RSI with SMA and Bollinger BandsRSI with SMA and Bollinger Bands
The SMA and BB use the RSI as a source. The source of the RSI is selectable.
With the right settings, you can effectively determine the trend phase and trend strength.
I personally use the following settings:
RSI with a 14-period applied to Price Close.
The SMA has a 26-period, and the Bollinger Bands have a period of 50 with a deviation of 2.
M-oscillator
Stochastic Trend mtfDefinition
The Stochastic RSI indicator (Stoch RSI) is actually an indicator of an indicator. It is used in technical analysis to provide a stochastic calculation to the RSI indicator. This means it's an RSI measure relative to its own high/low range over a user-defined time period. Stochastic RSI is an oscillator that calculates a value between 0 and 1 and then plots it as a line. This indicator is primarily used to identify overbought and oversold conditions.
It is important to remember that the Stoch RSI is an indicator of an indicator that is two steps away from the price. The RSI is one step away from the price and therefore a stochastic calculation of the RSI is two steps away. This is important because as with any indicator that is more than one step away from price, the Stoch RSI can be short-term disconnected from actual price action. However, as a range-bound indicator, the Stoch RSI's primary function is to identify cross-bought, overbought and oversold conditions.
Use
When we integrate it into our chart in the upper time frame, it both gives the direction of the trend more healthy and is more efficient in terms of noise reduction in terms of leaving the overbought-sold zones. Unlike the classic stochastic, I set the "d" value to 8. Even though the trend returns are a little late, we see healthier data on our graph. Trend changes in overbought zones are getting stronger. Coloring red indicates that the trend is selling, while painting green indicates that the trend is buying. I hope you find it useful, if you have any questions or suggestions, please feel free to ask.
Good luck...
It is not investment advice.
Machine Learning Momentum Oscillator [ChartPrime]The Machine Learning Momentum Oscillator brings together the K-Nearest Neighbors (KNN) algorithm and the predictive strength of the Tactical Sector Indicator (TSI) Momentum. This unique oscillator not only uses the insights from TSI Momentum but also taps into the power of machine learning therefore being designed to give traders a more comprehensive view of market momentum.
At its core, the Machine Learning Momentum Oscillator blends TSI Momentum with the capabilities of the KNN algorithm. Introducing KNN logic allows for better handling of noise in the data set. The TSI Momentum is known for understanding how strong trends are and which direction they're headed, and now, with the added layer of machine learning, we're able to offer a deeper perspective on market trends. This is a fairly classical when it comes to visuals and trading.
Green bars show the trader when the asset is in an uptrend. On the flip side, red bars mean things are heading down, signaling a bearish movement driven by selling pressure. These color cues make it easier to catch the sentiment and direction of the market in a glance.
Yellow boxes are also displayed by the oscillator. These boxes highlight potential turning points or peaks. When the market comes close to these points, they can provide a heads-up about the possibility of changes in momentum or even a trend reversal, helping a trader make informed choices quickly. These can be looked at as possible reversal areas simply put.
Settings:
Users can adjust the number of neighbours in the KNN algorithm and choose the periods they prefer for analysis. This way, the tool becomes a part of a trader's strategy, adapting to different market conditions as they see fit. Users can also adjust the smoothing used by the oscillator via the smoothing input.
Bitcoin to GOLD [presentTrading]**Introduction and How it is Different**
Unlike traditional indicators, the BTGR offers a unique perspective on market sentiment and asset valuation by juxtaposing two seemingly disparate assets: Bitcoin, the digital gold, and Gold, the traditional store of value. This article introduces an advanced version of this ratio, complete with upper and lower bands calculated using standard deviations. These bands add an extra layer of analytical depth, allowing for more nuanced trading strategies.
BTCUSD 12h bigger picture
**Economic Principles**
The BTGR is rooted in the economic principles of asset valuation and market sentiment. Gold has long been considered a safe haven asset, a place where investors park their money during times of economic uncertainty. Bitcoin, on the other hand, is often viewed as a high-risk, high-reward investment. By comparing the two, the BTGR provides insights into the broader market sentiment.
- Risk Appetite: A high BTGR indicates a bullish sentiment towards riskier assets like Bitcoin.
- Market Uncertainty: A low BTGR suggests a bearish sentiment and a flight to the safety of Gold.
- Asset Diversification: The BTGR can be used as a tool for portfolio diversification, helping investors balance risk and reward.
**How to Use It**
Setting Up the Indicator
- Platform: The indicator is designed for use on TradingView.
- Time Frame: A 480-minute time frame is recommended for more accurate signals.
- Parameters: The moving average is set at 200 periods, and the standard deviation is calculated over the same period.
**Trading Signal**
Long Entry: Consider going long when the BTGR crosses above the upper band.
Short Entry: Consider going short when the BTGR crosses below the lower band.
Note: Due to the issue that the number of trading is less than about 100 times, the corresponding strategy is not allowed to publish.
Philpose's Binary Turbo 1.2Hello there,
I'm thrilled to introduce my very first TradingView indicator - "Philpose's Binary Turbo 1.0." This indicator isn't just another tool; it's my unique take on binary options trading, powered by the Relative Strength Index (RSI).
Differences from Other Indicators:
This indicator is designed for traders who prefer short-term trading, as it uses a 1-minute timeframe.
It assumes that RSI crossovers of overbought and oversold levels can be used to generate binary options signals.
Users should backtest and evaluate the indicator's performance in different market conditions and consider risk management strategies.
Custom Logic: This indicator implements a custom trading logic based on RSI crossovers of overbought and oversold levels. Many indicators on TradingView use standard indicators, but this script incorporates unique logic.
Signal Tracking: It tracks and displays the last buy and sell signals on the chart. This visual representation can be helpful for traders to see when signals were generated.
Streak Tracking: The script keeps track of winning and losing streaks, which can provide traders with insights into their trading performance over time.
Table Summary: It creates a table summarizing various statistics related to the signals generated, such as total signals, wins, losses, and streaks. This tabular representation can be useful for traders to assess the indicator's performance.
How to Use:
To use this indicator effectively, follow these steps:
Add the Indicator: Copy and paste the script into TradingView's Pine Script editor. Then, apply the indicator to the chart.
Customize Parameters: Adjust the RSI parameters (period, overbought, and oversold levels) and the minimum bars between signals according to your trading strategy and preferences.
Interpret Signals: Buy signals are generated when the RSI crosses above the oversold level, and sell signals occur when it crosses below the overbought level.
Analyze Streaks: Keep an eye on the win and loss streaks to assess the indicator's performance and your trading strategy.
Review Table: The table at the top-right corner of the chart provides a summary of important statistics related to signals, wins, losses, and streaks.
Markets and Conditions:
The script can be used in various financial markets, including stocks, forex, commodities, and indices. However, it's important to note that binary options trading has a distinct risk profile and is available on certain platforms. Therefore, you should ensure that your chosen binary options platform supports TradingView indicators and that you understand the specific conditions of binary options trading.
Conditions for Use:
This indicator is designed for traders who prefer short-term trading, as it uses a 1-minute timeframe.
It assumes that RSI crossovers of overbought and oversold levels can be used to generate binary options signals.
Users should backtest and evaluate the indicator's performance in different market conditions and consider risk management strategies.
Please exercise caution when using any trading indicator or strategy, especially in binary options trading, as it involves a high level of risk, and you may lose your entire investment. It's advisable to thoroughly test any strategy on a demo account before trading with real funds and to seek the advice of a qualified financial advisor if you are unsure about your trading decisions.
Zaree - RSI Gradient FillDescription:
The "Zaree - RSI Gradient Fill" (RGF) indicator is a technical analysis tool designed to enhance the interpretation of the Relative Strength Index (RSI) by incorporating visual cues through gradient fill. This indicator aids traders in identifying potential overbought and oversold conditions in the market using the RSI as a key reference.
Details of the Indicator:
The indicator calculates the RSI of a selected source based on user-defined settings for length and source.
Traders have the option to choose from various types of moving averages (SMA, EMA, SMMA, WMA) to calculate the RSI.
RSI values and their corresponding moving average values are plotted on the chart for visual analysis.
The indicator offers customization through input settings for RSI length, RSI source, and moving average type and length.
Upper and lower bands for the RSI are displayed on the chart, providing visual cues for potential overbought and oversold conditions.
A center line is plotted on the chart to help traders identify the equilibrium point of the RSI.
The gradient fill feature enhances the visualization by coloring the space between the RSI plot and the center line based on RSI levels.
How to Use the Indicator:
Specify the RSI length and source for calculation.
Choose the desired moving average type and set the length for the moving average.
Observe the RSI values, moving average lines, and the center line plotted on the chart.
Pay attention to the position of the RSI values relative to the upper and lower bands. Values above the upper band suggest potential overbought conditions, while values below the lower band indicate potential oversold conditions.
Interpret the gradient fill between the RSI plot and the center line. The color changes provide additional visual cues about the RSI's strength compared to the center line.
Example of Usage:
As an experienced swing trader, you can leverage the RGF indicator to fine-tune your trading decisions. Here's an example of how you might use the indicator:
Select your preferred RSI length and source, such as the closing price.
Choose "SMA" as the moving average type and set the length to 14.
Observe the RSI values plotted on the chart along with the upper and lower bands.
Pay special attention to the gradient fill between the RSI plot and the center line. This coloring offers valuable insights into the RSI's position relative to equilibrium.
Look for instances where the RSI values cross above or below the upper and lower bands. These crossings can signal potential trend shifts or reversals.
Use the gradient fill colors to quickly assess the strength of the RSI's deviation from the center line.
Remember that the RGF indicator is a powerful tool to complement your trading strategy. Consider combining its insights with other technical and fundamental analyses for well-informed trading decisions.
Feel free to adjust the indicator settings according to your trading preferences and style. While the RGF indicator provides valuable visual cues, always consider the broader context of the market before making trading choices.
SADROCThe "Smoothed Accumulation/Distribution Rate of Change" (SADROC) indicator draws inspiration from the Chaikin Oscillator's use of accumulation and distribution, formatted in a manner just like the MACD (Moving Average Convergence Divergence) indicator. My goal was to create something with greater speed and accuracy than the classic MACD
Here's a breakdown of its key elements:
Inputs: Users can customize the indicator by specifying the fast length, slow length, and signal length to fit their preferences.
Calculations: The indicator calculates cumulative volume and then computes the Accumulation/Distribution (AD) value based on price and volume data. The SADROC is calculated as the Rate of Change of the exponential moving averages of the price. The difference between these two values is further smoothed to generate the final SADROC value.
Plotting: The indicator plots the SADROC line and a signal line on the chart. Additionally, it includes a histogram that visually represents the difference between SADROC and the signal line.
Zaree - FX Index RSI IndicatorDescription:
The "Zaree - FX Index RSI Indicator" (FIRI) is a technical analysis tool designed to provide insights into the relative strength of two selected currency indices using the Relative Strength Index (RSI). It allows traders to compare the RSI values of a primary currency index and a secondary currency index, helping them identify potential overbought and oversold conditions in the currency market.
Details of the Indicator:
The indicator calculates the RSI for both the primary and secondary currency indices based on the user's selections.
Traders can choose from a variety of currency indices to use as the primary and secondary indices for comparison.
The indicator offers settings for customizing the calculation of the RSI, including selecting the type of moving average (SMA, EMA, WMA, SMMA) and adjusting the length of the RSI and moving average.
Upper and lower RSI bands are displayed on the chart to highlight potential overbought and oversold conditions.
The RSI values and their corresponding moving average values are plotted on the chart, allowing traders to visually analyze the relative strength of the indices.
How to Use the Indicator:
Select the primary and secondary currency indices you want to compare from the provided dropdown menus. These indices will serve as the basis for RSI calculation.
Choose the type of moving average (SMA, EMA, WMA, SMMA) to use for RSI calculation and set the desired length for the moving average.
Decide whether you want to visualize the RSI and moving average values for the primary and secondary indices on the chart.
Observe the RSI values and moving averages plotted on the chart. The indicator's upper and lower bands can help you identify potential overbought (above the upper band) and oversold (below the lower band) conditions.
Pay attention to the intersections between the RSI values and the moving average lines. These intersections can provide insights into potential trend changes or reversals in the currency market.
Example of Usage:
Let's say you're a swing trader focusing on currency pairs involving the US Dollar (USD) and Euro (EUR). You want to compare the relative strength of the USD Index (USDINX) and the EUR Index (EURINX) to identify potential trading opportunities. Here's how you can use the FIRI indicator:
Select "USDINX" as the primary index and "EURINX" as the secondary index.
Choose "SMA" as the moving average type and set the RSI length to 14.
Enable the visualization of RSI values for both the primary and secondary indices.
Observe the chart to identify instances where the RSI values of the indices cross above the upper band (potential overbought) or below the lower band (potential oversold).
Look for intersections between the RSI values and the moving average lines. A bullish signal may occur when the RSI crosses above the moving average, indicating potential upward momentum, while a bearish signal may occur when the RSI crosses below the moving average, indicating potential downward momentum.
Remember that the FIRI indicator is a tool to assist you in your analysis. It's important to consider other technical and fundamental factors before making trading decisions.
Feel free to adjust the settings of the indicator based on your trading preferences and strategy. Keep in mind that no indicator is foolproof, and it's recommended to use the FIRI indicator in conjunction with other analysis techniques for a comprehensive trading approach.
Zaree - FX Index Spread IndicatorDescription:
The "Zaree - FX Index Spread Indicator" (FISI) is a powerful technical analysis tool designed to provide insights into the spread between two selected currency indices. By calculating and visualizing the percentage difference between the values of a primary and a secondary currency index, traders can gain valuable information about potential market dynamics and trends.
Details of the Indicator:
The indicator calculates the spread percentage between a primary and a secondary currency index, allowing traders to understand the relative strength of the two indices.
Traders can choose from a list of currency indices to use as the primary and secondary indices for comparison.
The indicator offers multiple methods for setting thresholds to identify potential trading opportunities, including standard deviations, percentile ranks, historical highs and lows, and fixed thresholds.
Users can customize the length of the calculation period and choose whether to display the primary index, secondary index, and the spread percentage on the chart.
Shaded areas on the chart indicate regions where the spread percentage is above or below predefined thresholds, helping traders identify potential trading signals.
How to Use the Indicator:
Select the primary and secondary currency indices you want to compare from the provided dropdown menus. These indices will be used to calculate the spread percentage.
Choose the method for setting thresholds by selecting one of the options: "Standard Deviations," "Percentile Ranks," "Historical Highs and Lows," or "Fixed Thresholds."
Depending on the selected method, configure the relevant threshold parameters, such as historical threshold percentage, upper and lower fixed thresholds, upper and lower percentile thresholds, or the standard deviation multiplier.
Choose whether to visualize the primary index, secondary index, and spread percentage on the chart by enabling the respective options.
Observe the chart to identify potential trading signals based on the interactions between the spread percentage and the predefined thresholds.
Example of Usage:
Suppose you're interested in trading currency pairs involving the US Dollar (USD) and Euro (EUR), and you want to monitor the spread between the USD Index (USDINX) and the EUR Index (EURINX). Here's how you can use the FISI indicator:
Select "USDINX" as the primary index and "EURINX" as the secondary index.
Choose the method for setting thresholds based on your strategy. For instance, you can select "Standard Deviations" and adjust the standard deviation multiplier.
Enable the visualization of the primary index, secondary index, and spread percentage on the chart.
Observe the shaded areas on the chart. If the spread percentage crosses above the upper threshold, it may indicate a potential market overextension. Conversely, if the spread percentage crosses below the lower threshold, it could suggest an oversold market condition.
Look for instances where the spread percentage approaches or crosses the predefined thresholds. Consider these instances as potential entry or exit points for your trades.
Remember that the FISI indicator is a tool to assist you in your analysis. It's recommended to combine its insights with other technical and fundamental factors before making trading decisions. Adjust the indicator settings and thresholds based on your trading strategy and preferences.
As with any trading tool, practice and observation are key. Over time, you can refine your trading strategy by analyzing historical data and observing how the indicator performs in different market conditions.
Feel free to experiment with different settings and methods to find the configuration that aligns best with your trading style and goals.
Market Health OscillatorDesigned to provide traders with a comprehensive view of the overall health of a market. By combining the rate of change of key indicators, the MHO offers insight into potential shifts in market sentiment.
Components:
Price Rate of Change: The MHO considers the rate of change of the price of an asset over a specified period. This element reflects the momentum of the asset's price movement, aiding in the assessment of potential trend shifts.
Volume Rate of Change: Tracking the rate of change of trading volume provides insights into market participation and interest. Changes in volume can signify shifts in market sentiment and potential trend reversals.
Volatility Rate of Change: The rate of change of volatility, often measured using the Average True Range (ATR), helps gauge the level of uncertainty in the market. An increase in volatility can indicate heightened market activity and potential reversals.
Advance-Decline Line: The MHO takes into account the Advance-Decline Line, which compares the number of advancing stocks to declining stocks. This component offers insights into market breadth and the underlying strength of the current trend.
Calculation and Interpretation:
The MHO aggregates the rate of change of these components and combines them to provide a single oscillator reading. This reading is then normalized to a range between -1 and 1. Positive values suggest bullish market health, while negative values indicate bearish conditions. The oscillator's extremes, coupled with divergence patterns, can signal potential market turning points.
Application:
Identify potential trend reversals or corrections by watching for extreme MHO readings.
Assess the overall health of a market by observing the general direction and amplitude of the oscillator.
Look for divergences between price and the MHO for insights into potential shifts in market sentiment.
This was inspired to offer a holistic perspective on market dynamics. By encompassing price, volume, volatility, and breadth factors, the MHO assists in a comprehensive assessment of market health.
Momentum EruptionIndicator: Momentum Eruption , using momentum to capture swing trading.
⏩Principle overview:
The core of Momentum Eruption is divided into two parts. One is to identify the trend direction. This is relatively clear. It is usually more effective to identify the direction through moving averages such as SMA or EMA. The second is to identify trading opportunities and use the idea of following the trend in large cycle and reversing the trend in small cycle. For example, when the large cycle is bullish and the small cycle is callback, if there are oversold conditions, a rebound from the previous low support, a long downward pin-bar, and an increase in trading volume at the same time, the extreme value of the price rebound or correction can be calculated. When following the trend, go long at the extreme value of the callback and go short at the extreme value of the rebound.
⏩Usage：
Signal: "B" stands for long buy signal. "S" stands for short sell signal.
Support and resistance: "Purple areas" represent support areas and "yellow areas" represent resistance areas.
🧿Tip I：
Adaptive signal. Take long buying as an example. When the purple area representing the support range appears, the market is bullish. If a "B" signal appears at this time, it means that you can consider buying and do a wave of short-term trading.
Usually there will be many short-term trading opportunities in a wave of rising trend.
🧿Tip II：
Since the market is reciprocating, the indicator will prompt many signals when it is trending. Each signal is observed and used independently, and it does not prompt the closing and profit taking points. Take profit and stop loss can be set according to your own trading cycle and style.
Regardless of whether it rises or falls, there will always be many swings that can be captured in the trend.
*The signals in the indicators are for reference only and not intended as investment advice. Past performance of a strategy is not indicative of future earnings results.
Multiple Ticker Stochastic RSIThe Stochastic RSI is a technical indicator ranging between 0 and 100, based on applying the Stochastic oscillator formula to a set of relative strength index (RSI). Unlike the original Stochastic RSI indicator, this allows you to define up to two additional tickers for which all three will be averaged and outputted visually looking like a standard Stochastic RSI indicator. Potential buy and sell visuals are included, as well as alerts. Please note that this indicator is not meant to be used by itself.
RelativeVolatilityIndicator with Trend FilterGuide to the Relative Volatility Indicator with Trend Filter (RVI_TF)
Introduction
The Relative Volatility Indicator with Trend Filter (RVI_TF) aims to provide traders with a comprehensive tool to analyze market volatility and trend direction. This unique indicator combines volatility ratio calculations with a trend filter to help you make more informed trading decisions.
Key Components
Scaled Volatility Ratio: This measures the current market volatility relative to historical volatility and scales the values for better visualization.
Fast and Slow Moving Averages for Volatility: These provide a smoothed representation of the scaled volatility ratio, making it easier to spot trends in market volatility.
Trend Filter: An additional line representing a long-term Simple Moving Average (SMA) to help you identify the prevailing market trend.
User Inputs
Short and Long ATR Period: These allow you to define the length for calculating the Average True Range (ATR), used in the volatility ratio.
Short and Long StdDev Period: Periods for short-term and long-term standard deviation calculations.
Min and Max Volatility Ratio for Scaling: Scale the volatility ratio between these min and max values.
Fast and Slow SMA Period for Volatility Ratio: Periods for the fast and slow Simple Moving Averages of the scaled volatility ratio.
Trend Filter Period: Period for the long-term SMA, used in the trend filter.
Show Trend Filter: Toggle to show/hide the trend filter line.
Trend Filter Opacity: Adjust the opacity of the trend filter line.
Visual Components
Histogram: The scaled volatility ratio is displayed as a histogram. It changes color based on the ratio value.
Fast and Slow Moving Averages: These are plotted over the histogram for additional context.
Trend Filter Line: Shown when the corresponding toggle is enabled, this line gives an indication of the general market trend.
How to Use
Volatility Analysis: Look for divergences between the fast and slow MAs of the scaled volatility ratio. It can signal potential reversals or continuation of trends.
Trend Confirmation: Use the Trend Filter line to confirm the direction of the current trend.
Conclusion
The RVI_TF is a multi-faceted indicator designed for traders who seek to integrate both volatility and trend analysis into their trading strategies. By providing a clearer understanding of market conditions, this indicator can be a valuable asset in a trader's toolkit.
Blackrock Spot ETF Premium BTCUSD (COINBASE) V1I created an indicator that takes the spot BTC/USD pair from major exchanges and compares it to the Spot BTC/USD pair on Coinbase that institutions will use for their Spot ETFs.
Blackrock Spot ETF Premium BTCUSD (COINBASE)
I suspect we will see a new "Kimchi Premium" where the Spot ETF pressures from institutions will raise the Coinbase Bitcoin price by a factor of 10-50% premium to the other exchanges.
Naturally excess coins from other exchanges will flow into Coinbase to capture this.
This indicator should be good for some time until one of the other exchanges delist or stop using BTCUSD "spot" If it breaks it I will update it if I remember.
FederalXBT,
Hybrid EMA AlgoLearner⭕️Innovative trading indicator that utilizes a k-NN-inspired algorithmic approach alongside traditional Exponential Moving Averages (EMAs) for more nuanced analysis. While the algorithm doesn't actually employ machine learning techniques, it mimics the logic of the k-Nearest Neighbors (k-NN) methodology. The script takes into account the closest 'k' distances between a short-term and long-term EMA to create a weighted short-term EMA. This combination of rule-based logic and EMA technicals offers traders a more sophisticated tool for market analysis.
⭕️Foundational EMAs: The script kicks off by generating a 50-period short-term EMA and a 200-period long-term EMA. These EMAs serve a dual purpose: they provide the basic trend-following capability familiar to most traders, akin to the classic EMA 50 and EMA 200, and set the stage for more intricate calculations to follow.
⭕️k-NN Integration: The indicator distinguishes itself by introducing k-NN (k-Nearest Neighbors) logic into the mix. This machine learning technique scans prior market data to find the closest 'neighbors' or distances between the two EMAs. The 'k' closest distances are then picked for further analysis, thus imbuing the indicator with an added layer of data-driven context.
⭕️Algorithmic Weighting: After the k closest distances are identified, they are utilized to compute a weighted EMA. Each of the k closest short-term EMA values is weighted by its associated distance. These weighted values are summed up and normalized by the sum of all chosen distances. The result is a weighted short-term EMA that packs more nuanced information than a simple EMA would.
Zaree - Predictive Imparity Momentum IndicatorThe "Zaree - Predictive Imparity Momentum Indicator" (Z-PIMI) is a custom indicator designed to measure the momentum difference between two currency pairs. Let's break down its components and functionality:
Inputs:
pimiLength: Defines the period for the RSI calculation.
selectedMAType: Allows the user to choose the type of moving average (SMA, EMA, WMA, VWMA) they want to apply to the PIMI.
maLength: Defines the period for the chosen moving average.
baseCurrency & quoteCurrency: These are the two currency pairs that the user wants to compare.
Timeframe Selection:
The user can select a specific timeframe for the analysis, or they can use the chart's current timeframe.
Calculation of Currency Indices:
The closing prices of the Base Currency and Quote Currency are fetched for the selected timeframe.
The RSI (Relative Strength Index) is calculated for both currencies using the pimiLength.
The PIMI is then calculated by subtracting the RSI of the Quote Currency from the RSI of the Base Currency.
Moving Average Calculation:
A moving average of the PIMI is calculated based on the user's selected type (selectedMAType) and period (maLength).
Style Settings:
These are hardcoded values that define the levels for the upper and lower bands. These bands can help identify overbought or oversold conditions.
Highs and Lows Calculation:
The highest and lowest values of the PIMI over specified periods (highsLength and lowsLength) are calculated. These can help identify extreme values or turning points.
Plotting:
The PIMI is plotted as a white line.
The moving average of the PIMI is plotted as a purple line.
The upper and lower bands are plotted as horizontal lines at specified levels.
The highest and lowest values of the PIMI are plotted as red and green lines, respectively.
Interpretation:
The PIMI provides a measure of the momentum difference between two currency pairs. When the PIMI is rising, it indicates that the Base Currency is gaining momentum relative to the Quote Currency, and vice versa.
The moving average can be used as a signal line. For instance, when the PIMI crosses above its moving average, it might be considered a bullish signal, and when it crosses below, it might be considered bearish.
The upper and lower bands, as well as the highs and lows lines, can help identify overbought or oversold conditions. For example, if the PIMI reaches or exceeds the upper band, it might indicate overbought conditions, suggesting a potential reversal or pullback.
Overall, the Z-PIMI offers a tool to compare the momentum of two currency pairs and identify potential trading opportunities based on their relative strength and established thresholds.
Fusion: Machine Learning SuiteThe Fusion: Machine Learning Suite combines multiple technical analysis dimensions and harnesses the predictive power of machine learning, seamlessly integrating a diverse array of classic and novel indicators to deliver precision, adaptability, and innovation.
Features and Capabilities
Multidimensional Analysis: Fusion: MLS integrates various technical analysis dimensions to offer a more comprehensive perspective.
Machine Learning Integration: Utilizing ML algorithms, Fusion: MLS offers adaptability to market changes.
Custom Indicators: Including dimensions like "Moon Lander", "Cap Line" and "Z-Pack" the indicator expands the scope of traditional technical analysis methods.
Tailored Customization: With customization options, Fusion: MLS allows traders to configure the tool to suit their specific strategies and market focus.
In the following sections, we'll explore the features and settings of Fusion: MLS in detail, providing insights into how it can be utilized.
Major Features and Settings
The indicator consists of several core components and settings, each designed to provide specific functionalities and insights. Here's an in-depth look:
Machine Learning Component
Distance Classifier: A Strategic Approach to Market Analysis
In the world of trading and investment, the ability to classify and predict price movements is paramount. Machine learning offers powerful tools for this purpose.
The Fusion: MLS indicator among others incorporates an Approximate Nearest Neighbors (ANN)* algorithm, a machine learning classification technique, and allows the selection of various distance functions .
This flexibility sets Fusion: MLS apart from existing solutions. The available distance functions include:
Euclidean: Standard distance metric, commonly used as a default.
Chebyshev: Also known as maximum value distance.
Manhattan: Sum of absolute differences.
Minkowski: Generalized metric that includes Euclidean and Manhattan as special cases.
Mahalanobis: Measures distance between points in a correlated space.
Lorentzian: Known for its robustness to outliers and noise.
*For a deeper understanding of the Approximate Nearest Neighbors (ANN) algorithm, traders are encouraged to refer to the relevant articles that can be found in the public domain.
Alternative scoring system
Fusion: MLS also includes a custom scoring alternative based on directional price action.
"Combined: Directional" and "Alpha: Directional" scoring types represent our own directional change algorithm, simple yet effective in displaying trend direction changes early on. They are visualized by color changes when scoring becomes below or above zero.
Changes in scoring quickly reflect shifts in buyer and seller sentiment.
Traders may choose signals by Color Change in the indicator settings to get alerts when scoring color shifts, not waiting until the histogram crosses the zero level.
Application in Trading
Machine learning classification has become an integral part of modern trading, offering innovative ways to analyze and interpret financial data.
Many algorithmic trading systems leverage ML classification to automate trading decisions. By continuously learning from real-time data, these systems can adapt to changing market conditions and execute trades with increased efficiency and accuracy.
ML classification allows for the development of tailored trading strategies as traders can select specific algorithms, dimensions, and filters that align with their trading style, goals, and the particular market they are operating.
We have integrated ML classification with traditional trading tools, such as moving averages and technical indicators. This fusion creates a more robust analysis framework, combining the strengths of classical techniques with the adaptability of machine learning.
Whether used independently or in conjunction with other tools, ML classification represents a significant advancement in trading technology, opening new avenues for exploration, innovation, and success in the financial world.
ML: Weighting System
The Fusion: MLS indicator introduces a unique weighting system that allows traders to customize the influence of various technical indicators in the machine learning process. This feature is not only innovative but also provides a level of control and adaptability that sets it apart from other indicators.
Customizable Weights
The weighting system allows users to assign specific weights to different indicators such as Moon Lander, RSI, MACD, Money Flow, Bollinger Bands, Cap Line, Z-Pack, Squeeze Momentum*, and MA Crossover. These weights can be adjusted manually, providing the ability to emphasize or de-emphasize specific indicators based on the trader's strategy or market conditions.
*Note, we determined via testing that the popular "Squeeze" indicator can actually be well replicated by simply using inputs of 15 & 199 in the bedrock indicator - MACD ; while we employed the standard "Squeeze" formula (developed by J. Carter ) in Fusion: MLS, traders are hereby made aware of our research findings regarding such.
The weighting system's importance lies in its ability to provide a more nuanced and personalized analysis. By adjusting the weights of different indicators a trader focusing on momentum strategies might assign higher weights to the Squeeze Momentum and MA Crossover indicators, while a trader looking for volatility might emphasize RSI and Bollinger Bands.
The ability to customize weights adds a layer of complexity and adaptability that is rare in standard machine-learning indicators.
Custom Indicators: Moon Lander
The "Moon Lander" is not just a catchy name; it's a robust feature inspired by principles from aerospace engineering and offers a unique perspective on trading analysis. Here's a conceptual overview:
Fast EMA and Kalman Matrix
"Moon Lander" incorporates both a Fast Exponential Moving Average (EMA) and a Kalman Matrix in its design. These two elements are combined to create a histogram, providing a specific approach to data analysis.
The Kalman Matrix, or Kalman Filter, is a mathematical concept used for estimating variables that can be measured indirectly and contain noise or uncertainty. It's a standard tool in machine learning and control systems, known for its ability to provide optimal estimates based on observed data.
Kalman Filter: A Navigational Tool
The Kalman filter, an essential part of "Moon Lander," is a mathematical concept known for its applications in navigation and control systems used by NASA in the apollo program :
Guidance in Uncertainty: Just as the Kalman filter helped guide complex aerospace missions through uncertain paths, it assists traders in navigating the often unpredictable financial markets.
Filtering Noise: In trading, the Kalman filter serves to filter out market noise, allowing traders to focus on the underlying trends.
Predictive Capabilities: Its ability to predict future states makes it a valuable tool for forecasting market movements and trend directions.
Custom Indicators: Cap Line and Z-Pack
Fusion: MLS integrates our additional proprietary custom indicators that have been published on TradingView earlier:
Cap Line: Delve into the specific functionalities and applications of our proprietary "Cap Line" indicator in the published description on TradingView.
Z-Pack: Explore the analytical perspectives, focused on the z-score methodology, and custom "Z-Pack" indicator by reviewing the published description on TradingView.
Buy/Sell Signal Generation Algorithms
Fusion: MLS offers various options for generating buy/sell signals, tailored to different trading strategies and perspectives:
Fusion: Allows traders to select any number of dimensions to receive buy/sell signals from, offering customized signal generation.
ML: Utilizes the machine learning ANN distance for signal generation.
Color Change: Generates signals by selected scoring type color change.
Displayed Dimension, Alpha Dimension: Generate signals based on specific selected dimensions.
These algorithms provide flexibility in determining buy/sell signals, catering to different trading styles and market conditions.
Filters
Filters are used to refine and selectively include or exclude signals based on specific criteria. Rather than generating signals, these filters act as gatekeepers, ensuring that only the signals meeting certain conditions are considered. Here's an overview of the filters used:
Dynamic State Predictor (DSP)
The DSP employs the Kalman Matrix to evaluate existing signals by comparing the fast and slow-moving averages, both processed through the Kalman Matrix. Based on the relationship between these averages, the DSP may exclude specific signals, depending on whether they align with upward or downward trends.
Average Directional Index (ADX)
The ADX filter evaluates the strength of existing trends and filters out signals that do not meet the specified ADX threshold and length, focusing on significant market movements.
Feature Engineering: RSI
Applies a filter to the existing signals, clearing out those that do not meet the criteria for RSI overbought or oversold threshold condition.
Feature Engineering: MACD
Assesses existing signals to identify changes in the strength, direction, momentum, and duration of a trend, filtering out those that do not align with MACD trend direction.
The Visual Component
The machine learning component is an internal component. However, the indicator also offers an equally important and useful visual component. It is a graphical representation of the multiple technical analysis dimensions, that can be combined in various ways (where the name "Fusion" comes from), allowing traders to visualize the underlying data and its analysis.
Displayed Dimension: Visualization and Normalization
The Fusion: MLS indicator offers a "Displayed Dimension" feature that visualizes various dimensions as a histogram. These dimensions may include RSI, MAs, BBs, MACD, etc.
RSI Dimension on the image + ML signals
Normalization: Each dimension is normalized. If any dimension has extreme values, a Fisher transformation is applied to bring them within a reasonable range.
Combined Dimension: When selecting the "Combined" option , the normalized values of the selected dimensions are combined using techniques such as standardization, normalization, or winsorization. This flexibility enables tailored visualization and analysis.
Alpha Dimension: Enhancing Analysis
The "Alpha Dimension" feature allows traders to select an additional dimension alongside the Displayed Dimension. This facilitates a combined analysis, enhancing the depth of insights.
Theme Selection
Fusion: MLS offers various themes such as "Sailfish", "Iceberg", "Moon", "Perl", "Candy" and "Monochrome" Traders can select a theme that resonates with their preference, enhancing visual appeal. There is also a "Custom" theme available that allows the user to choose the colors of the theme.
Customizing Fusion: MLS for Various Markets and Strategies
Fusion: MLS is designed with customization in mind. Traders can tailor the indicator to suit various markets and trading strategies. Selecting specific dimensions allows it to align with individual trading goals.
Selecting Dimensions: Choose the dimensions that resonate with your trading approach, whether focusing on trend-following, momentum, or other strategies.
Adjusting Parameters: Fine-tune the parameters of each dimension, including custom ones like "Moon Lander," to suit specific market conditions.
Theme Customization: Select a theme that aligns with your visual preferences, enhancing your chart's readability and appeal.
Utilizing Research: Leverage the underlying algorithms and research, such as machine learning classification by ANN and the Kalman filter, to deepen your understanding and application of Fusion: MLS.
Alerts
The indicator includes an alerting system that notifies traders when new buy or sell signals are detected.
Disclaimer
The information provided herein is intended for informational purposes only and should not be construed as investment advice, endorsement, nor a recommendation to buy or sell any financial instruments. Fusion: MLS is a technical analysis tool, and like all tools, it should be used with caution and in conjunction with other forms of analysis.
Traders and investors are encouraged to consult with a licensed financial professional and conduct their own research before making any trading or investment decisions. Past performance of the Fusion: MLS indicator or any trading strategy does not guarantee future results, and all trading involves risk. Users of Fusion: MLS should understand the underlying algorithms and assumptions and consider their individual risk tolerance and investment goals when using this tool.
Coppock Curve w/ Early Turns [QuantVue]The Coppock Curve is a momentum oscillator developed by Edwin Coppock in 1962. The curve is calculated using a combination of the rate of change (ROC) for two distinct periods, which are then subjected to a weighted moving average (WMA).
History of the Coppock Curve:
The Coppock Curve was originally designed for use on a monthly time frame to identify buying opportunities in stock market indices, primarily after significant declines or bear markets.
Historically, the monthly time frame has been the most popular for the Coppock Curve, especially for long-term trend analysis and spotting the beginnings of potential bull markets after bearish periods.
The signal wasn't initially designed for finding sell signals, however it can be used to look for tops as well.
When the indicator is above zero it indicates a hold. When the indicator drops below zero it indicates a sell, and when the indicator moves above zero it signals a buy.
While this indicator was originally designed to be used on monthly charts of the indices, many traders now use this on individual equities and etfs on all different time frames.
About this Indicator:
The Coppock Curve is plotted with colors changing based on its position relative to the zero line. When above zero, it's green, and when below, it's red. (default settings)
An absolute zero line is also plotted in black to serve as a reference.
In addition to the classic Coppock Curve, this indicator looks to identify "early turns" or potential reversals of the Coppock Curve rather than waiting for the indicator to cross above or below the zero line.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
PTS Pi-Osc V1
The PTS - Pi-Osc know as Precision Index Oscillator by Roger Medcalf - Precision Trading Systems.
How does the Pi-Osc work?
Pi-Osc is a highly sophisticated consensus type indicator comprising of many different component signals.
A technical traders tool that measures everything from divergences to probabilities all blended into one simple to use product.
The buy and selling opportunities are highlighted by the moves away from + or - 3.14.
Simple to use for all levels of experience from beginner to expert and offers a unique edge in terms of precision.
The components that go into computations are identified below.
Money flow index provides a simple snapshot of how sold out or pumped up a stock or future really is and when measured in three different time frames gives a slick consensus view of money flow.
Relative strength index (RSI) still the No1 most popular indicator in use today as its power to identify overbought and oversold qualities in sideways markets is exceptional.
Its poor performance in trends is greatly reduced when seamlessly integrated with the PI-Osc algorithm.
Demand index being one of the designers favourite indicators for measuring the future direction caused by a large volume trade is incorporated here as well as its exceptional efficiency as a divergence indicator.
James Sibbet's creation provides an additional stellar incisive cutting accuracy to the Pi-Osc. Sibbets creation is one of the only indicators with true predictive qualities as a leading indicator.
Divergences. Pi-Osc measures divergences which occur over many look back periods from two different indicators, realising that divergences are often spurious in their reliability, the indicator only factors 4% of the total indicator
reading from these. Paradoxically the buy and sell zones have to have at least one observation of a divergence to trigger a signal.
Volume is always a factor that precedes a price change, as stock prices cannot move without a real money value being assigned to it either as a recent trade or a bid-offer order being placed.
The designer's understanding of volume patterns is a very useful addition incorporated into the Pi-Osc indicators unique conception.
Momentum frequently decelerates prior to market turning points and PI-osc is monitoring several timeframes of smoothed momentum samples in its calculations.
But unlike a conventional rate of change or momentum indicator the Pi-Osc indicator scores a neutral reading when momentum is rising or falling fast, and a reading is only factored into the output when momentum is reducing, thus
indicating a higher probability of success.
Probability is another feature of this algorithm.
Although rarely used in industry standard oscillators, the designer has added a standard deviation (2.9) factor into this indicator as the more usual 2 standard deviations used in Bollinger bands is just not reliable enough to bet hard earned cash on.
Normally distributed price sets have a 99.9% containment within 3.3 standard deviations, so when this is breached the Pi-Osc adds or deducts a further value to its output number.
Stochastics have similar attributes to RSI oscillators and have contributed a factor into PI-osc due to their smooth and reliable ability to identify buying and selling points in non trending markets.
Price patterns. Generally the industry standard oscillators just use the closing price to calculate their values, and although some indicators such as the stochastic use the high and low in their mathematics, few oscillators are actually programmed to respond to unique candlestick chart set ups.
PI-osc is setting the standard with its intelligent programming to recognise when the current chart pattern is shouting buy signals. Several of the more reliable patterns are factored into the algorithm.
When all the maths is done, Pi-Osc does an exceptional job of determining true buying and selling points.
Basically the trading interpretation is made very simple for you, as the buy and sell zones are so logically determined, not by one factor but from a large consensus "vote" from more than one different computation.
The benefits of this indicator are that it saves valuable time in "confirming technical analysis signals" and all trades know time is precious as large price changes can be missed in seconds while checking other confirming factors.
It takes the hard work out of it, and lets your computer do the brain work.
Ideally this indicator is best as an entry signal, and exits are best done with a trailing stop which has a logical trend following exit, as its quite rare that the Pi-Osc will run right to the other extreme and issue a reverse signal.
Precision Index Oscillator has now got a new rule as a result of the gradual rise in market volatility.
Apart from the other well known main rules to wait for the bounce away from Pi and trade in the direction of the major trend, the new rule is to experiment to find the best historical timeframe.
In the old days it would fire up very nicely on a 10 minute chart of most things, and still does (sometimes) but the futures markets and the very volatile cryptocurrencies now go way out of the old extremities in terms of deviations from the norm.
So it is essential to know what the market volatility is capable of on each instrument.
The point being made here is that using this on very short term time frames is not as safe as used to be.
Institutions enjoy working together to drive the prices into areas where most traders did not expect them to go, taking out all the stops and getting a better price for themselves.
So the first task after ordering this product is to create multiple minute chart settings in your Trading View platform and then click through them and there you will find hopefully find the holy grail, just like finding the best guitar,
amplifier and effects pedal settings for creating your own personalized type of music, finding the best timeframe to use you Pi-Osc is the essential work.
The holy grail usually turns out to be nothing more complex than a stop watch:
If the best setting turns out to be 15 minutes or 30 seconds on a volatile market or a 4 hours minute chart on a very volatile market then so be it.
Who cares? Does it matter?
All that matters is you find the way to get to the best results from this product.
Precision Index Oscillator has eight rules
1. Trade in the direction of the major trend
2. Find the time frame that has worked best in historical testing ( This can be a different setting for each market )
3. ALWAYS use a stop loss
4. Wait for the bounce away from Pi
5. Wait for the bounce away from Pi
6 Wait for the bounce away from Pi
7 Wait for the bounce away from Pi
8. Remember the other seven rules.
Precision Index Oscillator clarification of rules 3 to 7
This indicator can stay locked at the extreme Pi level for many bars, days, hours, minutes, seconds etc.
Taking the signal before the bounce comes is like the well known phrase "catching the falling knife".
Taking the signal before the bounce is a "Pi-Crime" and is a bad idea. Ignoring this point will likely result in losses
As Ed Seykota puts it in his usual amusing style, the problem with catching falling knives is that there are more knives than we have fingers.
He is referring to a market sell off rather than a sell off in one market.
When everything is crashing and we buy all of the crashing things at once, yes you guessed it: A painful day for the fingers!
Suggested settings for various lengths:
There are no settings to change. The beauty of Pi-Osc is there are no settings to be changed.
Your testing of "Pi signal qualifications" is confined only to selecting a time frame which appears to have offered good Pi-trades in the past.
This does not guarantee future signals will be good, and this is why risk control is essential.
Of course it is smart to experiement with different time periods of chart.
Execution of trades:
Exercise caution with this product.
Risk control is essential and risking more than 1% to 1.5% of your capital from entry price to stop would NOT be advised:
As with hunting, firing out lots of small trades in a shot gun approach will lead to better results than gambling all on the first signal you see.
There is much more chance of hitting a bird with a shot gun than a canon and the ammunition is much cheaper.
Always always use a stop loss. Something like 3 to 7 times a fifty period average true range for example.
Whilst it is often possible that a Pi-bounce appears exactly at the precise high or low of the week and could be the only one you see it is risky just to pile into it instantly as some markets produce several failed signals which continue to move in the same direction.
The safest and least risky method is to wait for the trend to change after the Pi-bounce. This is subjective to your own definition of how to measure the trend as "changing" but I would suggest waiting for a 8-20 period Exponential average to turn around before entering a trade.
Once the trade is entered you can implement a trailing stop to allow maximum potential gains and if your style is one of wanting to take quick profits then it is wise to take only some partial profits and give the move a chance to go somewhere and exit the remainder when the trend changes.
If the move was picked up near the absolute top or bottom it could be a large mistake to bail out of all of it early.
Market selection is important:
Avoid markets in endless smooth trends. These are best trading with trend following products ( Pi-Osc is not a trend following product )
Look for a choppy up or down trend or sideways market with some cycle qualities to it.
Best results are on liquid markets, you can observe the past signals and often history repeats with the good previous signals tending to indicate that future signals may also be good. (This is not certain of course)
This is also true of a market showing several historically bad signals which may be leading to more bad signals.
If the past performance of this indicator is poor on the market you are viewing, then move to another market until one is found where the readings show good price action after the signals in historical data.
Time frames:
This product can be applied to any time frame of market but be aware as is stated above, the slower time frames yield more valid signals and shorter time frames lead to more randomness and noise ridden plots of lower significance.
That said, it provides a valid reason to enter a trade and can give good results providing good stops and risk control are used. I have seen plenty of valid signals on 30 second charts right up to weekly charts.
The reliability of short term intra day time frames is usually lower than weekly or daily time frames. As 10 minute time frame is more reliable than a 30 second chart.
Please take this into consideration, try slowing down the impulses to go fast.
I am now accepting payments in USD or CHF for this product
This is not because I expect a US Dollar collapse but as a precaution to spread currency risk over different classes.
As FX rates vary substantially you can find the option that is cheaper than the other and it is fine to do that and choose the cheaper payment option.
Thanks for reading and I hope you do well with Pi-Osc on Trading View, just remember all the eight rules. You do remember them don't you?
Roger Medcalf - Precision Trading Systems
Momentum Probability Oscillator [SS]This is the momentum based probability indicator.
What it does?
This takes the average of MFI, Stochastics and RSI and plots it out as an independent oscillator.
It then tracks bullish vs bearish instances. Bullish is defined as a greater move from open to high than open to low and inverse for bearish.
It stores this data and these averages and plots these levels as a graph.
The graph depicts the max bullish values at the top, the min bearish values at the bottom and the averages in between:
It will plot the average "threshold" value in yellow:
The threshold value is key. A ticker trading above the threshold is generally bullish. Below is bearish.
The threshold value frequently acts as support and resistance levels (see below):
Resistance:
Support:
The indicator also shows you the amount of time a ticker has spent in each region, over a defined lookback period (defaulted to 500):
When you see that cumulatively, more time has been spent in a bullish range or a bearish range, it can help you ascertain the prevailing sentiment at that time.
The indicator will also calculate the average price range based on the underlying oscillator value. It does this through use of ATR based techniques, as its not usually possible to calculate a price from an oscillator:
This is intended as a general reference and not a precise target, as it is using ATR as opposed to the actual technical value itself.
As this is an oscillator, you can use it to look for divergences as well. The advantage to having it formulated in this way is:
a) You get the power of all 3 indicators (stochastics, MFI and RSI) in one and
b) You are adding context to the underlying technical reading. The indicator is plotting out the average, max and min ranges for the selected ticker and performing assessments based on these ranges that add context to the current PA.
You also have the ability to see the specific technical levels associated with each specific technical indicator. If you open up the settings menu and select "Show Table", this will appear:
This will show you the exact values of each of the technicals the indicator is using in its range assessment.
And that is basically the bulk of the indicator!
I use this predominately on the smaller timeframes, especially when there is a lot of chop, to ascertain the overall sentiment.
I also will reference it on the 1 hour to see what the prevailing sentiment is and whether the stock is at an area of technical resistance or support. For example, here is what I referenced on SPY today:
QUICK NOTE:
It works best with RTH (regular trading hours) turned on and ETH (extended trading hours) turned off!
That's it!
Hopefully you like it and leave your comments and suggestions below!
Swing Point Oscillator with Trend Filter [Quantigenics]The "Swing Point Oscillator with Trend Filter" is a sophisticated trading oscillator designed to enhance trading decisions by adapting to market conditions. Oscillators typically signal overbought/oversold market states, often yielding false signals in strong trends. This trend indicator addresses this by implementing a 'Trend Filter' which changes color in strong trends, alerting traders to avoid typical oscillator reversals. In strong trends (when the trend Filter is red), mid-high or mid-low levels can be used for pullback entries. In more neutral markets (when the trend Filter is close to blue), extreme high and low levels (top and bottom) can be used, as a true 'over bought / over sold' oscillator. The oscillator combines components of the Stochastic Oscillator and the CCI, then normalizes the result, providing a unique, adaptive signal. The color-coded lines and Trend Filter offer clear visual cues, making this a comprehensive tool for various market scenarios.
Caution: Always use the indicator in conjunction with other tools and analysis methods to confirm trading decisions. Avoid trading solely based on this indicator.
GOLD 4HR
CL1! 4HR
How to Use:
Swing Point Oscillator: Displays the momentum of the price relative to its recent high and low.
Trend Filter: Highlights the general direction of the market trend.
Zones: Visual representation to categorize oscillator values (Up Zone and Down Zone).
Interpretation:
Oscillator:
When the oscillator moves upward and approaches or enters the Up Zone, it indicates increasing bullish momentum.
When the oscillator moves downward and approaches or enters the Down Zone, it suggests increasing bearish momentum.
Values near the middle (around zero) often indicate indecision or consolidation in the market.
Trend Filter:
A trend filter line above the Mid-High or below the Mid-Low suggests a strong trend.
When the trend filter is between the Mid-High and Mid-Low, it might indicate a weaker or sideways trend.
Its color will change based on its position relative to the zones. For instance, it turns red when indicating a stronger trend.
Zones:
Up Zone: The area between the Top Line and the Mid-High. Indicates strong bullish momentum when the oscillator is within this zone.
Down Zone: The area between the Mid-Low and the Bottom Line. Indicates strong bearish momentum when the oscillator is in this zone.
Trading Tips:
Bullish Scenario: Consider long positions when the oscillator is rising, and the trend filter indicates a strong upward trend.
Bearish Scenario: Consider short positions when the oscillator is falling, and the trend filter indicates a strong downward trend.
Heikin-Ashi Rolling Time Decay Volume OscillatorThe indicator calculates a time-decayed moving sum of volume data for both bullish (green) and bearish (red) candles. It then generates a volume share oscillator as a smoothed and weighted (time-decayed) moving sum of bullish volume (positive share) or bearish volume (negative share) relative to the total volume.
The volume share is displayed as an area chart with gradient fills representing overbought and oversold regions. Additionally, an Arnaud Legoux Moving Average (ALMA) of the volume oscillator is plotted on the chart.
Trend Momentum and Price Control :
This indicator serves as a powerful tool for traders to gauge trend momentum and identify which side, bulls or bears, is controlling price movements. When the volume oscillator trends strongly in the green territory, it suggests that bulls are in control of price movements, indicating a potential uptrend. Conversely, when the oscillator tilts into the red, it indicates bearish dominance and a potential downtrend. With the incorporation of ALMA for smoothing, this indicator becomes an essential tool for traders and analysts navigating the dynamics of traded assets.
Source Candles :
This indicator is designed to work with Heiken Ashi or Japanese candlesticks to discern candle bias, whether it's red or green. Heiken Ashi tends to produce red candles during downtrends and green candles during uptrends, providing a clearer trend indication. In contrast, traditional candlesticks alternate colors regardless of the dominant price direction. Users can select between "Heikin-Ashi Candles" and regular "Japanese Candles" as the source for price direction."
A time decay cumulative sum, also known as a weighted moving sum or exponentially weighted moving sum, offers several advantages when it comes to determining market dynamics compared to other methods:
Responsive to Recent Data: Time decay cumulative sum gives more weight to recent data points and gradually reduces the impact of older data. This responsiveness is crucial in rapidly changing market conditions where recent price and volume information is more relevant for analysis.
Adaptive to Market Volatility : It adapts to changes in market volatility. When markets are highly volatile, it places more emphasis on recent data to reflect the current market environment accurately. Conversely, during calmer periods, it considers older data less important.
Effective for Identifying Turning Points : Time decay cumulative sums are particularly effective at identifying turning points in market dynamics. They can indicate shifts from bullish to bearish sentiment and vice versa, providing early signals of potential trend reversals.
Reduces Lag : Traditional cumulative sums or simple moving averages can lag behind actual market changes, making them less effective for real-time decision-making. Time decay cumulative sums reduce this lag by giving more weight to recent events.
Dynamic Weighting: The weighting scheme can be adjusted to fit specific market dynamics or trading strategies. Traders can customize the decay rate or smoothing factor to align with their analysis goals and timeframes.
Improved Signal Clarity : The time decay cumulative sum can provide clearer and more precise signals for overbought and oversold conditions, as well as trend strength, due to its ability to emphasize recent relevant data.
In summary, a time decay cumulative sum is a valuable tool in determining market dynamics because it adapts to changing market conditions, reduces noise, and provides timely and accurate insights into trends, turning points, and the relative strength of bullish and bearish forces. Its responsiveness and adaptability make it an essential component of many technical analysis and trading strategies.
