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.
M-oscillator
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.
Support and Resistance Oscillator [CC]The Support and Resistance Oscillator is an experimental script I created to identify when the current price breaks a support or resistance line and reflect this value in an oscillator formula. This indicator uses a threshold to decide the dividing line between buying and selling points. Feel free to change the threshold or smoothing settings to see if you find anything better since this is so experimental. I'm double smoothing the difference between the indicator and its signal line to attempt to capture a combo of the price momentum combined with the general support and resistance levels. I have used dark colors for strong signals and lighter colors for normal signals and make sure to buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts or indicators you would like to see me publish!
Velocity Acceleration Convergence Divergence Indicator [CC]I created the Velocity Acceleration Convergence Divergence Indicator, and it is quite a mouthful if I do say so. I based this script on my two previous scripts: Velocity Indicator and Velocity Acceleration Indicator . This acts like a typical MACD but is much faster with the responses. This indicator is created by finding the difference between the Velocity Indicator and Velocity Acceleration Indicator to determine the overall trend strength of the underlying stock. Like the other scripts, I coded the general buy and sell signals the same, so you would want to buy when the indicator crosses over above the zero midline and sell when it crosses below the zero midline. I have also used the same colors, so darker colors for strong signals and lighter colors for normal signals.
Please let me know if you would like me to publish another script or if you want something custom done!
HTF Oscillators RSI/ROC/MFI/CCI/AO - Dynamic SmoothingThe Interplay of Time Frames: A Balanced View
Navigating the markets often involves interpreting trends from multiple angles. The HTF Oscillators with Dynamic Smoothing indicator enables you to do just that. This tool provides the option to integrate smoothed oscillator readings from Higher Time Frames (HTF) into lower time frame charts, such as a 1-minute chart. By doing so, the indicator offers a balanced viewpoint that bridges the gap between micro and macro perspectives, helping you make informed decisions without losing sight of the broader market context.
Features
Multi-Oscillator Support
Choose from a range of popular oscillators like the Relative Strength Index (RSI), Rate of Change (ROC), Money Flow Index (MFI), Commodity Channel Index (CCI), and Awesome Oscillator (AO). These oscillators are commonly used as foundational building blocks in trading strategy scripts by traders worldwide. Switch effortlessly between them, depending on your trading strategy and requirements. To maintain consistency and a familiar user experience, our script adopts the same visual aesthetics that you'll find in Pine Script indicators on TradingView: a sleek purple line for the oscillator and a transparent band filling. These visual elements are not only pleasing to the eye but also widely appreciated by the trading community.
Dynamic Smoothing
The unique dynamic smoothing feature calculates a smoothing factor based on the ratio of minutes between the Higher Time Frame (HTF) and your current time frame. This provides a sleek and responsive oscillator line that still holds the weight of the longer trend. One of the significant advantages of this feature is user experience; when you change your time frame, the HTF-values in your settings will remain consistent. This ensures that you can easily switch between different time frames without losing the insights provided by your selected HTF.
Visual Aids
Visual cues are an essential part of any trading strategy. The indicator not only plots signals to mark overbought and oversold conditions based on the dynamically smoothed oscillator but also provides you with the flexibility to customize your visual experience. You have the option to toggle on/off the display of these signals depending on your specific needs. Additionally, bands can be displayed at overbought and oversold levels, along with a reference middle line. If you switch between different oscillators (available in the parameter settings), remember to manually adjust the bands in the input settings to ensure signals matches with the type of oscillator to your liking.
User-Friendly Settings
We've grouped related settings together, making it easier for you to find what you're looking for. Adjust the oscillator type, length of bars, smoothing settings, and more with just a few clicks.
Information Table
A standout feature of this indicator is the real-time information table, which displays the values of all selected oscillators based on your specified Higher Time Frame (HTF) settings. This can be particularly useful for traders who depend on multiple indicators for their decision-making process. The data presented in the table is synchronized with the HTF options you've configured in the input settings, allowing for a more efficient and quick scan of values from higher time frames.
Educational Corner: The Power of the Information Table and Customization
The table incorporated into this indicator isn't just eye-candy; it's a practical tool designed to elevate your trading strategy. It dynamically displays real-time values of various oscillators for the HTF you've chosen. This is an exemplary use of TradingView's scripting capabilities to blend multiple indicators into a single visual panel, streamlining your analysis and decision-making process.
But here's the best part: You're not limited to what we've created. With some basic understanding of TradingView's scripting language, Pine Script, you can easily adapt this table to include different indicators that suit your unique trading style. The logic in the script is modular and can serve as a foundation for your own customized trading dashboard. So, go ahead, get creative and explore new combinations of indicators that will help you excel in your trading endeavors!
You no longer have to toggle between different charts or indicators to get the information you need; it's all there in one neatly organized table. We encourage you to tap into this feature and make it your own, empowering your trading like never before.
By doing so, you not only gain a more comprehensive toolset, but you also engage more deeply with your trading strategy, understanding its nuances and, ultimately, making more informed decisions.
Conclusion
The HTF Oscillators with Dynamic Smoothing is a versatile and powerful tool that brings together the best of both worlds: the perspective of higher time frames and the granularity of shorter ones. Its feature-rich setting options and real-time information table make it a potential useful addition to your trading toolkit.
Remember, while this indicator offers a comprehensive and smarter way to look at the markets, it is not a foolproof method for predicting market movements. Always use it in conjunction with other analysis methods and risk management strategies.
Velocity Acceleration Indicator [CC]The Velocity Acceleration Indicator was created by Scott Cong (Stocks and Commodities Sep 2023, pgs 8-15). This is another personal variation of his formula designed to capture the overall velocity acceleration of the underlying stock by applying the velocity formula to the original indicator to find the acceleration of the underlying velocity. I changed a few things around and managed actually to get less lag and quicker signals for this version, so make sure you compare the Velocity Indicator script that I published yesterday. This indicator is also visually similar to a typical stochastic indicator but uses a different underlying calculation. This works well as a momentum indicator, and the values are completely unbounded, so the best ways to determine bullish or bearish trends is either by using a crossover or crossunder between the indicator and the midline or to buy or sell the indicator when it reaches a high or low point and starts to fall or rise respectively. I used the zero line for my default version to help determine the bullish or bearish trends. I have also included multiple colors to differentiate between very strong signals and normal signals, so very strong signals are darker in color, and normal signals use lighter colors. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish! I will have some more new scripts in the next week or so.
Velocity Indicator [CC]The Velocity Indicator was created by Scott Cong (Stocks and Commodities Sep 2023, pgs 8-15). This is my variation of his formula designed to capture the overall velocity of the underlying stock by applying the typical velocity formula. This indicator is visually similar to a typical stochastic indicator but uses a different underlying calculation. This works well as a momentum indicator, and the values are completely unbounded, so the best ways to determine bullish or bearish trends is either by using a crossover or crossunder between the indicator and the midline or to buy or sell the indicator when it reaches a high or low point and starts to fall or rise respectively. For my default version, I used the zero line to help determine the bullish or bearish trends. I have also included multiple colors to differentiate between very strong signals and normal signals, so very strong signals are darker in color, and normal signals use lighter colors. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish! I will have some more new scripts in the next week or so.
L&S Volatility Index Refurbished█ Introduction
This is my second version of the L&S Volatility Index, hence the name "Refurbished".
The first version can be found at this link:
The reason I released a separate version is because I rewrote the source code from scratch with the aim of both improving the indicator and staying as close as possible to the original concept.
I feel that the first version was somewhat exotic and polluted in relation to the indicator originally described by the authors.
In short, the main idea remains the same, however, the way of presenting the result has been changed, reiterating what was said.
█ CONCEPTS
The L&S Volatility Index measures the volatility of price in relation to a moving average.
The indicator was originally described by Brazilian traders Alexandre Wolwacz (Stormer) and Fábio Figueiredo (Vlad) from L&S Educação Financeira.
Basically, this indicator can be used in two ways:
1. In a mean reversion strategy, when there is an unusual distance from it;
2. In a trend following strategy, when the price is in an acceptable region.
As an indicator of volatility, the greatest utility is shown in first case.
This is because it allows identifying abnormal prices, extremely stretched in relation to an average, including market crashes.
How the calculation is done:
First, the distance of the price from a given average in percentage terms is measured.
Then, the historical average volatility is obtained.
Finally the indicator is calculated through the ratio between the distance and the historical volatility.
According to the description proposed by the creators, when the L&S Volatility Index is above 30 it means that the price is "stretched".
The closer to 100 the more stretched.
When it reaches 0, it means the price is on average.
█ What to look for
Basically, you should look at non-standard prices.
How to identify it?
When the oscillator is outside the Dynamic Zone and/or the Fixed Zone (above 30), it is because the price is stretched.
Nothing on the market is guaranteed.
As with the RSI, it is not because the RSI is overbought or oversold that the price will necessarily go down or up.
It is critical to know when NOT to buy, NOT to sell or NOT to do anything.
It is always important to consider the context.
█ Improvements
The following improvements have been implemented.
It should be noted that these improvements can be disabled, thus using the indicator in the "purest" version, the same as the one conceived by the creators.
Resources:
1. Customization of limits and zones:
2. Customization of the timeframe, which can be different from the current one.
3. Repaint option (prints the indicator in real time even if the bar has not yet closed. This produces more signals).
4. Customization of price inputs. This affects the calculation.
5. Customization of the reference moving average (the moving average used to calculate the price distance).
6. Customization of the historical volatility calculation strategy.
- Accumulated ATR: calculates the historical volatility based on the accumulated ATR.
- Returns: calculates the historical volatility based on the returns of the source.
Both forms of volatility calculation have their specific utilities and applications.
Therefore, it is worthwhile to have both approaches available, and one should not necessarily replace the other.
Each method has its advantages and may be more appropriate in different contexts.
The first approach, using the accumulated ATR, can be useful when you want to take into account the implied volatility of prices over time,
reflecting broader price movements and higher impact events. It can be especially relevant in scenarios where unexpected events can drastically affect prices.
The second approach, using the standard deviation of returns, is more common and traditionally used to measure historical volatility.
It considers the variability of prices relative to their average, providing a more general measure of market volatility.
Therefore, both forms of calculation have their merits and can be useful depending on the context and specific analysis needs.
Having both options available gives users flexibility in choosing the most appropriate volatility measure for the situation at hand.
* When choosing "Accumulated ATR", if the indicator becomes difficult to see, there are 3 possibilities:
a) manually adjust the Fixed Zone value;
b) disable the Fixed Zone and use only the Dynamic Zone;
c) normalize the indicator.
7. Signal line (a moving average of the oscillator).
8. Option to normalize the indicator or not.
9. Colors to facilitate direction interpretation.
Since the L&S is a volatility indicator, it does not show whether the price is rising or falling.
This can sometimes confuse the user.
That said, the idea here is to show certain colors where the price is relative to the average, making it easier to analyze.
10. Alert messages for automations.
Short Term IndeXThe Short-Term Index (STIX) is a simple market indicator designed to assess short-term overbought or oversold conditions in the stock market. Leveraging a combination of advancing and declining issues, STIX provides valuable insights into market sentiment and potential reversals. To enhance its interpretability and reveal the underlying trend with greater clarity, STIX has been refined through a Heiken-Ashi transformation, ensuring a smoother representation of market dynamics.
Calculation and Methodology:
stix = ta.ema(adv / (adv + dec) * 100, len)
STIX is calculated by dividing the difference between the sum of advancing issues (ADV) by the total number of issues traded (ADV + DEC). This quotient is multiplied by 100 to express the result as a percentage. The STIX index ranges from 0 to 100, where extreme values indicate potential overbought (mainly above 60) or oversold (mainly below 40) market conditions.
Heiken-Ashi Transformation:
By applying a Heiken-Ashi transformation to STIX, the indicator gains improved visual clarity and noise reduction. This transformation enhances the ability to identify trend shifts and potential reversal points, making it an even more valuable tool for traders and investors.
Utility and Use Cases:
-The Short-Term Index (STIX) offers a range of practical applications-
1. Overbought/Oversold Conditions: STIX provides a clear indication of short-term overbought or oversold conditions, helping traders anticipate potential market reversals.
2. Reversal Points: STIX can help pinpoint potential reversal points in short-term market trends, providing traders with opportunities to enter or exit positions.
3. Trend Analysis: By observing STIX values over time, traders can assess the strength and sustainability of short-term trends, aiding in trend-following strategies.
The Short-Term Index (STIX), enhanced by its Heiken-Ashi transformation, equips traders and investors with a tool for assessing short-term market conditions, confirming price movements, and identifying potential reversal points. Its robust methodology and refined presentation contribute to a more comprehensive understanding of short-term market dynamics, enabling traders to make well-informed trading decisions.
See Also:
- Other Market Breadth Indicators-
Trig-Log Scaled Momentum OscillatorTaylor Series Approximations for Trigonometry:
1. The indicator starts by calculating sine and cosine values of the close price using Taylor Series approximations. These approximations use polynomial terms to estimate the values of these trigonometric functions.
Mathematical Component Formation:
2. The calculated sine and cosine values are then multiplied together. This gives us the primary mathematical component, termed as the 'trigComponent'.
Smoothing Process:
3. To ensure that our indicator is less susceptible to market noise and more reactive to genuine price movements, this 'trigComponent' undergoes a smoothing process using a simple moving average (SMA). The length of this SMA is defined by the user.
Logarithmic Transformation:
4. With our smoothed value, we apply a natural logarithm approximation. Again, this approximation is based on the Taylor expansion. This step ensures that all resultant values are positive and offers a different scale to interpret the smoothed component.
Dynamic Scaling:
5. To make our indicator more readable and comparable over different periods, the logarithmically transformed values are scaled between a range. This range is determined by the highest and lowest values of the transformed component over the user-defined 'lookback' period.
ROC (Rate of Change) Direction:
6. The direction of change in our scaled value is determined. This offers a quick insight into whether our mathematical component is increasing or decreasing compared to the previous value.
Visualization:
7. Finally, the indicator plots the dynamically scaled and smoothed mathematical component on the chart. The color of the plotted line depends on its direction (increasing or decreasing) and its boundary values.
