LBR-S310ROC @shrilssOriginally made by Linda Raschke, The S310ROC Indicator combines the Rate of Change (ROC) indicator with the 3-10 Oscillator (Modified MACD) and plots to capture rapid price movements and gauge market momentum.
- Rate of Change (ROC): This component of the indicator measures the percentage change in price over a specified short interval, which can be set by the user (default is 2 days). It is calculated by subtracting the closing price from 'X' days ago from the current close.
- 3-10 Oscillator (MACD; 3,10,16): This is a specialized version of the Moving Average Convergence Divergence (MACD) but uses simple moving averages instead of exponential. Using a fast moving average of 3 days and a slow moving average of 10 days with a smoothing period of 16.
- ROC Dots: A great feature based on the oscillator's readings. Dots are displayed directly on the oscillator or the price chart to provide visual momentum cues:
- Aqua Dots: Appear when all lines (ROC, MACD, Slowline) are sloping downwards, indicating bearish momentum and potentially signaling a sell opportunity.
- White Dots: Appear when all lines are sloping upwards, suggesting bullish momentum and possibly a buy signal.
Volatility
ROC [CHE] with Kernel SelectionIntroduction:
The script titled "ROC with Kernel Selection" utilizes Rate of Change (ROC) to analyze price momentum in financial markets. It incorporates a kernel selection mechanism to smooth ROC values, enhancing clarity in trend identification.
Middle Part:
The script begins by calculating ROC over a specified period using the formula:
roc = (close - close ) / close * 100
The period length determined by the user. The result is plotted alongside a zero line for reference.
The kernel selection aspect allows users to choose from various smoothing techniques:
Linear
Exponential
Epanechnikov
Triangular
Cosine
Each kernel applies a different weighting function to ROC values, influencing the sensitivity and smoothness of the plotted line. Users can customize parameters such as bandwidth and color preferences for up and down movements, facilitating visual interpretation.
The main logic of the script involves iterating through historical data to compute weighted averages of ROC values based on the selected kernel. It adjusts graphical elements dynamically, highlighting changes in momentum direction with color-coded lines and directional symbols (▲ or ▼).
Conclusion:
In conclusion, "ROC with Kernel Selection" offers a flexible toolset for traders and analysts to assess price momentum robustly. By integrating kernel-based smoothing techniques, it enhances the clarity of ROC signals, aiding in the identification of trends and potential reversals in financial markets.
Implied Volatility LevelsOverview:
The Implied Volatility Levels Indicator is a powerful tool designed to visualize different levels of implied volatility on your trading chart. This indicator calculates various implied volatility levels based on historical price data and plots them as dynamic dotted lines, helping traders identify significant market thresholds and potential reversal points.
Features:
Multi-Level Implied Volatility: The indicator calculates and plots multiple levels of implied volatility, including the mean and both positive and negative standard deviation multiples.
Dynamic Updates: The levels update in real-time, reflecting the latest market conditions without cluttering your chart with outdated information.
Customizable Parameters: Users can adjust the lookback period and the standard deviation multiplier to tailor the indicator to their trading strategy.
Visual Clarity: Implied volatility levels are displayed using distinct colors and dotted lines, providing clear visual cues without obstructing the view of price action.
Support for Multiple Levels: Includes additional levels (up to ±5 standard deviations) for in-depth market analysis.
How It Works:
The indicator computes the standard deviation of the closing prices over a user-defined lookback period. It then calculates various implied volatility levels by adding and subtracting multiples of this standard deviation from the mean price. These levels are plotted as dotted lines on the chart, offering traders a clear view of the current market's volatility landscape.
Usage:
Identify Key Levels: Use the plotted lines to spot potential support and resistance levels based on implied volatility.
Analyze Market Volatility: Understand how volatile the market is relative to historical data.
Plan Entry and Exit Points: Make informed trading decisions by observing where the price is in relation to the implied volatility levels.
Parameters:
Lookback Period (Days): The number of days to consider for calculating historical volatility (default is 252 days).
Standard Deviation Multiplier: A multiplier to adjust the distance of the levels from the mean (default is 1.0).
This indicator is ideal for traders looking to incorporate volatility analysis into their technical strategy, providing a robust framework for anticipating market movements and potential reversals.
Dickey-Fuller Test for Mean Reversion and Stationarity **IF YOU NEED EXTRA SPECIAL HELP UNDERSTANDING THIS INDICATOR, GO TO THE BOTTOM OF THE DESCRIPTION FOR AN EVEN SIMPLER DESCRIPTION**
Dickey Fuller Test:
The Dickey-Fuller test is a statistical test used to determine whether a time series is stationary or has a unit root (a characteristic of a time series that makes it non-stationary), indicating that it is non-stationary. Stationarity means that the statistical properties of a time series, such as mean and variance, are constant over time. The test checks to see if the time series is mean-reverting or not. Many traders falsely assume that raw stock prices are mean-reverting when they are not, as evidenced by many different types of statistical models that show how stock prices are almost always positively autocorrelated or statistical tests like this one, which show that stock prices are not stationary.
Note: This indicator uses past results, and the results will always be changing as new data comes in. Just because it's stationary during a rare occurrence doesn't mean it will always be stationary. Especially in price, where this would be a rare occurrence on this test. (The Test Statistic is below the critical value.)
The indicator also shows the option to either choose Raw Price, Simple Returns, or Log Returns for the test.
Raw Prices:
Stock prices are usually non-stationary because they follow some type of random walk, exhibiting positive autocorrelation and trends in the long term.
The Dickey-Fuller test on raw prices will indicate non-stationary most of the time since prices are expected to have a unit root. (If the test statistic is higher than the critical value, it suggests the presence of a unit root, confirming non-stationarity.)
Simple Returns and Log Returns:
Simple and log returns are more stationary than prices, if not completely stationary, because they measure relative changes rather than absolute levels.
This test on simple and log returns may indicate stationary behavior, especially over longer periods. (The test statistic being below the critical value suggests the absence of a unit root, indicating stationarity.)
Null Hypothesis (H0): The time series has a unit root (it is non-stationary).
Alternative Hypothesis (H1): The time series does not have a unit root (it is stationary)
Interpretation: If the test statistic is less than the critical value, we reject the null hypothesis and conclude that the time series is stationary.
Types of Dickey-Fuller Tests:
1. (What this indicator uses) Standard Dickey-Fuller Test:
Tests the null hypothesis that a unit root is present in a simple autoregressive model.
This test is used for simple cases where we just want to check if the series has a consistent statistical property over time without considering any trends or additional complexities.
It examines the relationship between the current value of the series and its previous value to see if the series tends to drift over time or revert to the mean.
2. Augmented Dickey-Fuller (ADF) Test:
Tests for a unit root while accounting for more complex structures like trends and higher-order correlations in the data.
This test is more robust and is used when the time series has trends or other patterns that need to be considered.
It extends the regular test by including additional terms to account for the complexities, and this test may be more reliable than the regular Dickey-Fuller Test.
For things like stock prices, the ADF would be more appropriate because stock prices are almost always trending and positively autocorrelated, while the Dickey-Fuller Test is more appropriate for more simple time series.
Critical Values
This indicator uses the following critical values that are essential for interpreting the Dickey-Fuller test results. The critical values depend on the chosen significance levels:
1% Significance Level: Critical value of -3.43.
5% Significance Level: Critical value of -2.86.
10% Significance Level: Critical value of -2.57.
These critical values are thresholds that help determine whether to reject the null hypothesis of a unit root (non-stationarity). If the test statistic is less than (or more negative than) the critical value, it indicates that the time series is stationary. Conversely, if the test statistic is greater than the critical value, the series is considered non-stationary.
This indicator uses a dotted blue line by default to show the critical value. If the test-static, which is the gray column, goes below the critical value, then the test-static will become yellow, and the test will indicate that the time series is stationary or mean reverting for the current period of time.
What does this mean?
This is the weekly chart of BTCUSD with the Dickey-Fuller Test, with a length of 100 and a critical value of 1%.
So basically, in the long term, mean-reversion strategies that involve raw prices are not a good idea. You don't really need a statistical test either for this; just from seeing the chart itself, you can see that prices in the long term are trending and no mean reversion is present.
For the people who can't understand that the gray column being above the blue dotted line means price doesn't mean revert, here is a more simple description (you know you are):
Average (I have to include the meaning because they may not know what average is): The middle number is when you add up all the numbers and then divide by how many numbers there are. EX: If you have the numbers 2, 4, and 6, you add them up to get 12, and then divide by 3 (because there are 3 numbers), so the average is 4. It tells you what a typical number is in a group of numbers.
This indicator checks if a time series (like stock prices) tends to return to its average value or time.
Raw prices, which is just the regular price chart, are usually not mean-reverting (It's "always" positively autocorrelating but this group of people doesn't like that word). Price follows trends.
Simple returns and log returns are more likely to have periods of mean reversion.
How to use it:
Gray Column (the gray bars) Above the Blue Dotted Line: The price does not mean revert (non-stationary).
Gray Column Below Blue Line: The time series mean reverts (stationary)
So, if the test statistic (gray column) is below the critical value, which is the blue dotted line, then the series is stationary and mean reverting, but if it is above the blue dotted line, then the time series is not stationary or mean reverting, and strategies involving mean reversion will most likely result in a loss given enough occurrences.
[SGM GARCH Volatility]I'm excited to share with you a Pine Script™ that I developed to analyze GARCH (Generalized Autoregressive Conditional Heteroskedasticity) volatility. This script allows you to calculate and plot GARCH volatility on TradingView. Let's see together how it works!
Introduction
Volatility is a key concept in finance that measures the variation in prices of a financial asset. The GARCH model is a statistical method that predicts future volatility based on past volatilities and prediction residuals (errors).
Indicator settings
We define several parameters for our indicator:
length = input.int(20, title="Length")
p = input.int(1, title="Lag order (p)")
q = input.int(1, title="Degree of moving average (q)")
cluster_value = input(0.2,title="cluster value")
length: The period used for the calculations, default 20.
p: The order of the delay for the GARCH model.
q: The degree of the moving average for the GARCH model.
cluster_value: A threshold value used to color the graph.
Calculation of logarithmic returns
We calculate logarithmic returns to capture price changes:
logReturns = math.log(close) - math.log(close )
Initializing arrays
We initialize arrays to store residuals and volatilities:
var float residuals = array.new_float(length, 0)
var float volatilities = array.new_float(length, 0)
We add the new logarithmic returns to the tables and keep their size constant:
array.unshift(residuals, logReturns)
if (array.size(residuals) > length)
array.pop(residuals)
We then calculate the mean and variance of the residuals:
meanResidual = array.avg(residuals)
varianceResidual = array.stdev(residuals, meanResidual)
volatility = math.sqrt(varianceResidual)
We update the volatility table with the new value:
array.unshift(volatilities, volatility)
if (array.size(volatilities) > length)
array.pop(volatilities)
GARCH volatility is calculated from accumulated data:
var float garchVolatility = na
if (array.size(volatilities) >= length and array.size(residuals) >= length)
alpha = 0.1 // Alpha coefficient
beta = 0.85 // Beta coefficient
omega = 0.01 // Omega constant
sumVolatility = 0.0
for i = 0 to p-1
sumVolatility := sumVolatility + beta * math.pow(array.get(volatilities, i), 2)
sumResiduals = 0.0
for j = 0 to q-1
sumResiduals := sumResiduals + alpha * math.pow(array.get(residuals, j), 2)
garchVolatility := math.sqrt(omega + sumVolatility + sumResiduals)
Plot GARCH volatility
We finally plot the GARCH volatility on the chart and add horizontal lines for easier visual analysis:
plt = plot(garchVolatility, title="GARCH Volatility", color=color.rgb(33, 149, 243, 100))
h1 = hline(0.1)
h2 = plot(cluster_value)
h3 = hline(0.3)
colorGarch = garchVolatility > cluster_value ? color.red: color.green
fill(plt, h2, color = colorGarch)
colorGarch: Determines the fill color based on the comparison between garchVolatility and cluster_value.
Using the script in your trading
Incorporating this Pine Script™ into your trading strategy can provide you with a better understanding of market volatility and help you make more informed decisions. Here are some ways to use this script:
Identification of periods of high volatility:
When the GARCH volatility is greater than the cluster value (cluster_value), it indicates a period of high volatility. Traders can use this information to avoid taking large positions or to adjust their risk management strategies.
Anticipation of price movements:
An increase in volatility can often precede significant price movements. By monitoring GARCH volatility spikes, traders can prepare for potential market reversals or accelerations.
Optimization of entry and exit points:
By using GARCH volatility, traders can better identify favorable times to enter or exit a position. For example, entering a position when volatility begins to decrease after a peak can be an effective strategy.
Adjustment of stops and objectives:
Since volatility is an indicator of the magnitude of price fluctuations, traders can adjust their stop-loss and take-profit orders accordingly. Periods of high volatility may require wider stops to avoid being exited from a position prematurely.
That's it for the detailed explanation of this Pine Script™ script. Don’t hesitate to use it, adapt it to your needs and share your feedback! Happy analysis and trading everyone!
DeltaDetector PINESCRIPTLABSDescription:
This technical indicator, DeltaDetector PINESCRIPTLABS, is designed to identify significant changes in the price of an asset relative to the previous close. Users can customize the percentage change they want to monitor.
Usage Instructions:
Adjust the desired percentage change using the "Price Change Value (%)" user input.
Observe the green diamonds to identify significant price increases above the specified percentage.
Observe the red diamonds to identify significant price decreases below the specified percentage.
"In the following image, we observe a 4-hour timeframe for EURUSD, where we set a candle change percentage of 0.45%. We can see how the price reacts afterwards to the size of these candles."
"In the pair BTCUSDT.P, we designated a single candle change percentage of 3%, and observed how the price reacted after that candle."
This allows you to easily identify significant price movements within the range specified by the percentage change you have set.
Español:
Descripción:
Este indicador técnico, DeltaDetector PINESCRIPTLABS, está diseñado para identificar cambios significativos en el precio de un activo en relación con el cierre anterior. Los usuarios pueden personalizar el porcentaje de cambio que desean monitorear.
Instrucciones de uso:
Ajuste el porcentaje de cambio deseado utilizando la entrada de usuario "Price Change Value (%)".
Observe los diamantes verdes para identificar aumentos significativos en el precio por encima del porcentaje especificado.
Observe los diamantes rojos para identificar disminuciones significativas en el precio por debajo del porcentaje especificado.
"En la siguiente imagen, observamos un marco de tiempo de 4 horas para EURUSD, donde establecimos un porcentaje de cambio de vela del 0,45%. Podemos ver cómo reacciona el precio después al tamaño de estas velas."
"En el par BTCUSDT.P, designamos un porcentaje de cambio de vela único del 3%, y observamos cómo reaccionó el precio después de esa vela."
Esto te permite identificar fácilmente movimientos significativos en el precio dentro del rango especificado por el porcentaje de cambio que has establecido.
VIX Percentile Rank HistogramVIX Percentile Rank Histogram
The VIX Percentile Rank Histogram provides a visual representation of the CBOE Volatility Index (VIX) percentile rank over a customizable lookback period, helping traders gauge market sentiment and make informed trading decisions.
Overview:
This indicator calculates the percentile rank of the VIX over a specified lookback period and displays it as a histogram. The histogram helps traders understand whether the current VIX level is relatively high or low compared to its recent history. This information is particularly useful for timing entries and exits in the S&P 500 or related ETFs and Mega Caps.
How It Works:
VIX Data Integration: The script fetches daily VIX close prices, regardless of the chart you are viewing, to analyze market volatility.
Percentile Rank Calculation: The indicator calculates the rank percentile of the VIX over the chosen lookback period.
Histogram Visualization: The histogram plots the difference between the flipped VIX percentile rank and 50, showing green bars for ranks below 50 (indicating lower market volatility) and red bars for ranks above 50 (indicating higher market volatility).
Usage:
This indicator is most effective when trading the S&P 500 (SPX, SPY, ES1!) or ETFs and Mega Caps that closely follow the S&P 500. It provides insight into market sentiment, helping traders make more informed decisions.
Timing Entries and Exits: Green histogram readings suggest it's a good time to enter or hold long positions, while red readings suggest considering exits or short positions.
Market Sentiment: A high VIX percentile rank (red bars) indicates market fear and uncertainty, while a low percentile rank (green bars) suggests investor confidence and reduced volatility.
Key Features:
Customizable Lookback Period: The default lookback period is set to 20 days, but can be adjusted based on the trader's average trade duration. For example, if your trades typically last 20 days, a 20-day lookback period helps contextualize the VIX level relative to its recent history.
Histogram Visualization: The histogram provides a clear visual representation of market volatility.
Green Bars: Indicate a lower-than-median VIX percentile rank, suggesting reduced market volatility.
Red Bars: Indicate a higher-than-median VIX percentile rank, suggesting increased market volatility.
Threshold Line: A dashed gray line at the 0 level serves as a visual reference for the median VIX rank.
Important Note:
This indicator always shows readings from the VIX, regardless of the chart you are viewing. For example, if you are looking at Natural Gas futures, this indicator will provide no relevant data. It works best when trading the S&P 500 or related ETFs and Mega Caps.
Supertrend + BB + Consecutive Candles + QQE + EMA [Pineify]Overview
This indicator, developed by Pineify, is a comprehensive tool designed to assist traders in making informed decisions by combining multiple technical analysis methods. It integrates Supertrend, Bollinger Bands (BB), Consecutive Candles, Quantitative Qualitative Estimation (QQE), and Exponential Moving Averages (EMA) into a single, cohesive script. This multi-faceted approach allows traders to analyze market trends, volatility, and potential buy/sell signals with greater accuracy.
Key Features
1. Supertrend: Utilizes the Supertrend indicator to identify the prevailing market trend. It provides clear buy and sell signals based on the direction of the trend.
2. Bollinger Bands (BB): Measures market volatility and identifies overbought or oversold conditions. The script calculates the middle, upper, and lower bands, along with the Bollinger Band Width (BBW) and Bollinger Band %B (BBR).
3. Consecutive Candles: Detects sequences of consecutive bullish or bearish candles, providing signals when a specified number of consecutive candles are detected.
4. Quantitative Qualitative Estimation (QQE): Combines the Relative Strength Index (RSI) with a smoothing factor to generate buy and sell signals based on the QQE methodology.
5. Exponential Moving Averages (EMA): Includes both fast and slow EMAs to identify potential crossovers, which are used as buy and sell signals.
How It Works
- Supertrend: The Supertrend indicator is calculated using a factor and ATR length. It plots the trend direction and generates buy/sell signals when the trend changes.
- Bollinger Bands: The BB indicator calculates the middle band as a Simple Moving Average (SMA) of the closing prices. The upper and lower bands are derived by adding and subtracting a multiple of the standard deviation from the middle band.
- Consecutive Candles: This feature counts the number of consecutive candles that close higher or lower than the previous candle. When the count reaches a specified threshold, it generates a buy or sell signal.
- QQE: The QQE indicator smooths the RSI values and calculates the QQE Fast and QQE Slow lines. Buy and sell signals are generated based on the crossover of these lines.
- EMA: The script calculates fast and slow EMAs and generates buy/sell signals based on their crossovers.
How to Use
1. Inputs: Customize the indicator settings through the input parameters:
- Supertrend Factor and ATR Length
- BB Length
- Consecutive Candles Counting
- QQE RSI Length
- Fast and Slow EMA Lengths
- Enable/Disable Alerts for various signals
2. Alerts: Set up alerts for Supertrend, Consecutive Candles, and EMA crossovers. Alerts can be enabled or disabled based on user preference.
3. Visualization: The indicator plots the Supertrend, Bollinger Bands, and EMA lines on the chart. It also marks buy and sell signals with arrows and labels for easy identification.
Concepts Underlying Calculations
- Supertrend: Based on the Average True Range (ATR) to determine the trend direction and potential reversal points.
- Bollinger Bands: Utilizes standard deviation to measure market volatility and identify overbought/oversold conditions.
- Consecutive Candles: A method to detect momentum by counting consecutive bullish or bearish candles.
- QQE: Enhances the traditional RSI by smoothing it and using a dynamic threshold to generate signals.
- EMA: A widely used moving average that gives more weight to recent prices, making it responsive to market changes.
This indicator is a powerful tool for traders looking to combine multiple technical analysis methods into a single, easy-to-use script. By integrating these diverse techniques, it provides a comprehensive view of market conditions and potential trading opportunities.
ATR by Time [QuantVue]"ATR by Time" incorporates time-specific volatility patterns by calculating the Average True Range (ATR) over a customizable period and comparing it to historical ATR values
at specific times of the day.
The Average True Range (ATR) is a popular technical indicator that measures market volatility by decomposing the entire range of an asset price for that period.
By taking the ATR at certain times of the day and comparing it to the current bar's ATR, traders can gain several potential advantages:
Volatility Pattern Recognition: Different times of the trading day often exhibit different levels of volatility. For instance, markets might be more volatile at the open and close compared to midday. By tracking ATR at specific times, traders can recognize these patterns and better predict periods of high or low volatility.
Risk Management: Understanding volatility trends throughout the day helps in better risk management. During periods of high expected volatility (indicated by higher ATR compared to the historical average), traders can adjust their stop-loss levels and position sizes accordingly to protect their capital.
Trend Confirmation and Divergence: This indicator can help confirm trends or identify potential reversals. For example, if the current ATR consistently exceeds the average ATR at specific times, it may confirm a strong trend. Conversely, if the current ATR falls below the historical average, it could signal a potential slowdown or reversal.
This indicator will work on all markets on all time frames. User can customize ATR length as well as the lookback period.
This script utilizes TradingView's RelativeValue library and averageAtTime function, which is used to compare a current data point in a time interval to an average of data points with corresponding time offsets across historical periods. Its purpose is to assess the significance of a value by considering the historical context within past time intervals.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
Supertrend Alert with Arrows and Time FilterOverview
This script is designed to generate trading signals based on the Supertrend indicator, a popular technical analysis tool. The Supertrend indicator is used to identify the direction of the market trend and potential reversal points.
Supertrend Settings
The script uses two sets of Supertrend settings:
Small Supertrend
Factor: 3.0
ATR Period: 10
Big Supertrend
Factor: 10.0
ATR Period: 30
These settings are fixed and should not be altered to maintain the integrity of the signal generation process.
Configurable Parameters
startHour: The hour at which signal generation begins.
endHour: The hour at which signal generation ends.
These parameters allow users to focus on specific trading hours, optimizing the signal relevance to their trading strategy.
Signal Types
The script generates two types of signals:
Type 1: Reversal Signal
Long Signal: Triggered when the big Supertrend is in an uptrend, and the small Supertrend transitions from a downtrend to an uptrend.
Short Signal: Triggered when the big Supertrend is in a downtrend, and the small Supertrend transitions from an uptrend to a downtrend.
Type 2: Trend Change Signal
Long Signal: Triggered when the big Supertrend changes from a downtrend to an uptrend.
Short Signal: Triggered when the big Supertrend changes from an uptrend to a downtrend.
How the Script Works
Initialization: The script initializes with predefined Supertrend settings.
Data Input: Market data (e.g., price data) is fed into the script.
Supertrend Calculation: The script calculates the Supertrend values using the predefined factors and ATR periods.
Signal Detection: The script monitors the Supertrend values and detects the defined signals based on the conditions mentioned above.
Time Filtering: Signals are filtered based on the specified startHour and endHour, ensuring only relevant signals are displayed within the desired timeframe.
Usage
Set Parameters: Define startHour and endHour according to your trading schedule.
Run Script: Execute the script with market data input.
Interpret Signals: Monitor the generated signals and use them to inform your trading decisions.
Originality
Dual Supertrend Usage: The use of both a small and a big Supertrend to generate signals adds a layer of complexity and reliability to the signals.
Time-Based Filtering: Allows traders to focus on specific trading hours, enhancing the relevance and accuracy of signals.
Two Signal Types: The combination of reversal signals and trend change signals provides comprehensive market insights.
Conclusion
This Supertrend Signal Generator is a robust tool for traders seeking to leverage the Supertrend indicator for more informed trading decisions. By combining dual Supertrend settings and configurable trading hours, the script offers unique and flexible signal generation capabilities.
Downside DeviationDownside deviation is a measure of downside risk that focuses on returns that fall below a minimum threshold or minimum acceptable return (MAR). It is used in the calculation of the Sortino ratio, a measure of risk-adjusted return. The Sortino ratio is like the Sharpe ratio, except that it replaces the standard deviation with downside deviation.
Sortino RatioThe Sortino ratio is a variation of the Sharpe ratio that differentiates harmful volatility from total overall volatility by using the asset's standard deviation of negative portfolio returns—downside deviation—instead of the total standard deviation of portfolio returns. The Sortino ratio takes an asset or portfolio's return and subtracts the risk-free rate, and then divides that amount by the asset's downside deviation. The ratio was named after Frank A. Sortino.
BBTrend w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "BB Trend" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█Introduction and How it is Different
The "BBTrend w SuperTrend decision - Strategy " is a trading strategy designed to identify market trends using Bollinger Bands and SuperTrend indicators. What sets this strategy apart is its use of two Bollinger Bands with different lengths to capture both short-term and long-term market trends, providing a more comprehensive view of market dynamics. Additionally, the strategy includes customizable take profit (TP) and stop loss (SL) settings, allowing traders to tailor their risk management according to their preferences.
BTCUSD 4h Long Performance
█ Strategy, How It Works: Detailed Explanation
The BBTrend strategy employs two key indicators: Bollinger Bands and SuperTrend.
🔶 Bollinger Bands Calculation:
- Short Bollinger Bands**: Calculated using a shorter period (default 20).
- Long Bollinger Bands**: Calculated using a longer period (default 50).
- Bollinger Bands use the standard deviation of price data to create upper and lower bands around a moving average.
Upper Band = Middle Band + (k * Standard Deviation)
Lower Band = Middle Band - (k * Standard Deviation)
🔶 BBTrend Indicator:
- The BBTrend indicator is derived from the absolute differences between the short and long Bollinger Bands' lower and upper values.
BBTrend = (|Short Lower - Long Lower| - |Short Upper - Long Upper|) / Short Middle * 100
🔶 SuperTrend Indicator:
- The SuperTrend indicator is calculated using the average true range (ATR) and a multiplier. It helps identify the market trend direction by plotting levels above and below the price, which act as dynamic support and resistance levels. * @EliCobra makes the SuperTrend Toolkit. He is GOAT.
SuperTrend Upper = HL2 + (Factor * ATR)
SuperTrend Lower = HL2 - (Factor * ATR)
The strategy determines market trends by checking if the close price is above or below the SuperTrend values:
- Uptrend: Close price is above the SuperTrend lower band.
- Downtrend: Close price is below the SuperTrend upper band.
Short: 10 Long: 20 std 2
Short: 20 Long: 40 std 2
Short: 20 Long: 40 std 4
█ Trade Direction
The strategy allows traders to choose their trading direction:
- Long: Enter long positions only.
- Short: Enter short positions only.
- Both: Enter both long and short positions based on market conditions.
█ Usage
To use the "BBTrend - Strategy " effectively:
1. Configure Inputs: Adjust the Bollinger Bands lengths, standard deviation multiplier, and SuperTrend settings.
2. Set TPSL Conditions: Choose the take profit and stop loss percentages to manage risk.
3. Choose Trade Direction: Decide whether to trade long, short, or both directions.
4. Apply Strategy: Apply the strategy to your chart and monitor the signals for potential trades.
█ Default Settings
The default settings are designed to provide a balance between sensitivity and stability:
- Short BB Length (20): Captures short-term market trends.
- Long BB Length (50): Captures long-term market trends.
- StdDev (2.0): Determines the width of the Bollinger Bands.
- SuperTrend Length (10): Period for calculating the ATR.
- SuperTrend Factor (12): Multiplier for the ATR to adjust the SuperTrend sensitivity.
- Take Profit (30%): Sets the level at which profits are taken.
- Stop Loss (20%): Sets the level at which losses are cut to manage risk.
Effect on Performance
- Short BB Length: A shorter length makes the strategy more responsive to recent price changes but can generate more false signals.
- Long BB Length: A longer length provides smoother trend signals but may be slower to react to price changes.
- StdDev: Higher values create wider bands, reducing the frequency of signals but increasing their reliability.
- SuperTrend Length and Factor: Shorter lengths and higher factors make the SuperTrend more sensitive, providing quicker signals but potentially more noise.
- Take Profit and Stop Loss: Adjusting these levels affects the risk-reward ratio. Higher take profit percentages can increase gains but may result in fewer closed trades, while higher stop loss percentages can decrease the likelihood of being stopped out but increase potential losses.
ATR Price Range Prediction V.2### ATR Price Range Prediction V.2
This script calculates the expected high and low prices for the current day based on the Average True Range (ATR) and displays the proportion of days where the daily range (high - low) is greater than or equal to the ATR. Additionally, the script provides an option to adjust the size of the text displayed in the top-right corner of the chart.
#### How It Works
1. **ATR Calculation**: The script calculates the ATR for a specified period (`atrPeriod`). ATR is a measure of volatility that represents the average range between the high and low prices over a specified number of periods.
2. **Expected High and Low Calculation**:
- **Expected High**: Calculated by adding the ATR value to the low price of the current day.
- **Expected Low**: Calculated by subtracting the ATR value from the high price of the current day.
3. **Proportion Calculation**: The script calculates the proportion of days where the daily range (high - low) is greater than or equal to the ATR value. This proportion is updated in real-time as new data comes in.
4. **Table Display**: Instead of displaying labels on each candle, the script shows the expected high, expected low, and the calculated proportion in a table located at the top-right corner of the chart. The size of the text in this table can be adjusted using the `Table Size` input.
5. **Color Coding**: The script changes the color of the bars to yellow if the daily range is greater than or equal to the ATR value, making it easy to identify these bars visually.
#### How to Use
- **ATR Period (`atrPeriod`)**: Adjust the period for the ATR calculation using the input parameter. The default value is 14.
- **Table Size (`tableSizeOption`)**: Choose the size of the text displayed in the table. Options include `tiny`, `small`, `normal`, `large`, and `huge`.
- **Expected High and Low**: Use the green and red lines to identify potential target prices or stop-loss levels for your trades. The green line represents the expected high, and the red line represents the expected low.
- **Proportion**: The table in the top-right corner of the chart shows the proportion of days where the daily range is greater than or equal to the ATR value. This can provide insight into the volatility of the asset.
- **Color Coding**: Yellow bars indicate days where the daily range is greater than or equal to the ATR value.
---
### ภาษาไทย
### ATR คาดการณ์ราคาสูงสุดและต่ำสุด พร้อมสัดส่วน
สคริปต์นี้คำนวณราคาสูงสุดและต่ำสุดที่คาดการณ์สำหรับวันปัจจุบันโดยอิงจากค่าเฉลี่ยช่วงที่แท้จริง (ATR) และแสดงสัดส่วนของวันที่ช่วงราคาต่อวัน (สูง - ต่ำ) มากกว่าหรือเท่ากับค่า ATR นอกจากนี้ยังมีตัวเลือกในการปรับขนาดข้อความที่แสดงในกล่องข้อความมุมขวาบนของกราฟ
#### วิธีการทำงาน
1. **การคำนวณ ATR**: สคริปต์คำนวณค่า ATR สำหรับช่วงเวลาที่กำหนด (`atrPeriod`) ATR เป็นมาตรวัดความผันผวนที่แสดงช่วงเฉลี่ยระหว่างราคาสูงสุดและต่ำสุดในช่วงเวลาที่กำหนด
2. **การคำนวณราคาสูงสุดและต่ำสุดที่คาดการณ์**:
- **ราคาสูงสุดที่คาดการณ์**: คำนวณโดยการบวกค่า ATR กับราคาต่ำสุดของวันปัจจุบัน
- **ราคาต่ำสุดที่คาดการณ์**: คำนวณโดยการลบค่า ATR จากราคาสูงสุดของวันปัจจุบัน
3. **การคำนวณสัดส่วน**: สคริปต์คำนวณสัดส่วนของวันที่ช่วงราคาต่อวัน (สูง - ต่ำ) มากกว่าหรือเท่ากับค่า ATR สัดส่วนนี้จะอัปเดตแบบเรียลไทม์เมื่อมีข้อมูลใหม่เข้ามา
4. **การแสดงผลในตาราง**: แทนที่จะแสดงป้ายกำกับบนแท่งเทียนแต่ละแท่ง สคริปต์จะแสดงราคาสูงสุดที่คาดการณ์ ราคาต่ำสุดที่คาดการณ์ และสัดส่วนที่คำนวณในตารางที่มุมขวาบนของกราฟ โดยสามารถปรับขนาดข้อความในตารางได้
5. **การใช้สี**: สคริปต์จะเปลี่ยนสีของแท่งเทียนเป็นสีเหลืองหากช่วงราคาต่อวันมากกว่าหรือเท่ากับค่า ATR ทำให้สามารถระบุแท่งเทียนเหล่านี้ได้ง่ายขึ้น
#### วิธีการใช้งาน
- **ATR Period (`atrPeriod`)**: ปรับช่วงเวลาสำหรับการคำนวณ ATR โดยใช้พารามิเตอร์การป้อนค่า ค่าเริ่มต้นคือ 14
- **Table Size (`tableSizeOption`)**: เลือกขนาดข้อความที่แสดงในตาราง ตัวเลือกได้แก่ `tiny`, `small`, `normal`, `large`, และ `huge`
- **ราคาสูงสุดและต่ำสุดที่คาดการณ์**: ใช้เส้นสีเขียวและสีแดงเพื่อระบุราคาที่เป็นเป้าหมายหรือระดับการหยุดขาดทุนสำหรับการซื้อขายของคุณ เส้นสีเขียวแสดงถึงราคาสูงสุดที่คาดการณ์และเส้นสีแดงแสดงถึงราคาต่ำสุดที่คาดการณ์
- **สัดส่วน**: ตารางที่มุมขวาบนของกราฟแสดงสัดส่วนของวันที่ช่วงราคาต่อวันมากกว่าหรือเท่ากับค่า ATR ซึ่งสามารถให้ข้อมูลเชิงลึกเกี่ยวกับความผันผวนของสินทรัพย์
- **การใช้สี**: แท่งเทียนสีเหลืองบ่งบอกถึงวันที่ช่วงราคาต่อวันมากกว่าหรือเท่ากับค่า ATR
_____
Trend Strength Signals [AlgoAlpha]🌟Introducing the Trend and Strength Signals indicator by AlgoAlpha ! This tool is designed to help you identify trends and gauge market strength with precision and ease. 📈🚀
🛠 Customizable Parameters : Adjust the period, standard deviation multiplier, gauge size, and colors to fit your trading style.
📊 Trend Detection : Visualize trends with clear color-coded signals for uptrends and downtrends.
📈 Strength Gauge : Assess market strength with a dynamic gauge that adapts to the current price action.
🔔 Alerts : Set alerts for bullish and bearish trend crossovers and take profit points to stay ahead of the market.
🎨 Visual Enhancements : Enjoy a clutter-free chart with the integration of plot shapes, color fills, and gradient gauges.
🚀 Quick Guide to Using the Trend and Strength Signals Indicator
Maximize your trading with the Trend and Strength Signals indicator by following these streamlined steps! 🎯✨
🛠 Add the Indicator : Add the indicator to your favorites. Customize settings like period, standard deviation multiplier, and colors to fit your trading style.
📊 Market Analysis : Observe the color-coded candles and gauge to understand market trend direction and strength. Use the alerts for key trading signals.
🔔 Alerts : Enable notifications for trend crossovers and take profit points to catch trading opportunities without constantly monitoring the chart.
⚙️ How it works
This indicator calculates the moving average and standard deviation of the closing price over a customizable period to identify the upper and lower bounds. When the price crosses these bounds, it signals an uptrend or downtrend. The gauge measures market strength by comparing the price to the moving average and scaling it over a customizable range, while the underlying logic uses concepts from the Bollinger Bands, this indicator gives a unique perspective on price behavior through added features and signals derived from it.
Unleash the power of trend and strength analysis with this comprehensive indicator! Happy trading! 🚀📈✨
Enhanced Reversal DetectionScript Description:
The "Enhanced Reversal Detection" indicator is a powerful tool designed to identify potential market reversals across various financial instruments. It incorporates a sophisticated algorithm that analyzes price action along with key technical indicators such as the Relative Strength Index (RSI), Bollinger Bands, and Moving Average (MA).
How to Use:
Adjustable Parameters: The indicator offers a range of adjustable parameters to cater to different trading preferences and market conditions.
RSI Length: Adjusts the length of the RSI calculation to fine-tune sensitivity.
Overbought Level: Sets the threshold for identifying overbought conditions on the RSI scale.
Oversold Level: Sets the threshold for identifying oversold conditions on the RSI scale.
Bollinger Bands Length: Determines the length of the Bollinger Bands calculation.
Bollinger Bands Multiplier: Adjusts the standard deviation multiplier for the Bollinger Bands, influencing band width.
Moving Average Length: Defines the length of the Moving Average calculation to capture trend direction.
Min Bars Between Signals: Sets the minimum number of bars required between consecutive reversal signals.
ADX Length: Adjusts the length of the Average Directional Index (ADX) calculation.
ADX Threshold: Defines the threshold value for ADX, serving as a filter for reversal signals.
Signal Generation: The indicator generates signals for both bullish and bearish reversals based on predefined criteria. A bullish reversal signal is triggered when the closing price exceeds the lower Bollinger Band and RSI falls below the oversold threshold. Conversely, a bearish reversal signal occurs when the closing price falls below the upper Bollinger Band and RSI surpasses the overbought threshold.
Alerts: Traders can opt to receive alerts for bullish and bearish reversal signals, enabling them to stay informed of potential trading opportunities even when away from the platform.
Publication Readiness:
To ensure readiness for publication in the TradingView public library, the script has been meticulously crafted and documented:
The code is extensively commented to provide clear explanations of parameters, calculations, and signal generation logic.
Best coding practices have been followed to enhance readability and maintainability.
Rigorous testing has been conducted to validate the accuracy and reliability of signal generation across various market conditions.
The script adheres to TradingView's guidelines and policies for script publication, ensuring compliance with platform standards and user expectations.
With its comprehensive features and user-friendly design, the "Enhanced Reversal Detection" indicator is poised to become a valuable asset for traders seeking to identify high-probability reversal opportunities in the financial markets.
Dynamic Adaptive Regression BandsThis script provides a dynamic adaptive regression band indicator that adjusts based on recent market volatility. The regression bands are calculated using a length parameter adapted to the ATR (Average True Range) to ensure responsiveness to market conditions.
Key Features:
Dynamic Length Adjustment: The length of the regression calculation is adjusted based on the ATR to reflect current market volatility.
Multiple Bands: The script plots upper and lower bands at different ratios (1.618, 2.618, and 4.236) to provide comprehensive support and resistance levels.
Detailed Fillings: The areas between bands are filled with different colors to visualize different levels of volatility and trend strength.
Usage:
Regression Line: The main regression line follows the general trend of the price.
Upper/Lower Bands: These bands represent volatility-adjusted support and resistance levels.
Extended Bands: Additional bands at different ratios provide extended support and resistance zones for further trend analysis.
Original Script Credit:
This script is inspired by the original "Regr Linear Bands" script by MarcoValente, published on Jan 15, 2017. The original script starts from a linear regression and uses Fibonacci parameters to add bands above and below. The original work incorporates range and volatility, making the price move between bands of the same color. The middle line (linear regression) serves as a good signal; after a break occurs, the price typically moves to the last or second last band.
Grid TraderGrid Trader Indicator ( GTx ):
Overview
The Grid Trader Indicator is a tool that helps traders visualize key levels within a specified trading range. The indicator plots accumulation and distribution levels, an entry level, an exit level, and a midpoint. This guide will help you understand how to use the indicator and its features for effective grid trading.
Basics of Trading Range, Grid Buy, and Grid Sell
Trading Range
A trading range is the horizontal price movement between a defined upper ( resistance ) and lower ( support ) level over a period of time. When a security trades within a range, it repeatedly moves between these two levels without trending upwards or downwards significantly. Traders often use the trading range to identify potential buy and sell points:
Upper Level (Resistance): This is the price level at which selling pressure overcomes buying pressure, preventing the price from rising further.
Lower Level (Support): This is the price level at which buying pressure overcomes selling pressure, preventing the price from falling further.
Grid Trading Strategy
Grid trading is a type of trading strategy that involves placing buy and sell orders at predefined intervals around a set price. It aims to profit from the natural market volatility by buying low and selling high in a range-bound market. The strategy divides the trading range into several grid levels where orders are placed.
Grid Buy
Grid buy orders are placed at intervals below the current price . When the price drops to these levels, buy orders are triggered . This strategy ensures that the trader buys more as the price falls, potentially lowering the average purchase price .
Grid Sell
Grid sell orders are placed at intervals above the current price . When the price rises to these levels, sell orders are triggered . This ensures that the trader sells portions of their holdings as the price increases, potentially securing profits at higher levels .
Key Points of Grid Trading
Grid Size : The interval between each buy and sell order. This can be constant (e.g., $2 intervals) or variable based on certain conditions.
Accumulation Range : The lower part of the trading range where buy orders are placed.
Distribution Range : The upper part of the trading range where sell orders are placed.
Midpoint : The average price of the entry and exit levels, often used as a reference point for balance.
As the price moves up and down within this range, your buy orders will be triggered as the price drops and your sell orders will be triggered as the price rises. This allows you to accumulate more of the asset at lower prices and sell portions at higher prices, profiting from the price oscillations within the defined range. Grid trading can be particularly effective in a sideways market where there is no clear long-term trend. However, it requires careful monitoring and adjustment of grid levels based on market conditions to minimize risks and maximize returns .
Configuring the Indicator :
Once the indicator is added, you will see a settings icon next to it. Click on it to open the settings menu.
Adjust the Upper Level , Lower Level , Entry Level , and Exit Level to match your trading strategy and market conditions.
Set the Levels Visibility to control how many bars back the levels will be plotted.
Interpreting the Levels :
Accumulation Levels : These are plotted below the entry level and are potential buy zones. They are labeled as Accumulation Level 1, 2, and 3.
Distribution Levels : These are plotted above the exit level and are potential sell zones. They are labeled as Distribution Level 1, 2, and 3.
Upper Level : Marked in fuchsia, indicating the top boundary of the trading range.
Exit Level : Marked in yellow, indicating the level at which you plan to exit trades.
Midpoint : Marked in white, indicating the average of the entry and exit levels.
Entry Level : Marked in yellow, indicating the level at which you plan to enter trades.
Lower Level : Marked in aqua, indicating the bottom boundary of the trading range.
By visualizing key levels, you can make informed decisions on where to place buy and sell orders, potentially maximizing your trading profits through systematic grid trading.
Double Vegas SuperTrend Enhanced - Strategy [presentTrading]
█ Introduction and How It Is Different
The "Double Vegas SuperTrend Enhanced" strategy is a sophisticated trading system that combines two Vegas SuperTrend Enhanced. Very Powerful!
Let's celebrate the joy of Children's Day on June 1st! Enjoyyy!
BTCUSD LS performance
The strategy aims to pinpoint market trends with greater accuracy and generate trades that align with the overall market direction.
This approach differentiates itself by integrating volatility adjustments and leveraging the Vegas Channel's width to refine the SuperTrend calculations, resulting in a dynamic and responsive trading system.
Additionally, the strategy incorporates customizable take-profit and stop-loss levels, providing traders with a robust framework for risk management.
-> check Vegas SuperTrend Enhanced - Strategy
█ Strategy, How It Works: Detailed Explanation
🔶 Vegas Channel and SuperTrend Calculations
The strategy initiates by calculating the Vegas Channel, which is derived from a simple moving average (SMA) and the standard deviation (STD) of the closing prices over a specified window length. This channel helps in measuring market volatility and forms the basis for adjusting the SuperTrend indicator.
Vegas Channel Calculation:
- vegasMovingAverage = SMA(close, vegasWindow)
- vegasChannelStdDev = STD(close, vegasWindow)
- vegasChannelUpper = vegasMovingAverage + vegasChannelStdDev
- vegasChannelLower = vegasMovingAverage - vegasChannelStdDev
SuperTrend Multiplier Adjustment:
- channelVolatilityWidth = vegasChannelUpper - vegasChannelLower
- adjustedMultiplier = superTrendMultiplierBase + volatilityAdjustmentFactor * (channelVolatilityWidth / vegasMovingAverage)
The adjusted multiplier enhances the SuperTrend's sensitivity to market volatility, making it more adaptable to changing market conditions.
BTCUSD Local picture.
🔶 Average True Range (ATR) and SuperTrend Values
The ATR is computed over a specified period to measure market volatility. Using the ATR and the adjusted multiplier, the SuperTrend upper and lower levels are determined.
ATR Calculation:
- averageTrueRange = ATR(atrPeriod)
**SuperTrend Calculation:**
- superTrendUpper = hlc3 - (adjustedMultiplier * averageTrueRange)
- superTrendLower = hlc3 + (adjustedMultiplier * averageTrueRange)
The SuperTrend levels are continuously updated based on the previous values and the current market trend direction. The market trend is determined by comparing the closing prices with the SuperTrend levels.
Trend Direction:
- If close > superTrendLowerPrev, then marketTrend = 1 (bullish)
- If close < superTrendUpperPrev, then marketTrend = -1 (bearish)
🔶 Trade Entry and Exit Conditions
The strategy generates trade signals based on the alignment of both SuperTrends. Trades are executed only when both SuperTrends indicate the same market direction.
Entry Conditions:
- Long Position: Both SuperTrends must signal a bullish trend.
- Short Position: Both SuperTrends must signal a bearish trend.
Exit Conditions:
- Positions are exited if either SuperTrend reverses its trend direction.
- Additional conditions include holding periods and configurable take-profit and stop-loss levels.
█ Trade Direction
The strategy allows traders to specify the desired trade direction through a customizable input setting. Options include:
- Long: Only enter long positions.
- Short: Only enter short positions.
- Both: Enter both long and short positions based on the market conditions.
█ Usage
To utilize the "Double Vegas SuperTrend Enhanced" strategy, traders need to configure the input settings according to their trading preferences and market conditions. The strategy includes parameters for ATR periods, Vegas Channel window lengths, SuperTrend multipliers, volatility adjustment factors, and risk management settings such as hold days, take-profit, and stop-loss percentages.
█ Default Settings
The strategy comes with default settings that can be adjusted to fit individual trading styles:
- trade Direction: Both (allows trading in both long and short directions for maximum flexibility).
- ATR Periods: 10 for SuperTrend 1 and 5 for SuperTrend 2 (shorter ATR period results in more sensitivity to recent price movements).
- Vegas Window Lengths: 100 for SuperTrend 1 and 200 for SuperTrend 2 (longer window length results in smoother moving averages and less sensitivity to short-term volatility).
- SuperTrend Multipliers: 5 for SuperTrend 1 and 7 for SuperTrend 2 (higher multipliers lead to wider SuperTrend channels, reducing the frequency of trades).
- Volatility Adjustment Factors: 5 for SuperTrend 1 and 7 for SuperTrend 2 (higher adjustment factors increase the responsiveness to changes in market volatility).
- Hold Days: 5 (defines the minimum duration a position is held, ensuring trades are not exited prematurely).
- Take Profit: 30% (sets the target profit level to lock in gains).
- Stop Loss: 20% (sets the maximum acceptable loss level to mitigate risk).
Volatility DashboardThis indicator calculates and displays volatility metrics for a specified number of bars (rolling window) on a TradingView chart. It can be customized to display information in English or Thai and can position the dashboard at various locations on the chart.
Inputs
Language: Users can choose between English ("ENG") and Thai ("TH") for the dashboard's language.
Dashboard Position: Users can specify where the dashboard should appear on the chart. Options include various positions such as "Bottom Right", "Top Center", etc.
Calculation Method: Currently, the script supports "High-Low" for volatility calculation. This method calculates the difference between the highest and lowest prices within a specified timeframe.
Bars: Number of bars used to calculate the volatility.
Display Logic
Fills the islast_vol_points array with the calculated volatility points.
Sets the table cells with headers and corresponding values:
=> Highest Volatility: The maximum value in the islast_vol_points array
=> Mean Volatility: The average value in the islast_vol_points array,
=> Lowest Volatility: The minimum value in the islast_vol_points array, Number of Bars: The rolling window size.
Volume True Range (VTR) and Volume Average True Range (VATR)This indicator uses lower-timeframe cumulative volume delta (CVD) candles to calculate the Volume True Range (VTR) of your instrument. The VTR is calculated similarly to the traditional true range, but uses volume instead (no price is involved in the calculation other than in the lower timeframe bar delta assignments). I haven't seen this concept developed before on TradingView or frankly the Internet, but I thought it seemed fairly intuitive; we can calculate the lower timeframe volume delta candles, so it makes sense to calculate a volume true range, which could show divergences in volume and price.
The VTR is calculated by the following code which uses the lower-timeframe CVD candles:
volumeTR = math.max(cvd_high - cvd_low, math.abs(cvd_high - nz(cvd_close )), math.abs(cvd_low - nz(cvd_close )))
The Volume Average True Range (VATR) is calculated by taking the RMA of the VTR, similarly to the ATR.
I would like to thank TradingView for the calculation of up/down intrabar volumes, which I referenced from their 'CVD - Cumulative Volume Delta Candles' indicator.
How to Use
The VTR and VATR can be used to identify price-volume trends and volatility divergences. A strong VTR (above the VATR of your specified length) can indicate the start or continuation of a trend, which you can identify via the VTR color (determined via price candle colors). Similarly, a rising VATR with most VTR bars of a specific color (green or red) will show that volume is moving in a specific price direction.
Additionally, the VATR plotted next to the ATR of the same length will show you volume volatility divergences. A strong VATR next to a muted/flat ATR indicates strong volume movement, which price might follow in the upcoming bars. Or, for trend reversals, a decreasing ATR after a strong trend combined with a rising VATR of the opposite trend may show a possible reversal.
Hope you all enjoy this.
-wbburgin
* Quick note: lower timeframe analysis returns only so much data. If you are on a high timeframe and the indicator is showing only a limited amount of bars, raise the lower timeframe (but still keep it below your current timeframe) so that the arrays can return more bars for you.
VolCorrBeta [NariCapitalTrading]Indicator Overview: VolCorrBeta
The VolCorrBeta indicator is designed to analyze and interpret intermarket relationships. This indicator combines volatility, correlation, and beta calculations to provide a comprehensive view of how certain assets (BTC, DXY, CL) influence the ES futures contract (I tailored this indicator to the ES contract, but it will work for any symbol).
Functionality
Input Symbols
BTCUSD : Bitcoin to USD
DXY : US Dollar Index
CL1! : Crude Oil Futures
ES1! : S&P 500 Futures
These symbols can be customized according to user preferences. The main focus of the indicator is to analyze how the price movements of these assets correlate with and lead the price movements of the ES futures contract.
Parameters for Calculation
Correlation Length : Number of periods for calculating the correlation.
Standard Deviation Length : Number of periods for calculating the standard deviation.
Lookback Period for Beta : Number of periods for calculating beta.
Volatility Filter Length : Length of the volatility filter.
Volatility Threshold : Threshold for adjusting the lookback period based on volatility.
Key Calculations
Returns Calculation : Computes the daily returns for each input symbol.
Correlation Calculation : Computes the correlation between each input symbol's returns and the ES futures contract returns over the specified correlation length.
Standard Deviation Calculation : Computes the standard deviation for each input symbol's returns and the ES futures contract returns.
Beta Calculation : Computes the beta for each input symbol relative to the ES futures contract.
Weighted Returns Calculation : Computes the weighted returns based on the calculated betas.
Lead-Lag Indicator : Calculates a lead-lag indicator by averaging the weighted returns.
Volatility Filter : Smooths the lead-lag indicator using a simple moving average.
Price Target Estimation : Estimates the ES price target based on the lead-lag indicator (the yellow line on the chart).
Dynamic Stop Loss (SL) and Take Profit (TP) Levels : Calculates dynamic SL and TP levels using volatility bands.
Signal Generation
The indicator generates buy and sell signals based on the filtered lead-lag indicator and confirms them using higher timeframe analysis. Signals are debounced to reduce frequency, ensuring that only significant signals are considered.
Visualization
Background Coloring : The background color changes based on the buy and sell signals for easy visualization (user can toggle this on/off).
Signal Labels : Labels with arrows are plotted on the chart, showing the signal type (buy/sell), the entry price, TP, and SL levels.
Estimated ES Price Target : The estimated price target for ES futures is plotted on the chart.
Correlation and Beta Dashboard : A table displayed in the top right corner shows the current correlation and beta values for relative to the ES futures contract.
Customization
Traders can customize the following parameters to tailor the indicator to their specific needs:
Input Symbols : Change the symbols for BTC, DXY, CL, and ES.
Correlation Length : Adjust the number of periods used for calculating correlation.
Standard Deviation Length : Adjust the number of periods used for calculating standard deviation.
Lookback Period for Beta : Change the lookback period for calculating beta.
Volatility Filter Length : Modify the length of the volatility filter.
Volatility Threshold : Set a threshold for adjusting the lookback period based on volatility.
Plotting Options : Customize the colors and line widths of the plotted elements.
Composite Risk IndicatorThe Composite Risk Indicator is a financial tool designed to assess market risk by analyzing the spreads between various asset classes. This indicator synthesizes information across six key spreads, normalizing each on a scale from 0 to 100 where higher values represent higher perceived risk. It provides a single, comprehensive measure of market sentiment and risk exposure.
Key Components of the CRI:
1. Stock Market to Bond Market Spread (SPY/BND): Measures the performance of stocks relative to bonds. Higher values indicate stronger stock performance compared to bonds, suggesting increased market optimism and higher risk.
2. Junk Bond to Treasury Bond Spread (HYG/GOVT): Assesses the performance of high-yield (riskier) bonds relative to government (safer) bonds. A higher ratio indicates increased appetite for risk.
3. Junk Bond to Investment Grade Bond Spread (HYG/LQD): Compares high-yield bonds to investment-grade corporate bonds. This ratio sheds light on the risk tolerance within the corporate bond market.
4. Growth to Value Spread (VUG/VTV): Evaluates the performance of growth stocks against value stocks. A higher value suggests a preference for growth stocks, often seen in risk-on environments.
5. Tech to Staples Spread (XLK/XLP): Measures the performance of technology stocks relative to consumer staples. This ratio highlights the market’s risk preference within equity sectors.
6. Small Cap Growth to Small Cap Value Spread (SLYG/SLYV): Compares small-cap growth stocks to small-cap value stocks, providing insight into risk levels in smaller companies.
Utility:
This indicator is particularly useful for investors and traders looking to gauge market sentiment, identify shifts in risk appetite, and make informed decisions based on a broad assessment of market conditions. The CRI can serve as a valuable addition to investment analysis and risk management strategies.
