Indicator
Scalper's Volatility Filter [QuantraSystems]Scalpers Volatility Filter
Introduction
The 𝒮𝒸𝒶𝓁𝓅𝑒𝓇'𝓈 𝒱𝑜𝓁𝒶𝓉𝒾𝓁𝒾𝓉𝓎 𝐹𝒾𝓁𝓉𝑒𝓇 (𝒮𝒱𝐹) is a sophisticated technical indicator, designed to increase the profitability of lower timeframe trading.
Due to the inherent decrease in the signal-to-noise ratio when trading on lower timeframes, it is critical to develop analysis methods to inform traders of the optimal market periods to trade - and more importantly, when you shouldn’t trade.
The 𝒮𝒱𝐹 uses a blend of volatility and momentum measurements, to signal the dominant market condition - trending or ranging.
Legend
The 𝒮𝒱𝐹 consists of a signal line that moves above and below a central zero line, serving as the indication of market regime.
When the signal line is positioned above zero, it indicates a period of elevated volatility. These periods are more profitable for trading, as an asset will experience larger price swings, and by design, trend-following indicators will give less false signals.
Conversely, when the signal line moves below zero, a low volatility or mean-reverting market regime dominates.
This distinction is critical for traders in order to align strategies with the prevailing market behaviors - leveraging trends in volatile markets and exercising caution or implementing mean-reversion systems in periods of lower volatility.
Case Study
Here we can see the indicator's unique edge in action.
Out of the four potential long entries seen on the chart - displayed via bar coloring, two would result in losses.
However, with the power of the 𝒮𝒱𝐹 a trader can effectively filter false signals by only entering momentum-trades when the signal line is above zero.
In this small sample of four trades, the 𝒮𝒱𝐹 increased the win rate from 50% to 100%
Methodology
The methodology behind the 𝒮𝒱𝐹 is based upon three components:
By calculating and contrasting two ATR’s, the immediate market momentum relative to the broader, established trend is calculated. The original method for this can be credited to the user @xinolia
A modified and smoothed ADX indicator is calculated to further assess the strength and sustainability of trends.
The ‘Linear Regression Dispersion’ measures price deviations from a fitted regression line, adding further confluence to the signals representation of market conditions.
Together, these components synthesize a robust, balanced view of market conditions, enabling traders to help align strategies with the prevailing market environment, in order to potentially increase expected value and win rates.
Indicator
Indicator
[blackcat] L2 Twisted Pair IndicatorOn the grand stage of the financial market, every trader is looking for a partner who can lead them to dance the tango well. The "Twisted Pair" indicator is that partner who dances gracefully in the market fluctuations. It weaves the rhythm of the market with two lines, helping traders to find the rhythm in the market's dance floor.
Imagine when the market is as calm as water, the "Twisted Pair" is like two ribbons tightly intertwined. They almost overlap on the chart, as if whispering: "Now, let's enjoy these quiet dance steps." This is the market consolidation period, the price fluctuation is not significant, traders can relax and slowly savor every detail of the market.
Now, let's describe the market logic of this code in natural language:
- **HJ_1**: This is the foundation of the market dance steps, by calculating the average price and trading volume, setting the tone for the market rhythm.
- **HJ_2** and **HJ_3**: These two lines are the arms of the dance partner, they help traders identify the long-term trend of the market through smoothing.
- **HJ_4**: This is a magnifying glass for market sentiment, it reveals the tension and excitement of the market by calculating the short-term deviation of the price.
- **A7** and **A9**: These two lines are the guide to the dance steps, they separate when the market volatility increases, guiding the traders in the right direction.
- **WATCH**: This is the signal light of the dance, when the two lines overlap, the market is calm; when they separate, the market is active.
The "Twisted Pair" indicator is like a carefully choreographed dance, it allows traders to find their own rhythm in the market dance floor, whether in a calm slow dance or a passionate tango. Remember, the market is always changing, and the "Twisted Pair" is the perfect dance partner that can lead you to dance out brilliant steps.
The script of this "Twisted Pair" uses three different types of moving averages: EMA (Exponential Moving Average), DEMA (Double EMA), and TEMA (Triple EMA). These types can be selected by the user through exchange input.
Here are the main functions of this code:
1. Defined the DEMA and TEMA functions: These two functions are used to calculate the corresponding moving averages. EMA is the exponential moving average, which is a special type of moving average that gives more weight to recent data. In the first paragraph, ema1 is the EMA of "length", and ema2 is the EMA of ema1. DEMA is 2 times of ema1 minus ema2.
2. Let users choose to use EMA, DEMA or TEMA: This part of the code provides an option for users to choose which type of moving average they want to use.
3. Defined an algorithm called "Twisted Pair algorithm": This part of the code defines a complex algorithm to calculate a value called "HJ". This algorithm involves various complex calculations and applications of EMA, DEMA, TEMA.
4. Plotting charts: The following code is used to plot charts on Tradingview. It uses the plot function to draw lines, the plotcandle function to draw candle (K-line) charts, and yellow and red to represent different conditions.
5. Specify colors: The last two lines of code use yellow and red K-line charts to represent the conditions of HJ_7. If the conditions of HJ_7 are met, the color of the K-line chart will change to the corresponding color. Indicator
Squeeze Momentum TD - A Revisited Version of the TTM SqueezeDescription:
The "Squeeze Momentum TD" is our unique take on the highly acclaimed TTM Squeeze indicator, renowned in the trading community for its efficiency in pinpointing market momentum. This script is a tribute and an extension to the foundational work laid by several pivotal figures in the trading industry:
• John Carter, for his creation of the TTM Squeeze and TTM Squeeze Pro, which revolutionized the way traders interpret volatility and momentum.
• Lazybear, whose original interpretation of the TTM Squeeze, known as the "Squeeze Momentum Indicator", provided an invaluable foundation for further development.
• Makit0, who evolved Lazybear's script to incorporate enhancements from the TTM Squeeze Pro, resulting in the "Squeeze PRO Arrows".
Our script, "Squeeze Momentum TD", represents a custom version developed after reviewing all variations of the TTM Squeeze indicator. This iteration focuses on a distinct visualization approach, featuring an overlay band on the chart for an user-friendly experience. We've distilled the essence of the TTM Squeeze and its advanced version, the TTM Squeeze Pro, into a form that emphasizes intuitive usability while retaining comprehensive analytical depth.
Features:
-Customizable Bollinger Bands and Keltner Channels: These core components of the TTM Squeeze.
-Dynamic Squeeze Conditions: Ranging from No Squeeze to High Compression.
-Momentum Oscillator: A linear regression-based momentum calculation, offering clear insights into market trends.
-User-Defined Color Schemes: Personalize your experience with adjustable colors for bands and plot shapes.
-Advanced Alert System: Alerts for key market shifts like Bull Watch Out, Bear Watch Out, and Momentum shifts.
-Adaptive Band Widths: Modify the band widths to suit your preference.
How to use it?
• Transition from Light Green to Dark Green: Indicates a potential end to the bullish momentum. This 'Bull Watch Out' signal suggests that traders should be cautious about continuing bullish trends.
• Transition from Light Red to Dark Red: Signals that the bearish momentum might be fading, triggering a 'Bear Watch Out' alert. It's a hint for traders to be wary of ongoing bearish trends.
• Shift from Dark Green to Light Green: This change suggests an increase in bullish momentum. It's an indicator for traders to consider bullish positions.
• Change from Dark Red to Light Red: Implies that bearish momentum is picking up. Traders might want to explore bearish strategies under this condition.
• Rapid Change from Light Red to Light Green: This swift shift indicates a quick transition from bearish to bullish sentiment. It's a strong signal for traders to consider switching to bullish positions.
• Quick Shift from Light Green to Light Red: Demonstrates a speedy change from bullish to bearish momentum. It suggests that traders might want to adjust their strategies to align with the emerging bearish trend.
Acknowledgements:
Special thanks to Beardy_Fred for the significant contributions to the development of this script. This work stands as a testament to the collaborative spirit of the trading community, continuously evolving to meet the demands of diverse trading strategies.
Disclaimer:
This script is provided for educational and informational purposes only. Users should conduct their own due diligence before making any trading decisions.
Indicator
Indicator
Indicator
Volume Exhaustion [AlgoAlpha]Introducing the Volume Exhaustion by AlgoAlpha, is an innovative tool that aims to identify potential exhaustion or peaks in trading volume , which can be a key indicator for reversals or continuations in market trends 🔶.
Key Features:
Signal Plotting : A special feature is the plotting of 'Release' signals, marked by orange diamonds, indicating points where the exhaustion index crosses under its previous value and is above a certain boundary. This could signify critical market points 🚨.
Calculation Length Customization : Users can adjust the calculation and Signal lengths to suit their trading style, allowing for flexibility in analysis over different time periods. ☝️
len = input(50, "Calculation Length")
len2 = input(8, "Signal Length")
Visual Appeal : The script offers customizable colors (col for the indicator and col1 for the background) enhancing the visual clarity and user experience 💡.
col = input.color(color.white, "Indicator Color")
col1 = input.color(color.gray, "Background Color")
Advanced Volume Processing : At its core, the script utilizes a combination of Hull Moving Average (HMA) and Exponential Moving Average (EMA) applied to the volume data. This sophisticated approach helps in smoothing out the volume data and reducing lag.
sv = ta.hma(volume, len)
ssv = ta.hma(sv, len)
Volume Exhaustion Detection : The script calculates the difference between the volume and its smoothed version, normalizing this value to create an exhaustion index (fff). Positive values of this index suggest potential volume exhaustion.
f = sv-ssv
ff = (f) / (ta.ema(ta.highest(f, len) - ta.lowest(f, len), len)) * 100
fff = ff > 0 ? ff : 0
Boundary and Zero Line : The script includes a boundary line (boundary) and a zero line (zero), with the area between them filled for enhanced visual interpretation. This helps in assessing the relative position of the exhaustion index.
Customizable Background : The script colors the background of the chart for better readability and to distinguish the indicator’s area clearly.
Overall, Volume Exhaustion is designed for traders who focus on volume analysis. It provides a unique perspective on volume trends and potential exhaustion points, which can be crucial for making informed trading decisions. This script is a valuable addition for traders looking to enhance their trading experience with advanced volume analysis tools. Indicator
Indicator
Indicator
Logarithmic Volatility Direction Index [IkkeOmar]The LVDI is a Mean-Reversion Indicator. it doesn't detect trends and does not give a signal per se.
What it does is tell you if we have a flashcrash based on the price action and volume that is available. It is not always easy to see with the naked eye, so this indicator can help you DCA into an asset in a smarter way, if you couple it with other trend systems.
Think of this indicator like a form of a volatility index.
Inputs:
len and lenWMA are integers representing different lengths for calculations, and src is the data source
Keep in mind that "Length" is the lookback for the WMA, and the Length smooting is the lookback for the SMA of the "volume_weighted".
WMA Calculation
wma_basic = math.log10(ta.wma(src, len))
This calculates the logarithm (base 10) of the Weighted Moving Average (WMA) of the source data over len periods. WMA is a type of moving average giving more importance to recent data. The reason I use log10, is to make it transformative over a longer timeframe. This makes it easier to see the growth direction. I like to use this for crypto, since there is asymetric upside.
Volume Filter:
average_volume = ta.sma(volume, lenWMA)
volume_weighted = math.log10(wma_basic * (volume / math.log10(average_volume)))
Here, the script first calculates the Simple Moving Average (SMA) of the trading volume over lenWMA periods. Then, it computes a volume-weighted value of the WMA, adjusted by the logarithmic ratio of current volume to average volume.
Distance and Score Calculation:
distance = math.log10(src) - math.log10(volume_weighted)
score = math.sign(distance) * math.pow(math.abs(distance), 2)
The script calculates the logarithmic difference between the source data and the volume-weighted WMA. The score is determined by the sign of this distance multiplied by its square. This potentially amplifies the impact of larger distances.
Plotting:
plot(volume_weighted, title="Volume Weighted WMA", color=color.blue, linewidth = 2)
plot(ta.sma(volume_weighted, lenWMA), title="Volume Weighted WMA", color=color.rgb(189, 160, 0))
Mathematical concepts
Weighted Moving Average (WMA):
WMA is a moving average that assigns more weight to recent data points. The idea is that recent prices are more relevant to the current trend than older prices.
Logarithms:
The use of log10 (logarithm base 10) is interesting. Logarithms help in normalizing data and can make certain patterns more visible, especially when dealing with exponential growth or decay.
Volume Weighting:
Multiplying the WMA by the ratio of current volume to average volume (both logarithmic) integrates volume into the analysis. High trading volume can signify stronger market interest and can thus validate price movements.
Distance and Score:
The distance measures how far the current price is from the volume-weighted WMA on a logarithmic scale. The score squares this distance, potentially highlighting large divergences.
Case example
In the case above (which is a low timeframe that shouldn't be your main system) we see the blue line going up before going below the moving average line (orange). This indicates a local bottom zone. Does that mean that we wont go lower? No! What you can do is calculate a zone range.
We have an average line, you can get that from the POC with the VRVP.
Then you take the low and high of that zone and take the average:
(3.17% + 2.33%) / 2 = 2.75%
This means that we expect that the price can fall an additional 2.75%! Low and behold. When you check the same chart as above:
Hope it makes sense!
Stay safe everyone!
Don't hesitate to ask any questions if you have any! Indicator
Advanced Dynamic Threshold RSI [Elysian_Mind]Advanced Dynamic Threshold RSI Indicator
Overview
The Advanced Dynamic Threshold RSI Indicator is a powerful tool designed for traders seeking a unique approach to RSI-based signals. This indicator combines traditional RSI analysis with dynamic threshold calculation and optional Bollinger Bands to generate weighted buy and sell signals.
Features
Dynamic Thresholds: The indicator calculates dynamic thresholds based on market volatility, providing more adaptive signal generation.
Performance Analysis: Users can evaluate recent price performance to further refine signals. The script calculates the percentage change over a specified lookback period.
Bollinger Bands Integration: Optional integration of Bollinger Bands for additional confirmation and visualization of potential overbought or oversold conditions.
Customizable Settings: Traders can easily customize key parameters, including RSI length, SMA length, lookback bars, threshold multiplier, and Bollinger Bands parameters.
Weighted Signals: The script introduces a unique weighting mechanism for signals, reducing false positives and improving overall reliability.
Underlying Calculations and Methods
1. Dynamic Threshold Calculation:
The heart of the Advanced Dynamic Threshold RSI Indicator lies in its ability to dynamically calculate thresholds based on multiple timeframes. Let's delve into the technical details:
RSI Calculation:
For each specified timeframe (1-hour, 4-hour, 1-day, 1-week), the Relative Strength Index (RSI) is calculated using the standard 14-period formula.
SMA of RSI:
The Simple Moving Average (SMA) is applied to each RSI, resulting in the smoothing of RSI values. This smoothed RSI becomes the basis for dynamic threshold calculations.
Dynamic Adjustment:
The dynamically adjusted threshold for each timeframe is computed by adding a constant value (5 in this case) to the respective SMA of RSI. This dynamic adjustment ensures that the threshold reflects changing market conditions.
2. Weighted Signal System:
To enhance the precision of buy and sell signals, the script introduces a weighted signal system. Here's how it works technically:
Signal Weighting:
The script assigns weights to buy and sell signals based on the crossover and crossunder events between RSI and the dynamically adjusted thresholds. If a crossover event occurs, the weight is set to 2; otherwise, it remains at 1.
Signal Combination:
The weighted buy and sell signals from different timeframes are combined using logical operations. A buy signal is generated if the product of weights from all timeframes is equal to 2, indicating alignment across timeframe.
3. Experimental Enhancements:
The Advanced Dynamic Threshold RSI Indicator incorporates experimental features for educational exploration. While not intended as proven strategies, these features aim to offer users a glimpse into unconventional analysis. Some of these features include Performance Calculation, Volatility Calculation, Dynamic Threshold Calculation Using Volatility, Bollinger Bands Module, Weighted Signal System Incorporating New Features.
3.1 Performance Calculation:
The script calculates the percentage change in the price over a specified lookback period (variable lookbackBars). This provides a measure of recent performance.
pctChange(src, length) =>
change = src - src
pctChange = (change / src ) * 100
recentPerformance1H = pctChange(close, lookbackBars)
recentPerformance4H = pctChange(request.security(syminfo.tickerid, "240", close), lookbackBars)
recentPerformance1D = pctChange(request.security(syminfo.tickerid, "1D", close), lookbackBars)
3.2 Volatility Calculation:
The script computes the standard deviation of the closing price to measure volatility.
volatility1H = ta.stdev(close, 20)
volatility4H = ta.stdev(request.security(syminfo.tickerid, "240", close), 20)
volatility1D = ta.stdev(request.security(syminfo.tickerid, "1D", close), 20)
3.3 Dynamic Threshold Calculation Using Volatility:
The dynamic thresholds for RSI are calculated by adding a multiplier of volatility to 50.
dynamicThreshold1H = 50 + thresholdMultiplier * volatility1H
dynamicThreshold4H = 50 + thresholdMultiplier * volatility4H
dynamicThreshold1D = 50 + thresholdMultiplier * volatility1D
3.4 Bollinger Bands Module:
An additional module for Bollinger Bands is introduced, providing an option to enable or disable it.
// Additional Module: Bollinger Bands
bbLength = input(20, title="Bollinger Bands Length")
bbMultiplier = input(2.0, title="Bollinger Bands Multiplier")
upperBand = ta.sma(close, bbLength) + bbMultiplier * ta.stdev(close, bbLength)
lowerBand = ta.sma(close, bbLength) - bbMultiplier * ta.stdev(close, bbLength)
3.5 Weighted Signal System Incorporating New Features:
Buy and sell signals are generated based on the dynamic threshold, recent performance, and Bollinger Bands.
weightedBuySignal = rsi1H > dynamicThreshold1H and rsi4H > dynamicThreshold4H and rsi1D > dynamicThreshold1D and crossOver1H
weightedSellSignal = rsi1H < dynamicThreshold1H and rsi4H < dynamicThreshold4H and rsi1D < dynamicThreshold1D and crossUnder1H
These features collectively aim to provide users with a more comprehensive view of market dynamics by incorporating recent performance and volatility considerations into the RSI analysis. Users can experiment with these features to explore their impact on signal accuracy and overall indicator performance.
Indicator Placement for Enhanced Visibility
Overview
The design choice to position the "Advanced Dynamic Threshold RSI" indicator both on the main chart and beneath it has been carefully considered to address specific challenges related to visibility and scaling, providing users with an improved analytical experience.
Challenges Faced
1. Differing Scaling of RSI Results:
RSI values for different timeframes (1-hour, 4-hour, and 1-day) often exhibit different scales, especially in markets like gold.
Attempting to display these RSIs on the same chart can lead to visibility issues, as the scaling differences may cause certain RSI lines to appear compressed or nearly invisible.
2. Candlestick Visibility vs. RSI Scaling:
Balancing the visibility of candlestick patterns with that of RSI values posed a unique challenge.
A single pane for both candlesticks and RSIs may compromise the clarity of either, particularly when dealing with assets that exhibit distinct volatility patterns.
Design Solution
Placing the buy/sell signals above/below the candles helps to maintain a clear association between the signals and price movements.
By allocating RSIs beneath the main chart, users can better distinguish and analyze the RSI values without interference from candlestick scaling.
Doubling the scaling of the 1-hour RSI (displayed in blue) addresses visibility concerns and ensures that it remains discernible even when compared to the other two RSIs: 4-hour RSI (orange) and 1-day RSI (green).
Bollinger Bands Module is optional, but is turned on as default. When the module is turned on, the users can see the upper Bollinger Band (green) and lower Bollinger Band (red) on the main chart to gain more insight into price actions of the candles.
User Flexibility
This dual-placement approach offers users the flexibility to choose their preferred visualization:
The main chart provides a comprehensive view of buy/sell signals in relation to candlestick patterns.
The area beneath the chart accommodates a detailed examination of RSI values, each in its own timeframe, without compromising visibility.
The chosen design optimizes visibility and usability, addressing the unique challenges posed by differing RSI scales and ensuring users can make informed decisions based on both price action and RSI dynamics.
Usage
Installation
To ensure you receive updates and enhancements seamlessly, follow these steps:
Open the PulseWire platform.
Navigate to the "Indicators" tab in the top menu.
Click on "Community Scripts" and search for "Advanced Dynamic Threshold RSI Indicator."
Select the indicator from the search results and click on it to add to your chart.
This ensures that any future updates to the indicator can be easily applied, keeping you up-to-date with the latest features and improvements.
Review Code
Open PulseWire and navigate to the Pine Editor.
Copy the provided script.
Paste the script into the Pine Editor.
Click "Add to Chart."
Configuration
The indicator offers several customizable settings:
RSI Length: Defines the length of the RSI calculation.
SMA Length: Sets the length of the SMA applied to the RSI.
Lookback Bars: Determines the number of bars used for recent performance analysis.
Threshold Multiplier: Adjusts the multiplier for dynamic threshold calculation.
Enable Bollinger Bands: Allows users to enable or disable Bollinger Bands integration.
Interpreting Signals
Buy Signal: Generated when RSI values are above dynamic thresholds and a crossover occurs.
Sell Signal: Generated when RSI values are below dynamic thresholds and a crossunder occurs.
Additional Information
The indicator plots scaled RSI lines for 1-hour, 4-hour, and 1-day timeframes.
Users can experiment with additional modules, such as machine-learning simulation, dynamic real-life improvements, or experimental signal filtering, depending on personal preferences.
Conclusion
The Advanced Dynamic Threshold RSI Indicator provides traders with a sophisticated tool for RSI-based analysis, offering a unique combination of dynamic thresholds, performance analysis, and optional Bollinger Bands integration. Traders can customize settings and experiment with additional modules to tailor the indicator to their trading strategy.
Disclaimer: Use of the Advanced Dynamic Threshold RSI Indicator
The Advanced Dynamic Threshold RSI Indicator is provided for educational and experimental purposes only. The indicator is not intended to be used as financial or investment advice. Trading and investing in financial markets involve risk, and past performance is not indicative of future results.
The creator of this indicator is not a financial advisor, and the use of this indicator does not guarantee profitability or specific trading outcomes. Users are encouraged to conduct their own research and analysis and, if necessary, consult with a qualified financial professional before making any investment decisions.
It is important to recognize that all trading involves risk, and users should only trade with capital that they can afford to lose. The Advanced Dynamic Threshold RSI Indicator is an experimental tool that may not be suitable for all individuals, and its effectiveness may vary under different market conditions.
By using this indicator, you acknowledge that you are doing so at your own risk and discretion. The creator of this indicator shall not be held responsible for any financial losses or damages incurred as a result of using the indicator.
Kind regards,
Ely Indicator
Indicator
Indicator
Indicator
Robust Bollinger Bands with Trend StrengthThe "Robust Bollinger Bands with Trend Strength" indicator is a technical analysis tool designed assess price volatility, identify potential trading opportunities, and gauge trend strength. It combines several robust statistical methods and percentile-based calculations to provide valuable information about price movements with Improved Resilience to Noise while mitigating the impact of outliers and non-normality in price data.
Here's a breakdown of how this indicator works and the information it provides:
Bollinger Bands Calculation: Similar to traditional Bollinger Bands, this indicator calculates the upper and lower bands that envelop the median (centerline) of the price data. These bands represent the potential upper and lower boundaries of price movements.
Robust Statistics: Instead of using standard deviation, this indicator employs robust statistical measures to calculate the bands (spread). Specifically, it uses the Interquartile Range (IQR), which is the range between the 25th percentile (low price) and the 75th percentile (high price). Robust statistics are less affected by extreme values (outliers) and data distributions that may not be perfectly normal. This makes the bands more resistant to unusual price spikes.
Median as Centerline: The indicator utilizes the median of the chosen price source (either HLC3 or VWMA) as the central reference point for the bands. The median is less affected by outliers than the mean (average), making it a robust choice. This can help identify the center of price action, which is useful for understanding whether prices are trending or ranging.
Trend Strength Assessment: The indicator goes beyond the standard Bollinger Bands by incorporating a measure of trend strength. It uses a robust rank-based correlation coefficient to assess the relationship between the price source and the bar index (time). This correlation coefficient, calculated over a specified length, helps determine whether a trend is strong, positive (uptrend), negative (down trend), or non-existent and weak. When the rank-based correlation coefficient shifts it indicates exhaustion of a prevailing trend. Trend Strength" indicator is designed to provide statistically valid information about trend strength while minimizing the impact of outliers and data distribution characteristics. The parameter choices, including a length of 14 and a correlation threshold of +/-0.7, considered to offer meaningful insights into market conditions and statistical validity (p-value ,0.05 statistically significant). The use of rank-based correlation is a robust alternative to traditional Pearson correlation, especially in the context of financial markets.
Trend Fill: Based on the robust rank-based correlation coefficient, the indicator fills the area between the upper and lower Bollinger Bands with different colors to visually represent the trend strength. For example, it may use green for an uptrend, red for a down trend, and a neutral color for a weak or ranging market. This visual representation can help traders quickly identify potential trend opportunities. In addition the middle line also informs about the overall trend direction of the median. Indicator
VWMA/SMA Delta Volatility (Statistical Anomaly Detector)The "VWMA/SMA Delta Volatility (Statistical Anomaly Detector)" indicator is a tool designed to detect and visualize volatility in a financial market's price data. The indicator calculates the difference (delta) between two moving averages (VWMA/SMA) and uses statistical analysis to identify anomalies or extreme price movements. Here's a breakdown of its components:
Hypothesis:
The hypothesis behind this indicator is that extreme price movements or anomalies in the market can be detected by analyzing the difference between two moving averages and comparing it to a statistically derived normal distribution. When the MA delta (the difference between two MAs: VWMA/SMA) exceeds a certain threshold based on standard deviation and the Z-score coefficient, it may indicate increased market volatility or potential trading opportunities.
Calculation of MA Delta:
The indicator calculates the MA delta by subtracting a simple moving average (SMA) from a volume-weighted moving average (VWMA) of a selected price source. This calculation represents the difference in the market's short-term and long-term trends.
Statistical Analysis:
To detect anomalies, the indicator performs statistical analysis on the MA delta. It calculates a moving average (MA) of the MA delta and its standard deviation over a specified sample size. This MA acts as a baseline, and the standard deviation is used to measure how much the MA delta deviates from the mean.
Delta Normalization:
The MA delta, lower filter, and upper filter are normalized using a function that scales them to a specific range, typically from -100 to 100. Normalization helps in comparing these values on a consistent scale and enhances their visual representation.
Visual Representation:
The indicator visualizes the results through histograms and channels:
The histogram bars represent the normalized MA delta. Red bars indicate negative and below-lower-filter values, green bars indicate positive and above-upper-filter values, and silver bars indicate values within the normal range.
It also displays a Z-score channel, which represents the upper and lower filters after normalization. This channel helps traders identify price levels that are statistically significant and potentially indicative of market volatility.
In summary, the "MA Delta Volatility (Statistical Anomaly Detector)" indicator aims to help traders identify abnormal price movements in the market by analyzing the difference between two moving averages and applying statistical measures. It can be a valuable tool for traders looking to spot potential opportunities during periods of increased volatility or to identify potential market anomalies. Indicator
ATR Adaptive RSI OscillatorThe " ATR Adaptive RSI Oscillator " is a versatile technical analysis tool designed to help traders make informed decisions in dynamic market conditions. It combines the Relative Strength Index (RSI) with the Average True Range (ATR) to provide adaptive and responsive insights into price trends.
Key Features :
Adaptive RSI Periods : The indicator introduces the concept of adaptive RSI periods based on the ATR (Average True Range) of the market. When enabled, it dynamically adjusts the RSI calculation period, offering longer periods during high volatility and shorter periods during low volatility. This adaptability enhances the accuracy of RSI signals across varying market conditions.
Volume-Based Smoothing : The indicator includes a smoothing feature that computes a time-decayed weighted moving average of RSI values over the last two bars, using volume-based weights. This approach offers a time-sensitive smoothing effect, reducing noise for a clearer view of trend strength compared to the standard RSI.
Divergence Detection : Traders can enable divergence detection to identify potential reversal points in the market. The indicator highlights regular bullish and bearish divergences, providing valuable insights into market sentiment shifts.
Customizable Parameters : Traders have the flexibility to customize various parameters, including RSI length, adaptive mode, ATR length, and divergence settings, to tailor the indicator to their trading strategy.
Overbought and Oversold Levels : The indicator includes overbought (OB) and oversold (OS) boundary lines that can be adjusted to suit individual preferences. These levels help traders identify potential reversal zones.
The "ATR Adaptive RSI Oscillator" is a powerful tool for traders seeking to adapt their trading strategies to changing market dynamics. Whether you're a trend follower or a contrarian trader, this indicator provides valuable insights to support your decision-making process. Indicator
Indicator
Indicator
RSI Supreme Multi-Method [MyTradingCoder]Introducing the "RSI Supreme Multi-Method" indicator, a powerful tool that combines the Relative Strength Index (RSI) with selectable manipulation methods to identify overbought and oversold conditions in the market, along with the ability to detect divergences for enhanced trading insights.
The indicator features four distinct manipulation methods for the RSI, each providing valuable insights into market conditions:
1. Standard RSI Method: The indicator uses the traditional RSI calculation to identify overbought and oversold areas.
2. Volatility Weighted RSI Method: This method applies a volatility formula to the RSI calculation, allowing for a more responsive indication of market conditions during periods of heightened volatility. Users can adjust the length of the volatility formula to fine-tune this method.
3. Smoothed RSI Method: The smoothed RSI method utilizes a smoothing algorithm to reduce noise in the RSI values, presenting a clearer representation of overbought and oversold conditions. The length of the smoothing can be adjusted to match your trading preferences.
4. Session Weighted RSI Method: With this innovative method, users can specify multipliers for different time sessions throughout the day to manipulate the base RSI. Each session can be customized with start and end times, enabling or disabling specific sessions, and specifying the multiplier for each session. This feature allows traders to adapt the RSI to different market sessions dynamically.
Additionally, the "RSI Supreme Multi-Method" indicator draws divergences on the oscillator, providing an extra layer of analysis for traders. Divergences occur when the direction of the RSI differs from the direction of the price movement, potentially signaling trend reversals.
Key Settings:
RSI Length: Adjust the length of the base RSI before applying any manipulation.
RSI Source: Determine the data source for the base RSI calculation.
Overbought Value: Set the RSI value at which overbought conditions are indicated.
Oversold Value: Set the RSI value at which oversold conditions are indicated.
RSI Type: Choose from four options: Standard, Smoothed, Volatility Manipulated, or Session Manipulated.
Volatility Manipulated Settings: Adjust the length of the volatility formula (applicable to Volatility Manipulated method).
Smoothed Settings: Adjust the length of the smoothing (applicable to Smoothed method).
Session Manipulated Settings: Customize six different time sessions with start and end times, enable or disable specific sessions, and specify multipliers for each session.
Divergence Color: Adjust the color of the drawn divergences to suit your chart's aesthetics.
Divergence Tuning: Fine-tune the sensitivity of the divergence detection for more accurate signals.
The "RSI Supreme Multi-Method" indicator is a versatile and comprehensive tool that can be used to identify overbought and oversold areas, as well as to spot potential trend reversals through divergences. However, like all technical analysis tools, it should be used in conjunction with other indicators and analysis methods to make well-informed trading decisions.
Enhance your trading insights with the "RSI Supreme Multi-Method" indicator and gain an edge in identifying critical market conditions and divergences with precision. Indicator
Buyers & Sellers / RangeBuyers & Sellers / Range
Volatility oscillator that measures the relationship of Buying & Selling Pressure to True Range.
In other words, how much % Buyers and Sellers separately occupy the Bar
BSP is a part of Bar Range. Entire bar metrics will always have bigger value than its composite elements (body and wicks).
Since there will be NO chance of BP or SP being more than ATR, their ratio would serve crucial Volatility details.
Hence, we can relate each of them to the overall range.
As a result we have simultaneous measurements of proportions buyers and sellers to the bar.
Default mode shows BP/ATR and SP/ATR mirrored. When one rises, the other falls to compensate.
Buying Pressure / True Range ⬆️🟢 ⬇️🔵
Selling Pressure / True Range ⬆️🔴 ⬇️🟠
They are being averaged in 2 different ways:
Pre-average first, then relate as ratio
Related first, then Averaged
Enable "Preaveraged" to use already averaged BSP and Ranges in ratio instead of averaging the ratio of BSP to individual bar. For example, we're looking BP/ATR, in calculation of buyers / Range it will use "MA(Buying Pressure) / MA(True Range)" instead of "MA(Buying Pressure / True Range)".
Due such calculation, it is going to be more lagging than in off mode. Nevertheless, it reduces noise from the impact of individual bar change.
Second way of noise reduction is enabling "Body / Range"
BSP Body / Range where Bullish & Bearish Body = Buying & Selling Pressure - Relevant Wick
Buying Body = Buying Pressure - Lower Wick
Selling Body = Selling Pressure - Upper Wick
And only then it is divided to ATR.
Note that Balance line differs because body is less than it used to be with wicks. So change in wicks won't play any role in computing the ratio anymore. Thus, signals of their crossings will be more reliable than in default mode. Indicator
Developing Market Profile / TPO [Honestcowboy]The Developing Market Profile Indicator aims to broaden the horizon of Market Profile / TPO research and trading. While standard Market Profiles aim is to show where PRICE is in relation to TIME on a previous session (usually a day). Developing Market Profile will change bar by bar and display PRICE in relation to TIME for a user specified number of past bars.
What is a market profile?
"Market Profile is an intra-day charting technique (price vertical, time/activity horizontal) devised by J. Peter Steidlmayer. Steidlmayer was seeking a way to determine and to evaluate market value as it developed in the day time frame. The concept was to display price on a vertical axis against time on the horizontal, and the ensuing graphic generally is a bell shape--fatter at the middle prices, with activity trailing off and volume diminished at the extreme higher and lower prices."
For education on market profiles I recommend you search the net and study some profitable traders who use it.
Key Differences
Does not have a value area but distinguishes each column in relation to the biggest column in percentage terms.
Updates bar by bar
Does not take sessions into account
Shows historical values for each bar
While there is an entire education system build around Market Profiles they usually focus on a daily profile and in some cases how the value area develops during the day (there are indicators showing the developing value area).
The idea of trading based on a developing value area is what inspired me to build the Developing Market Profile.
🟦 CALCULATION
Think of this Developing Market Profile the same way as you would think of a moving average. On each bar it will lookback 200 bars (or as user specified) and calculate a Market Profile from those bars (range).
🔹Market Profile gets calculated using these steps:
Get the highest high and lowest low of the price range.
Separate that range into user specified amount of price zones (all spaced evenly)
Loop through the ranges bars and on each bar check in which price zones price was, then add +1 to the zones price was in (we do this using the OccurenceArray)
After it looped through all bars in the range it will draw columns for each price zone (using boxes) and make them as wide as the OccurenceArray dictates in number of bars
🔹Coloring each column:
The script will find the biggest column in the Profile and use that as a reference for all other columns. It will then decide for each column individually how big it is in % compared to the biggest column. It will use that percentage to decide which color to give it, top 20% will be red, top 40% purple, top 60% blue, top 80% green and all the rest yellow. The user is able to adjust these numbers for further customisation.
The historical display of the profiles uses plotchar() and will not only use the color of the column at that time but the % rating will also decide transparancy for further detail when analysing how the profiles developed over time. Each of those historical profiles is calculated using its own 200 past bars. This makes the script very heavy and that is why it includes optimisation settings, more info below.
🟦 USAGE
My general idea of the markets is that they are ever changing and that in studying that changing behaviour a good trader is able to distinguish new behaviour from old behaviour and adapt his approach before losing traders "weak hands" do.
A Market Profile can visually show a trader what kind of market environment we currently are in. In training this visual feedback helps traders remember past market environments and how the market behaved during these times.
Use the history shown using plotchars in colors to get an idea of how the Market Profile looked at each bar of the chart.
This history will help in studying how price moves at different stages of the Market Profile development.
I'm in no way an expert in trading Market Profiles so take this information with a grain of salt. Below an idea of how I would trade using this indicator:
🟦 SETTINGS
🔹MARKET PROFILING
Lookback: The amount of bars the Market Profile will look in the past to calculate where price has been the most in that range
Resolution: This is the amount of columns the Market Profile will have. These columns are calculated using the highest and lowest point price has been for the lookback period
Resolution is limited to a maximum of 32 because of pinescript plotting limits (64). Each plotchar() because of using variable colors takes up 2 of these slots
🔹VISUAL SETTINGS
Profile Distance From Chart: The amount of bars the market profile will be offset from the current bar
Border width (MP): The line thickness of the Market Profile column borders
Character: This is the character the history will use to show past profiles, default is a square.
Color theme: You can pick 5 colors from biggest column of the Profile to smallest column of the profile.
Numbers: these are for % to decide column color. So on default top 20% will be red, top 40% purple... Always use these in descending order
Show Market Profile: This setting will enable/disable the current Market Profile (columns on right side of current bar)
Show Profile History: This setting will enable/disable the Profile History which are the colored characters you see on each bar
🔹OPTIMISATION AND DEBUGGING
Calculate from here: The Market Profile will only start to calculate bar by bar from this point. Setting is needed to optimise loading time and quite frankly without it the script would probably exceed pulsewire loading time limits.
Min Size: This setting is there to avoid visual bugs in the script. Scaling the chart there can be issues where the Market Profile extends all the way to 0. To avoid this use a minimum size bigger than the bugged bottom box Indicator
