticipate potential price reversals or continuations, aligning their trades with key market levels where significant buying or selling has occurred.
Justification for Combining These Components:
1. Enhanced Signal Accuracy and Context:
• The combination of ATR-based trailing stops with order block detection provides a dual-layered approach to trade decisions:
• ATR Trailing Stop offers trend-following signals based on volatility, helping traders capture market momentum.
• Order Blocks provide context to these signals by highlighting critical price levels where market participants have previously shown strong interest.
• This fusion allows traders to filter signals more effectively, ensuring trades are aligned with both market trends and key support/resistance zones.
2. Dynamic Risk Management:
• Using the ATR to set a dynamic trailing stop ensures that the stop-loss level adapts to the changing volatility of the market. When combined with order block detection, traders gain an additional layer of risk management:
• Stop Loss Placement: Traders can place stops just outside identified order blocks to protect against sudden price reversals while maintaining a tight stop aligned with current market volatility.
3. Reducing Market Noise and Avoiding False Signals:
• The indicator includes a mechanism to avoid repetitive signals, requiring a minimum gap between signals. This reduces noise and helps traders avoid multiple false entries in choppy market conditions.
• Order Blocks provide additional validation: For example, a buy signal generated near a Buyer Order Block carries more weight, as it aligns both with the ATR-based momentum and a key support area.
4. Improving Entry and Exit Strategies:
• Entry Points: The indicator generates buy (long) signals when the price crosses above the ATR trailing stop and sell (short) signals when it crosses below. These signals are enhanced by considering their proximity to order blocks, ensuring trades are initiated at strategic price levels.
• Exit Points: The ATR trailing stop provides a dynamic exit strategy, allowing trades to run while adjusting to market volatility. Traders can also use order blocks as targets or potential reversal points to exit trades.
5. Providing a Comprehensive Trading Tool:
• This indicator is unique in its integration of volatility and price level analysis, offering a well-rounded approach to trading. It combines the best of both worlds: trend-following momentum with the ATR and price action sensitivity through order blocks, making it suitable for different market conditions and trading styles.
How to Use the Indicator:
• Set the Parameters:
• Choose an ATR Period (default is 10) to define the number of bars for ATR calculation.
• Set the ATR Multiplier (default is 1.5) to adjust the sensitivity of the trailing stop.
• Define the Order Block Lookback Period (default is 20) to determine how many bars back the script will search for order blocks. Recommended 50.
• Interpret the Signals:
• BUY Signal: When the price crosses above the ATR trailing stop, indicating upward momentum. Confirm this signal by checking if it is near a Buyer Order Block.
• SELL Signal: When the price crosses below the ATR trailing stop, indicating downward momentum. Look for proximity to a Seller Order Block for added confidence.
• Monitor and Manage Trades:
• Use the ATR trailing stop for dynamic stop-loss placement.
• Watch for price action around the order blocks to make informed decisions about taking profits or cutting losses.
Conclusion:
The ATR+Order Block Indicator combines volatility and price action analysis in a unique way that offers traders a comprehensive tool for making informed trading decisions. By leveraging the strengths of both ATR-based dynamic stops and order block detection, it provides a balanced approach to trend-following and support/resistance trading, enhancing overall trading effectiveness and confidence.
Rempi Volume
Greetings, dear traders. I present to your attention the concept of a Rempi Volume indicator + info table.
Rempi Volume displays volume in a color palette, where:
gray color - very weak volume,
blue color - weak volume,
green color - normal volume,
orange color - high volume,
red color - very high volume,
purple color - ultra high volume
The indicator also supports the function of displaying a moving average, the default is 20.
The indicator can color bars on the main price chart, depending on how much volume is currently inside the bar.
The Rempi Volume indicator table has the following information for the trader:
Current Bar -information about the current bar: its volume in real time, as well as the percentage of buyers and sellers.
Previous Bar - information about the previous bar: its volume, as well as the percentage of buyers and sellers. (data is updated at bar close)
10 Bar Volume Comparison - data on the volume of buyers or sellers for the previous 10 bars on the chart.
Volume Change - changing the amount of volume between the current and previous bar, in real time.
Average Volume - average trading volume for the current day.
Market Volatility - market volatility and recommendations.
Current Trend - current trend on the market.
RSI - RSI indicator and recommendations.
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Приветствую вас уважаемые трейдеры. Вашему вниманию представляю концепт индикатора объемов Rempi Volume + информативная таблица.
Rempi Volume отображает объем в цветовой палитре , где:
серый цвет - очень слабый объем,
голубой цвет - слабый объем,
зеленый цвет - нормальный объем,
оранжевый цвет - высокий объем,
красный цвет - очень высокий объем,
фиолетовый цвет - ультра высокий объем
Также индикатор поддерживает функцию отображения скользящей средней, по умолчанию равна 20.
Индикатор может окрашивать бары на основном графике цены, в зависимости ,какой объем в данный момент внутри бара.
Таблица индикатора Rempi Volume имеет следующую информацию для трейдера:
Current Bar - информация о текущем баре: его объем в режиме реального времени, а также процентное соотношение покупателей и продавцов.
Previous Bar - информация о предыдущем баре: его объем , а также процентное соотношение покупателей и продавцов. ( данные обновляются на закрытии бара )
10 Bar Volume Comparison - данные об объеме покупателей или продавцов за предыдущие 10 баров на графике.
Volume Change - изменение количества объема между текущим и предыдущим баром,в режиме реального времени.
Average Volume - средний объем торгов за текущий день.
Market Volatility - волатильность рынка и рекомендации.
Current Trend - текущее направление рынка.
RSI - показатель RSI и рекомендации.
Uptrick: Momentum-Volatility Composite Signal### Title: Uptrick: Momentum-Volatility Composite Signal
### Overview
The "Uptrick: Momentum-Volatility Composite Signal" is an innovative trading tool designed to offer traders a sophisticated synthesis of momentum, volatility, volume flow, and trend detection into a single comprehensive indicator. This tool stands out by providing an integrated view of market dynamics, which is critical for identifying potential trading opportunities with greater precision and confidence. Its unique approach differentiates it from traditional indicators available on the TradingView platform, making it a valuable asset for traders aiming to enhance their market analysis.
### Unique Features
This indicator integrates multiple crucial elements of market behavior:
- Momentum Analysis : Utilizes Rate of Change (ROC) metrics to assess the speed and strength of market movements.
- Volatility Tracking : Incorporates Average True Range (ATR) metrics to measure market volatility, aiding in risk assessment.
- Volume Flow Analysis : Analyzes shifts in volume to detect buying or selling pressure, adding depth to market understanding.
- Trend Detection : Uses the difference between short-term and long-term Exponential Moving Averages (EMA) to detect market trends, providing insights into potential reversals or confirmations.
Customization and Inputs
The Uptrick indicator offers a variety of user-defined settings tailored to fit different trading styles and strategies, enhancing its adaptability across various market conditions:
Rate of Change Length (rocLength) : This setting defines the period over which momentum is calculated. Shorter periods may be preferred by day traders who need to respond quickly to market changes, while longer periods could be better suited for position traders looking at more extended trends.
ATR Length (atrLength) : Adjusts the timeframe for assessing volatility. A shorter ATR length can help day traders manage the quick shifts in market volatility, whereas longer lengths might be more applicable for swing or position traders who deal with longer-term market movements.
Volume Flow Length (volumeFlowLength): Determines the analysis period for volume flow to identify buying or selling pressure. Day traders might opt for shorter periods to catch rapid volume changes, while longer periods could serve swing traders to understand the accumulation or distribution phases better.
Short EMA Length (shortEmaLength): Specifies the period for the short-term EMA, crucial for trend detection. Shorter lengths can aid day traders in spotting immediate trend shifts, whereas longer lengths might help swing traders in identifying more sustainable trend changes.
Long EMA Length (longEmaLength): Sets the period for the long-term EMA, which is useful for observing longer-term market trends. This setting is particularly valuable for position traders who need to align with the broader market direction.
Composite Signal Moving Average Length (maLength): This parameter sets the smoothing period for the composite signal's moving average, helping to reduce noise in the signal output. A shorter moving average length can be beneficial for day traders reacting to market conditions swiftly, while a longer length might help swing and position traders in smoothing out less significant fluctuations to focus on significant trends.
These customization options ensure that traders can fine-tune the Uptrick indicator to their specific trading needs, whether they are scanning for quick opportunities or analyzing more prolonged market trends.
### Functionality Details
The indicator operates through a sophisticated algorithm that integrates multiple market dimensions:
1. Momentum and Volatility Calculation : Combines ROC and ATR to gauge the market’s momentum and stability.
2. Volume and Trend Analysis : Integrates volume data with EMAs to provide a comprehensive view of current market trends and potential shifts.
3. Signal Composite : Each component is normalized and combined into a composite signal, offering traders a nuanced perspective on when to enter or exit trades.
The indicator performs its calculations as follows:
Momentum and Volatility Calculation:
roc = ta.roc(close, rocLength)
atr = ta.atr(atrLength)
Volume and Trend Analysis:
volumeFlow = ta.cum(volume) - ta.ema(ta.cum(volume), volumeFlowLength)
emaShort = ta.ema(close, shortEmaLength)
emaLong = ta.ema(close, longEmaLength)
emaDifference = emaShort - emaLong
Composite Signal Calculation:
Normalizes each component (ROC, ATR, volume flow, EMA difference) and combines them into a composite signal:
rocNorm = (roc - ta.sma(roc, rocLength)) / ta.stdev(roc, rocLength)
atrNorm = (atr - ta.sma(atr, atrLength)) / ta.stdev(atr, atrLength)
volumeFlowNorm = (volumeFlow - ta.sma(volumeFlow, volumeFlowLength)) / ta.stdev(volumeFlow, volumeFlowLength)
emaDiffNorm = (emaDifference - ta.sma(emaDifference, longEmaLength)) / ta.stdev(emaDifference, longEmaLength)
compositeSignal = (rocNorm + atrNorm + volumeFlowNorm + emaDiffNorm) / 4
### Originality
The originality of the Uptrick indicator lies in its ability to merge diverse market metrics into a unified signal. This multi-faceted approach goes beyond traditional indicators by offering a deeper, more holistic analysis of market conditions, providing traders with insights that are not only based on price movements but also on underlying market dynamics.
### Practical Application
The Uptrick indicator excels in environments where understanding the interplay between volume, momentum, and volatility is crucial. It is especially useful for:
- Day Traders : Can leverage real-time data to make quick decisions based on sudden market changes.
- Swing Traders : Benefit from understanding medium-term trends to optimize entry and exit points.
- Position Traders : Utilize long-term market trend data to align with overall market movements.
### Best Practices
To maximize the effectiveness of the Uptrick indicator, consider the following:
- Combine with Other Indicators : Use alongside other technical tools like RSI or MACD for additional validation.
- Adapt Settings to Market Conditions : Adjust the indicator settings based on the asset and market volatility to improve signal accuracy.
- Risk Management : Implement robust risk management strategies, including setting stop-loss orders based on the volatility measured by the ATR.
### Practical Examples and Demonstrations
- Example for Day Trading : In a volatile market, a trader notices a sharp increase in the momentum score coinciding with a surge in volume but stable volatility, signaling a potential bullish breakout.
- Example for Swing Trading : On a 4-hour chart, the indicator shows a gradual alignment of decreasing volatility and increasing buying volume, suggesting a strengthening upward trend suitable for a long position.
### Alerts and Their Uses
- Alert Configurations : Set alerts for when the composite score crosses predefined thresholds to capture potential buy or sell events.
- Strategic Application : Use alerts to stay informed of significant market moves without the need to continuously monitor the markets, enabling timely and informed trading decisions.
Technical Notes
Efficiency and Compatibility: The indicator is designed for efficiency, running smoothly across different trading platforms including TradingView, and can be easily integrated with existing trading setups. It leverages advanced mathematical models for normalizing and smoothing data, ensuring consistent and reliable signal quality across different market conditions.
Limitations : The effectiveness of the Uptrick indicator can vary significantly across different market conditions and asset classes. It is designed to perform best in liquid markets where data on volume, volatility, and price trends are readily available and reliable. Traders should be aware that in low-liquidity or highly volatile markets, the signals might be less reliable and require additional confirmation.
Usage Recommendations : While the Uptrick indicator is a powerful tool, it is recommended to use it in conjunction with other analysis methods to confirm signals. Traders should also continuously monitor the performance and adjust settings as needed to align with their specific trading strategies and market conditions.
### Conclusion
The "Uptrick: Momentum-Volatility Composite Signal" is a revolutionary tool that offers traders an advanced methodology for analyzing market dynamics. By combining momentum, volatility, volume, and trend detection into a single, cohesive indicator, it provides a powerful, actionable insight into market movements, making it an indispensable tool for traders aiming to optimize their trading strategies.
Deviation Adjusted MA Overview
The Deviation Adjusted MA is a custom indicator that enhances traditional moving average techniques by introducing a volatility-based adjustment. This adjustment is implemented by incorporating the standard deviation of price data, making the moving average more adaptive to market conditions. The key feature is the combination of a customizable moving average (MA) type and the application of deviation percentage to modify its responsiveness. Additionally, a smoothing layer is applied to reduce noise, improving signal clarity.
Key Components
Customizable Moving Averages
The script allows the user to select from four different types of moving averages:
Simple Moving Average (SMA): A basic average of the closing prices over a specified period.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to recent price changes.
Weighted Moving Average (WMA): Weights prices differently, favoring more recent ones but in a linear progression.
Volume-Weighted Moving Average (VWMA): Adjusts the average by trading volume, placing more weight on high-volume periods.
Standard Deviation Calculation
The script calculates the standard deviation of the closing prices over the selected maLength period.
Standard deviation measures the dispersion or volatility of price movements, giving a sense of market volatility.
Deviation Percentage and Adjustment
Deviation Percentage is calculated by dividing the standard deviation by the base moving average and multiplying by 100 to express it as a percentage.
The base moving average is adjusted by this deviation percentage, making the indicator responsive to changes in volatility. The result is a more dynamic moving average that adapts to market conditions.
The parameter devMultiplier is available to scale this adjustment, allowing further fine-tuning of sensitivity.
Smoothing the Adjusted Moving Average
After adjusting the moving average based on deviation, the script applies an additional Exponential Moving Average (EMA) with a length defined by the smoothingLength input.
This EMA serves as a smoothing filter to reduce the noise that could arise from the raw adjustments of the moving average. The smoothing makes trend recognition more consistent and removes short-term fluctuations that could otherwise distort the signal.
Use cases
The Deviation Adjusted MA indicator serves as a dynamic alternative to traditional moving averages by adjusting its sensitivity based on volatility. The script offers extensive customization options through the selection of moving average type and the parameters controlling smoothing and deviation adjustments.
By applying these adjustments and smoothing, the script enables users to better track trends and price movements, while providing a visual cue for changes in market sentiment.
Kijun_ATROVERVIEW
Kijun + ATR is an indicator that combines Lagging Kijun Base Line From Ichimoku Cloud (direction indicator) and Volatility Indicator ATR.
By combining ATR with kijun we can filter out noise from Base Line.
CALCULATIONS
Kijun is calculated by taking average of lowest and highest point of price over set lenght.
ATR is just default Tradingview Indicator that calculates average true range of price over set period of time.
WORKING
When both close > lower and not close < upper are true indicator indicate long by color limeand indicates short when close < upper by color fuchsia (Color can be changed in settings)
Indicator works best in Trending Market Regimes can have problems by signaling tops in Consolidating Market Regimes during bear markets and by sygnaling bottom in short consolidating market regimes during bull market.
TRIN (Arms Index) Trading StrategyThe TRIN (Arms Index), also known as the Short-Term Trading Index, is a technical indicator designed to gauge the internal strength or weakness of the market. It compares the number of advancing and declining stocks to the advancing and declining volume (AD Volume). A TRIN value above 1.0 generally indicates bearish market conditions, while a value below 1.0 suggests bullish market sentiment.
Strategy Rules:
Entry Condition (Long Position): When the TRIN value is above 1.0, the strategy enters a long position, indicating that the market may be oversold, and a potential reversal could occur.
Exit Condition: The strategy exits the long position when the closing price is higher than the previous day’s high, signaling a potential rebound in the market.
This strategy aims to capitalize on short-term market inefficiencies by entering trades during periods of potential market weakness and exiting when signs of recovery appear.
How the TRIN Index Works:
The TRIN is calculated as follows:
TRIN=Advancing Issues / Declining IssuesAdvancing Volume / Declining Volume
TRIN=Advancing Volume / Declining VolumeAdvancing Issues / Declining Issues
A TRIN value above 1.0 indicates that the market is potentially oversold (more declining stocks with higher volume), while a value below 1.0 suggests the market may be overbought (more advancing stocks with higher volume) .
Empirical Evidence:
Market Sentiment Indicator: The TRIN has been widely used as a sentiment indicator. Research by Zweig (1997) suggests that extreme TRIN values can serve as a contrarian signal, indicating potential turning points in the market. For instance, a TRIN above 2.0 is often considered a sign of panic selling, which can precede a market bottom .
Overbought/Oversold Conditions: Studies have shown that indicators like TRIN, which measure market breadth and volume, can be effective in identifying overbought and oversold conditions. According to Fama and French (1988), market sentiment indicators that consider both price and volume data can offer insights into future price movements .
Risks and Limitations:
False Signals:
One of the primary risks of using the TRIN-based strategy is the possibility of false signals. A TRIN value above 1.0 does not always guarantee a market rebound, especially in sustained bearish trends. In such cases, the strategy might enter long positions prematurely, leading to losses.
Research by Brock, Lakonishok, and LeBaron (1992) found that while market indicators like TRIN can be useful, they are not foolproof and can generate multiple false positives, particularly in volatile markets .
Market Regimes:
The effectiveness of the TRIN index can vary depending on the market regime. In strongly trending markets, either bullish or bearish, the TRIN may not provide reliable reversal signals, and relying on it could result in trades that go against the prevailing trend. For instance, during strong bear markets, the TRIN may frequently remain above 1.0, leading to multiple losing trades as the market continues to decline.
Short-Term Focus:
The TRIN strategy is inherently short-term focused, aiming to capture quick market reversals. This makes it sensitive to market noise and less effective for longer-term investors. Moreover, short-term trading strategies often require more frequent adjustments and can incur higher transaction costs, which may erode profitability over time.
Liquidity and Execution Risk:
Since the TRIN strategy requires entering and exiting trades based on short-term market movements, it is vulnerable to liquidity and execution risks. In fast-moving markets, the execution of trades may be delayed, leading to slippage and potentially unfavorable entry or exit points.
Conclusion:
The TRIN (Arms Index) Trading Strategy can be an effective tool for traders looking to capitalize on short-term market inefficiencies and potential reversals. However, it is important to recognize the risks associated with this strategy, including false signals, sensitivity to market regimes, and execution risks. Traders should employ proper risk management techniques and consider combining the TRIN with other indicators to improve the robustness of the strategy.
While the TRIN provides valuable insights into market sentiment, it is not a standalone solution and should be used in conjunction with a broader trading plan that takes into account both technical and fundamental analysis.
References:
Arms, Richard W. "Volume Adjusted Moving Averages." Technical Analysis of Stocks & Commodities, 1993.
Zweig, Martin. Winning on Wall Street. Warner Books, 1997.
Fama, Eugene F., and Kenneth R. French. "Permanent and Temporary Components of Stock Prices." Journal of Political Economy, 1988.
Brock, William, Josef Lakonishok, and Blake LeBaron. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns." Journal of Finance, 1992.
Dema AFR | viResearchDema AFR | viResearch
Conceptual Foundation and Innovation
The "Dema AFR" indicator combines the Double Exponential Moving Average (DEMA) with an Average True Range (ATR)-based adaptive factor to create a responsive and adaptable trend-following system. The DEMA is known for its ability to smooth price data while reducing lag, making it highly effective for trend detection. By incorporating the ATR as a volatility factor, this indicator adapts dynamically to market conditions, allowing traders to capture trends while accounting for changes in volatility. The result is the Adaptive Factor Range (AFR), which provides clear signals for potential trend shifts and helps manage risk through its adaptive nature. This combination of DEMA smoothing and an ATR-based factor enables traders to follow trends more effectively while maintaining sensitivity to changing market conditions.
Technical Composition and Calculation
The "Dema AFR" script consists of two main components: the Double Exponential Moving Average (DEMA) and the Adaptive Factor Range (AFR). The DEMA is calculated over a user-defined length, smoothing out price fluctuations while reducing lag compared to traditional moving averages. The ATR is used to create a dynamic factor that adjusts the AFR based on market volatility. The factor is calculated by multiplying the ATR by a user-defined factor value, which scales the ATR to define upper and lower bounds for the AFR. The Adaptive Factor Range is derived from the DEMA, with upper and lower bounds set by adding or subtracting the ATR-based factor from the DEMA. When the price moves outside these bounds, the AFR is adjusted, and signals are generated. If the lower bound is exceeded, the AFR adjusts upward, while exceeding the upper bound causes the AFR to adjust downward. This dynamic adjustment helps the indicator stay responsive to market movements.
Features and User Inputs
The "Dema AFR" script provides several customizable inputs, allowing traders to tailor the indicator to their strategies. The DEMA Length controls the smoothing period for the DEMA, while the ATR Period defines the window for calculating the Average True Range. The ATR Factor determines the scale of the adaptive factor, controlling how much the AFR adjusts to volatility. Additionally, customizable bar colors and alert conditions allow traders to visualize the trend direction and receive notifications when key trend shifts occur.
Practical Applications
The "Dema AFR" indicator is designed for traders who want to capture trends while adapting to market volatility. The adaptive nature of the AFR makes it responsive to trend changes, providing early signals of potential trend reversals as the AFR adjusts to market movements. By incorporating ATR into the AFR calculation, the indicator adjusts to changing volatility, helping traders manage risk by staying aligned with market conditions. The AFR also helps confirm whether a price move is supported by momentum, improving the accuracy of trade entries and exits.
Advantages and Strategic Value
The "Dema AFR" script offers a significant advantage by combining the smoothness of the DEMA with the adaptability of the ATR-based factor. This dynamic combination allows the indicator to adjust to market conditions, providing more reliable trend signals in both trending and volatile markets. The adaptive nature of the AFR reduces the risk of false signals and helps traders stay on the right side of the trend while managing risk through volatility-adjusted ranges.
Alerts and Visual Cues
The script includes alert conditions that notify traders of key trend changes. The "Dema AFR Long" alert is triggered when the AFR indicates a potential upward trend, while the "Dema AFR Short" alert signals a potential downward trend. Visual cues such as color changes in the bar chart help traders quickly identify shifts in trend direction, allowing them to make informed decisions in real time.
Summary and Usage Tips
The "Dema AFR | viResearch" indicator provides traders with a powerful tool for trend analysis by combining DEMA smoothing with an ATR-based adaptive factor. This script helps traders stay aligned with trends while accounting for market volatility, improving their ability to detect trend reversals and manage risk. By incorporating this indicator into your trading strategy, you can make more informed decisions, whether in trending or volatile market environments. The "Dema AFR" offers a reliable and flexible solution for traders at all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Kalman PSaR [BackQuant]Kalman PSaR
Overview and Innovation
The Kalman PSaR combines the well-known Parabolic SAR (PSaR) with the advanced smoothing capabilities of the Kalman Filter . This innovative tool aims to enhance the traditional PSaR by integrating Kalman filtering, which reduces noise and improves trend detection. The Kalman PSaR adapts dynamically to price movements, making it a highly effective indicator for spotting trend shifts while minimizing the impact of false signals caused by market volatility.
Please Find the Basic Kalman Here:
Kalman Filter Dynamics
The Kalman Filter is a powerful algorithm for estimating the true value of a system amidst noisy data. In the Kalman PSaR, this filter is applied to the high, low, and closing prices, resulting in a smoother and more accurate representation of price action. The filter’s parameters—process noise and measurement noise—are customizable, allowing traders to fine-tune the sensitivity of the indicator to market conditions. By reducing the impact of noise, the Kalman-filtered PSaR offers clearer signals for identifying trend reversals and continuations.
Enhanced PSaR Calculation
The traditional Parabolic SAR is a popular trend-following indicator that highlights potential entry and exit points based on price acceleration. In the Kalman PSaR, this calculation is enhanced by the Kalman-filtered prices, providing a smoother and more reliable signal. The indicator continuously updates based on the acceleration factor and max step values, while the Kalman filter ensures that sudden price spikes or market noise do not trigger false signals.
Min Step and Max Step: These settings control the sensitivity of the PSaR. The Min Step sets the initial acceleration factor, while the Max Step limits how fast the PSaR adapts to price changes, helping traders fine-tune the indicator’s responsiveness.
Optional Smoothing Techniques To further enhance the signal clarity, the Kalman PSaR includes an optional smoothing feature. Traders can choose from various smoothing methods, such as SMA, Hull, EMA, WMA, TEMA, and more, to reduce short-term fluctuations and emphasize the underlying trend. The smoothing period is customizable, allowing traders to adjust the indicator’s behavior according to their preferred trading style and timeframe.
Color-Coded Candle Painting The Kalman PSaR features color-coded candles that change according to the trend direction. When the price is above the PSaR, candles are painted green to indicate a long trend, and when the price is below the PSaR, candles are painted red to signal a short trend. This visual representation makes it easy to interpret market sentiment at a glance, improving decision-making speed during fast-moving markets.
Key Features and Customization
Kalman Filter Customization: The process noise and measurement noise parameters allow traders to adjust how aggressively the filter adapts to price changes, making it suitable for both volatile and stable markets.
Smoothing Options: A variety of moving average types, such as SMA, Hull, EMA, and more, can be applied to smooth the PSaR values, ensuring that the signal remains clear even in choppy markets.
Dynamic Trend Detection: The Kalman PSaR dynamically updates based on price movements, helping traders spot trend reversals early while filtering out false signals caused by short-term volatility.
Bar Coloring and PSaR Plotting: Traders can choose to color candles based on trend direction or plot the PSaR directly on the chart for additional visual clarity.
Practical Applications
Trend-Following Strategies: The Kalman PSaR excels in trend-following strategies by providing timely signals of trend changes. The dynamic nature of the indicator allows traders to capture significant price movements while avoiding market noise.
Reversal Identification: The indicator’s ability to filter out noise and provide smoother signals makes it ideal for identifying reversals in volatile markets.
Risk Management: By plotting clear stop levels based on the PSaR, traders can use this indicator to effectively manage risk, placing stop-loss orders at key points based on the trend direction.
Conclusion
The Kalman PSaR is a fusion of the classic Parabolic SAR and the Kalman filter, offering enhanced trend detection with reduced noise. Its customizable filtering and smoothing options, combined with dynamic trend-following capabilities, make it a versatile tool for traders seeking to improve their timing and signal accuracy. The adaptive nature of the Kalman filter, combined with the robust PSaR logic, helps traders stay on the right side of the market and manage risk more effectively.
Kalman Filter RoC with Adaptive Thresholds [BackQuant]Kalman Filter RoC with Adaptive Thresholds
Another Kalman Script !!
Please Find the Basic Kalman Here:
Overview and Purpose
The Kalman Filter RoC with Adaptive Thresholds is an advanced tool designed for traders seeking to refine their trend detection and momentum analysis. By combining the robustness of the Kalman filter with the Rate of Change (RoC) indicator, this tool offers a highly responsive and adaptive method to identify shifts in market trends. The inclusion of adaptive thresholding further enhances the indicator’s precision by dynamically adjusting to market volatility, providing traders with reliable entry and exit signals.
Kalman Filter Dynamics
The Kalman Filter is renowned for its ability to estimate the true state of a system amidst noisy data. In this indicator, the Kalman filter is applied to the price data to smooth out fluctuations and generate a more accurate representation of the underlying trend. This is particularly useful in volatile markets where noise can obscure the true direction of price movements. The Kalman filter adapts in real-time based on user-defined parameters, such as process noise and measurement noise, making it highly customizable for different market conditions.
Rate of Change (RoC) and Smoothing The Rate of Change (RoC) is a classic momentum indicator that measures the percentage change in price over a specific period. By integrating it with the Kalman-filtered price, the RoC becomes more responsive to genuine price trends while filtering out short-term noise. An optional smoothing feature using the ALMA (Arnaud Legoux Moving Average) further refines the signal, allowing traders to adjust the calculation length and smoothing factor (sigma) for even greater precision.
Adaptive Thresholds A key innovation in this indicator is the adaptive thresholding mechanism. Traditional RoC indicators rely on static thresholds to identify overbought or oversold conditions, but the Kalman Filter RoC adapts these thresholds dynamically. The adaptive thresholds are calculated based on the historical volatility of the filtered RoC values, allowing the indicator to adjust in response to changing market conditions. This feature reduces the risk of false signals in choppy or highly volatile markets.
Divergence Detection The Kalman Filter RoC also includes divergence detection, helping traders identify when the momentum of the RoC diverges from the price action. Divergences can often signal potential reversals or trend continuations, making them a valuable tool in any trader’s toolkit. Regular and hidden divergences are plotted directly on the chart, providing visual cues for traders to act upon.
Customization and Flexibility This indicator offers a wide range of customization options, making it suitable for various trading strategies and market conditions:
Process Noise & Measurement Noise: These parameters control how sensitive the Kalman filter is to price changes and help traders fine-tune the balance between noise reduction and signal responsiveness.
ALMA Smoothing: Traders can apply ALMA smoothing to the RoC signal to reduce short-term volatility and improve signal clarity.
Adaptive Threshold Calculation Period: The length of the lookback period for the adaptive thresholds can be adjusted, allowing traders to tailor the indicator to fit their specific trading style.
Practical Applications
Trend Detection: The Kalman-filtered RoC helps identify shifts in momentum, making it easier for traders to spot emerging trends early. The dynamic thresholding ensures that these signals are reliable, even in volatile markets.
Divergence Trading: Divergences between the RoC and price action are clear indicators of potential trend reversals. The visual plotting of divergences simplifies the process of identifying these opportunities.
Momentum Analysis: The combination of Kalman filtering and RoC provides a smoother, more accurate view of market momentum, helping traders stay on the right side of the market.
Conclusion
The Kalman Filter RoC is a powerful and adaptable tool that merges advanced filtering techniques with momentum analysis. Its real-time responsiveness and dynamic thresholding make it a highly effective indicator for identifying trends, managing risk, and capitalizing on divergence signals. Traders looking to enhance their trend-following or momentum strategies will find this indicator to be a valuable addition to their toolkit.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
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