Asymmetric volatilityThe "Asymmetric Volatility" indicator is designed to visualize the differences in volatility between upward and downward price movements of a selected instrument. It operates on the principle of analyzing price movements over a specified time period, with particular focus on the symmetrical evaluation of both price rises and falls.
User Parameters:
- Length: This parameter specifies the number of bars (candles) used to calculate the average volatility. The larger the value, the longer the time period, and the smoother the volatility data will be.
- Source: This represents the input data for the indicator calculations. By default, the close value of each bar is used, but the user can choose another data source (such as open, high, low, or any custom value).
Operational Algorithm:
1. Movement Calculation:
- UpMoves: Computed as the positive difference between the current bar value and the previous bar value, if it is greater than zero.
- DownMoves: Computed as the positive difference between the previous bar value and the current bar value, if it is greater than zero.
2. Volatility Calculation:
- UpVolatility: This is the arithmetic mean of the UpMoves values over the specified period.
- DownVolatility: This is the arithmetic mean of the DownMoves values over the specified period.
3. Graphical Representation:
- The indicator displays two plots: upward and downward volatility, represented by green and red lines, respectively.
- The background color changes based on which volatility is dominant: a green background indicates that upward volatility prevails, while a red background indicates downward volatility.
The indicator allows traders to quickly assess in which direction the market is more volatile at the moment, which can be useful for making trading decisions and evaluating the current market situation.
Стандартное отклонение
Multi-Chart Relative Strength Oscillator[ChartGalaxy]The Multi-Chart Relative Strength Oscillator is a powerful tool designed to compare the relative strength of up to 10 different market symbols (such as indices, stocks, or commodities). By normalizing each symbol's performance, this oscillator highlights which symbols are showing strength or weakness relative to each other over a selected time period.
Key Features:
Multiple Symbols Comparison: Compare up to 10 different symbols simultaneously.
Oscillator Calculation: Each symbol's price is normalized and converted into an oscillator, allowing for easy comparison of relative strength
Custom Timeframes: Choose any resolution (e.g., daily, weekly) for analyzing the symbols.
Dynamic Labeling: Each symbol is labeled on the chart for easy identification with color-coded labels that match the plotted lines.
Strength Classification: Symbols are classified as "Strong", "Neutral", or "Weak" based on their performance relative to others.
Optional Symbol Table: A table of the symbols and their strength is displayed on the chart, giving a quick overview of the current market conditions.
How it Works:
Symbol Input: The user can input up to 10 market symbols (such as indices or stocks) they wish to compare.
Oscillator Calculation: The indicator calculates the normalized value of each symbol over the selected time period, adjusting for standard deviation to create a relative strength oscillator.
Visual Comparison: The symbols are plotted as oscillating lines on the chart, color-coded for easy differentiation. Additionally, labels appear on the right side of each plot to indicate the symbol.
Strength Assessment: Each symbol is classified as Strong/Weal/Neutral
Use Cases:
Sector Rotation Analysis: Compare different sectors (e.g., Energy, Technology, Healthcare) to see which sectors are gaining or losing relative strength.
Asset Comparison: Analyze a group of stocks, commodities, or other assets to determine which are outperforming or underperforming.
Market Overview: Get a broad overview of the market by comparing key indices and sectors to gauge the overall market sentiment.
Customization Options:
Resolution Selection: Users can select their preferred timeframe for analysis (e.g., daily, weekly).
Custom Symbol Selection: Input any symbol supported by TradingView to compare performance.
Visual Clarity: Each symbol is plotted with distinct colors, and a label with the symbol’s name appears alongside the chart, making it easy to identify each line.
This indicator is ideal for traders looking to conduct sector analysis, asset comparison, or relative strength studies across multiple symbols, providing them with an intuitive and easy-to-read visual tool.
Outlier changes alertAn indicator that calculates click (price change), percentage change, and Z-score changes while displaying outliers based on defined ranges.
Outlier Detection:
Mark outliers (for price, percentage, Z-score) based on user-defined thresholds. For example, any price movement exceeding a certain Z-score or percentage change could be marked as an outlier and displayed on chart.
Indicator Overview:
1. Click (Price Change):
Calculate the absolute price change from one period to another (e.g., from the current closing price to the previous closing price).
2. Percentage Change:
Calculate the percentage price change over a specific period, showing how much the price has changed in relative terms compared to the previous price.
3. Z-Score:
Compute the Z-score to standardize the price change relative to its historical average and standard deviation. The Z-score helps in detecting whether a price movement is an outlier or falls within a normal range of volatility.
Standard Deviation based Upper Lower RangeThis script makes use of historical data for finding the standard deviation on daily returns. Based on the mean and standard deviation, the upper and lower range for the stock is shown upto 2x standard deviation. These bounds can be treated as volatility range for the next n trading sessions. This volatility is based on historical data. Users can change the lookback historical period, and can also set the time period (days) for upcoming trading sessions.
This indicator can be useful in determining stoploss and target levels along with the traditional support/resistance levels. It can also be useful in option trading where one needs to determine a range beyond which it is safe to sell an option.
A range of 1 SD has around 65% to 68% probability that it will not be breached. A range of 2 SD has around 95% probability that it will not be breached.
The indicator is based on Normal distribution theory. In future editions, I envision to also calculate the skewness and kurtosis so that we can determine if a stock is properly following Normal Distribution theory. That may further favor the calculated range.
Statistical Anomaly IndicatorThe Statistical Anomaly Indicator is a sophisticated tool designed for traders to detect and highlight candles that significantly deviate from the expected price action based on statistical analysis. By leveraging historical price data, this indicator calculates an anticipated price range using a pricing model rooted in the mean and standard deviation of historical returns. When the actual price moves outside these statistical boundaries, the corresponding candles are marked on the chart, providing traders with unique insights into potential market anomalies.
Purpose and Unique Insights
The primary purpose of the Statistical Anomaly Indicator is to aid traders in identifying periods of abnormal price movements that may signify overbought or oversold conditions, potential reversals, or trend continuations. By highlighting these statistical outliers, the indicator offers:
Early Detection of Market Anomalies: Spot unusual price actions promptly.
Enhanced Decision-Making: Make more informed trading decisions by understanding when prices deviate from historical norms.
Versatility Across Markets: Applicable in various market contexts, whether trending or ranging.
This tool benefits both novice traders, by simplifying complex statistical concepts into visual cues, and experienced traders, by adding a quantitative edge to their analysis.
Methodology
Calculate the return of the period
return(t) = (close - close )/close
Calculate the mean of past returns within a specified window
mean = ta.sma(return , period)
Calculate the standard deviation of past returns within a specified window
stdev = ta.stdev(return , period)
Establish price upper and lower bound using the last close, mean and standard deviation
upper_bound = close * (1 + mean + stdev)
lower_bound = close * (1 + mean - stdev)
Mark the candles where the close price exceeds the established price range
close > upper_bound or close < lower_bound
Visual Presentation on the Chart
Color-Coded Triangles: The indicator places color-coded triangles below the bars of the candles that exceed the expected price range.
Green Triangles: Indicate a close above the upper bound (potential overbought condition).
Red Triangles: Indicate a close below the lower bound (potential oversold condition).
Immediate Recognition: These visual cues enable traders to quickly identify statistical anomalies without sifting through numerical data.
Practical Applications for Traders
Identifying Overbought/Oversold Conditions: Recognize when the asset price may have moved too far in one direction and could be due for a correction.
Spotting Potential Reversals: Use deviations as early signals of possible market reversals.
Confirming Trend Continuations: In strong trends, deviations might indicate momentum is continuing rather than reversing.
Identifying historical trends in the price action.
Combining with Other Tools and Analysis
To maximize the effectiveness of the Statistical Anomaly Indicator:
Pair with the Mean and Standard Deviation Lines Indicator:
Provides additional context by displaying the mean and standard deviation levels directly on the chart.
Use in Conjunction with Fundamental Analysis:
Validate whether statistical anomalies are supported by underlying economic factors or news events.
Integrate with Other Technical Indicators.
Limitations and Caveats
Not a Standalone Tool: Should not be used in isolation; always consider the broader market context.
Statistical Assumptions: Based on historical data; past performance does not guarantee future results.
False Signals: Like all indicators, it may generate false positives, especially in highly volatile or low-volume markets which is why context is needed to interpret the signals.
Parameter Selection: The chosen period for calculating mean and standard deviation can significantly affect the indicator's sensitivity.
Conclusion
The Statistical Anomaly Indicator offers a quantitative approach to identifying unusual price movements in the market. By transforming complex statistical data into simple visual signals, it empowers traders to make more informed decisions. Whether you're a novice trader seeking to understand market dynamics or an experienced trader looking to refine your strategy, this indicator provides practical benefits. Remember to integrate it with fundamental analysis and other technical tools to validate signals and enhance your trading decisions.
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.
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.
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.
RSI Standard Deviation | viResearchRSI Standard Deviation | viResearch
The "RSI Standard Deviation" indicator, developed by viResearch, introduces a new approach to combining the Relative Strength Index (RSI) with a standard deviation measure to offer a more dynamic view of market momentum. By applying standard deviation to the RSI values, this indicator refines the traditional RSI, providing a more precise and adaptive way to measure overbought and oversold conditions. This unique combination allows traders to better understand the underlying volatility in RSI movements, leading to more informed decisions in trending and ranging markets.
Technical Composition and Calculation:
The core of the "RSI Standard Deviation" lies in calculating the RSI based on user-defined input parameters and then applying standard deviation to these RSI values. This method enhances the sensitivity of the RSI, making it more responsive to market volatility.
RSI Calculation:
RSI Length (len): The script computes the Relative Strength Index over a customizable length (default: 21), offering a traditional measure of momentum in the market. The RSI tracks the speed and change of price movements, oscillating between 0 and 100 to indicate overbought and oversold conditions.
Standard Deviation Applied to RSI:
Standard Deviation Length (sdlen): The script calculates the standard deviation of the RSI values over a user-defined period (default: 35). This standard deviation represents the volatility in RSI movements, adding a new layer of analysis to traditional RSI.
Upper (u) and Lower (d) Bands:
The standard deviation values are used to create upper and lower bands around the RSI, offering an adaptive range that expands or contracts based on market volatility. This helps traders identify moments when the market is more likely to reverse or continue its trend.
Trend Identification:
Uptrend (L): The script identifies an uptrend when the RSI moves above the lower band and stays above the midline (50). This indicates that the market is gaining upward momentum, potentially signaling a long position.
Downtrend (S): A downtrend is identified when the RSI moves below 50, suggesting a weakening market and a potential short position.
Features and User Inputs:
The "RSI Standard Deviation" script offers various customization options, enabling traders to tailor it to their specific needs and strategies:
RSI Length: Traders can adjust the length of the RSI calculation to control how quickly the indicator responds to price movements.
Standard Deviation Length: Adjusting the standard deviation length allows users to control the sensitivity of the upper and lower bands, fine-tuning the indicator’s responsiveness to market volatility.
Source Input: The script can be applied to different price sources, offering flexibility in how it calculates RSI and standard deviation values.
Practical Applications:
The "RSI Standard Deviation" indicator is particularly useful in volatile markets, where traditional RSI may produce false signals due to rapid price movements. By adding a standard deviation measure, traders can filter out noise and better identify trends.
Key Uses:
Trend Following: The standard deviation bands provide a clearer view of momentum shifts in the RSI, allowing traders to follow the trend more confidently.
Volatility Assessment: The indicator dynamically adjusts to market volatility, making it easier to assess when the market is overbought or oversold and when a trend reversal is likely.
Signal Confirmation: By comparing the RSI to the adaptive standard deviation bands, traders can confirm signals and avoid false entries during periods of high volatility.
Advantages and Strategic Value:
The "RSI Standard Deviation" offers several advantages:
Enhanced Precision: The combination of RSI and standard deviation results in a more refined momentum indicator that adapts to market conditions.
Noise Reduction: The standard deviation bands help filter out short-term market noise, making it easier to identify significant trend changes.
Dynamic Volatility Awareness: By using standard deviation, the indicator adjusts its bands based on real-time volatility, providing more accurate overbought and oversold signals.
Summary and Usage Tips:
The "RSI Standard Deviation" is a powerful tool for traders looking to enhance their RSI analysis with volatility measures. For optimal performance, traders should experiment with different RSI and standard deviation lengths to suit their trading timeframe and strategy. Whether used to follow trends or confirm momentum signals, the "RSI Standard Deviation" provides a reliable and adaptive solution for modern trading environments.
Inverted SD Dema RSI | viResearchInverted SD Dema RSI | viResearch
The "Inverted SD Dema RSI" developed by viResearch introduces a new approach to trend analysis by combining the Double Exponential Moving Average (DEMA), Standard Deviation (SD), and Relative Strength Index (RSI). This unique indicator provides traders with a tool to capture market trends by integrating volatility-based thresholds. By using the smoothed DEMA along with standard deviation, the indicator offers improved responsiveness to price fluctuations, while RSI thresholds offer insight into overbought and oversold market conditions.
At the core of the "Inverted SD Dema RSI" is the combination of DEMA and standard deviation for a more nuanced view of market volatility. The use of RSI further aids in detecting price extremes and potential trend reversals.
DEMA Calculation (sublen): The Double Exponential Moving Average (DEMA) smoothes out price data over a user-defined period, reducing lag compared to traditional moving averages. This provides a clearer representation of the market's overall direction.
Standard Deviation Calculation (sublen_2): The standard deviation of the DEMA is used to define the upper (u) and lower (d) bands, highlighting areas where price volatility may signal a change in trend. These dynamic bands help traders gauge price volatility and potential breakouts or breakdowns.
RSI Calculation (len): The script applies the Relative Strength Index (RSI) to the smoothed DEMA values, allowing traders to detect momentum shifts based on a modified data set. This provides a more accurate reflection of market strength when combined with the DEMA.
Thresholds: The RSI is compared to user-defined thresholds (70 for overbought and 55 for oversold conditions). These thresholds help in identifying potential market reversals, especially when the price breaks outside of the calculated standard deviation bands.
Uptrend (L): An uptrend signal is generated when the RSI exceeds the upper threshold (70) and the price is not above the upper standard deviation band, indicating that there may be room for further price appreciation.
Downtrend (S): A downtrend signal occurs when the RSI falls below the lower threshold (55), indicating that the price may continue to decline.
The "Inverted SD Dema RSI" offers a wide range of customizable settings, allowing traders to adjust the indicator based on their trading style or market conditions.
DEMA Length (sublen): Controls the period used to smooth the price data, impacting the sensitivity of the DEMA to recent price movements.
Standard Deviation Length (sublen_2): Defines the length over which the standard deviation is calculated, helping traders control the width of the upper and lower bands.
RSI Length (len): Adjusts the period used for the RSI calculation, providing flexibility in determining overbought and oversold conditions.
RSI Thresholds: Traders can define their own levels for detecting trend reversals, with default values of 70 for an uptrend and 55 for a downtrend.
The "Inverted SD Dema RSI" is particularly well-suited for traders looking to capture trends while accounting for volatility and momentum. By using a smoothed DEMA as the foundation, it effectively filters out noise, making it ideal for detecting reliable trends in volatile markets.
Key Uses:
Trend Following: The indicator’s combination of DEMA, standard deviation, and RSI helps traders follow trends more effectively by reducing noise and identifying key momentum shifts.
Volatility Filtering: The use of standard deviation bands provides a dynamic measure of volatility, ensuring that traders are aware of potential breakouts or breakdowns in the market.
Momentum Detection: The inclusion of RSI ensures that the indicator is not only focused on trend direction but also on the strength of the underlying momentum, helping traders avoid entering trades during weak trends.
The "Inverted SD Dema RSI" provides several key advantages over traditional trend-following indicators:
Reduced Lag: The use of DEMA ensures faster trend detection, reducing the lag associated with simple moving averages.
Noise Reduction: The integration of standard deviation helps filter out irrelevant price movements, making it easier to identify significant trends.
Momentum Awareness: The addition of RSI provides valuable insight into the strength of trends, helping traders avoid false signals during periods of weak momentum.
The "Inverted SD Dema RSI" offers a powerful blend of trend-following and momentum detection, making it a versatile tool for modern traders. By integrating DEMA, standard deviation, and RSI, the indicator provides a comprehensive view of market trends and volatility. Traders are encouraged to experiment with different settings for the DEMA length, standard deviation, and RSI thresholds to fine-tune the indicator for their specific trading strategies. Whether used for trend confirmation, volatility assessment, or momentum analysis, the "Inverted SD Dema RSI" offers a valuable tool for traders seeking a comprehensive approach to market analysis.
Standard Deviation [Vogaz]This Pine Script indicator provides a visualization of standard deviation bands plotted as fixed horizontal lines on the TradingView chart. The bands are based on the last candle's closing price and are designed to help traders identify potential volatility levels and deviations from the average price.
Features:
Standard Deviation Calculation: The indicator calculates standard deviation based on a user-defined length and source price. It then creates bands around the last candle's close price, showing potential ranges of price volatility.
Customizable Multipliers: You can adjust the multipliers for standard deviation levels (e.g., 1x, 2x, 3x) to set how far the bands are from the closing price.
Adjustable Line Thickness and Length: Customize the thickness and length of the horizontal lines. The lines extend backwards from the current bar to show the range over a user-defined number of bars.
Color Settings: Each band and the closing price line have configurable colors for better visual differentiation. You can set colors for:
Standard Deviation 1 Band (up and down)
Standard Deviation 2 Band (up and down)
Standard Deviation 3 Band (up and down)
Last Close Price Line
Inputs:
Length: Number of periods for calculating standard deviation.
Source: Price type used for standard deviation calculation (e.g., closing price).
StdDev Multipliers: Multipliers for different standard deviation bands.
Line Thickness: Thickness of the horizontal lines.
Line Length: Length of the lines extending from the current bar.
Line Colors: Colors for the bands and the last close price line.
Use Case:
This indicator is useful for traders who want to visualize price volatility and deviations around the last closing price. By analyzing these bands, traders can make informed decisions about potential price movements and market conditions.
How to Use:
Add the Indicator to Your Chart: Apply the indicator to your TradingView chart.
Adjust Settings: Modify the standard deviation multipliers, line thickness, and length according to your preferences.
Analyze the Bands: Use the bands to assess price volatility and identify potential trading signals.
Z-Score AggregatorOverview:
This indicator is designed to take multiple other indicators as inputs, calculate their respective Z-scores, and then aggregate these Z-scores to provide a comprehensive measure. By transforming the inputs into Z-scores, this indicator standardizes the data, enabling a more accurate comparison across different indicators, each of which may have different scales and distributions.
This indicator is beneficial for Mean-Reversion style trading and investing as it standardizes indicators and lets them work together in one system.
The Z-score, which represents how many standard deviations an element is from the mean, is a crucial statistical tool in this process. It allows the indicator to normalize the varying data points, ensuring that each indicator's contribution to the aggregate score is proportional to its deviation from the average performance.
Inputs:
Z-score length: How far Back it will take into account the inputs
Number Of Sources: This is to set the number of inputs the indicator uses so it calculates them properly and uses only the number of indicators you want.
Source Inputs: 1-10 inputs (no need to use them all as long as you set the number of used indicators beforehand).
Note:
There are three indicators used in this example which are CCI, RSI and Sharpe Ratio. The indicator calculates their individual Z-scores and takes an average. Because Number Of Sources is set to 3 it only uses the first 3 indicators in use.
VPSA - Volume Price Spread AnalysisDear Analysts and Traders,
I am pleased to present the latest version of my indicator, based on the logic of analyzing spread and volume. In this version, the indicator examines spread and volume using min-max normalization. The statistical value is captured through Z-Score standardization, and I have added configurable alerts based on the normalized values of spread, volume, and the sigmas for these variables.
Theory and Evolution of the Indicator
The normalization function used in this program allows for the comparison of two values with different ranges on a single chart. The values that reach the highest within the examined range are assigned a value of one. As in previous versions, I have adopted a bar chart where the wider bar represents volume and the narrower bar represents spread. I believe that using normalization is the most intuitive approach, as the standardization in the earlier sVPSA version could cause confusion. This was due to smaller bars for higher actual values and negative bars, which required additional reliance on actual volume data and significant proficiency in using the indicator. These were limitations stemming from the computational aspect of these issues. As in the previously mentioned script, I also used Z-Score standardization here, which serves as a measure of deviation from the mean. This is visualized in the script as the color of the bars, which in the default configuration are as follows: below one sigma - blue; above one sigma up to two sigmas - green; above two sigmas up to three sigmas - red; and above three sigmas - fuchsia. Additionally, I applied an exponential moving average in this indicator to minimize the influence of older candles on the mean. The indicator has been enhanced with configurable alerts, allowing for substantial control over the conditions triggering them. The alerts enable the definition of normalized variable values and sigma values. Furthermore, the program allows for the definition of logical dependencies for these conditions.
Summary
The program I have developed is a synthesis of the most important and useful functions from the indicators I previously created. The indicator is a standalone and powerful tool that facilitates effective analysis of the spread-volume relationship, which is one of the fundamental methods of analysis according to the Wyckoff and VSA methodologies. The alerts introduced in this version provide extensive possibilities for controlling the dynamics of any market.
Should you encounter any errors or have suggestions regarding the indicator, please feel free to contact me.
I wish you successful analyses! All the best!
CatTheTrader
Fibonacci Linear Regression Bands[Pinescriptlabs]🎯 This script is designed to draw Fibonacci-based linear regression bands.
It calculates and draws a linear regression channel and its Fibonacci levels across different time frames (5m, 15m, 30m, and 4h).
📊 How to use it?
🔍 Multidimensional Analysis
This strategy allows you to view the market from a multidimensional perspective, integrating long-term trends with short-term price action. By doing so, you can dynamically adjust your trades based on market developments, moving between time frames as needed. This not only enables you to capture large movements within the primary trend but also to exploit smaller fluctuations.
⏳ Time Frame Interaction
4-Hour Time Frame with Regression Channel: By using a regression channel on a broader time frame (like 4 hours), you gain a perspective on the dominant trend. This provides you with a solid foundation to evaluate the general market direction. In this scenario, you might deactivate the Fibonacci levels to avoid cluttering the visualization, focusing solely on the regression channel that shows you the prevailing trend.
Lower Time Frames with Regression and Fibonacci: You can activate the regression lines and Fibonacci levels on lower time frames (like 5m, 15m, or 30m) to obtain more precise signals. Here, Fibonacci levels will help you identify potential entry and exit points within the broader time frame.
🚩 Reversal Zone Identification
If the price breaks the regression channel on a lower time frame and approaches a key Fibonacci level, this could indicate a potential reversal.
🎯 Multiple Scenarios
By using different combinations of regression channels and Fibonacci levels across various time frames, you can create trading scenarios. For example, you could be in a long position on the 4-hour time frame while simultaneously trading within a lower time frame, taking advantage of bounces at Fibonacci levels.
🎯 Confluence Zone Identification
Zones where regression lines and Fibonacci levels coincide become areas of confluence. These zones represent points where a strong price reaction is likely to occur. If a Fibonacci retracement aligns with the upper or lower edge of a regression channel, this point acts as a significant support or resistance level.
⚙️ Input Configuration?
Activate/Deactivate Regression Lines: Click on the squares under "Linear Settings" to activate or deactivate the regression line in different time frames. If a square is colored, the regression line for that time frame is activated.
Show/Hide Fibonacci: Check or uncheck the boxes under "Fibonacci Settings" to show or hide Fibonacci levels in the selected time frames.
Fibonacci Color: Click on the color box under "Fibonacci Color" to select a new color for the Fibonacci levels.
Español:
🎯 Este script está diseñado para dibujar bandas de regresión lineal basadas en Fibonacci.
Calcula y dibuja un canal de regresión lineal y sus niveles de Fibonacci en diferentes marcos de tiempo (5m, 15m, 30m y 4h).
📊 ¿Cómo usarlo?
🔍 Análisis Multidimensional
Esta estrategia te permite ver el mercado desde una perspectiva multidimensional, integrando las tendencias a largo plazo con la acción del precio a corto plazo. Al hacerlo, puedes ajustar dinámicamente tus operaciones según la evolución del mercado, moviéndote entre marcos de tiempo según sea necesario. Esto no solo te permite captar movimientos grandes dentro de la tendencia principal, sino también explotar fluctuaciones más pequeñas
⏳ Interacción entre Marcos Temporales
Marco de Tiempo de 4 Horas con Canal de Regresión: Al utilizar un canal de regresión en un marco temporal más amplio (como 4 horas), obtienes una perspectiva sobre la tendencia dominante. Esto te da una base sólida para evaluar la dirección general del mercado. En este escenario, podrías desactivar los niveles de Fibonacci para evitar sobrecargar la visualización, enfocándote solo en el canal de regresión que muestra la tendencia predominante.
Marcos Temporales Menores con Regresión y Fibonacci: Puedes activar las líneas de regresión y los niveles de Fibonacci en marcos temporales menores (como 5m, 15m o 30m) para obtener señales más precisas. Aquí, los niveles de Fibonacci te ayudarán a identificar posibles puntos de entrada y salida dentro del marco temporal más amplio.
🚩 Identificación de Zonas de Reversión
Si el precio rompe el canal de regresión en un marco de tiempo menor y se aproxima a un nivel clave de Fibonacci, esto podría indicar una posible reversión.
🎯 Multiplicidad de Escenarios
Al usar diferentes combinaciones de canales de regresión y niveles de Fibonacci en varios marcos de tiempo, puedes crear escenarios de trading. Por ejemplo, podrías estar en una posición larga en el marco temporal de 4 horas, mientras que simultáneamente operas en un marco temporal menor aprovechando los rebotes en los niveles de Fibonacci.
🎯 Identificación de Zonas de Confluencia
Las zonas donde las líneas de regresión y los niveles de Fibonacci coinciden se convierten en áreas de confluencia. Estas zonas representan puntos donde es probable que ocurra una fuerte reacción del precio. Si un retroceso de Fibonacci se alinea con el borde superior o inferior de un canal de regresión, este punto actúa como un soporte o resistencia significativo.
⚙️ ¿Configuración de Inputs?
Activar/Desactivar Líneas de Regresión: Haz clic en los cuadrados bajo "Linear Settings" para activar o desactivar la línea de regresión en diferentes marcos temporales. Si un cuadrado está coloreado, la línea de regresión para ese marco temporal está activada.
Mostrar/Ocultar Fibonacci: Marca o desmarca las casillas bajo "Fibonacci Settings" para mostrar u ocultar los niveles de Fibonacci en los marcos temporales seleccionados.
Color de Fibonacci: Haz clic en el cuadro de color bajo "Fibonacci Color" para seleccionar un nuevo color para los niveles de Fibonacci.
Panoramic VWAP### Panoramic VWAP Indicator Overview
The Panoramic VWAP indicator provides a way to display up to four Volume Weighted Average Price (VWAP) lines on a chart, each anchored to different timeframes. This indicator also includes options for displaying standard deviation bands and close lines, offering a comprehensive view of price action across multiple time horizons.
### Key Features
Quad VWAPs : The indicator allows for the display of four VWAP lines simultaneously. Each line can be set to a different timeframe, enabling traders to analyze market conditions across various periods on a single chart.
Standard Deviation Bands : Users can enable bands around each VWAP line, which represent standard deviations or percentage levels from the VWAP. These bands help in assessing volatility and identifying potential overbought or oversold conditions.
Close Lines : The indicator includes an option to show close lines, marking the price's closing level relative to the VWAP. This feature is useful for examining how the market closes in relation to VWAP, which can be important for understanding trend strength or potential reversals.
### How It Looks
VWAP Lines : Multiple VWAP lines are displayed, each reflecting different timeframes. The lines change color depending on whether the price is above or below the VWAP, indicating bullish or bearish momentum.
Bands : Optional bands around the VWAP lines provide a visual indication of volatility, with the potential to identify overbought or oversold areas.
Close Lines : These lines represent the price's closing level relative to the VWAP and can be displayed to add further context to the analysis.
### How to Use It
Trend Analysis :
- Price above a VWAP line indicates bullish momentum .
- Price below a VWAP line suggests bearish momentum .
Support and Resistance :
- VWAP lines often act as dynamic support and resistance. Price approaching a VWAP line from above may find support, while approaching from below may encounter resistance.
Volatility Assessment :
- Bands around the VWAP lines can signal areas of potential reversal. Upper bands may indicate overbought conditions, while lower bands may indicate oversold conditions.
Multiple Timeframe Analysis :
- The ability to display VWAPs from different timeframes simultaneously allows for the identification of confluence zones, where multiple VWAP levels align, indicating potentially significant support or resistance levels.
Customization :
- The indicator settings are customizable, allowing users to choose which VWAP lines, bands, and close lines to display, along with adjustments for visual preferences like line thickness and colors.
### Practical Application
Intraday Trading : Traders can use the VWAPs and bands to identify potential entry and exit points during the trading day based on price interactions with these levels.
Swing Trading : Monitoring VWAP lines across different timeframes can help identify key levels where price might reverse or gain momentum, aiding in decisions about holding or exiting positions.
Long-Term Analysis : VWAP lines on higher timeframes can serve as dynamic support or resistance levels, providing context for long-term trend analysis and investment decisions.
The Panoramic VWAP indicator allows for a detailed analysis of price trends and levels across multiple timeframes, combining VWAPs, standard deviation bands, and close lines in a single, customizable tool.
Multi-Step FlexiSuperTrend - Strategy [presentTrading]At the heart of this endeavor is a passion for continuous improvement in the art of trading
█ Introduction and How it is Different
The "Multi-Step FlexiSuperTrend - Strategy " is an advanced trading strategy that integrates the well-known SuperTrend indicator with a nuanced and dynamic approach to market trend analysis. Unlike conventional SuperTrend strategies that rely on static thresholds and fixed parameters, this strategy introduces multi-step take profit mechanisms that allow traders to capitalize on varying market conditions in a more controlled and systematic manner.
What sets this strategy apart is its ability to dynamically adjust to market volatility through the use of an incremental factor applied to the SuperTrend calculation. This adjustment ensures that the strategy remains responsive to both minor and major market shifts, providing a more accurate signal for entries and exits. Additionally, the integration of multi-step take profit levels offers traders the flexibility to scale out of positions, locking in profits progressively as the market moves in their favor.
BTC 6hr Long/Short Performance
█ Strategy, How it Works: Detailed Explanation
The Multi-Step FlexiSuperTrend strategy operates on the foundation of the SuperTrend indicator, but with several enhancements that make it more adaptable to varying market conditions. The key components of this strategy include the SuperTrend Polyfactor Oscillator, a dynamic normalization process, and multi-step take profit levels.
🔶 SuperTrend Polyfactor Oscillator
The SuperTrend Polyfactor Oscillator is the heart of this strategy. It is calculated by applying a series of SuperTrend calculations with varying factors, starting from a defined "Starting Factor" and incrementing by a specified "Increment Factor." The indicator length and the chosen price source (e.g., HLC3, HL2) are inputs to the oscillator.
The SuperTrend formula typically calculates an upper and lower band based on the average true range (ATR) and a multiplier (the factor). These bands determine the trend direction. In the FlexiSuperTrend strategy, the oscillator is enhanced by iteratively applying the SuperTrend calculation across different factors. The iterative process allows the strategy to capture both minor and significant trend changes.
For each iteration (indexed by `i`), the following calculations are performed:
1. ATR Calculation: The Average True Range (ATR) is calculated over the specified `indicatorLength`:
ATR_i = ATR(indicatorLength)
2. Upper and Lower Bands Calculation: The upper and lower bands are calculated using the ATR and the current factor:
Upper Band_i = hl2 + (ATR_i * Factor_i)
Lower Band_i = hl2 - (ATR_i * Factor_i)
Here, `Factor_i` starts from `startingFactor` and is incremented by `incrementFactor` in each iteration.
3. Trend Determination: The trend is determined by comparing the indicator source with the upper and lower bands:
Trend_i = 1 (uptrend) if IndicatorSource > Upper Band_i
Trend_i = 0 (downtrend) if IndicatorSource < Lower Band_i
Otherwise, the trend remains unchanged from the previous value.
4. Output Calculation: The output of each iteration is determined based on the trend:
Output_i = Lower Band_i if Trend_i = 1
Output_i = Upper Band_i if Trend_i = 0
This process is repeated for each iteration (from 0 to 19), creating a series of outputs that reflect different levels of trend sensitivity.
Local
🔶 Normalization Process
To make the oscillator values comparable across different market conditions, the deviations between the indicator source and the SuperTrend outputs are normalized. The normalization method can be one of the following:
1. Max-Min Normalization: The deviations are normalized based on the range of the deviations:
Normalized Value_i = (Deviation_i - Min Deviation) / (Max Deviation - Min Deviation)
2. Absolute Sum Normalization: The deviations are normalized based on the sum of absolute deviations:
Normalized Value_i = Deviation_i / Sum of Absolute Deviations
This normalization ensures that the oscillator values are within a consistent range, facilitating more reliable trend analysis.
For more details:
🔶 Multi-Step Take Profit Mechanism
One of the unique features of this strategy is the multi-step take profit mechanism. This allows traders to lock in profits at multiple levels as the market moves in their favor. The strategy uses three take profit levels, each defined as a percentage increase (for long trades) or decrease (for short trades) from the entry price.
1. First Take Profit Level: Calculated as a percentage increase/decrease from the entry price:
TP_Level1 = Entry Price * (1 + tp_level1 / 100) for long trades
TP_Level1 = Entry Price * (1 - tp_level1 / 100) for short trades
The strategy exits a portion of the position (defined by `tp_percent1`) when this level is reached.
2. Second Take Profit Level: Similar to the first level, but with a higher percentage:
TP_Level2 = Entry Price * (1 + tp_level2 / 100) for long trades
TP_Level2 = Entry Price * (1 - tp_level2 / 100) for short trades
The strategy exits another portion of the position (`tp_percent2`) at this level.
3. Third Take Profit Level: The final take profit level:
TP_Level3 = Entry Price * (1 + tp_level3 / 100) for long trades
TP_Level3 = Entry Price * (1 - tp_level3 / 100) for short trades
The remaining portion of the position (`tp_percent3`) is exited at this level.
This multi-step approach provides a balance between securing profits and allowing the remaining position to benefit from continued favorable market movement.
█ Trade Direction
The strategy allows traders to specify the trade direction through the `tradeDirection` input. The options are:
1. Both: The strategy will take both long and short positions based on the entry signals.
2. Long: The strategy will only take long positions.
3. Short: The strategy will only take short positions.
This flexibility enables traders to tailor the strategy to their market outlook or current trend analysis.
█ Usage
To use the Multi-Step FlexiSuperTrend strategy, traders need to set the input parameters according to their trading style and market conditions. The strategy is designed for versatility, allowing for various market environments, including trending and ranging markets.
Traders can also adjust the multi-step take profit levels and percentages to match their risk management and profit-taking preferences. For example, in highly volatile markets, traders might set wider take profit levels with smaller percentages at each level to capture larger price movements.
The normalization method and the incremental factor can be fine-tuned to adjust the sensitivity of the SuperTrend Polyfactor Oscillator, making the strategy more responsive to minor market shifts or more focused on significant trends.
█ Default Settings
The default settings of the strategy are carefully chosen to provide a balanced approach between risk management and profit potential. Here is a breakdown of the default settings and their effects on performance:
1. Indicator Length (10): This parameter controls the lookback period for the ATR calculation. A shorter length makes the strategy more sensitive to recent price movements, potentially generating more signals. A longer length smooths out the ATR, reducing sensitivity but filtering out noise.
2. Starting Factor (0.618): This is the initial multiplier used in the SuperTrend calculation. A lower starting factor makes the SuperTrend bands closer to the price, generating more frequent trend changes. A higher starting factor places the bands further away, filtering out minor fluctuations.
3. Increment Factor (0.382): This parameter controls how much the factor increases with each iteration of the SuperTrend calculation. A smaller increment factor results in more gradual changes in sensitivity, while a larger increment factor creates a wider range of sensitivity across the iterations.
4. Normalization Method (None): The default is no normalization, meaning the raw deviations are used. Normalization methods like Max-Min or Absolute Sum can make the deviations more consistent across different market conditions, improving the reliability of the oscillator.
5. Take Profit Levels (2%, 8%, 18%): These levels define the thresholds for exiting portions of the position. Lower levels (e.g., 2%) capture smaller profits quickly, while higher levels (e.g., 18%) allow positions to run longer for more significant gains.
6. Take Profit Percentages (30%, 20%, 15%): These percentages determine how much of the position is exited at each take profit level. A higher percentage at the first level locks in more profit early, reducing exposure to market reversals. Lower percentages at higher levels allow for a portion of the position to benefit from extended trends.
Fear/Greed Zone Reversals [UAlgo]The "Fear/Greed Zone Reversals " indicator is a custom technical analysis tool designed for TradingView, aimed at identifying potential reversal points in the market based on sentiment zones characterized by fear and greed. This indicator utilizes a combination of moving averages, standard deviations, and price action to detect when the market transitions from extreme fear to greed or vice versa. By identifying these critical turning points, traders can gain insights into potential buy or sell opportunities.
🔶 Key Features
Customizable Moving Averages: The indicator allows users to select from various types of moving averages (SMA, EMA, WMA, VWMA, HMA) for both fear and greed zone calculations, enabling flexible adaptation to different trading strategies.
Fear Zone Settings:
Fear Source: Select the price data point (e.g., close, high, low) used for Fear Zone calculations.
Fear Period: This defines the lookback window for calculating the Fear Zone deviation.
Fear Stdev Period: This sets the period used to calculate the standard deviation of the Fear Zone deviation.
Greed Zone Settings:
Greed Source: Select the price data point (e.g., close, high, low) used for Greed Zone calculations.
Greed Period: This defines the lookback window for calculating the Greed Zone deviation.
Greed Stdev Period: This sets the period used to calculate the standard deviation of the Greed Zone deviation.
Alert Conditions: Integrated alert conditions notify traders in real-time when a reversal in the fear or greed zone is detected, allowing for timely decision-making.
🔶 Interpreting Indicator
Greed Zone: A Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity.
Fear Zone Reversal: A Fear Zone is highlighted when the price deviates significantly below the chosen moving average of the selected price source. This suggests market sentiment might be leaning towards fear, potentially indicating a buying opportunity. When the indicator identifies a reversal from a fear zone, it suggests that the market is transitioning from a period of intense selling pressure to a more neutral or potentially bullish state. This is typically indicated by an upward arrow (▲) on the chart, signaling a potential buy opportunity. The fear zone is characterized by high price volatility and overselling, making it a crucial point for traders to consider entering the market.
Greed Zone Reversal: Conversely, a Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity. When the indicator detects a reversal from a greed zone, it indicates that the market may be moving from an overbought condition back to a more neutral or bearish state. This is marked by a downward arrow (▼) on the chart, suggesting a potential sell opportunity. The greed zone is often associated with overconfidence and high buying activity, which can precede a market correction.
🔶 Why offer multiple moving average types?
By providing various moving average types (SMA, EMA, WMA, VWMA, HMA) , the indicator offers greater flexibility for traders to tailor the indicator to their specific trading strategies and market preferences. Different moving averages react differently to price data and can produce varying signals.
SMA (Simple Moving Average): Provides an equal weighting to all data points within the specified period.
EMA (Exponential Moving Average): Gives more weight to recent data points, making it more responsive to price changes.
WMA (Weighted Moving Average): Allows for custom weighting of data points, providing more flexibility in the calculation.
VWMA (Volume Weighted Moving Average): Considers both price and volume data, giving more weight to periods with higher trading volume.
HMA (Hull Moving Average): A combination of weighted moving averages designed to reduce lag and provide a smoother curve.
Offering multiple options allows traders to:
Experiment: Traders can try different moving averages to see which one produces the most accurate signals for their specific market.
Adapt to different market conditions: Different market conditions may require different moving average types. For example, a fast-moving market might benefit from a faster moving average like an EMA, while a slower-moving market might be better suited to a slower moving average like an SMA.
Personalize: Traders can choose the moving average that best aligns with their personal trading style and risk tolerance.
In essence, providing a variety of moving average types empowers traders to create a more personalized and effective trading experience.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Premarket Std Dev BandsOverview
The Premarket Std Dev Bands indicator is a powerful Pine Script tool designed to help traders gain deeper insights into the premarket session's price movements. This indicator calculates and displays the standard deviation bands for premarket trading, providing valuable information on price volatility and potential support and resistance levels during the premarket hours.
Key Features
Premarket Focus: Specifically designed to analyze price movements during the premarket session, offering unique insights not available with traditional indicators.
Customizable Length: Users can adjust the averaging period for calculating the standard deviation, allowing for tailored analysis based on their trading strategy.
Standard Deviation Bands: Displays both 1 and 2 standard deviation bands, helping traders identify significant price movements and potential reversal points.
Real-Time Updates: Continuously updates the premarket open and close prices, ensuring the bands are accurate and reflective of current market conditions.
How It Works
Premarket Session Identification: The script identifies when the current bar is within the premarket session.
Track Premarket Prices: It tracks the open and close prices during the premarket session.
Calculate Premarket Moves: Once the premarket session ends, it calculates the price movement and stores it in an array.
Compute Averages and Standard Deviation: The script calculates the simple moving average (SMA) and standard deviation of the premarket moves over a specified period.
Plot Standard Deviation Bands: Based on the calculated standard deviation, it plots the 1 and 2 standard deviation bands around the premarket open price.
Usage
To utilize the Premarket Std Dev Bands indicator:
Add the script to your TradingView chart.
Adjust the Length input to set the averaging period for calculating the standard deviation.
Observe the plotted standard deviation bands during the premarket session to identify potential trading opportunities.
Benefits
Enhanced Volatility Analysis: Understand price volatility during the premarket session, which can be crucial for making informed trading decisions.
Support and Resistance Levels: Use the standard deviation bands to identify key support and resistance levels, aiding in better entry and exit points.
Customizable and Flexible: Tailor the averaging period to match your trading style and strategy, making this indicator versatile for various market conditions.
VWAP Bands [UAlgo]The "VWAP Bands " indicator is designed to provide traders with valuable insights into market trends and potential support/resistance levels using Volume Weighted Average Price (VWAP) bands. This indicator integrates the core concepts of VWAP with additional trend analysis features, making it a versatile tool for both range trading and trend-following strategies.
The VWAP bands are plotted based on the standard deviation multipliers, creating upper and lower bands around the VWAP. These bands serve as dynamic support and resistance levels. When the price approaches these bands, traders can anticipate potential reversals or continuations of the current trend. Additionally, the indicator provides visual cues for trend strength and potential trend changes, helping traders make informed decisions in various market conditions.
🔶 Settings
Source (Data Source): The data source for VWAP calculations. The default setting is the typical price (HLC3), which is the average of the high, low, and close prices.
Length: The number of bars used in the VWAP calculation. This determines the lookback period for the indicator.
Standard Deviation Multiplier: The multiplier applied to the standard deviation to create the primary upper and lower VWAP bands. This setting controls the distance of the bands from the VWAP.
Secondary Standard Deviation Multiplier: The multiplier applied to the standard deviation to create the secondary upper and lower VWAP bands, providing additional levels of support and resistance.
Display Trend: A toggle to enable or disable the display of the trend analysis feature. When enabled, the indicator highlights trend strength and potential trend changes.
Display Trend Crossovers: A toggle to enable or disable the display of trend crossover signals. When enabled, the indicator plots shapes to indicate where trend switches are likely occurring.
🔶 Calculations
The calculations behind the "VWAP Bands " indicator begin with determining the Volume Weighted Average Price (VWAP), which provides a comprehensive view of the average price of an asset, weighted by trading volume. This gives a more accurate representation of the asset's true average price over a specified period.
The first step in this process involves summing the trading volume over a chosen period, typically represented by the length parameter. Simultaneously, the product of the price (usually an average of the high, low, and close prices) and the trading volume is calculated and summed. By dividing this cumulative price-volume product by the total volume, we obtain the VWAP value. This VWAP serves as the central anchor around which the price action oscillates.
To enhance the utility of VWAP, we introduce standard deviation calculations. Standard deviation measures the extent of price dispersion from the VWAP, providing insight into price volatility. By calculating the variance (which involves the squared deviations of price) and then taking its square root, we derive the standard deviation. This helps in understanding how far prices typically stray from the VWAP.
With the VWAP and standard deviation in hand, we then establish upper and lower bands by adding and subtracting multiples of the standard deviation from the VWAP. These bands act as dynamic support and resistance levels, adapting to changes in market volatility. The primary bands, set by the first standard deviation multiplier, are augmented by secondary bands defined by a larger multiplier, offering additional layers of potential support and resistance.
It also integrates trend analysis, highlighting areas where the price action suggests a strong or weak trend. This is achieved by overlaying colored zones above and below the bands, indicating the strength and direction of the trend. When the price crosses these bands, it signals potential trend changes, aiding traders in making timely decisions.
🔶 Disclaimer
The "VWAP Bands " indicator is provided for educational and informational purposes only. It is not intended as financial advice and should not be construed as such.
Trading involves significant risk and may not be suitable for all investors. Before using this indicator or making any investment decisions, it is important to conduct thorough research and consider your financial situation.
Options Overlay [Lite] IVR IV Skew Delta Expmv MurreyMath Expiry𝗡𝗼𝗻-𝗼𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝗧𝗢𝗦 𝗮𝗻𝗱 𝗧𝗮𝘀𝘁𝘆𝗧𝗿𝗮𝗱𝗲 𝗹𝗶𝗸𝗲 𝗜𝗩𝗥 𝗢𝗽𝘁𝗶𝗼𝗻𝘀 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘁𝗼𝗼𝗹 𝘄𝗶𝘁𝗵 𝗱𝗲𝗹𝗮𝘆𝗲𝗱 𝗼𝗽𝘁𝗶𝗼𝗻 𝗰𝗵𝗮𝗶𝗻 𝗱𝗮𝘁𝗮
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✅ Enhanced Murrey Math levels (horizontal scale)
✅ Options expirations (vertical scale)
Designed to help you assess market conditions and make well-informed trading decisions, this tool is an essential addition for every serious options trader!
Ticker Information:
This indicator is currently implemented for 5 liquid tickers: NASDAQ:AAPL NASDAQ:AMZN AMEX:DIA NYSE:ORCL and NASDAQ:TSLA
How does the indicator work and why is it unique?
This Pine Script indicator is a complex tool designed to provide various option metrics and visualization tools for options market traders. The indicator extracts raw options data from an external data provider (ORATS), processes and refines the delayed data package using pineseed, and sends it to TradingView, visualizing the data using specific formulas (see detailed below) or interpolated values (e.g., delta distances). This method of incorporating options data into a visualization framework is unique and entirely innovative on TradingView.
The indicator aims to offer a comprehensive view of the current state of options for the implemented instruments, including implied volatility (IV), IV rank (IVR), options skew, and expected market movements, which are objectively measured as detailed below.
The options metrics we display may be familiar to options traders from various major brokerage platforms such as TastyTrade, IBKR, TOS, Tradier, TD Ameritrade, Schwab, etc.
Key Features:
IV Rank (IVR) : The implied volatility rank compares the current IV to the lowest and highest values over the past 52 weeks. The IVR indicator helps determine whether options are relatively cheap or expensive.
IV Average (IVx) : The implied volatility displayed in the options chain, calculated similarly to the VIX. IVx values are aggregated within the 35-70 day expiration cycle.
IV Change (5 days) : The change in implied volatility over the past five trading days. This indicator provides a quick insight into the recent changes in IV.
Expected Move (Exp. Move) : The expected movement for the options expiration cycle, calculated using the price of the ATM (at-the-money) straddle, the first OTM (out-of-the-money) strangle, and the second OTM strangle.
Options Skew : The price difference between put and call options with the same expiration date. Vertical and horizontal skew indicators help understand market sentiment and potential price movements.
Visualization Tools:
Informational IVR Panel : A tabular display mode that presents the selected indicators on the chart. The panel’s placement, size, and content are customizable, including color and tooltip settings.
1 STD, Delta, and Expected Move : Visualization of fundamental classic options metrics corresponding to expirations with bell curves.
Colored Label Tooltips : Detailed tooltips above the bell curves showing options metrics for each expiration.
Adaptive Murrey Math Lines : A horizontal line system based on the principles of Murrey Math Lines, helping identify important price levels and market structures.
Expiration Lines : Displays both monthly and weekly options expirations. The indicator supports various color and style settings, as well as the regulation of the number of expirations displayed.
🟨 𝗗𝗘𝗧𝗔𝗜𝗟𝗘𝗗 𝗗𝗢𝗖𝗨𝗠𝗘𝗡𝗧𝗔𝗧𝗜𝗢𝗡 🟨
🔶 Auto-Updating Option Metrics and Curved Lines
🔹 Interpolated DELTA Curves (16,20,25,30,40)
In our indicator, the curve layer settings allow you to choose the delta value for displaying the delta curve: 16, 20, 25, 30, or even 40. The color of the curve can be customized, and you can also hide the delta curve by selecting the "-" option.
It's important to mention that we display interpolated deltas from the actual option chain of the underlying asset using the Black-Scholes model. This ensures that the 16 delta truly reflects the theoretical, but accurate, 16 delta distance. (For example, deltas shown by brokerages for individual strikes are rounded; a 0.16 delta might actually be 0.1625.)
🔹 Expected Move Curve (Exp.mv)
The expected move is the predicted dollar change in the underlying stock's price by a given option's expiration date, with 68% certainty. It is calculated using the expiration's pricing and implied volatility levels. We chose the TastyTrade method for calculating expected move, as we found it to be the most expressive.
Expected Move Calculation
Expected Move = (ATM straddle price x 0.6) + (1st OTM strangle price x 0.3) + (2nd OTM strangle price x 0.1)
For example , if stock XYZ is trading at 121 and the ATM straddle is 4.40, the 120/122 strangle is 3.46, and the 119/123 strangle is 2.66, the expected move is calculated as follows: 4.40 x 0.60 = 2.64; 3.46 x 0.30 = 1.04; 2.66 x 0.10 = 0.27; Expected move = 2.64 + 1.04 + 0.27 = ±3.9
In this example below, the TastyTrade platform indicates the expected move on the option chain with a brown color, and the exact value is displayed behind the ± symbol for each expiration. By default, we also use brown for this indication, but this can be changed or the curve display can be turned off.
🔹 Standard Deviation Curve (1 STD)
One standard deviation of a stock encompasses approximately 68.2% of outcomes in a distribution of occurrences based on current implied volatility.
We use the expected move formula to calculate the one standard deviation range of a stock. This calculation is based on the days-to-expiration (DTE) of our option contract, the stock price, and the implied volatility of a stock:
Calculation:
Standard Deviation = Closing Price * Implied Volatility * sqrt(Days to Expiration / 365)
According to options literature, there is a 68% probability that the underlying asset will fall within this one standard deviation range at expiration.
If the 1 STD and Exp.mv displays are both enabled, the indicator fills the area between them with a light gray color. This is because both represent probability distributions that appear as a "bell curve" when graphed, making it visually appealing.
Tip and Note:
The 1 STD line might appear jagged at times , which does not indicate a problem with the indicator. This is normal immediately after market open (e.g., during the first data refresh of the day) or if the expirations are illiquid (e.g., weekly expirations). The 1 STD value is calculated based on the aggregated IVx for the expirations, and the aggregated IVx value for weekly expirations updates less frequently due to lower trading volume. In such cases, we recommend enabling the "Only Monthly Expirations" option to smooth out the bell curve.
∑ Quant Observation:
The values of the expected move and the 1st standard deviation (1STD) will not match because they use different calculation methods, even though both are referred to as representing 68% of the underlying asset's movement in options literature. The expected move is based on direct market pricing of ATM options. The 1STD, on the other hand, uses the averaged implied volatility (IVX) for the given expiration to determine its value. Based on our experience, it is better to consider the area between the expected move and the 1STD as the true representation of the original 68% rule.
🔶 IVR Dashboard Panel Rows
🔹 IVR (IV Rank)
The Implied Volatility Rank (IVR) indicator helps options traders assess the current level of implied volatility (IV) in comparison to the past 52 weeks. IVR is a useful metric to determine whether options are relatively cheap or expensive. This can guide traders on whether to buy or sell options. We calculate IVrank, like TastyTrade does.
IVR Calculation:
IV Rank = (current IV - 52 week IV low) / (52 week IV high - 52 week IV low)
IVR Levels and Interpretations:
IVR 0-10 (Green): Very low implied volatility rank. Options might be "cheap," potentially a good time to buy options.
IVR 10-35 (White): Normal implied volatility rank. Options pricing is relatively standard.
IVR 35-50 (Orange): Almost high implied volatility rank.
IVR 50-75 (Red): Definitely high implied volatility rank. Options might be "expensive," potentially a good time to sell options for higher premiums.
IVR above 75 (Highlighted Red): Ultra high implied volatility rank. Indicates very high levels, suggesting a favorable time for selling options.
The panel refreshes automatically if the symbol is implemented. You can hide the panel or change the position and size.
🔹IVx (Implied Volatility Index)
The Implied Volatility Index (IVx) displayed in the option chain is calculated similarly to the VIX. The Cboe uses standard and weekly SPX options to measure the expected volatility of the S&P 500. A similar method is utilized to calculate IVx for each option expiration cycle.
For our purposes on the IVR Panel, we aggregate the IVx values specifically for the 35-70 day monthly expiration cycle . This aggregated value is then presented in the screener and info panel, providing a clear and concise measure of implied volatility over this period.
IVx Color coding:
IVx above 30 is displayed in orange.
IVx above 60 is displayed in red
IVx on curve:
The IVx values for each expiration can be viewed by hovering the mouse over the colored tooltip labels above the Curve.
IVx avg on IVR panel :
If the option is checked in the IVR panel settings, the IVR panel will display the average IVx values up to the optimal expiration.
Important Note:
The IVx value alone does not provide sufficient context. There are stocks that inherently exhibit high IVx values. Therefore, it is crucial to consider IVx in conjunction with the Implied Volatility Rank (IVR), which measures the IVx relative to its own historical values. This combined view helps in accurately assessing the significance of the IVx in relation to the specific stock's typical volatility behavior.
This indicator offers traders a comprehensive view of implied volatility, assisting them in making informed decisions by highlighting both the absolute and relative volatility measures.
🔹IVx 5 days change %
We are displaying the five-day change of the IV Index (IVx value). The IV Index 5-Day Change column provides quick insight into recent expansions or decreases in implied volatility over the last five trading days.
Traders who expect the value of options to decrease might view a decrease in IVX as a positive signal. Strategies such as Strangle and Ratio Spread can benefit from this decrease.
On the other hand, traders anticipating further increases in IVX will focus on the rising IVX values. Strategies like Calendar Spread or Diagonal Spread can take advantage of increasing implied volatility.
This indicator helps traders quickly assess changes in implied volatility, enabling them to make informed decisions based on their trading strategies and market expectations.
🔹 Vertical Pricing Skew
At TanukiTrade, Vertical Pricing Skew refers to the difference in pricing between put and call options with the same expiration date at the same distance (at expected move). We analyze this skew to understand market sentiment. This is the same formula used by TastyTrade for calculations.
We calculate the interpolated strike price based on the expected move , taking into account the neighboring option prices and their distances. This allows us to accurately determine whether the CALL or PUT options are more expensive.
PUT Skew (red): Put options are more expensive than call options, indicating the market expects a downward move (▽). If put options are more expensive by more than 20% at the same expected move distance, we color it lighter red.
CALL Skew (green): Call options are more expensive than put options, indicating the market expects an upward move (△). If call options are priced more than 30% higher at the examined expiration, we color it lighter green.
Vertical Skew on Curve:
The degree of vertical pricing skew for each expiration can be viewed by hovering over the points above the curve. Hover with mouse for more information.
Vertical Skew on IVR panel:
We focus on options with 35-70 days to expiration (DTE) for optimal analysis in case of vertical skew. Hover with mouse for more information.
This approach helps us gauge market expectations accurately, providing insights into potential price movements. Remember, we always evaluate the skew at the expected move using linear interpolation to determine the theoretical pricing of options.
🔹 Delta Skew 🌪️ (Twist)
We have a new metric that examines which monthly expiration indicates a "Delta Skew Twist" where the 16 delta deviates from the monthly STD. This is important because, under normal circumstances, the 16 delta is positioned between the expected move and the standard deviation (STD1) line (see Exp.mv & 1STD exact definitions above). However, if the interpolated 16 delta line exceeds the STD1 line either upwards or downwards, it represents a special case of vertical skew on the option chain.
Normal case : exp.move < delta16 < std1
Delta Skew Twist: exp.move < std1 < delta16
We indicate this with direction-specific colors (red/green) on the delta line. We also color the section of the delta curve affected by the delta skew in this case, even if you choose to display a lower delta, such as 30, instead of 16.
If "Colored Labels with Tooltips" is enabled, we also display a 🌪️ symbol in the tooltip for the expirations affected by Delta Skew.
If you have enabled the display of 'Vertical Pricing Skew' on the IVR Panel, a 🌪️ symbol will also appear next to the value of the vertical skew, and the tooltip will indicate from which expiration Delta Skew is observed.
🔹 Horizontal IVx Skew
In options pricing, it is typically expected that the implied volatility (IVx) increases for options with later expiration dates. This means that options further out in time are generally more expensive. At TanukiTrade, we refer to the phenomenon where this expectation is reversed—when the IVx decreases between two consecutive expirations—as Horizontal Skew or IVx Skew.
Horizontal IVx Skew occurs when: Front Expiry IVx < Back Expiry IVx
This scenario can create opportunities for traders who prefer diagonal or calendar strategies . Based on our experience, we categorize Horizontal Skew into two types:
Weekly Horizontal Skew:
When IVx skew is observed between two consecutive non-monthly expirations, the displayed value is the rounded-up percentage difference. On hover, the approximate location of this skew is also displayed. The precise location can be seen on this indicator.
Monthly Horizontal Skew:
When IVx skew is observed between two consecutive monthly expirations , the displayed value is the rounded-up percentage difference. On hover, the approximate location of this skew is also displayed. The precise location can be seen on our Overlay indicator.
The Monthly Vertical IVx skew is consistently more liquid than the weekly vertical IVx skew. Weekly Horizontal IVx Skew may not carry relevant information for symbols not included in the 'Weeklies & Volume Masters' preset in our Options Screener indicator.
If the options chain follows the normal IVx pattern, no skew value is displayed.
Color codes or tooltip labels above curve:
Gray - No horizontal skew;
Purple - Weekly horizontal skew;
BigBlue - Monthly horizontal skew
The display of monthly and weekly IVx skew can be toggled on or off on the IVR panel. However, if you want to disable the colored tooltips above the curve, this can only be done using the "Colored labels with tooltips" switch.
We indicate this range with colorful information bubbles above the upper STD line.
🔶 The Option Trader’s GRID System: Adaptive MurreyMath + Expiry Lines
At TanukiTrade, we utilize Enhanced MurreyMath and Expiry lines to create a dynamic grid system, unlike the basic built-in vertical grids in TradingView, which provide no insight into specific price levels or option expirations.
These grids are beneficial because they provide a structured layout, making important price levels visible on the chart. The grid automatically resizes as the underlying asset's volatility changes, helping traders identify expected movements for various option expirations.
The Option Trader’s GRID System part of this indicator can be used without limitations for all instruments . There are no type or other restrictions, and it automatically scales to fit every asset. Even if we haven't implemented the option metrics for a particular underlying asset, the GRID system will still function!
🔹 SETUP OF YOUR OPTIONS GRID SYSTEM
You can setup your new grid system in 3 easy steps!
STEP1: Hide default horizontal grid lines in TradingView
Right-click on an empty area of your chart, then select “Settings.” In the Chart settings -> Canvas -> Grid lines section, disable the display of horizontal lines to avoid distraction.
SETUP STEP2: Scaling fix
Right-click on the price scale on the right side, then select "Scale price chart only" to prevent the chart from scaling to the new horizontal lines!
STEP3: Enable Tanuki Options Grid
As a final step, make sure that both the vertical (MurreyMath) and horizontal (Expiry) lines are enabled in the Grid section of our indicator.
You are done, enjoy the new grid system!
🔹 HORIZONTAL: Enhanced MurreyMath Lines
Murrey Math lines are based on the principles observed by William Gann, renowned for his market symmetry forecasts. Gann's techniques, such as Gann Angles, have been adapted by Murrey to make them more accessible to ordinary investors. According to Murrey, markets often correct at specific price levels, and breakouts or returns to these levels can signal good entry points for trades.
At TanukiTrade, we enhance these price levels based on our experience , ensuring a clear display. We acknowledge that while MurreyMath lines aren't infallible predictions, they are useful for identifying likely price movements over a given period (e.g., one month) if the market trend aligns.
Our opinion: MurreyMath lines are not crystal balls (like no other tool). They should be used to identify that if we are trading in the right direction, the price is likely to reach the next unit step within a unit time (e.g. monthly expiration).
One unit step is the distance between Murrey Math lines, such as between the 0/8 and 1/8 lines. This interval helps identify different quadrants and is crucial for recognizing support and resistance levels.
Some option traders use Murrey Math lines to gauge the movement speed of an instrument over a unit time. A quadrant encompasses 4 unit steps.
Key levels, according to TanukiTrade, include:
Of course, the lines can be toggled on or off, and their default color can also be changed.
🔹 VERTICAL: Expiry Lines
The indicator can display monthly and weekly expirations as dashed lines, with customizable colors. Weekly expirations will always appear in a lighter shade compared to monthly expirations.
Monthly Expiry Lines:
You can turn off the lines indicating monthly expirations, or set the direction (past/future/both) and the number of lines to be drawn.
Weekly Expiry Lines:
You can display weekly expirations pointing to the future. You can also turn them off or specify how many weeks ahead the lines should be drawn.
Of course, the lines can be toggled on or off, and their default color can also be changed.
TIP: Hide default vertical grid lines in TradingView
Right-click on an empty area of your chart, then select “Settings.” In the Chart settings -> Canvas -> Grid lines section, disable the display of vertical lines to avoid distraction. Same, like steps above at MurreyMath lines.
🔶 ADDITIONAL IMPORTANT COMMENTS
- U.S. market only:
Since we only deal with liquid option chains: this option indicator only works for the USA options market and do not include future contracts; we have implemented each selected symbol individually.
- Why is there a slight difference between the displayed data and my live brokerage data? There are two reasons for this, and one is beyond our control.
- Brokerage Calculation Differences:
Every brokerage has slight differences in how they calculate metrics like IV and IVx. If you open three windows for TOS, TastyTrade, and IBKR side by side, you will notice that the values are minimally different. We had to choose a standard, so we use the formulas and mathematical models described by TastyTrade when analyzing the options chain and drawing conclusions.
- Option-data update frequency:
According to TradingView's regulations and guidelines, we can update external data a maximum of 5 times per day. We strive to use these updates in the most optimal way:
(1st update) 15 minutes after U.S. market open
(2nd, 3rd, 4th updates) 1.5–3 hours during U.S. market open hours
(5th update) 10 minutes before market close.
You don’t need to refresh your window, our last refreshed data-pack is always automatically applied to your indicator , and you can see the time elapsed since the last update at the bottom of your indicator.
- Skewed Curves:
The delta, expected move, and standard deviation curves also appear relevantly on a daily or intraday timeframe. Data loss is experienced above a daily timeframe: this is a TradingView limitation.
- Weekly illiquid expiries:
Especially for instruments where weekly options are illiquid: the weekly expiration STD1 data is not relevant. In these cases, we recommend checking in the "Display only Monthly labels" checkbox to avoid displaying not relevant weekly options expirations.
-Timeframe Issues:
Our option indicator visualizes relevant data on a daily resolution. If you see strange or incorrect data (e.g., when the options data was last updated), always switch to a daily (1D) timeframe. If you still see strange data, please contact us.
Disclaimer:
Our option indicator uses approximately 15min-3 hour delayed option market snapshot data to calculate the main option metrics. Exact realtime option contract prices are never displayed; only derived metrics and interpolated delta are shown to ensure accurate and consistent visualization. Due to the above, this indicator can only be used for decision support; exclusive decisions cannot be made based on this indicator . We reserve the right to make errors.This indicator is designed for options traders who understand what they are doing. It assumes that they are familiar with options and can make well-informed, independent decisions. We work with public data and are not a data provider; therefore, we do not bear any financial or other liability.
HilalimSB Strategy HilalimSB A Wedding Gift 🌙
What is HilalimSB🌙?
First of all, as mentioned in the title, HilalimSB is a wedding gift.
HilalimSB - Revealing the Secrets of the Trend
HilalimSB is a powerful indicator designed to help investors analyze market trends and optimize trading strategies. Designed to uncover the secrets at the heart of the trend, HilalimSB stands out with its unique features and impressive algorithm.
Hilalim Algorithm and Fixed ATR Value:
HilalimSB is equipped with a special algorithm called "Hilalim" to detect market trends. This algorithm can delve into the depths of price movements to determine the direction of the trend and provide users with the ability to predict future price movements. Additionally, HilalimSB uses its own fixed Average True Range (ATR) value. ATR is an indicator that measures price movement volatility and is often used to determine the strength of a trend. The fixed ATR value of HilalimSB has been tested over long periods and its reliability has been proven. This allows users to interpret the signals provided by the indicator more reliably.
ATR Calculation Steps
1.True Range Calculation:
+ The True Range (TR) is the greatest of the following three values:
1. Current high minus current low
2. Current high minus previous close (absolute value)
3. Current low minus previous close (absolute value)
2.Average True Range (ATR) Calculation:
-The initial ATR value is calculated as the average of the TR values over a specified period
(typically 14 periods).
-For subsequent periods, the ATR is calculated using the following formula:
ATRt=(ATRt−1×(n−1)+TRt)/n
Where:
+ ATRt is the ATR for the current period,
+ ATRt−1 is the ATR for the previous period,
+ TRt is the True Range for the current period,
+ n is the number of periods.
Pine Script to Calculate ATR with User-Defined Length and Multiplier
Here is the Pine Script code for calculating the ATR with user-defined X length and Y multiplier:
//@version=5
indicator("Custom ATR", overlay=false)
// User-defined inputs
X = input.int(14, minval=1, title="ATR Period (X)")
Y = input.float(1.0, title="ATR Multiplier (Y)")
// True Range calculation
TR1 = high - low
TR2 = math.abs(high - close )
TR3 = math.abs(low - close )
TR = math.max(TR1, math.max(TR2, TR3))
// ATR calculation
ATR = ta.rma(TR, X)
// Apply multiplier
customATR = ATR * Y
// Plot the ATR value
plot(customATR, title="Custom ATR", color=color.blue, linewidth=2)
This code can be added as a new Pine Script indicator in TradingView, allowing users to calculate and display the ATR on the chart according to their specified parameters.
HilalimSB's Distinction from Other ATR Indicators
HilalimSB emerges with its unique Average True Range (ATR) value, presenting itself to users. Equipped with a proprietary ATR algorithm, this indicator is released in a non-editable form for users. After meticulous testing across various instruments with predetermined period and multiplier values, it is made available for use.
ATR is acknowledged as a critical calculation tool in the financial sector. The ATR calculation process of HilalimSB is conducted as a result of various research efforts and concrete data-based computations. Therefore, the HilalimSB indicator is published with its proprietary ATR values, unavailable for modification.
The ATR period and multiplier values provided by HilalimSB constitute the fundamental logic of a trading strategy. This unique feature aids investors in making informed decisions.
Visual Aesthetics and Clear Charts:
HilalimSB provides a user-friendly interface with clear and impressive graphics. Trend changes are highlighted with vibrant colors and are visually easy to understand. You can choose colors based on eye comfort, allowing you to personalize your trading screen for a more enjoyable experience. While offering a flexible approach tailored to users' needs, HilalimSB also promises an aesthetic and professional experience.
Strong Signals and Buy/Sell Indicators:
After completing test operations, HilalimSB produces data at various time intervals. However, we would like to emphasize to users that based on our studies, it provides the best signals in 1-hour chart data. HilalimSB produces strong signals to identify trend reversals. Buy or sell points are clearly indicated, allowing users to develop and implement trading strategies based on these signals.
For example, let's imagine you wanted to open a position on BTC on 2023.11.02. You are aware that you need to calculate which of the buying or selling transactions would be more profitable. You need support from various indicators to open a position. Based on the analysis and calculations it has made from the data it contains, HilalimSB would have detected that the graph is more suitable for a selling position, and by producing a sell signal at the most ideal selling point at 08:00 on 2023.11.02 (UTC+3 Istanbul), it would have informed you of the direction the graph would follow, allowing you to benefit positively from a 2.56% decline.
Technology and Innovation:
HilalimSB aims to enhance the trading experience using the latest technology. With its innovative approach, it enables users to discover market opportunities and support their decisions. Thus, investors can make more informed and successful trades. Real-Time Data Analysis: HilalimSB analyzes market data in real-time and identifies updated trends instantly. This allows users to make more informed trading decisions by staying informed of the latest market developments. Continuous Update and Improvement: HilalimSB is constantly updated and improved. New features are added and existing ones are enhanced based on user feedback and market changes. Thus, HilalimSB always aims to provide the latest technology and the best user experience.
Social Order and Intrinsic Motivation:
Negative trends such as widespread illegal gambling and uncontrolled risk-taking can have adverse financial effects on society. The primary goal of HilalimSB is to counteract these negative trends by guiding and encouraging users with data-driven analysis and calculable investment systems. This allows investors to trade more consciously and safely.
What is HilalimSB Strategy🌙?
HilalimSB Strategy is a strategy that is supported by the HilalimSB algorithm created by the creator of HilalimSB and continues transactions with take profit and stop loss levels determined by users who strategically and automatically open transactions as a result of the data it receives and automatically closes transactions under necessary conditions. It is a first in the tradingview world with its unique take profit and stop loss markings. HilalimSB Strategy is open to users' initiatives and is a trading strategy developed on BTC.
What does the HilalimSB Strategy target?
The main purpose of HilalimSB Strategy is to reduce the transaction load of traders and to be integrated into various brokerage firms and operated by automatic trading bots, and it is aimed to serve this purpose. In addition to the strategies currently available in the markets, HilalimSB Strategy offers a useful infrastructure to traders with its useful interface. HilalimSB Strategy, which was decided to be published as a result of various calculations, was offered to the users with its unique visual effects after the completion of the testing procedures under market conditions.
HilalimSB Strategy and Heikin Ashi
HilalimSB Strategy produces data in Heikin Ashi chart types, but since Heikin Ashi chart types have their own calculation method, HilalimSB Strategy has been published in a way that cannot produce data in this chart type due to HilalimSB Strategy's ideology of appealing to all types of users, and any confusion that may arise is prevented in this way.
After the necessary conditions determined by the creator of HilalimSB are met, HilalimSB Heikin Ashi will be shared exclusively with invited users only, upon request, to users who request an invitation.
Differences between HilalimSB Strategy and HilalimSB
HilalimSB Strategy has been shared as a strategy and its features have been explained above. HilalimSB is a trading indicator and this is the main difference between them.We can explain it briefly this way.
Here are the differences between indicators and strategies:
1.Purpose and Use:
Indicators: Analyze market data to provide information about price movements and trends. They typically generate buy and sell signals and give traders clues about when to make trades in the market.
Strategies: These are plans for trading based on specific rules. They use signals from indicators and other market data to execute buy and sell transactions.
2.Features:
Indicators: Operate independently and are based on specific mathematical formulas. Examples include moving averages, RSI, and MACD.
Strategies: Combine one or more indicators and other market analysis tools to create a comprehensive trading plan. This plan determines entry and exit points, risk management, and trade size.
3.Scope:
Indicators: Are single analysis tools focusing on specific time frames or price movements.
Strategies: Are comprehensive trading plans that typically involve multiple trades over a certain period.
4.Decision Making:
Indicators: Provide information to traders and help in the decision-making process.
Strategies: Are direct decision-making mechanisms that execute trades automatically according to predetermined rules.
5.Automation:
Indicators: Are mostly interpreted manually and used based on the trader’s discretion.
Strategies: Can be used in automated trading systems and execute trades automatically according to the set rules.
The shared image is a 1-hour chart of BTCUSDC.P determined by the user as 1 percent take profit and 1 percent stop loss. And transactions were opened on Binance with the commission rate determined as 0.017 for the USDC trading pair.
HilalimSB Strategy, which presents users with completely concrete data, has proven itself in testing processes and is a project of SB that aims to reach all user profiles.🌙
Trend Maestro - Linear Regression & Volatility BandsTrend Maestro - Linear Regression & Volatility Bands
Description:
The "Trend Maestro - Linear Regression & Volatility Bands" indicator is meticulously designed to provide traders with a clear understanding of market trends through the application of linear regression techniques and enhanced market data visualization. This tool is essential for traders looking to interpret long-term trends and market stability. Here's how the indicator functions and what makes it a unique addition to your trading toolkit:
1. Linear Regression Calculation:
At the heart of this indicator lies the linear regression calculation, which identifies the primary trend direction over a specified period. It does this by computing a line of best fit through the closing prices, helping to smooth out price fluctuations and highlight the prevailing trend direction. Users have the flexibility to adjust both the length of the regression and the offset period, enabling them to tailor the indicator's responsiveness to different market conditions.
2. Visualization Through Volatility Bands:
The volatility bands, plotted at half, one, two, and three standard deviations around the linear regression line, serve primarily as a visualization tool rather than a basis for investment decisions.
These bands:
Measure the dispersion of price from the trend line, providing a graphical representation of volatility.
Help traders visually assess the market's stability and the reliability of the current trend, with broader bands indicating higher volatility and narrower bands suggesting more stability.
3. Customization Features:
The indicator offers customization options including toggle switches for bar color and the display of SD bands, enhancing visual clarity. These settings allow traders to personalize the display according to their visual preferences and analysis requirements.
By incorporating these elements, the "Trend Maestro - Linear Regression & Volatility Bands" indicator offers a framework for understanding market trends through both quantitative calculations and qualitative visual aids. This makes it a valuable tool for those looking to make informed decisions based on longer-term market observations.
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
