Uber VQ (Lite) - Volatility Quality Index [UTS]Name: Uber VQI (Lite) - Volatility Quality Index
Created: 2022/11/22
Copyright: © UberTradingSystems
Description:
The volatility quality index was first introduced by Thomas Stridsman in Technical Analysis of Stocks and Commodities magazine in the August 2002 edition.
This powerful indicator points out the difference between bad and good volatility in order to identify better trade opportunities in the market.
It is suggested to use this indicator as a confirmation signal together with the other indicators in your system.
Lite Version
Please note that this "Lite" version offers full functionality but is constrained to Euro / US-Dollar trading pairs only.
You can find it as "EURUSD" on many providers such as FXCM, Oanda, Capital.com, Currency.com etc.
If you like this indicator, consider checking out the original. More details under "Author's instructions" and "Signature" sections below.
General Usage
Stridsman suggested buying (or "to go long") when VQ has increased in the previous 10 bars and selling (or "to go short") when it has decreased in the previous 10 bars.
This indicator has been updated to reflect its modern iterations. One of the following signals are choosable trading signal generator:
VQ Sum
Short MA
Long MA
All three signal triggering conditions can selectively be drawn on the indicator for study and reference purposes.
In addition, generated buy and sell signals can be drawn on the indicator and are modifiable too.
Alerts
To allow alert notifications, generated signals are connected as selectable "Long Signal" and "Short Signal" to the indicator alerts.
The conditions can be found on the alert sections of the indicator.
In the menu right to the indicator name, press the three dots and select "Add alert on ...".
Under condition options select one of the following:
Long Signal
Short Signal
It is advised to select "Once per bar close" as alert execution option.
Moving Averages
To fine-tune the "Short MA" and "Long MA" calculation, 16 different Moving Averages are available to choose from:
ALMA (Arnaud Legoux Moving Average)
DEMA (Double Exponential Moving Average)
EMA (Exponential Moving Average)
FRAMA (Fractal Adaptive Moving Average)
HMA (Hull Moving Average)
JURIK (Jurik Moving Average)
KAMA (Kaufman Adaptive Moving Average)
Kijun (Kijun-sen / Tenkan-sen of Ichimoku)
LSMA (Least Square Moving Average)
RMA (Running Moving Average)
SMA (Simple Moving Average)
SuperSmoothed (Super Smoothed Moving Average)
TEMA (Triple Exponential Moving Average)
VWMA (Volume Weighted Moving Average)
WMA (Weighted Moving Average)
ZLEMA (Zero Lag Moving Average)
A freely determinable length allows for sensitivity adjustments that fit your own requirements.
在腳本中搜尋"Volatility"
Relative VolatilityRelative Volatility is a technical indicator designed to assess changes in market volatility by comparing fast and slow Average True Range (ATR) values. It operates by subtracting a slower ATR (e.g., 50-period ATR) from a faster ATR (e.g., 20-period ATR) and visualizing the result as a histogram. This enables traders to determine whether volatility is increasing or decreasing over time.
This indicator can help traders recognize volatility trends, which can inform decisions related to trade entries, exits, and risk management.
Interpreting Volatility Changes
Increasing Volatility: When the histogram is above zero, it indicates that the fast ATR is greater than the slow ATR, signifying an increase in short-term volatility compared to the long-term average. This may suggest heightened market activity and potential trading opportunities.
Decreasing Volatility: When the histogram is below zero, it shows that the fast ATR is less than the slow ATR, indicating a decrease in short-term volatility relative to the long-term average. This may suggest consolidating markets or reduced trading activity.
Relative Volatility assists traders in monitoring and analyzing changes in market volatility, providing insights that can enhance trading strategies and decision-making processes.
GKD-C Volatility-Adaptive Rapid RSI T3 [Loxx]Giga Kaleidoscope GKD-C Volatility-Adaptive Rapid RSI T3 is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C Volatility-Adaptive Rapid RSI T3
Adaptive Momentum: Mastering Market Dynamics with Advanced RSI Techniques
The Volatility-Adaptive Rapid RSI T3 is a sophisticated technical indicator that combines the concepts of Rapid RSI, Volatility Adaptation, and T3 smoothing. This combination results in a more responsive, accurate, and adaptable momentum oscillator compared to the regular RSI.
The Rapid RSI is a variation of the RSI designed to provide faster and more responsive signals. It does this by modifying the way average gains and losses are calculated, using a simple moving average (SMA) instead of an exponential moving average (EMA). This makes the Rapid RSI more sensitive to recent price changes, allowing traders to identify overbought and oversold conditions more quickly.
Volatility adaptation is a concept that adjusts the parameters of an indicator based on the current market volatility. In the context of the Volatility-Adaptive Rapid RSI T3, the volatility is calculated using the standard deviation of price changes over a specified period. This value is then used to adjust the T3 smoothing period, making the indicator more adaptive to changing market conditions. When the market is volatile, the indicator will respond more quickly to price changes, while in less volatile markets, the indicator will be less sensitive, reducing the likelihood of false signals.
T3 smoothing, developed by Tim Tilson, is a powerful and flexible moving average technique that aims to reduce lag and improve the responsiveness of an indicator. It utilizes a combination of multiple exponential moving averages with varying degrees of weighting to create a smoother and more accurate representation of the underlying data. The T3 smoothing method is applied to the price data before the Rapid RSI calculation, enhancing the overall responsiveness of the indicator.
By combining these three concepts, the Volatility-Adaptive Rapid RSI T3 offers several advantages over the regular RSI:
1. Faster and more responsive signals: The Rapid RSI and T3 smoothing components allow the indicator to respond more quickly to price changes, potentially leading to earlier entry and exit points.
2. Adaptability to market conditions: The volatility adaptation feature enables the indicator to adjust its sensitivity based on the current market volatility. This helps to reduce false signals in less volatile markets and increase responsiveness in more volatile markets.
2. Smoother representation of price data: The T3 smoothing technique provides a more accurate and smoother representation of the underlying data, making it easier to identify trends and potential reversals.
In conclusion, the Volatility-Adaptive Rapid RSI T3 is a powerful technical indicator that offers several improvements over the regular RSI. Its responsiveness, adaptability, and smoothing capabilities make it a valuable tool for traders seeking to identify overbought and oversold conditions more accurately. However, it is essential to remember that no indicator is perfect, and using the Volatility-Adaptive Rapid RSI T3 in conjunction with other technical indicators and analysis tools can provide more reliable trading signals.
Additional Features
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
It's important to note that, like any other technical analysis tool, Heiken Ashi "better" candles are not foolproof and should be used in conjunction with other indicators and analysis techniques to make well-informed trading decisions.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Volatility-Adaptive Rapid RSI T3 as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Volatility-Adaptive Rapid RSI T3
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
Multi-Panel: Trade-Volatility-Probability [Loxx]Multi-Panel: Trade-Volatility-Probability shows user selected and volatility-based price levels and probabilities on the chart. This is useful for both options and all styles of up/down trading methods that rely on volatility.
Trading Panel: Shows trading information to take profits and stop-loss based on multiples of volatility. Also shows equity inputs by the user to calculate optimal position size
Key things to note about the Trading Panel
-Trade side: Long or short. you change this this to change the take profit and SL levels in displayed on the table to be used w/ up/down trading styles that rely on volatility stops
-Account size: User enters total balance available for trade
-Risk: Total % of account size you're willing to lose should the SL be hit
-Position size: Size of the position given the SL and your preferred Risk
-Take profit/Stop loss levels: Based on multipliers selected by the user in settings. These shouldn't be changed unless you really know what you're doing with volatility stops
-Entry: Source price. can be 1 of 37 different prices. See Loxx's Expanded Source Types:
Volatility Panel: Shows information about the volatility the user selected to be used to take profit/stop-loss/range calculations. Volatility types included are:
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility. That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Chi-squared Confidence Interval:
Confidence interval of volatility is calculated using an inverse CDF of a Chi-Squared Distribution. You can change the volatility input used to either realized, upper confidence interval, or lower confidence interval. This is included in case you'd like to see how far price can extend if volatility hits it's upper or lower confidence levels. Generally, you'd just used realized volatility, so I wouldn't change this setting.
Inverse CDF of a Chi-Squared Distribution
The chi-square distribution is a one-parameter family of curves. The parameter ν is the degrees of freedom.
The icdf of the chi-square distribution is
x=F^−1(p∣ν) = {x:F(x∣ν) = p}
where
p=F(x∣ν)= ∫ (t^(v-2)/2 * e^t/2) / (2^(v/2) / Γ(v/2))
ν is the degrees of freedom, and Γ( · ) is the Gamma function. The result p is the probability that a single observation from the chi-square distribution with ν degrees of freedom falls in the interval .
Additional notes on Volatility Panel
-Shows both current timeframe volatility per candle at whatever date backward you select
-Shows annualized volatility basaed on selected days per year and per bar volatility; this is automaitcally caulculated no matter the timeframe used. This means that it'll calculate annualized volatility for the current candle even on the 1 second timeframe. Days per year should be 252 for everything but cryptocurrency; however, for all types of tradable assets, anything over the 3 day timeframe will calculate on 365 days.
Probability Panel
This panel shows the probability levels of a user selected upper and lower price boundary. This includes the inside range of volatility between the lower and upper price levels and the outside probability below the lower price level and above the upper price level. These values are calculated using the CDF (cumulative density function) of a normal distribution. In simpler terms, CDF returns area under a bell curve between two points left and right, or for our purposes, high and low. This yeilds the probabilities you see in the Probability Panel. See the following graphic to visualize how this works:
The red line is the entry bar; the yellow line is the "mean" but in this case just the chosen source price.
Other things to know
You can turn on/off all labels and levels and fills
Dynamic Volatility EnvelopeDynamic Volatility Envelope: Indicator Overview
The Dynamic Volatility Envelope is an advanced, multi-faceted technical indicator designed to provide a comprehensive view of market trends, volatility, and potential future price movements. It centers around a customizable linear regression line, enveloped by dynamically adjusting volatility bands. The indicator offers rich visual feedback through gradient coloring, candle heatmaps, a background volatility pulse, and an on-chart trend strength meter.
Core Calculation Mechanism
Linear Regression Core :
-A central linear regression line is calculated based on a user-defined source (e.g., close, hl2) and lookback period.
-The regression line can be optionally smoothed using an Exponential Moving Average (EMA) to reduce noise.
-The slope of this regression line is continuously calculated to determine the current trend direction and strength.
Volatility Channel :
-Dynamic bands are plotted above and below a central basis line. This basis is typically the calculated regression line but shifts to an EMA in Keltner mode.
-The width of these bands is determined by market volatility, using one of three user-selectable modes:
ATR Mode : Bandwidth is a multiple of the Average True Range (ATR).
Standard Deviation Mode : Bandwidth is a multiple of the Standard Deviation of the source data.
Keltner Mode (EMA-based ATR) : ATR-based bands are plotted around a central Keltner EMA line, offering a smoother channel.
The channel helps identify dynamic support and resistance levels and assess market volatility.
Future Projection :
The indicator can project the current regression line and its associated volatility bands into the future for a user-defined number of bars. This provides a visual guide for potential future price pathways based on current trend and volatility characteristics.
Candle Heatmap Coloring :
-Candle bodies and/or wicks/borders can be colored based on the price's position within the upper and lower volatility bands.
-Colors transition in a gradient from bearish (when price is near the lower band) through neutral (mid-channel) to bullish (when price is near the upper band), providing an intuitive visual cue of price action relative to the dynamic envelope.
Background Volatility Pulse :
The chart background color can be set to dynamically shift based on a ratio of short-term to long-term ATR. This creates a "pulse" effect, where the background subtly changes color to indicate rising or falling market volatility.
Trend Strength Meter :
An on-chart text label displays the current trend status (e.g., "Strong Bullish", "Neutral", "Bearish") based on the calculated slope of the regression line relative to user-defined thresholds for normal and strong trends.
Key Features & Components
-Dynamic Linear Regression Line: Core trend indicator with optional smoothing and slope-based gradient coloring.
-Multi-Mode Volatility Channel: Choose between ATR, Standard Deviation, or Keltner (EMA-based ATR) calculations for band width.
-Customizable Vertical Gradient Channel Fills: Visually distinct fills for upper and lower channel segments with user-defined top/bottom colors and gradient spread.
-Future Projection: Extrapolates regression line and volatility bands to forecast potential price paths.
-Price-Action Based Candle Heatmap: Intuitive candle coloring based on position within the volatility channel, with adjustable gradient midpoint.
-Volatility-Reactive Background Gradient: Subtle background color shifts to reflect changes in market volatility.
-On-Chart Trend Strength Meter: Clear textual display of current trend direction and strength.
-Extensive Visual Customization: Fine-tune colors, line styles, widths, and gradient aggressiveness for most visual elements.
-Comprehensive Tooltips: Detailed explanations for every input setting, ensuring ease of use and understanding.
Visual Elements Explained
Regression Line : The primary trend line. Its color dynamically changes (e.g., green for uptrend, red-pink for downtrend, neutral for flat) based on its slope, with smooth gradient transitions.
Volatility Channel :
Upper & Lower Bands : These lines form the outer boundaries of the envelope, acting as dynamic support and resistance levels.
Channel Fill : The area between the band center and the outer bands is filled with a vertical gradient. For example, the upper band fill might transition from a darker green near the center to a lighter green at the upper band.
Band Borders : The lines outlining the upper and lower bands, with customizable color and width.
Future Projection Lines & Fill :
Projected Regression Line : An extension of the current regression line into the future, typically styled differently (e.g., dashed).
Projected Channel Bands : Extensions of the upper and lower volatility bands.
Projected Area Fill : A semi-transparent fill between the projected upper and lower bands.
Candle Heatmap Coloring : When enabled, candles are colored based on their closing price's relative position within the channel. Bullish colors appear when price is in the upper part of the channel, bearish in the lower, and neutral in the middle. Users can choose to color the entire candle body or just the wicks and borders.
Background Volatility Pulse : The chart's background color subtly shifts (e.g., between a calm green and an agitated red-pink) to reflect the current volatility regime.
Trend Strength Meter : A text label (e.g., "TREND: STRONG BULLISH") positioned on the chart, providing an at-a-glance summary of the trend.
Configuration Options
Users can tailor the indicator extensively via the settings panel, with options logically grouped:
Core Analysis Engine : Adjust regression source data, lookback period, and EMA smoothing for the regression line.
Regression Line Visuals : Control visibility, line width, trend-based colors (uptrend, downtrend, flat), slope thresholds for trend definition, strong slope multiplier (for Trend Meter), and color gradient sharpness.
Volatility Channel Configuration : Select band calculation mode (ATR, StdDev, Keltner), set relevant periods and multipliers. Customize colors for vertical gradient fills (upper/lower, top/bottom), border line colors, widths, and the gradient spread factor for fills.
Future Projection Configuration : Toggle visibility, set projection length (number of bars), line style, and colors for projected regression and band areas.
Appearance & Candle Theme : Set default bull/bear candle colors, enable/disable candle heatmap, choose if body color matches heatmap, and configure heatmap gradient target colors (bull, neutral, bear) and the gradient's midpoint.
Background Volatility Pulse : Enable/disable the background effect and configure short/long ATR periods for the volatility calculation.
Trend Strength Meter : Enable/disable the meter, and choose its on-chart position and text size.
Interpretation Notes
-The Regression Line is the primary indicator of trend direction. Its slope and color provide immediate insight.
-The Volatility Bands serve as dynamic support and resistance zones. Price approaching or touching these bands may indicate potential turning points or breakouts. The width of the channel itself reflects market volatility – widening suggests increasing volatility, while narrowing suggests consolidation.
Future Projections are not predictions but rather an extension of current conditions. They can help visualize potential areas where price might interact with projected support/resistance if the current trend and volatility persist.
Candle Heatmap Coloring offers a quick visual assessment of where price is trading within the dynamic envelope, highlighting strength or weakness relative to the channel.
The Background Volatility Pulse gives a contextual feel for overall market agitation or calmness.
This indicator is designed to be a comprehensive analytical tool. Its signals and visualizations are best used in conjunction with other technical analysis techniques, price action study, and robust risk management practices. It is not intended as a standalone trading system.
Risk Disclaimer
Trading and investing in financial markets involve substantial risk of loss and is not suitable for every investor. The Dynamic Volatility Envelope indicator is provided for analytical and educational purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance is not indicative of future results. Always use sound risk management practices and never trade with capital you cannot afford to lose. The developers assume no liability for any financial losses incurred based on the use of this indicator.
RSI Volatility Suppression Zones [BigBeluga]RSI Volatility Suppression Zones is an advanced indicator that identifies periods of suppressed RSI volatility and visualizes these suppression zones on the main chart. It also highlights breakout dynamics, giving traders actionable insights into potential market momentum.
🔵 Key Features:
Detection of Suppression Zones:
Identifies periods where RSI volatility is suppressed and marks these zones on the main price chart.
Breakout Visualization:
When the price breaks above the suppression zone, the box turns aqua, and an upward label is drawn to indicate a bullish breakout.
If the price breaks below the zone, the box turns purple, and a downward label is drawn for a bearish breakout.
Breakouts accompanied by a "+" label represent strong moves caused by short-lived, tight zones, signaling significant momentum.
Wave Labels for Consolidation:
If the suppression zone remains unbroken, a "wave" label is displayed within the gray box, signifying continued price stability within the range.
Gradient Intensity Below RSI:
A gradient strip below the RSI line increases in intensity based on the duration of the suppressed RSI volatility period.
This visual aid helps traders gauge how extended the low volatility phase is.
🔵 Usage:
Identify Breakouts: Use color-coded boxes and labels to detect breakouts and their direction, confirming potential trend continuation or reversals.
Evaluate Market Momentum: Leverage "+" labels for strong breakout signals caused by short suppression phases, indicating significant market moves.
Monitor Price Consolidation: Observe gray boxes and wave labels to understand ongoing consolidation phases.
Analyze RSI Behavior: Utilize the gradient strip to measure the longevity of suppressed volatility phases and anticipate breakout potential.
RSI Volatility Suppression Zones provides a powerful visual representation of RSI volatility suppression, breakout signals, and price consolidation, making it a must-have tool for traders seeking to anticipate market movements effectively.
ADW - Volatility MapThe ADW - Volatility Map script is a tool for traders to measure and visualize the volatility of a specific asset. It uses both the Average True Range (ATR) and True Range (TR) values in combination with the Commodity Channel Index (CCI) to provide a comprehensive map of the market's volatility.
Average True Range (ATR) : ATR is a measure of market volatility. It measures the average of true price ranges over a time period. In this script, we use it to calculate the ATR-CCI which gives us a more precise measure of volatility.
True Range (TR) : TR is the greatest distance the price moved during a period. It is used in this script to calculate the TR-CCI, adding another level of detail to our volatility measurement.
Commodity Channel Index (CCI) : CCI is a versatile indicator that can be used to identify a new trend or warn of extreme conditions. We use it to scale and compare the ATR and TR values, hence providing a relative measure of volatility.
The script interprets the CCI values and provides four different conditions for both ATR and TR:
Is Low (CCI < 0)
Is High (CCI > 0)
Is Extremely Low (CCI <= -100)
Is Extremely High (CCI >= 100)
The interpretation of these conditions is displayed on the chart using colour highlighting. When the ATR or TR are low, high, extremely low, or extremely high, the script fills the chart accordingly.
In addition, the script has an option `awaitBarConfirmation` set at the beginning. If this is true, the script will only display indicators for fully formed bars, ensuring that the indicators you see are based on confirmed information.
Note: The colours for different conditions can be customized at the beginning of the script, allowing you to personalize the visual output to match your preferences.
This script is designed to provide a visually clear and immediate understanding of the market's volatility. Use it to enhance your decision-making process and adapt your trading strategy to the current market conditions.
Advanced Volatility Activator [AlgoFuego]🔵 Advanced Volatility Activator (AVA)
The Advanced Volatility Activator (AVA) is an innovative technical analysis indicator designed to help traders identify and react to market volatility.
By blending adaptive volatility metrics with a refined moving‑average algorithm, the indicator offers traders a dynamically responsive framework for trend identification.
🔸Dynamic Volatility Analysis
The indicator examines the high and low prices of each candle to evaluate market movements.
It categorizes price movements into different states (e.g., outside bars, inside bars, higher highs, lower lows) to provide insight into market conditions, then calculates price averages for bars that make a new high or low price.
This moving average serves as a baseline for volatility adjustments, aligning the tool with well-established technical indicators.
🔸 Customizable Sensitivity
Through the input, users can fine‑tune how responsive the moving average is to price fluctuations.
A higher sensitivity setting makes the moving average less responsive to rapid market changes, enabling the indicator to adapt to different market environments and trading styles.
🔸Integrated Multi-Timeframe Table
A distinctive feature of this indicator is its integrated table display, which provides a summary signal across multiple time frames.
This table serves as a quick reference guide for traders to compare market trends across different time periods.
This at‑a‑glance view empowers traders to confirm trend direction from intraday to higher‑timeframe perspectives without switching charts.
🔹 How It Works
1. Initial Setup
The indicator defines two baseline values: the current high and the current low.
These serve as reference points for all subsequent price comparisons and moving‑average calculations.
2. Volatility Smoothing
The indicator calculates the smoothed volatility range using an exponential moving average (EMA) of the absolute differences between successive prices.
This helps smooth out the erratic price movements of the simple moving average and improves the measurement of volatility.
3. Trend Probability Calculation
A Simple Moving Average (SMA) of the combined high‑low series is calculated.
That SMA is then compared against the smoothed volatility range from step 2 to estimate how likely it is that a genuine trend is forming.
4. Directional Counters
Two counters: bullish and bearish, track consecutive moves up or down.
Whichever counter increases more rapidly signals the prevailing market bias.
5. Drawing the Trend Line
Finally, the code generates a trend line that dynamically adapts to real‑time volatility.
The result is a clear, responsive visual that mirrors actual market behavior.
🔹 Visual & Table Customization
Color Coding
Upward and downward trends are easily distinguished by customizable color settings, enhancing visual clarity for decision-making.
Upward Movements
A lighter blue hue indicates an upward trend.
Downward Movements
An orange hue indicates a downward trend.
Candlestick Highlighting
The indicator plots candlesticks with the same trendline color so that the chart maintains a consistent visual theme, thus reinforcing the signal's clarity.
Table Configuration and Customization
This additional layer of information helps traders compare signals between different time horizons, which is essential for a comprehensive multi-timeframe strategy.
The code supports multiple user-defined timeframes (e.g., 15, 60, 240, and 480 minutes).
For each timeframe, the indicator queries the market data to determine if the signal is Bullish, Bearish, or No signal.
Visibility and Positioning
The table can be toggled on or off via a user input. Its position on the chart is also customizable, ranging from top-right to bottom-left, allowing flexibility based on personal chart layouts.
Color Settings
The table cells are populated with both the timeframe labels and the corresponding market signal text (e.g., "Bullish", "Bearish", "No signal"). Background colors for each signal cell change dynamically depending on the current state, making it easy for traders to assess market sentiment at a glance.
Users can adjust colors for the background, borders, and text of the table itself.
Moreover, specific colors are set to denote bullish signals (blue), bearish signals (orange), or no signal (default dark theme).
🔹 How to use
Before entering long trades, ensure that prices are above the Advanced Volatility Activator Line and the line indicates an upward movement.
🔹 Practical Benefits
Enhanced Market Awareness
By highlighting periods of low volatility, the indicator can serve as an early warning system for potential market reversals or breakouts.
The supplementary table offers a high-level overview of these signals across multiple timeframes, which aids in confirming trends or reversals.
Customizable and Versatile
Both the indicator and the table are highly customizable. Traders can fine-tune the sensitivity, adjust periods for the moving average, select color schemes, and choose their preferred timeframes, all allowing for a tool that adapts to various trading styles and market conditions.
Intuitive Visualization
The clearly defined color-coded trendline provides an immediate visual cue, making it easier for traders to interpret market trends at a glance.
Whether you are a short-term trader needing precise entry and exit points or a multi-timeframe analyst looking for broader trend confirmation, this indicator provides valuable insights on both a micro- and macro-level.
🔹 Disclosure
While this indicator is useful and ideally suited for active traders who require precise, customizable signals to navigate rapidly changing markets, it's critical to understand that past performance is not necessarily indicative of future results, and there are many more factors that go into being a profitable trader.
TS Volatility-Adjusted EWMAThe TS Volatility-Adjusted Exponentially Weighted Moving Average (EWMA) is a dynamic trend-following indicator designed to adapt to changing market volatility. Unlike traditional moving averages, this indicator adjusts its sensitivity based on market conditions, making it more responsive during periods of high volatility and smoother when markets are calmer.
Key Features:
Volatility Adjustment: The EWMA length is dynamically scaled using the Average True Range (ATR), making it adaptive to market volatility. This allows the indicator to react quickly when volatility spikes and remain stable when volatility drops.
User-Controlled Smoothing: The indicator includes an optional smoothing period, allowing you to adjust how smooth or reactive the line is to price changes. If you prefer a more smoothed-out trend, simply increase the smoothing length.
This indicator is perfect for trend-following traders who want an adaptive tool that stays responsive to the market’s volatility. The TS Volatility-Adjusted EWMA helps you confidently follow market trends, whether you’re riding a long-term trend or catching shorter-term movements.
Volumetric Volatility Breaker Blocks [UAlgo]The "Volumetric Volatility Breaker Blocks " indicator is designed for traders who want a comprehensive understanding of market volatility combined with volume analysis. This indicator provides a clear visualization of significant volatility areas (or blocks), characterized by price movements that exceed a specific volatility threshold, as calculated using the ATR (Average True Range). The concept is enhanced by integrating volume-based insights, offering a view of market activity that helps users to recognize when significant price changes are being supported by an appropriate level of market participation.
The indicator calculates breaker blocks for both bullish and bearish market conditions, providing distinct visual elements that identify periods of high volatility and substantial volume divergence. The focus on both volume and volatility makes this tool versatile, allowing traders to assess the strength of price movements as well as areas where price might break above or below previously established levels.
It supports adjustable parameters, such as volatility length, smoothness factor, and volume display, allowing traders to fine-tune the indicator according to their trading strategy and market environment. The highlighted breaker blocks assist in identifying zones of potential price reversal or continuation, which can be critical for making informed trading decisions.
🔶 Key Features
Volatility-Based Block Identification: The indicator uses the Average True Range (ATR) to determine the volatility of the market. When the ATR exceeds a specified threshold (smooth ATR multiplied by a user-defined multiplier), it highlights these areas as volatility blocks. The idea is to mark periods where price activity is significantly divergent from normal conditions, which often signals market opportunities.
Volume Integrated Analysis: In addition to tracking volatility, the indicator incorporates volume data, allowing traders to see the amount of activity that occurs during these high-volatility periods. This helps in identifying whether a price movement is likely sustainable or whether it lacks market support.
User Adjustable Parameters: The indicator offers customization options for the volatility length (using ATR), smooth length, and multiplier for sensitivity adjustment. These settings enable users to modify the indicator’s responsiveness to market conditions.
The option to display the last few volatility blocks allows traders to manage clutter on their charts and focus only on the most recent significant data.
Mitigation Method: Users can select between different mitigation methods ("Close" or "Wick") to determine how blocks are broken. This adds an extra layer of adaptability, allowing traders to modify the indicator's response based on different price action strategies.
Dynamic Visual Representation: The indicator dynamically draws boxes for volatility blocks and shades them according to market direction, with split areas showing the bullish and bearish strength contributions. It also provides percentage volume for each block, helping traders understand the relative market participation during these moves.
🔶 Interpreting the Indicator
Identifying High Volatility Areas: When a new volatility block appears, it signifies that the market is experiencing higher-than-usual volatility, driven by increased ATR values. Traders should pay attention to these blocks, as they often indicate that a significant price move is occurring. Bullish blocks suggest upward pressure, whereas bearish blocks indicate downward pressure.
Volume Insights: The volume associated with each volatility block provides an insight into how much market participation accompanies these moves. Higher volume within a block implies that the market is actively supporting the price change, which may be a sign of continuation. Low volume suggests that the movement may lack the strength to persist.
Bullish vs. Bearish Strength Analysis: Each block is split into bullish and bearish strength, giving a clearer picture of what’s happening within the volatility period. If the bullish portion dominates, it indicates strong upward sentiment during that period. Conversely, if the bearish side is more prominent, there is more selling pressure. This breakdown helps in understanding intra-block market dynamics.
Volume Percentage Display: The indicator also displays the volume percentage in each block, which provides context for the strength of the move relative to recent market activity. Higher percentages mean more market engagement, which could confirm the legitimacy of a trend or a significant breakout.
🔶 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.
Expected Move by Option's Implied Volatility High Liquidity
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols with high option liquidity.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options.There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry. This script will display Expected Move data for Symbols within the range of JBL-NOTE in alphabetical order.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Expected Move by Option's Implied Volatility Symbols: EAT - GBDC
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of EAT-GDBC in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Expected Move by Option's Implied Volatility Symbols: CLFD-EARN This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of CLFD - EARN in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Expected Move by Option's Implied Volatility Symbols: A - AZZ
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of A - AZZ in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Ultimate Volatility Indicator [CC]The Ultimate Volatility Indicator was created by Richard Poster (Stocks and Commodities July 2021 pg 21) and this is a very simple but effective indicator. The idea behind volatility indicators is that when the indicator rises above a certain threshold then volatility is high enough and you can make a good amount of money riding the trend in the current direction and then exit when volatility drops below the threshold or until the underlying trend changes.
I have included a threshold that you can change from the default but I would recommend trying out different values to see what works best for you. This indicator will let you know as soon as volatility increases and reacts very quickly. I have included strong buy and sell signals in addition to normal ones so darker colors are strong buy and sell signals and lighter colors are normal signals. Buy when the line turns green and sell when it turns red.
Please let me know if you would like to see me publish any other indicators!
Ultimate Volatility OscillatorThis is a Premium Volatility indicator which aims to set a framework for Advanced Volatility Studies.
The indicator allows plotting multiple Volatility Studies, including:
Squeeze
Bollinger Bands Volatility
Volatility Index
TTM Squeeze
It enables 3 distinct view modes out of the box:
Oscillator Mode
Histogram Mode
Oscillator + Histogram Mode
And includes the Volatility Belt, which is super-useful to spot volatility changes in a compact mode.
Additional volatility studies might be included down the road.
If you're interested in this one, please PM me.
Adaptive Momentum For Loop Volatility | viResearchAdaptive Momentum For Loop Volatility | viResearch
Conceptual Foundation and Innovation
The "Adaptive Momentum For Loop Volatility" script introduces an innovative approach to momentum and volatility analysis by combining a for-loop system with adaptive momentum calculations. This method leverages a dynamic scoring mechanism within a volatility-based framework, allowing traders to capture trend shifts with sensitivity to recent market volatility. By adapting to changes in price movement, the script provides signals that are both trend-following and volatility-aware.
The script also integrates an Adaptive Trailing Stop feature, which uses an ATR-based volatility stop to dynamically track the trend. This approach is designed to assist traders in positioning themselves effectively during trending markets while staying protected by an adaptive trailing stop when the trend shows signs of reversal.
Technical Composition and Calculation
The "Adaptive Momentum For Loop Volatility" script comprises several technical components to create a responsive momentum and volatility indicator:
Adaptive For-Loop Scoring System: A custom for-loop scoring system evaluates the subject price (typically the close) over a defined range. The loop checks for conditions indicating upward or downward momentum, adjusting the score accordingly. The score then serves as the volatility multiplier for the ATR-based stop.
Volatility Stop Calculation: An ATR-based trailing stop is calculated based on the adaptive score. The stop adjusts in response to the latest score, allowing it to move closer to or further from the price depending on the current volatility.
Range Plot: The script includes an upper and lower boundary based on a percentage deviation from a moving average, giving a sense of possible price movement within the range. This additional visual aid helps traders identify potential overextension points within the trend.
Features and User Inputs
The script includes several customizable inputs, allowing traders to tailor the indicator to specific assets and market conditions:
Length: Controls the period used for the ATR calculation, affecting the responsiveness of the stop. Multiplier: Adjusts the volatility stop’s sensitivity based on recent price action. Percentage for Range Plot: Defines the width of the range plotted around the moving average, offering insights into expected price deviations. Adaptive Scoring Parameters: The for-loop’s scoring range (variables a and b) can be adjusted to fine-tune momentum detection. Alert and Bar Color Customization: Alerts are provided to notify the user of long and short signals. The background and bar colors visually indicate current trend direction.
Practical Applications
This script is ideal for traders who wish to capture both trend and volatility in their trading strategies. Key applications include:
Trend Confirmation and Reversal Detection: The volatility-based stop helps confirm trend direction, making it easier to spot potential reversals.
Adaptive Trailing Stop: The ATR stop protects gains by adjusting dynamically as the market’s volatility changes. Traders can use this feature to manage risk and secure profits in trending markets.
Range Bound Trading: The range plot highlights potential overbought and oversold levels, making it useful for identifying when prices are likely to revert to the mean.
Advantages and Strategic Value
The "Adaptive Momentum For Loop Volatility" script provides a unique blend of momentum and volatility analysis, offering an edge over traditional indicators. Its adaptive nature helps traders stay in trades during strong trends and exit promptly during reversals, reducing exposure to adverse price movements. The customizable parameters make it versatile and adaptable to various asset classes and market conditions.
Summary and Usage Tips
Incorporate the "Adaptive Momentum For Loop Volatility" script into your trading system to enhance trend analysis and risk management. Use the for-loop scoring system to detect early momentum shifts, and rely on the volatility stop to maintain a position until the trend shows signs of exhaustion. Adjust the range plot settings to suit the asset’s typical price movements for a more accurate portrayal of expected price fluctuations. Remember, backtesting across different market conditions is essential to understanding how the script performs and adapting it as needed.
As with all indicators, note that historical results are not indicative of future performance, so complement this tool with other market insights to make well-rounded trading decisions.
Adaptive Volatility-Controlled LSMA [QuantAlgo]Adaptive Volatility-Controlled LSMA by QuantAlgo 📈💫
Introducing the Adaptive Volatility-Controlled LSMA (Least Squares Moving Average) , a powerful trend-following indicator that combines trend detection with dynamic volatility adjustments. This indicator is designed to help traders and investors identify market trends while accounting for price volatility, making it suitable for a wide range of assets and timeframes. By integrating LSMA for trend analysis and Average True Range (ATR) for volatility control, this tool provides clearer signals during both trending and volatile market conditions.
💡 Core Concept and Innovation
The Adaptive Volatility-Controlled LSMA leverages the precision of the LSMA to track market trends and combines it with the sensitivity of the ATR to account for market volatility. LSMA fits a linear regression line to price data, providing a smoothed trend line that is less reactive to short-term noise. The ATR, on the other hand, dynamically adjusts the volatility bands around the LSMA, allowing the indicator to filter out false signals and respond to significant price moves. This combination provides traders with a reliable tool to identify trend shifts while managing risk in volatile markets.
📊 Technical Breakdown and Calculations
The indicator consists of the following components:
1. Least Squares Moving Average (LSMA): The LSMA calculates a linear regression line over a defined period to smooth out price fluctuations and reveal the underlying trend. It is more reactive to recent data than traditional moving averages, allowing for quicker trend detection.
2. ATR-Based Volatility Bands: The Average True Range (ATR) measures market volatility and creates upper and lower bands around the LSMA. These bands expand and contract based on market conditions, helping traders identify when price movements are significant enough to indicate a new trend.
3. Volatility Extensions: To further account for rapid market changes, the bands are extended using additional volatility measures. This ensures that trend signals are generated when price movements exceed both the standard volatility range and the extended volatility range.
⚙️ Step-by-Step Calculation:
1. LSMA Calculation: The LSMA is computed using a least squares regression method over a user-defined length. This provides a trend line that adapts to recent price movements while smoothing out noise.
2. ATR and Volatility Bands: ATR is calculated over a user-defined length and is multiplied by a factor to create upper and lower bands around the LSMA. These bands help detect when price movements are substantial enough to signal a new trend.
3. Trend Detection: The price’s relationship to the LSMA and the volatility bands is used to determine trend direction. If the price crosses above the upper volatility band, a bullish trend is detected. Conversely, a cross below the lower band indicates a bearish trend.
✅ Customizable Inputs and Features:
The Adaptive Volatility-Controlled LSMA offers a variety of customizable options to suit different trading or investing styles:
📈 Trend Settings:
1. LSMA Length: Adjust the length of the LSMA to control its sensitivity to price changes. A shorter length reacts quickly to new data, while a longer length smooths the trend line.
2. Price Source: Choose the type of price (e.g., close, high, low) that the LSMA uses to calculate trends, allowing for different interpretations of price data.
🌊 Volatility Controls:
ATR Length and Multiplier: Adjust the length and sensitivity of the ATR to control how volatility is measured. A higher ATR multiplier widens the bands, making the trend detection less sensitive, while a lower multiplier tightens the bands, increasing sensitivity.
🎨 Visualization and Alerts:
1. Bar Coloring: Customize bar colors to visually distinguish between uptrends and downtrends.
2. Volatility Bands: Enable or disable the display of volatility bands on the chart. The bands provide visual cues about trend strength and volatility thresholds.
3. Alerts: Set alerts for when the price crosses the upper or lower volatility bands, signaling potential trend changes.
📈 Practical Applications
The Adaptive Volatility-Controlled LSMA is ideal for traders and investors looking to follow trends while accounting for market volatility. Its key use cases include:
Identifying Trend Reversals: The indicator detects when price movements break through volatility bands, signaling potential trend reversals.
Filtering Market Noise: By applying ATR-based volatility filtering, the indicator helps reduce false signals caused by short-term price fluctuations.
Managing Risk: The volatility bands adjust dynamically to account for market conditions, helping traders manage risk and improve the accuracy of their trend-following strategies.
⭐️ Summary
The Adaptive Volatility-Controlled LSMA by QuantAlgo offers a robust and flexible approach to trend detection and volatility management. Its combination of LSMA and ATR creates clearer, more reliable signals, making it a valuable tool for navigating trending and volatile markets. Whether you're detecting trend shifts or filtering market noise, this indicator provides the tools you need to enhance your trading and investing strategy.
Note: The Adaptive Volatility-Controlled LSMA is a tool to enhance market analysis. It should be used in conjunction with other analytical tools and should not be relied upon as the sole basis for trading or investment decisions. No signals or indicators constitute financial advice, and past performance is not indicative of future results.
TASC 2022.03 Relative Strength Volatility-Adjusted EMA█ OVERVIEW
TASC's March 2022 edition of Traders' Tips includes the "Relative Strength Moving Averages - Part 3: The Relative Strength Volatility-Adjusted Exponential Moving Average" article authored by Vitali Apirine. This is the code that implements the "RS VolatAdj EMA" from the article.
█ CONCEPTS
In a three-part article series, Vitaly Apirine examines ways to filter price movements and define turning points by applying the Relative Strength concept to exponential moving averages . The resulting indicator is more responsive and is intended to account for the relative strength of volatility .
█ CALCULATIONS
The calculation process uses the following steps:
Select an appropriate volatility index (in our case it is VIX ).
Calculate up day volatility (UV) smoothed by a 10-day EMA.
Calculate down day volatility (DV) smoothed by a 10-day EMA.
Take the absolute value of the difference between UV and DV and divide by the sum of UV and DV. This is the Volatility Strength we need.
Calculate a MLTP constant - the weighting multiplier for an exponential moving average.
Combine Volatility Strength and MLTP to create an exponential moving average on current price data.
Join TradingView!
GCM Volatility-Adaptive Trend ChannelScript Description
Name: GCM Volatility-Adaptive Trend Channel (GCM VATC)
Overview
The GCM Volatility-Adaptive Trend Channel (VATC) is a comprehensive trading tool that merges the low-lag, smooth-trending capabilities of the Jurik Moving Average (JMA) with the classic volatility analysis of Bollinger Bands (BB).
By displaying both trend and volatility in a single, intuitive interface, this indicator aims to help traders see when a trend is stable versus when it's becoming volatile and might be poised for a change.
Core Components:
JMA Trend System: At its core are three dynamically colored JMA lines (Baseline, Fast, and Slow) that provide a clear view of trend direction. The lines change color based on their slope, offering immediate visual feedback on momentum. A colored ribbon between the Baseline and Fast JMA visualizes shorter-term momentum shifts.
Standard Bollinger Bands: Layered on top are standard Bollinger Bands. Calculated from the price, these bands serve as a classic measure of market volatility. They help identify periods where the market is expanding (high volatility) or contracting (low volatility).
How to Use It
By combining these two powerful concepts, this indicator provides a unified view of both trend and volatility. It can help traders to:
Identify the primary trend direction using the smooth JMA lines.
Gauge the strength and stability of that trend.
See when the market is becoming volatile (bands widening) or consolidating (bands contracting), which can often precede a significant price move or a change in trend.
A Note on Originality & House Rules Compliance
This indicator does not introduce a new mathematical formula. Instead, its strength lies in the thoughtful combination of two well-respected, publicly available concepts: the Jurik Moving Average and Bollinger Bands. The JMA implementation is a standard public version. The goal was to create a practical, all-in-one tool for trend and volatility analysis.
This script is published as fully open-source in compliance with TradingView's House Rules. It utilizes standard, publicly available algorithms and does not contain any protected or hidden code.
Settings
All lengths, sources, and colors for the JMA lines and Bollinger Bands are fully customizable in the settings menu, allowing you to tailor the indicator to your specific trading style and asset.
I hope with this indicator Traders even Beginner can can control their emotions which increase the probabilities of the winning rates and cutting the losing strength
Purposely I Didn't plant the High low or Buy Sell signals in the chart. Because everything is in the chart where volatility Signal with the Bollinger Band and Buy Sell Signal in the JMA Dynamic colors. and that's enough to decide when to take trade and when not to.
Thank You and Happy Trading
Swing-Based Volatility IndexSwing-Based Volatility Index
This indicator helps traders quickly determine whether the market has moved enough over the past few hours to justify scalping.
It measures the percentage price swing (high to low) over a configurable time window (e.g., last 4–8 hours) and compares it to a minimum threshold (e.g., 1%).
✅ If the percent move exceeds the threshold → Market is volatile enough to scalp (green background).
🚫 If it's below the threshold → Market is too quiet (red background).
Features:
Adjustable lookback period in hours
Custom threshold for volatility sensitivity
Automatically adapts to the current chart timeframe
This tool is ideal for scalpers and short-term traders who want to avoid entering trades in low-volatility environments.
H-Infinity Volatility Filter [QuantAlgo]Introducing the H-Infinity Volatility Filter by QuantAlgo 📈💫
Enhance your trading/investing strategy with the H-Infinity Volatility Filter , a powerful tool designed to filter out market noise and identify clear trend signals in volatile conditions. By applying an advanced H∞ filtering process, this indicator assists traders and investors in navigating uncertain market conditions with improved clarity and precision.
🌟 Key Features:
🛠 Customizable Noise Parameters: Adjust worst-case noise and disturbance settings to tailor the filter to various market conditions. This flexibility helps you adapt the indicator to handle different levels of market volatility and disruptions.
⚡️ Dynamic Trend Detection: The filter identifies uptrends and downtrends based on the filtered price data, allowing you to quickly spot potential shifts in the market direction.
🎨 Color-Coded Visuals: Easily differentiate between bullish and bearish trends with customizable color settings. The indicator colors the chart’s candles according to the detected trend for immediate clarity.
🔔 Custom Alerts: Set alerts for trend changes, so you’re instantly informed when the market transitions from bullish to bearish or vice versa. Stay updated without constantly monitoring the charts.
📈 How to Use:
✅ Add the Indicator: Add the H-Infinity Volatility Filter to your favourites and apply it to your chart. Customize the noise and disturbance parameters to match the volatility of the asset you are trading/investing. This allows you to optimize the filter for your specific strategy.
👀 Monitor Trend Shifts: Watch for clear visual signals as the filter detects uptrends or downtrends. The color-coded candles and line plots help you quickly assess market conditions and potential reversals.
🔔 Set Alerts: Configure alerts to notify you when the trend changes, allowing you to react quickly to potential market shifts without needing to manually track price movements.
🌟 How It Works and Academic Background:
The H-Infinity Volatility Filter is built on the foundations of H∞ (H-infinity) control theory , a mathematical framework originating from the field of engineering and control systems. Developed in the 1980s by notable engineers such as George Zames and John C. Doyle , this theory was designed to help systems perform optimally under uncertain and noisy conditions. H∞ control focuses on minimizing the worst-case effects of disturbances and noise, making it a powerful tool for managing uncertainty in complex environments.
In financial markets, where unpredictable price fluctuations and noise often obscure meaningful trends, this same concept can be applied to price data to filter out short-term volatility. The H-Infinity Volatility Filter adopts this approach, allowing traders and investors to better identify potential trends by reducing the impact of random price movements. Instead of focusing on precise market predictions, the filter increases the probability of highlighting significant trends by smoothing out market noise.
This indicator works by processing historical price data through an H∞ filter that continuously adjusts based on worst-case noise levels and disturbances. By considering several past states, it estimates the current price trend while accounting for potential external disruptions that might influence price behavior. Parameters like "worst-case noise" and "disturbance" are user-configurable, allowing traders to adapt the filter to different market conditions. For example, in highly volatile markets, these parameters can be adjusted to manage larger price swings, while in more stable markets, they can be fine-tuned for smoother trend detection.
The H-Infinity Volatility Filter also incorporates a dynamic trend detection system that classifies price movements as bullish or bearish. It uses color-coded candles and plots—green for bullish trends and red for bearish trends—to provide clear visual cues for market direction. This helps traders and investors quickly interpret the trend and act on potential signals. While the indicator doesn’t guarantee accuracy in trend prediction, it significantly reduces the likelihood of false signals by focusing on meaningful price changes rather than random fluctuations.
How It Can Be Applied to Trading/Investing:
By applying the principles of H∞ control theory to financial markets, the H-Infinity Volatility Filter provides traders and investors with a sophisticated tool that manages uncertainty more effectively. Its design makes it suitable for use in a wide range of markets—whether in fast-moving, volatile environments or calmer conditions.
The indicator is versatile and can be used in both short-term trading and medium to long-term investing strategies. Traders can tune the filter to align with their specific risk tolerance, asset class, and market conditions, making it an ideal tool for reducing the effects of market noise while increasing the probability of detecting reliable trend signals.
For investors, the filter can help in identifying medium to long-term trends by filtering out short-term price swings and focusing on the broader market direction. Whether applied to stocks, forex, commodities, or cryptocurrencies, the H-Infinity Volatility Filter helps traders and investors interpret market behavior with more confidence by offering a more refined view of price movements through its noise reduction techniques.
Disclaimer:
The H-Infinity Volatility Filter is designed to assist in market analysis by filtering out noise and volatility. It should not be used as the sole tool for making trading or investment decisions. Always incorporate other forms of analysis and risk management strategies. No statements or signals from this indicator or us should be considered financial advice. Past performance is not indicative of future results.
[UPRIGHT Trading] Volatility Trend Filter (VTF) AlgoHello Traders,
As some of you know, I have had this in Beta for a long while now and it's finally time for a full release.
I originally designed this to be an Unreal Algo add-on to track & stay in the trade a little better, but the VTF Algo has become a full Algorithm and can be used standalone with supreme accuracy.
It's for beginners and advanced traders alike. I've made the settings very customizable, but also easy to just jump right in.
How it works:
It uses volatility , deviations, and tons of statistical calculations, confirmations, moving averages, and filters to bring you the most accurate Supply & Demand predictive algorithm possible. The VTF Algo will automatically normalize different volatility in any type of market to help avoid getting Chopped up and give a forward-looking approach to accurate Price Action and confirmation. It will automatically show support and resistance in real-time. The channel that The VTF Algo creates will help traders confirm whether they should stay in the trade or get out fast. As the green top grows it naturally acts as Supply and as the red bottom grows it acts as Demand, when one of them far exceeds the other the direction price will proceed to is clear to see.
Features:
-Easy-to-read Price Action & Trend channel.
-Exceptional Chop Filter (grayed center).
-Accurate Buy/Sell and Topline Continuation Signals.
-Rejection Signals.
-Multiple-Timeframe Customizable Trend Table. Showing Directional Arrows (see bottom right of picture).
-Bullish / Bearish Growing Blocks.
-Fully Customizable with Clean and Cleaner Mode.
The VTF Algo was made with all different types of traders in mind.
Some like things Ultra Crispy Clean:
Others like things a little more clean but can move their focus to where it's needed:
Lastly, there are those who don't mind things looking a little busy:
Topline Continuation Signals, Auto-Supply/Demand, and a Real-Time Multiple Timeframe Trend Table (in the bottom-right) corner:
Meshes perfectly as an Algo Add-on for Unreal Algo © (as originally designed) to enhance "The Simple Strat" © :
I tried to make everything as customizable as possible. So adding or removing or color-changing is super easy.
Happy Trading.
Cheers,
Mike
