Dynamic RSI Bollinger Bands with Waldo Cloud
TradingView Indicator Description: Dynamic RSI Bollinger Bands with Waldo Cloud
Title: Dynamic RSI Bollinger Bands with Waldo Cloud
Short Title: Dynamic RSI BB Waldo
Overview:
Introducing an experimental indicator, the Dynamic RSI Bollinger Bands with Waldo Cloud, designed for adventurous traders looking to explore new dimensions in technical analysis. This indicator overlays on your chart, providing a unique perspective by integrating the Relative Strength Index (RSI) with Bollinger Bands, creating a dynamic trading tool that adapts to market conditions through the lens of momentum and volatility.
What is it?
This innovative indicator combines the traditional Bollinger Bands with the RSI in a way that hasn't been commonly explored. Here's a breakdown:
RSI Integration: The RSI is calculated with customizable length settings, and its values are used not just for momentum analysis but as the basis for the Bollinger Bands. This means the position and width of the bands are directly influenced by the RSI, offering a visual representation of momentum within the context of price volatility.
Dynamic Bollinger Bands: Instead of using price directly, the Bollinger Bands are calculated using a scaled version of the RSI. This scaling is done to fit the RSI values into the price range, ensuring the bands are relevant to the actual price movement. The standard deviation for these bands is also scaled accordingly, providing a unique volatility measure that's momentum-driven.
Waldo Cloud: Named after a visual representation concept, the 'Waldo Cloud' refers to the colored area between the Bollinger Bands, which changes based on various conditions:
Purple when RSI is overbought.
Blue when RSI is oversold.
Green for bullish conditions, defined by the fast-moving average crossing above the slow one, RSI is bullish, and the price is above the slow MA.
Red for bearish conditions, when the fast MA crosses below the slow MA, the RSI is bearish, and the price is below the slow MA.
Gray for neutral market conditions.
Moving Averages: Two simple moving averages (Fast MA and Slow MA) are included, which can be toggled on or off, offering additional trend analysis through crossovers.
How to Use It:
Given its experimental nature, this indicator should be used with caution and in conjunction with other analysis methods:
Identifying Market Conditions: Use the color of the Waldo Cloud to gauge market sentiment. A green cloud might suggest a good time to consider long positions, while a red cloud could indicate potential shorting opportunities. Purple and blue clouds highlight extreme conditions that might precede reversals.
Volatility and Momentum: The dynamic nature of the Bollinger Bands based on RSI provides insight into how momentum is affecting price volatility. When the bands are wide, it might indicate high momentum and potential trend continuation or reversal, depending on the RSI's position relative to its overbought/oversold levels.
Trend Confirmation: The moving average crossovers can act as confirmation signals. For instance, a bullish crossover (fast MA over slow MA) within a green cloud might strengthen a buy signal, whereas a bearish crossover in a red cloud might reinforce a sell decision.
Customization: Adjust the RSI length, overbought/oversold levels, and moving average lengths to suit different trading styles or market conditions. Experiment with these settings to find what works best for your strategy.
Combining with Other Indicators: Since this is an experimental tool, it's advisable to use it alongside established indicators like traditional Bollinger Bands, MACD, or trend lines to validate signals.
Conclusion:
The Dynamic RSI Bollinger Bands with Waldo Cloud is an experimental venture into combining momentum with volatility visually and interactively. It's designed for traders who are open to exploring new methods of market analysis.
Remember, due to its experimental status, this indicator should be part of a broader trading strategy, and backtesting or paper trading is recommended before applying it in live trading scenarios. Keep an eye on how the market reacts to the signals provided by this indicator and always consider risk management practices.
Komut dosyalarını "relative strength" için ara
RSI Crossover dipali parikhThis script generates buy and sell signals based on the crossover of the Relative Strength Index (RSI) and the RSI-based Exponential Moving Average (EMA). It also includes an additional condition for both buy and sell signals that the RSI-based EMA must be either above or below 50.
Key Features:
Buy Signal: Triggered when:
The RSI crosses above the RSI-based EMA.
The RSI-based EMA is above 50.
A green "BUY" label will appear below the bar when the buy condition is met.
Sell Signal: Triggered when:
The RSI crosses below the RSI-based EMA.
The RSI-based EMA is below 50.
A red "SELL" label will appear above the bar when the sell condition is met.
Customizable Inputs:
RSI Length: Adjust the period for calculating the RSI (default is 14).
RSI-based EMA Length: Adjust the period for calculating the RSI-based EMA (default is 9).
RSI Threshold: Adjust the threshold (default is 50) for when the RSI-based EMA must be above or below.
Visuals:
The RSI is plotted as a blue line.
The RSI-based EMA is plotted as an orange line.
Buy and sell signals are indicated by green "BUY" and red "SELL" labels.
Alerts:
Alerts can be set for both buy and sell conditions to notify you when either condition is met.
How to Use:
Use this script to identify potential buy and sell opportunities based on the behavior of the RSI relative to its EMA.
The buy condition indicates when the RSI is strengthening above its EMA, and the sell condition signals when the RSI is weakening below its EMA.
Strategy Use:
Ideal for traders looking to leverage RSI momentum for entering and exiting positions.
The RSI-based EMA filter helps smooth out price fluctuations, focusing on stronger signals.
This script is designed for both discretionary and algorithmic traders, offering a simple yet effective method for spotting trend reversals and continuation opportunities using RSI.
Composite Oscillation Indicator Based on MACD and OthersThis indicator combines various technical analysis tools to create a composite oscillator that aims to capture multiple aspects of market behavior. Here's a breakdown of its components:
* Individual RSIs (xxoo1-xxoo15): The code calculates the RSI (Relative Strength Index) of numerous indicators, including volume-based indicators (NVI, PVI, OBV, etc.), price-based indicators (CCI, CMO, etc.), and moving averages (WMA, ALMA, etc.). It also includes the RSI of the MACD histogram (xxoo14).
* Composite RSI (xxoojht): The individual RSIs are then averaged to create a composite RSI, aiming to provide a more comprehensive view of market momentum and potential turning points.
* MACD Line RSI (xxoo14): The RSI of the MACD histogram incorporates the momentum aspect of the MACD indicator into the composite measure.
* Double EMA (co, coo): The code employs two Exponential Moving Averages (EMAs) of the composite RSI, with different lengths (9 and 18 periods).
* Difference (jo): The difference between the two EMAs (co and coo) is calculated, aiming to capture the rate of change in the composite RSI.
* Smoothed Difference (xxp): The difference (jo) is further smoothed using another EMA (9 periods) to reduce noise and enhance the signal.
* RSI of Smoothed Difference (cco): Finally, the RSI is applied to the smoothed difference (xxp) to create the core output of the indicator.
Market Applications and Trading Strategies:
* Overbought/Oversold: The indicator's central line (plotted at 50) acts as a reference for overbought/oversold conditions. Values above 50 suggest potential overbought zones, while values below 50 indicate oversold zones.
* Crossovers and Divergences: Crossovers of the cco line above or below its previous bar's value can signal potential trend changes. Divergences between the cco line and price action can also provide insights into potential trend reversals.
* Emoji Markers: The code adds emoji markers ("" for bullish and "" for bearish) based on the crossover direction of the cco line. These can provide a quick visual indication of potential trend shifts.
* Colored Fill: The area between the composite RSI line (xxoojht) and the central line (50) is filled with color to visually represent the prevailing market sentiment (green for above 50, red for below 50).
Trading Strategies (Examples):
* Long Entry: Consider a long entry (buying) signal when the cco line crosses above its previous bar's value and the composite RSI (xxoojht) is below 50, suggesting a potential reversal from oversold conditions.
* Short Entry: Conversely, consider a short entry (selling) signal when the cco line crosses below its previous bar's value and the composite RSI (xxoojht) is above 50, suggesting a potential reversal from overbought conditions.
* Confirmation: Always combine the indicator's signals with other technical analysis tools and price action confirmation for better trade validation.
Additional Notes:
* The indicator offers a complex combination of multiple indicators. Consider testing and optimizing the parameters (EMAs, RSI periods) to suit your trading style and market conditions.
* Backtesting with historical data can help assess the indicator's effectiveness and identify potential strengths and weaknesses in different market environments.
* Remember that no single indicator is perfect, and the cco indicator should be used in conjunction with other forms of analysis to make informed trading decisions.
By understanding the logic behind this composite oscillator and its potential applications, you can incorporate it into your trading strategy to potentially identify trends, gauge market sentiment, and generate trading signals.
Dynamic Sentiment RSI [UAlgo]The Dynamic Sentiment RSI is a technical analysis tool that combines the classic RSI (Relative Strength Index) concept with dynamic sentiment analysis, offering traders enhanced insights into market conditions. Unlike the traditional RSI, this indicator integrates volume weighting, sentiment factors, and smoothing features to provide a more nuanced view of momentum and potential market reversals. It is designed to assist traders in detecting overbought/oversold conditions, momentum shifts, and to generate potential buy or sell signals using crossover and crossunder techniques. By dynamically adjusting based on sentiment and volume factors, this RSI offers better adaptability to varying market conditions, making it suitable for different trading styles and timeframes.
This tool is particularly helpful for traders who wish to explore not only price movement but also the underlying market sentiment, offering a more comprehensive approach to momentum analysis. The sentiment factor amplifies the RSI's sensitivity to price shifts, making it easier to detect early signals of market reversals or the continuation of a trend.
🔶 Key Features
Dynamic Sentiment Calculation: The indicator incorporates a "Sentiment Factor" that adjusts the RSI length dynamically based on a multiplier, helping traders better understand market sentiment at different time intervals.
Volume Weighting: When enabled, the RSI calculations are weighted by volume, allowing traders to give more importance to price movements with higher trading volume, which may provide more accurate signals.
Smoothing Feature: A customizable smoothing period is applied to the RSI to help filter out noise and make the signal smoother. This feature is particularly useful for traders who prefer to focus on long-term trends while minimizing false signals.
Step Size Customization: A "Step Size" input allows users to round the sentiment RSI to predefined intervals, making the results easier to interpret and act upon. This feature allows you to focus on significant sentiment changes and ignore minor fluctuations.
Crossover/Crossunder Alerts: The indicator includes crossover and crossunder signals on the zero-line, helping traders identify potential buy and sell opportunities as the smoothed RSI crosses these levels.
The indicator offers a clear visual display with multiple color-coded lines and areas:
Sentiment RSI: Plotted as an area chart, color-coded based on sentiment strength.
Raw RSI: A purple line representing the raw adjusted RSI.
Smoothed RSI: A dynamic line, color-coded aqua or orange based on its position relative to the zero line.
Buy/Sell Signals: Triangle shapes are plotted at crossovers and crossunders, providing clear entry and exit points.
🔶 Interpreting the Indicator
Sentiment RSI
-This line represents the sentiment-adjusted RSI, where the higher the value, the stronger the bullish sentiment, and the lower the value, the stronger the bearish sentiment. It is rounded to step intervals, making it easier to detect significant shifts in sentiment.
- A positive sentiment RSI (above 0) suggests bullish market conditions, while a negative sentiment RSI (below 0) suggests bearish conditions.
Smoothed RSI
The smoothed RSI helps reduce noise and shows the trend more clearly.
Crossovers of the zero line are significant:
- Crossover above zero: Indicates that bullish momentum is building, potentially signaling a buying opportunity.
- Crossunder below zero: Signals a shift towards bearish momentum, potentially indicating a sell signal.
Traders should look for these crossovers in conjunction with other signals for more accurate entry/exit points.
Raw RSI (Adjusted)
The raw adjusted RSI offers a less smoothed, more responsive version of the RSI. While it may be noisier, it provides early signals of market reversals and trends.
Crossover/Crossunder Signals
- When the smoothed RSI crosses above the zero line, a "Signal Up" triangle appears, indicating a potential buying opportunity.
- When the smoothed RSI crosses below the zero line, a "Signal Down" triangle appears, signaling a potential sell opportunity.
These signals help traders time their entries and exits by identifying momentum shifts.
Volume Weighting (Optional)
- If volume weighting is enabled, the RSI will give more weight to periods of higher trading volume, making the signals more reliable when the market is highly active.
Strong Up/Down Levels (40/-40)
- These dotted lines represent extreme sentiment levels. When the sentiment RSI reaches 40 or -40, the market may be nearing an overbought or oversold condition, respectively. This could be a signal for traders to prepare for potential reversals or shifts in momentum.
By combining the various components of this indicator, traders can gain a comprehensive view of market sentiment and price action, helping them make more informed trading decisions. The combination of sentiment factors, volume weighting, and smoothing makes this indicator highly flexible and suitable for a variety of trading strategies.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Multi-Chart Widget [LuxAlgo]The Multi-Chart Widget tool is a comprehensive solution crafted for traders and investors looking to analyze multiple financial instruments simultaneously. With the capability to showcase up to three additional charts, users can customize each chart by selecting different financial instruments, and timeframes.
Users can add various widely used technical indicators to the charts such as the relative strength index, Supertrend, moving averages, Bollinger Bands...etc.
🔶 USAGE
The tool offers traders and investors a comprehensive view of multiple charts simultaneously. By displaying up to three additional charts alongside the primary chart, users can analyze assets across different timeframes, compare their performance, and make informed decisions.
Users have the flexibility to choose from various customizable chart types, including the recently added "Volume Candles" option.
This tool allows adding to the chart some of the most widely used technical indicators, such as the Supertrend, Bollinger Bands, and various moving averages.
In addition to the charting capabilities, the tool also features a dynamic statistic panel that provides essential metrics and key insights into the selected assets. Users can track performance indicators such as relative strength, trend, and volatility, enabling them to identify trends, patterns, and trading opportunities efficiently.
🔶 DETAILS
A brief overview of the indicators featured in the statistic panel is given in the sub-section below:
🔹Dual Supertrend
The Dual Supertrend is a modified version of the Supertrend indicator, which is based on the concept of trend following. It generates buy or sell signals by analyzing the asset's price movement. The Dual Supertrend incorporates two Supertrend indicators with different parameters to provide potentially more accurate signals. It helps traders identify trend reversals and establish trend direction in a more responsive manner compared to a single Supertrend.
🔹Relative Strength Index
The Relative Strength Index is a momentum oscillator that measures the speed and change of price movements. RSI oscillates between 0 and 100 and is typically used to identify overbought or oversold conditions in a market. Traditionally, RSI values above 70 are considered overbought, suggesting that the asset may be due for a reversal or correction, while RSI values below 30 are considered oversold, indicating potential buying opportunities.
🔹Volatility
Volatility in trading refers to the degree of variation or fluctuation in the price of a financial instrument, such as a stock, currency pair, or commodity, over a certain period of time. It is a measure of the speed and magnitude of price changes and reflects the level of uncertainty or risk in the market. High volatility implies that prices are experiencing rapid and significant movements, while low volatility suggests that prices are relatively stable and are not changing much. Traders often use volatility as an indicator to assess the potential risk and return of an investment and to make informed decisions about when to enter or exit trades.
🔹R-Squared (R²)
R-squared, also known as the coefficient of determination, is a statistical measure that indicates the proportion of the variance in the dependent variable that is predictable from the independent variable(s). In other words, it quantifies the goodness of fit of a regression model to the observed data. R-squared values range from %0 to %100, with higher values indicating a better fit of the model to the data. An R-squared of 100% means that all movements of a security are completely explained by movements in the index, while an R-squared value of %0 indicates that the model does not explain any of the variability in the dependent variable.
In simpler terms, in investing, a high R-squared, from 85% to 100%, indicates that the stock’s or fund’s performance moves relatively in line with the index. Conversely, a low R-squared (around 70% or less) indicates that the fund's performance tends to deviate significantly from the movements of the index.
🔶 SETTINGS
🔹Mini Chart(s) Generic Settings
Mini Charts Separator: This option toggles the visibility of the separator lines.
Number Of Bars: Specifies the number of bars to be displayed for each mini chart.
Horizontal Offset: Determines the distance at which the mini charts will be displayed from the primary chart.
🔹Mini Chart Settings: Top - Middle - Bottom
Mini Chart Top/Middle/Bottom: Toggle the visibility of the selected mini chart.
Symbol: Choose the financial instrument to be displayed in the mini chart. If left as an empty string, it will default to the current chart instrument.
Timeframe: This option determines the timeframe used for calculating the mini charts. If a timeframe lower than the chart's timeframe is selected, the calculations will be based on the chart's timeframe.
Chart Type: Selection from various chart types for the mini charts, including candles, volume candles, line, area, columns, high-low, and Heikin Ashi.
Chart Size: Determines the size of the mini chart.
Technical Indicator: Selection from various technical indicators to be displayed on top of the mini charts.
Note : Chart sizing is relative to other mini charts. For example, If all the mini charts are sized to x5 relative to each other, the result will be the same as if they were all sized as x1. This is because the relative proportions between the mini charts remain consistent regardless of their absolute sizes. Therefore, their positions and sizes relative to each other remain unchanged, resulting in the same visual representation despite the differences in absolute scale.
🔹Supertrend Settings
ATR Length: is the lookback length for the ATR calculation.
Factor: is what the ATR is multiplied by to offset the bands from price.
Color: color customization option.
🔹Moving Average Settings
Type: is the type of the moving average, available types of moving averages include SMA (Simple Moving Average), EMA (Exponential Moving Average), RMA (Root Mean Square Moving Average), HMA (Hull Moving Average), WMA (Weighted Moving Average), and VWMA (Volume Weighted Moving Average).
Source: Determines what data from each bar will be used in calculations.
Length: The time period to be used in calculating the Moving Average.
Color: Color customization option.
🔹Bollinger Bands Settings
Basis Type: Determines the type of Moving Average that is applied to the basis plot line.
Source: Determines what data from each bar will be used in calculations.
Length: The time period to be used in calculating the Moving Average which creates the base for the Upper and Lower Bands.
StdDev: The number of Standard Deviations away from the Moving Average that the Upper and Lower Bands should be.
Color: Color customization options for basis, upper and lower bands.
🔹Mini Chart(s) Panel Settings
Mini Chart(s) Panel: Controls the visibility of the panel containing the mini charts.
Dual Supertrend: Toggles the display of the evaluated dual super trend, based on the super trend settings provided below the option. The definitions for the options are the same as stated above for the super trend.
Relative Strength Index: Toggles the display of the evaluated RSI, based on the source and length settings provided below the option.
Volatility: Toggles the display of the calculated Volatility, based on the length settings provided below the option.
R-Squared: Toggles the display of the calculated R-Squared (R²), based on the length settings provided below the option.
🔶 LIMITATIONS
The tool allows users to display mini charts featuring various types of instruments alongside the primary chart instrument. However, there's a limitation: the selected primary chart instrument must have an ACTIVE market status. Alternatively, if the primary chart instrument is not active, the mini chart instruments must belong to the same exchange and have the same type as the primary chart instrument.
Wall Street Cheat Sheet IndicatorThe Wall Street Cheat Sheet Indicator is a unique tool designed to help traders identify the psychological stages of the market cycle based on the well-known Wall Street Cheat Sheet. This indicator integrates moving averages and RSI to dynamically label market stages, providing clear visual cues on the chart.
Key Features:
Dynamic Stage Identification: The indicator automatically detects and labels market stages such as Disbelief, Hope, Optimism, Belief, Thrill, Euphoria, Complacency, Anxiety, Denial, Panic, Capitulation, Anger, and Depression. These stages are derived from the emotional phases of market participants, helping traders anticipate market movements.
Technical Indicators: The script uses two key technical indicators:
200-day Simple Moving Average (SMA): Helps identify long-term market trends.
50-day Simple Moving Average (SMA): Aids in recognizing medium-term trends.
Relative Strength Index (RSI): Assesses the momentum and potential reversal points based on overbought and oversold conditions.
Clear Visual Labels: The current market stage is displayed directly on the chart, making it easy to spot trends and potential turning points.
Usefulness:
This indicator is not just a simple mashup of existing tools. It uniquely combines the concept of market psychology with practical technical analysis tools (moving averages and RSI). By labeling the psychological stages of the market cycle, it provides traders with a deeper understanding of market sentiment and potential future movements.
How It Works:
Disbelief: Detected when the price is below the 200-day SMA and RSI is in the oversold territory, indicating a potential bottom.
Hope: Triggered when the price crosses above the 50-day SMA, with RSI starting to rise but still below 50, suggesting an early uptrend.
Optimism: Occurs when the price is above the 50-day SMA and RSI is between 50 and 70, indicating a strengthening trend.
Belief: When the price is well above the 50-day SMA and RSI is between 70 and 80, showing strong bullish momentum.
Thrill and Euphoria: Identified when RSI exceeds 80, indicating overbought conditions and potential for a peak.
Complacency to Depression: These stages are identified based on price corrections and drops relative to moving averages and declining RSI values.
Best Practices:
High-Time Frame Focus: This indicator works best on high-time frame charts, specifically the 1-week Bitcoin (BTCUSDT) chart. The longer time frame provides a clearer picture of the overall market cycle and reduces noise.
Trend Confirmation: Use in conjunction with other technical analysis tools such as trendlines, Fibonacci retracement levels, and support/resistance zones for more robust trading strategies.
How to Use:
Add the Indicator: Apply the Wall Street Cheat Sheet Indicator to your TradingView chart.
Analyze Market Stages: Observe the dynamic labels indicating the current stage of the market cycle.
Make Informed Decisions: Use the insights from the indicator to time your entries and exits, aligning your trades with the market sentiment.
This indicator is a valuable tool for traders looking to understand market psychology and make informed trading decisions based on the stages of the market cycle.
Ultimate Momentum"Ultimate Momentum" – Elevating Your Momentum Analysis
Experience a refined approach to momentum analysis with "Ultimate Momentum," a sophisticated indicator seamlessly combining the strengths of RSI and CCI. This tool offers a nuanced understanding of market dynamics with the following features:
1. Harmonious Fusion: Witness the dynamic interplay between RSI and CCI, providing a comprehensive understanding of market nuances.
2. Optimized CCI Dynamics: Delve confidently into market intricacies with optimized CCI parameters, enhancing synergy with RSI for a nuanced perspective on trends.
3. Standardized Readings: "Ultimate Momentum" standardizes RSI and CCI, ensuring consistency and reliability in readings for refined signals.
4. Native TradingView Integration: Immerse yourself in the reliability of native TradingView codes for RSI and CCI, ensuring stability and compatibility.
How RSI and CCI Work Together:
RSI (Relative Strength Index): Captures price momentum with precision, measuring the speed and change of price movements.
CCI (Commodity Channel Index): Strategically integrated to complement RSI, offering a unique perspective on price fluctuations and potential trend reversals.
Why "Ultimate Momentum"?
In a crowded landscape, "Ultimate Momentum" stands out, redefining how traders interpret momentum. Gain a profound understanding of market dynamics, spot trend reversals, and make informed decisions.
Your Insights Matter:
Share your suggestions to enhance "Ultimate Momentum" in the comments. Your feedback is crucial as we strive to deliver an unparalleled momentum analysis tool.
Risk Reward Optimiser [ChartPrime]█ CONCEPTS
In modern day strategy optimization there are few options when it comes to optimizing a risk reward ratio. Users frequently need to experiment and go through countless permutations in order to tweak, adjust and find optimal in their data.
Therefore we have created the Risk Reward Optimizer.
The Risk Reward Optimizer is a technical tool designed to provide traders with comprehensive insights into their trading strategies.
It offers a range of features and functionalities aimed at enhancing traders' decision-making process.
With a focus on comprehensive data, it is there to help traders quickly and efficiently locate Risk Reward optimums for inbuilt of custom strategies.
█ Internal and external Signals:
The script can optimize risk to reward ratio for any type of signals
You can utilize the following :
🔸Internal signals ➞ We have included a number of common indicators into the optimizer such as:
▫️ Aroon
▫️ AO (Awesome Oscillator)
▫️ RSI (Relative Strength Index)
▫️ MACD (Moving Average Convergence Divergence)
▫️ SuperTrend
▫️ Stochastic RSI
▫️ Stochastic
▫️ Moving averages
All these indicators have 3 conditions to generate signals :
Crossover
High Than
Less Than
🔸External signal
▫️ by incorporating your own indicators into the analysis. This flexibility enables you to tailor your strategy to your preferences.
◽️ How to link your signal with the optimizer:
In order to be able to analysis your signal we need to read it and to do so we would need to PLOT your signal with a defined value
plot( YOUR LONG Condition ? 100 : 0 , display = display.data_window)
█ Customizable Risk to Reward Ratios:
This tool allows you to test seven different customizable risk to reward ratios , helping you determine the most suitable risk-reward balance for your trading strategy. This data-driven approach takes the guesswork out of setting stop-loss and take-profit levels.
█ Comprehensive Data Analysis:
The tool provides a table displaying key metrics, including:
Total trades
Wins
Losses
Profit factor
Win rate
Profit and loss (PNL)
This data is essential for refining your trading strategy.
🔸 It includes a tooltip for each risk to reward ratio which gives data for the:
Most Profitable Trade USD value
Most Profitable Trade % value
Most Profitable Trade Bar Index
Most Profitable Trade Time (When it occurred)
Position and size is adjustable
█ Visual insights with histograms:
Visualize your trading performance with histograms displaying each risk to reward ratio trade space, showing total trades, wins, losses, and the ratio of profitable trades.
This visual representation helps you understand the strengths and weaknesses of your strategy.
It offers tooltips for each RR ratio with the average win and loss percentages for further analysis.
█ Dynamic Highlighting:
A drop-down menu allows you to highlight the maximum values of critical metrics such as:
Profit factor
Win rate
PNL
for quick identification of successful setups.
█ Stop Loss Flexibility:
You can adjust stop-loss levels using three different calculation methods:
ATR
Pivot
VWAP
This allows you to align risk-reward ratios with your preferred risk tolerance.
█ Chart Integration:
Visualize your trades directly on your price chart, with each trade displayed in a distinct color for easy tracking.
When your take-profit (TP) level is reached , the tool labels the corresponding risk-reward ratio for that specific TP, simplifying trade management.
█ Detailed Tooltips:
Tooltips provide deeper insights into your trading performance. They include information about the most profitable trade, such as the time it occurred, the bar index, and the percentage gain. Histogram tooltips also offer average win and loss percentages for further analysis.
█ Settings:
█ Code:
In summary, the Risk Reward Optimizer is a data-driven tool that offers traders the ability to optimize their risk-reward ratios, refine their strategies, and gain a deeper understanding of their trading performance. Whether you're a day trader, swing trader, or investor, this tool can help you make informed decisions and improve your trading outcomes.
RSRWDescription:
The given Pine-Script, titled "Real Relative Strength (RSRW)," is designed to evaluate the relative strength of the selected security compared to a benchmark security, defaulting to "SPY". It utilizes TradingView’s programming language and is structured to run on its platform.
Functionality:
Rolling Price Change Calculation:
It calculates the rolling price change for both the selected security and the comparison
security over a user-defined length of periods, defaulting to 12.
Rolling ATR Change Calculation:
It computes the Average True Range (ATR) over the specified length for both securities,
providing insights into market volatility.
Power Index Calculation:
It computes the power index by dividing the rolling move of the comparison security by its
rolling ATR, offering a measure of market strength or weakness relative to volatility.
Real Relative Strength (RRS) Calculation:
It determines the Real Relative Strength of the selected security against the benchmark,
adjusting the relative price move by the power index and dividing by the security's rolling
ATR.
Correlation:
The script also evaluates the correlation between the selected security and the compared
security over the defined length, providing a correlation coefficient that is represented
visually by different colors.
Visual Representation:
The Real Relative Strength is plotted with a blue line.
A red line represents the baseline (0).
Correlation is displayed with a color-coded line, ranging from green (high positive
correlation) to red (high negative correlation).
Utility:
This script is valuable for traders and investors looking to assess the relative performance of securities against a benchmark, factoring in volatility and correlation, enabling more informed investment decisions based on market dynamics.
License:
This script is subject to the terms of the Mozilla Public License 2.0.
Divergance Based on Vortex IndicatorThe Vortex-Based Divergence Indicator represents a groundbreaking approach to analyzing market dynamics within the realm of technical analysis. Drawing inspiration from the concept of vortices and their cyclical patterns, this indicator strives to illuminate potential divergence points within financial markets, providing traders with valuable insights for informed decision-making.
At its foundation, the Vortex-Based Divergence Indicator builds upon the principles of the Vortex Indicator, a well-established tool for gauging momentum and identifying potential trend reversals. However, this innovative indicator goes a step further by focusing on the divergences that can occur between the Vortex Indicator and the actual price movements.
Divergences, which arise when the direction of an indicator's movement contradicts the direction of price action, hold paramount significance within the Vortex-Based Divergence Indicator. By integrating this indicator with other renowned oscillators, such as the Relative Strength Index (RSI) or the Moving Average Convergence Divergence (MACD), traders can augment their analytical capabilities significantly.
These complementary oscillators can corroborate or validate the signals generated by the Vortex-Based Divergence Indicator. For instance, when the Vortex-Based Divergence Indicator hints at a potential trend reversal, cross-referencing this insight with the RSI's overbought or oversold levels can enhance the accuracy of the prediction. Likewise, employing the MACD to confirm momentum shifts in conjunction with the Vortex Indicator's signals can provide a more comprehensive view of market dynamics.
It's crucial to emphasize the importance of synergy when combining these indicators. Rather than relying solely on the Vortex-Based Divergence Indicator, incorporating other oscillators acts as a checks-and-balances system, reducing false signals and enhancing the overall reliability of the trading strategy. However, prudent traders also recognize that no indicator or combination thereof is foolproof. Additional factors, such as fundamental analysis and market news, should also be considered to achieve well-rounded trading decisions.
In essence, the Vortex-Based Divergence Indicator's integration with established oscillators like RSI and MACD offers traders a powerful toolkit to navigate complex market landscapes. By leveraging the strengths of each indicator and cross-referencing their insights, traders can elevate their trading strategies to new heights of accuracy and effectiveness.
Dee_MeterHere's how you can effectively use the Dee Meter indicator:
1. **Understanding the Basics**:
- Dee Meter evaluates the market sentiment across various sectors.
- It calculates the overall market trend and presents it in percentage form through a line graph.
2. **Indicator Results**:
- When you add the Dee Meter indicator to your chart, you'll notice two key results: Bull and Bear percentages, along with a line graph.
- The Bull percentage reflects the strength of bullish (positive) sentiment, while the Bear percentage indicates bearish (negative) sentiment.
- For example, if the Bull percentage is 55% and the Bear percentage is 45%, it signifies that the bulls currently have a stronger influence in the market.
3. **Interpreting Percentages**:
- Utilize the Bull and Bear percentages to craft your analysis strategy.
- A high Bull percentage in a bullish market suggests strong bullish momentum.
- In the case of a bullish trend showing signs of weakening (e.g., a double top pattern), monitor the Bull and Bear percentages for early reversal indications.
- A decrease in the Bull percentage and an increase in the Bear percentage could hint at a potential market reversal.
4. **Line Graph Analysis**:
- The line graph visually depicts the strength of bulls (green line) and bears (red line) over time.
- During a bullish trend, the green line rises while the red line remains lower, indicating bullish strength.
- Conversely, during a bearish trend, the red line climbs higher, indicating bearish dominance.
5. **Cross Over and Cross Under**:
- Cross-over and cross-under scenarios occur when the market abruptly reverses direction.
- For instance, in a bullish market that suddenly turns bearish, the red line could cross above the green line, indicating increased bearish power.
- In a bearish market that experiences a sudden influx of buying activity, the green line might cross above the red line, signifying strong buying interest.
6. **Applying the Indicator**:
- Use the Dee Meter to build your own trading strategies and make informed decisions.
- Keep an eye on changes in Bull and Bear percentages to identify shifts in market sentiment.
- Monitor line graph movements to assess the relative strength of bulls and bears.
In summary, the Dee Meter indicator is a valuable tool for assessing market sentiment and confirming trends in the Indian market. By understanding and utilizing the Bull and Bear percentages, line graph analysis, and cross-over/cross-under scenarios, you can develop effective trading strategies and trade with greater confidence.
Market Smith IndicatorsMarket Smith has a collection of tools that are useful for identifying stocks. On their charts they have a 21/50/200 day moving averages, high and low pivot points, a relative strength line, and a relative strength rating. This script contains indicators for the following:
21/50/200 Day Moving Averages
High and Low pivot points
A Relative Strength line
A Relative Strength rating
21/50/200 Day Moving Averages
The 21/50/200 Day moving averages are simple moving averages. They are visible in any chart increment but to use them properly you need to set you charts to be by day. Labels will appear on the right of the lines to show that they are representative of 21/50/200 day moving averages.
High and Low pivot points
The High and Low pivot points are green for high pivot points and red for low points. They are show in the Market Smith style with the numbers simply above the pivot points.
Relative Strength line
The Relative Strength line is a line that shows the strength of the stock compared to the S&P 500. In this case we utilize the SPX ticker to compare the stock to. This line is almost identical to the Market Smith tool and is an excellent tool to determine how a stock is doing compared to the market. When movements in the stock and shown with sideways trending of the RS line that means that the stock is following the market. When a stock is outperforming the market the RS line will follow.
Relative Strength rating
Thank you to ©Fred6724 for the RS Rating inspiration. They wrote excellent open source code for a RS Rating comparable to Market Smith. As the RS Rating in Market Smith is not open source it is difficult to know exactly how it is being calculated. After simplifying Fred's code and building upon a few ideas I had I compared the RS Rating to multiple Market Smith Ratings. The rating is close but often off by multiple points. If there is anyone who has a better idea on how to get this rating or how to improve on the code please send me a PM or fork this project. This rating is a good indicator to see how a certain stock compares to other stocks in the market. In Market Smith they are able to utilize their database to compare it to all other stocks. Since we do not have access to the same tools we are only able to compare it to the percentage of stocks above the 200, 150, 100, 50, and 20 day moving average.
Using these tools together are a small fraction what make people like Bill O'neill and Jim Roppel so successful. I plan on updating the RS Rating as I continue to work on this project so if there is anyone who has ideas then please send me a PM. Ultimately the goal of this project is to have a solution that is identical to Market Smith.
D-Bot Alpha RSI Breakout StrategyHello dear Traders,
Here is a simple yet effective strategy to use, for best profit higher time frame, such as daily.
Structure of the code
The code defines inputs for SMA (simple moving average) length, RSI (relative strength index) length, RSI entry level, RSI stop loss level, and RSI take profit level. The default values of these variables can be customized as per the user's preferences.
The script calculates SMA and RSI based on the input parameters and the closing price of the asset.
Trading logic
This strategy allows the placement of a long position when:
The RSI crosses above the RSI entry level and
The close price is above the SMA value.
After entering a long position, it applies a trailing stop mechanism. The stop price is updated to the close price if the close price is lower than the last close price.
The script closes the long position when:
RSI falls below the stop loss level.
RSI reaches or exceeds the take profit level.
If the trailing stop is activated (once RSI reaches or exceeds the take profit level), the closing price falls below the trailing stop level.
Strengths
The strategy includes mechanisms for entering a position, taking profit, and stopping losses, which are fundamental aspects of a trading strategy.
It applies a trailing stop mechanism that allows to capture further gains if the price keeps increasing while protecting from losses if the price starts to decrease.
Weaknesses
This strategy only contemplates long positions. Depending on the market situation, the strategy may miss opportunities for short selling when the market is on a downward trend.
The choice of the fixed RSI entry, stop loss, and take profit levels may not be ideal for all market conditions or assets. It might benefit from a more adaptive mechanism that adjusts these levels according to market volatility or trend.
The strategy doesn't factor in trading costs (such as spread or commission), which could have a significant impact on the net profit, especially if the user is trading with a high frequency or in a low liquidity market.
How to trade with this strategy
Given these parameters and the strategy outlined by the code, the trader would enter a long position when the RSI crosses above the RSI entry level (default 34) and the closing price is above the SMA value (SMA calculated with default period of 200). The trader would exit the position when either the RSI falls below the RSI stop loss level (default 30), or RSI rises above the RSI take profit level (default 50), or when the trailing stop is hit.
Remember "The strategies I have prepared are entirely for educational purposes and should not be considered as investment advice. Support your trades using other tools. Wishing everyone profitable trades..."
Ultimate Balance StrategyThe Ultimate Balance Oscillator Strategy harnesses the power of the Ultimate Balance Oscillator to deliver a comprehensive and disciplined approach to trading. By combining the insights of the Rate of Change (ROC), Relative Strength Index (RSI), Commodity Channel Index (CCI), Williams Percent Range, and Average Directional Index (ADX) from TradingView, this strategy offers traders a systematic way to navigate the markets with precision.
The core principle of this strategy lies in its ability to identify optimal entry and exit points based on the movement of the Ultimate Balance Oscillator. When the oscillator line crosses below the 0.75 level, a buy signal is generated, indicating a potential opportunity for a bullish trend reversal. Conversely, when the oscillator line crosses above the 0.25 level, it triggers an exit signal, suggesting a possible end to a bullish trend.
Key Features:
1. Objective Market Analysis: The Ultimate Balance Oscillator Strategy provides a disciplined and objective approach to market analysis. By relying on the quantified insights of multiple indicators, it helps traders cut through market noise and focus on key signals, improving decision-making and reducing emotional biases.
2. Enhanced Timing and Precision: This strategy's entry and exit signals are based on the specific thresholds of the Ultimate Balance Oscillator. By waiting for confirmation through the crossing of these levels, traders can potentially enter trades at opportune moments and exit with greater precision, maximizing profit potential and minimizing risk exposure.
3. Customizability and Adaptability: The strategy offers flexibility, allowing traders to customize the parameters to fit their preferred trading style and timeframes. Whether you're a short-term trader or a long-term investor, the Ultimate Balance Oscillator Strategy can be adjusted to suit your specific needs, making it adaptable to various market conditions.
4. Real-time Alerts: Stay informed and never miss a potential trade opportunity with the strategy's built-in alert system. Set personalized alerts for buy and exit signals to receive timely notifications, ensuring you're always aware of the latest developments in the market.
5. Backtesting and Optimization: Before applying the strategy to live trading, it's recommended to conduct thorough backtesting and optimization. By testing the strategy's performance over historical data and fine-tuning the parameters, you can gain insights into its strengths and weaknesses, enabling you to make informed adjustments and increase its effectiveness.
Trading involves risk. Use the Ultimate Balance Oscillator Strategy at your own discretion. Past performance is not indicative of future results.
Stochastic RSI of Smoothed Price [Loxx]What is Stochastic RSI of Smoothed Price?
This indicator is just as it's title suggests. There are six different signal types, various price smoothing types, and seven types of RSI.
This indicator contains 7 different types of RSI:
RSX
Regular
Slow
Rapid
Harris
Cuttler
Ehlers Smoothed
What is RSI?
RSI stands for Relative Strength Index . It is a technical indicator used to measure the strength or weakness of a financial instrument's price action.
The RSI is calculated based on the price movement of an asset over a specified period of time, typically 14 days, and is expressed on a scale of 0 to 100. The RSI is considered overbought when it is above 70 and oversold when it is below 30.
Traders and investors use the RSI to identify potential buy and sell signals. When the RSI indicates that an asset is oversold, it may be considered a buying opportunity, while an overbought RSI may signal that it is time to sell or take profits.
It's important to note that the RSI should not be used in isolation and should be used in conjunction with other technical and fundamental analysis tools to make informed trading decisions.
What is RSX?
Jurik RSX is a technical analysis indicator that is a variation of the Relative Strength Index Smoothed ( RSX ) indicator. It was developed by Mark Jurik and is designed to help traders identify trends and momentum in the market.
The Jurik RSX uses a combination of the RSX indicator and an adaptive moving average (AMA) to smooth out the price data and reduce the number of false signals. The adaptive moving average is designed to adjust the smoothing period based on the current market conditions, which makes the indicator more responsive to changes in price.
The Jurik RSX can be used to identify potential trend reversals and momentum shifts in the market. It oscillates between 0 and 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend . Traders can use these levels to make trading decisions, such as buying when the indicator crosses above 50 and selling when it crosses below 50.
The Jurik RSX is a more advanced version of the RSX indicator, and while it can be useful in identifying potential trade opportunities, it should not be used in isolation. It is best used in conjunction with other technical and fundamental analysis tools to make informed trading decisions.
What is Slow RSI?
Slow RSI is a variation of the traditional Relative Strength Index ( RSI ) indicator. It is a more smoothed version of the RSI and is designed to filter out some of the noise and short-term price fluctuations that can occur with the standard RSI .
The Slow RSI uses a longer period of time than the traditional RSI , typically 21 periods instead of 14. This longer period helps to smooth out the price data and makes the indicator less reactive to short-term price fluctuations.
Like the traditional RSI , the Slow RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Slow RSI is a more conservative version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also be slower to respond to changes in price, which may result in missed trading opportunities. Traders may choose to use a combination of both the Slow RSI and the traditional RSI to make informed trading decisions.
What is Rapid RSI?
Same as regular RSI but with a faster calculation method
What is Harris RSI?
Harris RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by Larry Harris and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Harris RSI uses a different calculation formula compared to the traditional RSI . It takes into account both the opening and closing prices of a financial instrument, as well as the high and low prices. The Harris RSI is also normalized to a range of 0 to 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend .
Like the traditional RSI , the Harris RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Harris RSI is a more advanced version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Harris RSI and the traditional RSI to make informed trading decisions.
What is Cuttler RSI?
Cuttler RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by Curt Cuttler and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Cuttler RSI uses a different calculation formula compared to the traditional RSI . It takes into account the difference between the closing price of a financial instrument and the average of the high and low prices over a specified period of time. This difference is then normalized to a range of 0 to 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend .
Like the traditional RSI , the Cuttler RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Cuttler RSI is a more advanced version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Cuttler RSI and the traditional RSI to make informed trading decisions.
What is Ehlers Smoothed RSI?
Ehlers smoothed RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by John Ehlers and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Ehlers smoothed RSI uses a different calculation formula compared to the traditional RSI . It uses a smoothing algorithm that is designed to reduce the noise and random fluctuations that can occur with the standard RSI . The smoothing algorithm is based on a concept called "digital signal processing" and is intended to improve the accuracy of the indicator.
Like the traditional RSI , the Ehlers smoothed RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Ehlers smoothed RSI can be useful in identifying longer-term trends and momentum shifts in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Ehlers smoothed RSI and the traditional RSI to make informed trading decisions.
What is Stochastic RSI?
Stochastic RSI (StochRSI) is a technical analysis indicator that combines the concepts of the Stochastic Oscillator and the Relative Strength Index (RSI). It is used to identify potential overbought and oversold conditions in financial markets, as well as to generate buy and sell signals based on the momentum of price movements.
To understand Stochastic RSI, let's first define the two individual indicators it is based on:
Stochastic Oscillator: A momentum indicator that compares a particular closing price of a security to a range of its prices over a certain period. It is used to identify potential trend reversals and generate buy and sell signals.
Relative Strength Index (RSI): A momentum oscillator that measures the speed and change of price movements. It ranges between 0 and 100 and is used to identify overbought or oversold conditions in the market.
Now, let's dive into the Stochastic RSI:
The Stochastic RSI applies the Stochastic Oscillator formula to the RSI values, essentially creating an indicator of an indicator. It helps to identify when the RSI is in overbought or oversold territory with more sensitivity, providing more frequent signals than the standalone RSI.
The formula for StochRSI is as follows:
StochRSI = (RSI - Lowest Low RSI) / (Highest High RSI - Lowest Low RSI)
Where:
RSI is the current RSI value.
Lowest Low RSI is the lowest RSI value over a specified period (e.g., 14 days).
Highest High RSI is the highest RSI value over the same specified period.
StochRSI ranges from 0 to 1, but it is usually multiplied by 100 for easier interpretation, making the range 0 to 100. Like the RSI, values close to 0 indicate oversold conditions, while values close to 100 indicate overbought conditions. However, since the StochRSI is more sensitive, traders typically use 20 as the oversold threshold and 80 as the overbought threshold.
Traders use the StochRSI to generate buy and sell signals by looking for crossovers with a signal line (a moving average of the StochRSI), similar to the way the Stochastic Oscillator is used. When the StochRSI crosses above the signal line, it is considered a bullish signal, and when it crosses below the signal line, it is considered a bearish signal.
It is essential to use the Stochastic RSI in conjunction with other technical analysis tools and indicators, as well as to consider the overall market context, to improve the accuracy and reliability of trading signals.
Signal types included are the following;
Fixed Levels
Floating Levels
Quantile Levels
Fixed Middle
Floating Middle
Quantile Middle
Extras
Alerts
Bar coloring
Loxx's Expanded Source Types
MomentumIndicatorsLibrary "MomentumIndicators"
This is a library of 'Momentum Indicators', also denominated as oscillators.
The purpose of this library is to organize momentum indicators in just one place, making it easy to access.
In addition, it aims to allow customized versions, not being restricted to just the price value.
An example of this use case is the popular Stochastic RSI.
# Indicators:
1. Relative Strength Index (RSI):
Measures the relative strength of recent price gains to recent price losses of an asset.
2. Rate of Change (ROC):
Measures the percentage change in price of an asset over a specified time period.
3. Stochastic Oscillator (Stoch):
Compares the current price of an asset to its price range over a specified time period.
4. True Strength Index (TSI):
Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the
absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized
in a range between 100 and -100.
5. Stochastic Momentum Index (SMI):
Combination of the True Strength Index with a signal line to help identify turning points in the market.
6. Williams Percent Range (Williams %R):
Compares the current price of an asset to its highest high and lowest low over a specified time period.
7. Commodity Channel Index (CCI):
Measures the relationship between an asset's current price and its moving average.
8. Ultimate Oscillator (UO):
Combines three different time periods to help identify possible reversal points.
9. Moving Average Convergence/Divergence (MACD):
Shows the difference between short-term and long-term exponential moving averages.
10. Fisher Transform (FT):
Normalize prices into a Gaussian normal distribution.
11. Inverse Fisher Transform (IFT):
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is through the
application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity, to a scale limited
between -1 and +1, allowing them to be more easily visualized and compared.
12. Premier Stochastic Oscillator (PSO):
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing average of
the %K value, resulting in a symmetric scale of 1 to -1
# Indicators of indicators:
## Stochastic:
1. Stochastic of RSI (Relative Strengh Index)
2. Stochastic of ROC (Rate of Change)
3. Stochastic of UO (Ultimate Oscillator)
4. Stochastic of TSI (True Strengh Index)
5. Stochastic of Williams R%
6. Stochastic of CCI (Commodity Channel Index).
7. Stochastic of MACD (Moving Average Convergence/Divergence)
8. Stochastic of FT (Fisher Transform)
9. Stochastic of Volume
10. Stochastic of MFI (Money Flow Index)
11. Stochastic of On OBV (Balance Volume)
12. Stochastic of PVI (Positive Volume Index)
13. Stochastic of NVI (Negative Volume Index)
14. Stochastic of PVT (Price-Volume Trend)
15. Stochastic of VO (Volume Oscillator)
16. Stochastic of VROC (Volume Rate of Change)
## Inverse Fisher Transform:
1.Inverse Fisher Transform on RSI (Relative Strengh Index)
2.Inverse Fisher Transform on ROC (Rate of Change)
3.Inverse Fisher Transform on UO (Ultimate Oscillator)
4.Inverse Fisher Transform on Stochastic
5.Inverse Fisher Transform on TSI (True Strength Index)
6.Inverse Fisher Transform on CCI (Commodity Channel Index)
7.Inverse Fisher Transform on Fisher Transform (FT)
8.Inverse Fisher Transform on MACD (Moving Average Convergence/Divergence)
9.Inverse Fisher Transfor on Williams R% (Williams Percent Range)
10.Inverse Fisher Transfor on CMF (Chaikin Money Flow)
11.Inverse Fisher Transform on VO (Volume Oscillator)
12.Inverse Fisher Transform on VROC (Volume Rate of Change)
## Stochastic Momentum Index:
1.Stochastic Momentum Index of RSI (Relative Strength Index)
2.Stochastic Momentum Index of ROC (Rate of Change)
3.Stochastic Momentum Index of VROC (Volume Rate of Change)
4.Stochastic Momentum Index of Williams R% (Williams Percent Range)
5.Stochastic Momentum Index of FT (Fisher Transform)
6.Stochastic Momentum Index of CCI (Commodity Channel Index)
7.Stochastic Momentum Index of UO (Ultimate Oscillator)
8.Stochastic Momentum Index of MACD (Moving Average Convergence/Divergence)
9.Stochastic Momentum Index of Volume
10.Stochastic Momentum Index of MFI (Money Flow Index)
11.Stochastic Momentum Index of CMF (Chaikin Money Flow)
12.Stochastic Momentum Index of On Balance Volume (OBV)
13.Stochastic Momentum Index of Price-Volume Trend (PVT)
14.Stochastic Momentum Index of Volume Oscillator (VO)
15.Stochastic Momentum Index of Positive Volume Index (PVI)
16.Stochastic Momentum Index of Negative Volume Index (NVI)
## Relative Strength Index:
1. RSI for Volume
2. RSI for Moving Average
rsi(source, length)
RSI (Relative Strengh Index). Measures the relative strength of recent price gains to recent price losses of an asset.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of RSI
roc(source, length)
ROC (Rate of Change). Measures the percentage change in price of an asset over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of ROC
stoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Compares the current price of an asset to its price range over a specified time period.
Parameters:
kLength
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Oscillator and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Oscillator and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Oscillator and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
stoch(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Customized source. Compares the current price of an asset to its price range over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
kLength : (int) Period of loopback to calculate the stochastic
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Stoch and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Stoch and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Stoch and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
tsi(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet)
TSI (True Strengh Index). Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized in a range between 100 and -100.
Parameters:
source : (float) Source of series (close, high, low, etc.)
shortLength : (int) Short length
longLength : (int) Long length
maType : (int) Type of Moving Average for TSI
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) TSI
smi(sourceTSI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
SMI (Stochastic Momentum Index). A TSI (True Strengh Index) plus a signal line.
Parameters:
sourceTSI : (float) Source of series for TSI (close, high, low, etc.)
shortLengthTSI : (int) Short length for TSI
longLengthTSI : (int) Long length for TSI
maTypeTSI : (int) Type of Moving Average for Signal of TSI
almaOffsetTSI : (float) Offset for Arnaud Legoux Moving Average
almaSigmaTSI : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSetTSI : (int) Offset for Least Squares Moving Average
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
Returns: A tuple with TSI, signal of TSI and histogram of difference
wpr(source, length)
Williams R% (Williams Percent Range). Compares the current price of an asset to its highest high and lowest low over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of Williams R%
cci(source, length, maType, almaOffset, almaSigma, lsmaOffSet)
CCI (Commodity Channel Index). Measures the relationship between an asset's current price and its moving average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
maType : (int) Type of Moving Average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) Series of CCI
ultimateOscillator(fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Combines three different time periods to help identify possible reversal points.
Parameters:
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
ultimateOscillator(source, fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Customized source. Combines three different time periods to help identify possible reversal points.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
macd(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet)
MACD (Moving Average Convergence/Divergence). Shows the difference between short-term and long-term exponential moving averages.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Period for fast moving average
slowLength : (int) Period for slow moving average
signalLength : (int) Signal length
maTypeFast : (int) Type of fast moving average
maTypeSlow : (int) Type of slow moving average
maTypeMACD : (int) Type of MACD moving average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: A tuple with MACD, Signal, and Histgram
fisher(length)
Fisher Transform. Normalize prices into a Gaussian normal distribution.
Parameters:
length
Returns: A tuple with Fisher Transform and signal
fisher(source, length)
Fisher Transform. Customized source. Normalize prices into a Gaussian normal distribution.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length
Returns: A tuple with Fisher Transform and signal
inverseFisher(source, length, subtrahend, denominator)
Inverse Fisher Transform.
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is
through the application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity,
to a scale limited between -1 and +1, allowing them to be more easily visualized and compared.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period for loopback
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of Inverse Fisher Transform
premierStoch(length, smoothlen)
Premier Stochastic Oscillator (PSO).
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing
average of the %K value, resulting in a symmetric scale of 1 to -1.
Parameters:
length : (int) Period for loopback
smoothlen : (int) Period for smoothing
Returns: (float) Series of PSO
premierStoch(source, smoothlen, subtrahend, denominator)
Premier Stochastic Oscillator (PSO) of custom source.
Normalizes the source by applying a five-period double exponential smoothing average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
smoothlen : (int) Period for smoothing
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of PSO
stochRsi(sourceRSI, lengthRSI, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceRSI
lengthRSI
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochRoc(sourceROC, lengthROC, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceROC
lengthROC
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochUO(fastLength, middleLength, slowLength, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
fastLength
middleLength
slowLength
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochWPR(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochFT(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVolume(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMFI(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochOBV(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochNVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVT(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVROC(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
iftRSI(sourceRSI, lengthRSI, lengthIFT)
Parameters:
sourceRSI
lengthRSI
lengthIFT
iftROC(sourceROC, lengthROC, lengthIFT)
Parameters:
sourceROC
lengthROC
lengthIFT
iftUO(fastLength, middleLength, slowLength, lengthIFT)
Parameters:
fastLength
middleLength
slowLength
lengthIFT
iftStoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD, lengthIFT)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
lengthIFT
iftTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftFisher(length, lengthIFT)
Parameters:
length
lengthIFT
iftMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftWPR(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftMFI(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftCMF(length, lengthIFT)
Parameters:
length
lengthIFT
iftVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftVROC(length, lengthIFT)
Parameters:
length
lengthIFT
smiRSI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiROC(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVROC(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiWPR(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCCI(source, length, maTypeCCI, almaOffsetCCI, almaSigmaCCI, lsmaOffSetCCI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
maTypeCCI
almaOffsetCCI
almaSigmaCCI
lsmaOffSetCCI
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiUO(fastLength, middleLength, slowLength, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
fastLength
middleLength
slowLength
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVol(shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMFI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCMF(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiOBV(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVT(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiNVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
rsiVolume(length)
Parameters:
length
rsiMA(sourceMA, lengthMA, maType, almaOffset, almaSigma, lsmaOffSet, lengthRSI)
Parameters:
sourceMA
lengthMA
maType
almaOffset
almaSigma
lsmaOffSet
lengthRSI
Easy RSI by nnamWhat Does this Indicator Do?
The Easy RSI Indicator color codes candles based on their RSI Value vs. Open / Close (Red / Green). It plots the current price and current RSI value on the chart in real-time. Additionally, when the RSI Value is in an oversold or overbought condition, it plots that signal on the chart in real-time.
The initial candle color is the standard Red / Green Tradingview color, but a Gradient is added to the color which either darkens or lightens the color based on the RSI Value.
As seen in the screenshot below, the higher the RSI Value, the brighter the Green Color is. The lower the RSI Value, the brighter the Red Color is.
The current Price and current RSI Value are both plotted on the chart by default, but can be optionally switched off by the trader.
As seen in the screenshot below, the prices and RSI Values are easily seen while visually tracking the price in real-time.
RSI Overbought Values are plotted when the Overbought condition is triggered. The Default is RED for Overbought and GREEN for Oversold.
As seen in the screenshot below, with all three labels turned on under the input settings (these are ON by default) you can see the overbought condition, the current RSI Value, and current price all in one centralized area. Oversold Values are also plotted when turned on under the input settings.
As shown in the screenshot below, the candle is GREEN (as evident by the green candle outline) but the RSI Value is low and shows lower than average relative strength. This turns the bar color ORANGE vs, GREEN showing that the relative strength of the move is subpar.
As shown on the screenshot below, if the trader has the standard Tradingview Price label switched on (in the Tradingview Chart Settings), the color of the bar is also translated to the price are for an easy to recognize RSI Value just by looking at the price. Even if the current candle is RED, when the RSI is higher than lower, the color will be green / greenish and even if the current candle is GREEN, when the RSI Value is lower than higher, the color will be red-ish / orange in color giving the user a quick view of RSI Value.
If you have any questions or feature requests for this Indicator please do not hesitate to reach out and ask.
GOOD LUCK trading!!
~nnamdert
Poly Cycle [Loxx]This is an example of what can be done by combining Legendre polynomials and analytic signals. I get a way of determining a smooth period and relative adaptive strength indicator without adding time lag.
This indicator displays the following:
The Least Squares fit of a polynomial to a DC subtracted time series - a best fit to a cycle.
The normalized analytic signal of the cycle (signal and quadrature).
The Phase shift of the analytic signal per bar.
The Period and HalfPeriod lengths, in bars of the current cycle.
A relative strength indicator of the time series over the cycle length. That is, adaptive relative strength over the cycle length.
The Relative Strength Indicator, is adaptive to the time series, and it can be smoothed by increasing the length of decreasing the number of degrees of freedom.
Other adaptive indicators based upon the period and can be similarly constructed.
There is some new math here, so I have broken the story up into 5 Parts:
Part 1:
Any time series can be decomposed into a orthogonal set of polynomials .
This is just math and here are some good references:
Legendre polynomials - Wikipedia, the free encyclopedia
Peter Seffen, "On Digital Smoothing Filters: A Brief Review of Closed Form Solutions and Two New Filter Approaches", Circuits Systems Signal Process, Vol. 5, No 2, 1986
I gave some thought to what should be done with this and came to the conclusion that they can be used for basic smoothing of time series. For the analysis below, I decompose a time series into a low number of degrees of freedom and discard the zero mode to introduce smoothing.
That is:
time series => c_1 t + c_2 t^2 ... c_Max t^Max
This is the cycle. By construction, the cycle does not have a zero mode and more physically, I am defining the "Trend" to be the zero mode.
The data for the cycle and the fit of the cycle can be viewed by setting
ShowDataAndFit = TRUE;
There, you will see the fit of the last bar as well as the time series of the leading edge of the fits. If you don't know what I mean by the "leading edge", please see some of the postings in . The leading edges are in grayscale, and the fit of the last bar is in color.
I have chosen Length = 17 and Degree = 4 as the default. I am simply making sure by eye that the fit is reasonably good and degree 4 is the lowest polynomial that can represent a sine-like wave, and 17 is the smallest length that lets me calculate the Phase Shift (Part 3 below) using the Hilbert Transform of width=7 (Part 2 below).
Depending upon the fit you make, you will capture different cycles in the data. A fit that is too "smooth" will not see the smaller cycles, and a fit that is too "choppy" will not see the longer ones. The idea is to use the fit to try to suppress the smaller noise cycles while keeping larger signal cycles.
Part 2:
Every time series has an Analytic Signal, defined by applying the Hilbert Transform to it. You can think of the original time series as amplitude * cosine(theta) and the transformed series, called the quadrature, can be thought of as amplitude * sine(theta). By taking the ratio, you can get the angle theta, and this is exactly what was done by John Ehlers in . It lets you get a frequency out of the time series under consideration.
Amazon.com: Rocket Science for Traders: Digital Signal Processing Applications (9780471405672): John F. Ehlers: Books
It helps to have more references to understand this. There is a nice article on Wikipedia on it.
Read the part about the discrete Hilbert Transform:
en.wikipedia.org
If you really want to understand how to go from continuous to discrete, look up this article written by Richard Lyons:
www.dspguru.com
In the indicator below, I am calculating the normalized analytic signal, which can be written as:
s + i h where i is the imagery number, and s^2 + h^2 = 1;
s= signal = cosine(theta)
h = Hilbert transformed signal = quadrature = sine(theta)
The angle is therefore given by theta = arctan(h/s);
The analytic signal leading edge and the fit of the last bar of the cycle can be viewed by setting
ShowAnalyticSignal = TRUE;
The leading edges are in grayscale fit to the last bar is in color. Light (yellow) is the s term, and Dark (orange) is the quadrature (hilbert transform). Note that for every bar, s^2 + h^2 = 1 , by construction.
I am using a width = 7 Hilbert transform, just like Ehlers. (But you can adjust it if you want.) This transform has a 7 bar lag. I have put the lag into the plot statements, so the cycle info should be quite good at displaying minima and maxima (extrema).
Part 3:
The Phase shift is the amount of phase change from bar to bar.
It is a discrete unitary transformation that takes s + i h to s + i h
explicitly, T = (s+ih)*(s -ih ) , since s *s + h *h = 1.
writing it out, we find that T = T1 + iT2
where T1 = s*s + h*h and T2 = s*h -h*s
and the phase shift is given by PhaseShift = arctan(T2/T1);
Alas, I have no reference for this, all I doing is finding the rotation what takes the analytic signal at bar to the analytic signal at bar . T is the transfer matrix.
Of interest is the PhaseShift from the closest two bars to the present, given by the bar and bar since I am using a width=7 Hilbert transform, bar is the earliest bar with an analytic signal.
I store the phase shift from bar to bar as a time series called PhaseShift. It basically gives you the (7-bar delayed) leading edge the amount of phase angle change in the series.
You can see it by setting
ShowPhaseShift=TRUE
The green points are positive phase shifts and red points are negative phase shifts.
On most charts, I have looked at, the indicator is mostly green, but occasionally, the stock "retrogrades" and red appears. This happens when the cycle is "broken" and the cycle length starts to expand as a trend occurs.
Part 4:
The Period:
The Period is the number of bars required to generate a sum of PhaseShifts equal to 360 degrees.
The Half-period is the number of bars required to generate a sum of phase shifts equal to 180 degrees. It is usually not equal to 1/2 of the period.
You can see the Period and Half-period by setting
ShowPeriod=TRUE
The code is very simple here:
Value1=0;
Value2=0;
while Value1 < bar_index and math.abs(Value2) < 360 begin
Value2 = Value2 + PhaseShift ;
Value1 = Value1 + 1;
end;
Period = Value1;
The period is sensitive to the input length and degree values but not overly so. Any insight on this would be appreciated.
Part 5:
The Relative Strength indicator:
The Relative Strength is just the current value of the series minus the minimum over the last cycle divided by the maximum - minimum over the last cycle, normalized between +1 and -1.
RelativeStrength = -1 + 2*(Series-Min)/(Max-Min);
It therefore tells you where the current bar is relative to the cycle. If you want to smooth the indicator, then extend the period and/or reduce the polynomial degree.
In code:
NewLength = floor(Period + HilbertWidth+1);
Max = highest(Series,NewLength);
Min = lowest(Series,NewLength);
if Max>Min then
Note that the variable NewLength includes the lag that comes from the Hilbert transform, (HilbertWidth=7 by default).
Conclusion:
This is an example of what can be done by combining Legendre polynomials and analytic signals to determine a smooth period without adding time lag.
________________________________
Changes in this one : instead of using true/false options for every single way to display, use Type parameter as following :
1. The Least Squares fit of a polynomial to a DC subtracted time series - a best fit to a cycle.
2. The normalized analytic signal of the cycle (signal and quadrature).
3. The Phase shift of the analytic signal per bar.
4. The Period and HalfPeriod lengths, in bars of the current cycle.
5. A relative strength indicator of the time series over the cycle length. That is, adaptive relative strength over the cycle length.
EM_RSI Gradient Candles
I've missed the beautiful trend visualization of Heiken Ashi candles ever since I first learned they don't play well with other indicators largely due to the method with which they're plotted.
I wanted to color code a gradient onto candles to help visualize trend strength, and the Relative Strength Index was the first thing to come to mind. For coloring, it's possible the new color.from_gradient function would have worked, but I couldn't guarantee a highly customizable indicator with a single gradient so I took a more classic approach.
First, RSI was calculated using Tradingview's built-in RSI code.
Then I broke down the RSI's range of 1-100 into 10 tiers and assigned each a color option with the ability to turn any particular tier off if desired.
I found it to be extremely modular and helpful in visualizing both trend strength and identifying potential trend reversals due to a reduction in strength.
You can use it on every candle to help inform decisions, or keep all but <10 and >90 turned off so that it only changes candle color during the most extreme trends.
Or anything in between!
This is my first self-coded indicator so I'm already proud.
Please let me know what you think, and feel free to suggest improvements for future versions in the comments!
Non-Rescaled RSI█ OVERVIEW
Relative Strength Index is a momentum oscillator developed by J. Wilder. The original version of RSI rescaled the relative strength measurement to range. While the rescaling is useful for readability, This non-rescaled version tells the exact average relative strength of the movement for the past period, and give another way to put the relative strength reading into context of current market condition.
█ Description & How To Use
1. The (+/-) in relative strength value indicates the direction
Example 1: Relative Strength of 2.33 means average gain is 2.33 bigger than average loss for the past period (Equivalent to RSI 70)
Example 2: Relative Strength of -2.33 means average loss is 2.33 bigger than average gain for the past period (Equivalent to RSI 30)
Example 3: Relative Strength of 0 means average gain is equal to average loss for the past period (Equivalent to RSI 50)
Look at comparison below:
2. You can use it exactly how you would use RSI: Overbought/Oversold state, Divergence, Trend identification, Failure Swings etc..
█ Features
- Overbought/Oversold line still maintainable as standard RSI level (70,30) in user input screen. The script will recalculate and plot the ob/os level accordingly
- Value Label to indicate the RSI and RS value
- Custom Gradient Color Scheme
█ Limitation
The Relative Strength absolute value is capped at 20 to avoid ratio value too big(or too small). This is enough to get accurate equivalent of RSI reading between 5-95
█ Disclaimer
Past performance is not an indicator of future results.
My opinions and research are my own and do not constitute financial advice in any way whatsoever.
Nothing published by me constitutes an investment/trading recommendation, nor should any data or Content published by me be relied upon for any investment/trading activities.
I strongly recommends that you perform your own independent research and/or speak with a qualified investment professional before making any financial decisions.
Traders Dynamic Index(RSI) w/ Bull&Bear Control ZonesMomentum (RSI) is one of the most commonly used indicators for trading, but the vast majority of traders who use it, simply apply it as an oscillator to measure overbought and oversold conditions. However, momentum is much more complex than that and using a basic RSI fails to highlight these complexities.
What this highlights are some of the areas/zones that many people may not even know about or are unaware what the RSI can actually reveal about a particular trend.
What this indicator is showing:
Fast moving RSI (Green) - 1 period
Slow moving RSI (Red) - 9 period
Bollinger Bands
Relative Strength: 1 - 100
Bearish Control Zone: 30(Below) - 45
Bullish Control Zone: 60 - 70 (Above)
How this identifies trends:
Bear Market(Bearish Control Zone):
-Support: 20(Below) - 30
-Resistance: 55 - 65
-Momentum will test resistance but will fail to hold support at 50
Bull Market(Bullish Control Zone):
-Support: 45 - 50
-Resistance: 80 - 90(Above)
-Momentum will test support but will not continue past the 45 support
How this identifies reversals:
If a market is bullish, but loses support at 45 and tests 30, it has begun reversal. If a market is bearish, but breaks 60 and tests 70, it has begun reversal.
-A bull market reversal is confirmed if it finds resistance at 60 after testing bearish support
-A bear market reversal is confirmed if it finds support at 50 after testing bullish resistance
Slow & Fast RSI w/ Boll Bands:
-The Slow and Fast RSI crossovers will act as Intermediate trends within the Macro trend - Fast crosses slow, bullish. Slow cross fast, bearish.
-Use in confluence with the Macro trend.
-While under Bearish Control, the Slow RSI will act as resistance for the Fast RSI.
-While under Bullish Control, the Slow RSI will act as support for the Fast RSI.
-The two will have an impulsive crossover when the Macro trend reverses.
-The Bollinger Bands will act as a volatility gauge for potential approaching tests of Support & Resistances. (Expansions & Contractions)
This is an analog of TDIGM (GoldMinds)
-Added Bullish/Bearish Control Zones.
-Changed Fast RSI to Green and Slow RSI to Red.
MFI RSI w STOCH OVERLAY V3Combines: Relative Strength (purple) and RSI Stoch (Orange/gray), Money Flow (green) all in one indicator window.
On screen indicator text identifier will read in this order: "RSI/STOCH/MFI V3"
// Changes from original version \\
It was important to bring forth the RSI indicator as the most visually important line and its relationship to the background.
A: Major visual changes from my first published one..as default now
1: Increased RSI line to size 3
2: Increased MFI line to size 2
3: Separated all Bar Line Fields in the background for custom editing, total of 5 now. Much easier to distinguish when the RSI enters these fields.
B: Other major changes as default now
1: Sped up the indicators from 14 to 11, for quicker response. (user can adjust back to 14 or another number)
2: Increased user friendly inputs to adjust colors, lines, data, etc.
3: (darken / lighten and change background colors, increase/decrease line strengths and colors, adjust field data inputs)
Enjoy and Good Luck Trading.
ForecastForecast (FC), indicator documentation
Type: Study, not a strategy
Primary timeframe: 1D chart, most plots and the on-chart table only render on daily bars
Inspiration: Robert Carver’s “forecast” concept from Advanced Futures Trading Strategies, using normalized, capped signals for comparability across markets
⸻
What the indicator does
FC builds a volatility-normalized momentum forecast for a chosen symbol, optionally versus a benchmark. It combines an EWMAC composite with a channel breakout composite, then caps the result to a common scale. You can run it in three data modes:
• Absolute: Forecast of the selected symbol
• Relative: Forecast of the ratio symbol / benchmark
• Combined: Average of Absolute and Relative
A compact table can summarize the current forecast, short-term direction on the forecast EMAs, correlation versus the benchmark, and ATR-scaled distances to common price EMAs.
⸻
PineScreener, relative-strength screening
This indicator is excellent for screening on relative strength in PineScreener, since the forecast is volatility-normalized and capped on a common scale.
Available PineScreener columns
PineScreener reads the plotted series. You will see at least these columns:
• FC, the capped forecast
• from EMA20, (price − EMA20) / ATR in ATR multiples
• from EMA50, (price − EMA50) / ATR in ATR multiples
• ATR, ATR as a percent of price
• Corr, weekly correlation with the chosen benchmark
Relative mode and Combined mode are recommended for cross-sectional screens. In Relative mode the calculation uses symbol / benchmark, so ensure the ratio ticker exists for your data source.
⸻
How it works, step by step
1. Volatility model
Compute exponentially weighted mean and variance of daily percent returns on D, annualize, optionally blend with a long lookback using 10y %, then convert to a price-scaled sigma.
2. EWMAC momentum, three legs
Daily legs: EMA(8) − EMA(32), EMA(16) − EMA(64), EMA(32) − EMA(128).
Divide by price-scaled sigma, multiply by leg scalars, cap to Cap = 20, average, then apply a small FDM factor.
3. Breakout momentum, three channels
Smoothed position inside 40, 80, and 160 day channels, each scaled, then averaged.
4. Composite forecast
Average the EWMAC composite and the breakout composite, then cap to ±20.
Relative mode runs the same logic on symbol / benchmark.
Combined mode averages Absolute and Relative composites.
5. Weekly correlation
Pearson correlation between weekly closes of the asset and the benchmark over a user-set length.
6. Direction overlay
Two EMAs on the forecast series plus optional green or red background by sign, and optional horizontal level shading around 0, ±5, ±10, ±15, ±20.
⸻
Plots
• FC, capped forecast on the daily chart
• 8-32 Abs, 8-32 Rel, single-leg EWMAC plus breakout view
• 8-32-128 Abs, 8-32-128 Rel, three-leg composite views
• from EMA20, from EMA50, (price − EMA) / ATR
• ATR, ATR as a percent of price
• Corr, weekly correlation with the benchmark
• Forecast EMA1 and EMA2, EMAs of the forecast with an optional fill
• Backgrounds and guide lines, optional sign-based background, optional 0, ±5, ±10, ±15, ±20 guides
Most plots and the table are gated by timeframe.isdaily. Set the chart to 1D to see them.
⸻
Inputs
Symbol selection
• Absolute, Relative, Combined
• Vs. benchmark for Relative mode and correlation, choices: SPY, QQQ, XLE, GLD
• Ticker or Freeform, for Freeform use full TradingView notation, for example NASDAQ:AAPL
Engine selection
• Include:
• 8-32-128, three EWMAC legs plus three breakouts
• 8-32, simplified view based on the 8-32 leg plus a 40-day breakout
EMA, applied to the forecast
• EMA1, EMA2, with line-width controls, plus color and opacity
Volatility
• Span, EW volatility span for daily returns
• 10y %, blend of long-run volatility
• Thresh, Too volatile, placeholders in this version
Background
• Horizontal bg, level shading, enabled by default
• Long BG, Hedge BG, colors and opacities
Show
• Table, Header, Direction, Gain, Extension
• Corr, Length for correlation row
Table settings
• Position, background, opacity, text size, text color
Lines
• 0-lines, 10-lines, 5-lines, level guides
⸻
Reading the outputs
• Forecast > 0, bullish tilt; Forecast < 0, bearish or hedge tilt
• ±10 and ±20 indicate strength on a uniform scale
• EMA1 vs EMA2 on the forecast, EMA1 above EMA2 suggests improving momentum
• Table rows, label colored by sign, current forecast value plus a green or red dot for the forecast EMA cross, optional daily return percent, weekly correlation, and ATR-scaled EMA9, EMA20, EMA50 distances
⸻
Data handling, repainting, and performance
• Daily and weekly series are fetched with request.security().
• Calculations use closed bars, values can update until the bar closes.
• No lookahead, historical values do not repaint.
• Weekly correlation updates during the week, it finalizes on weekly close.
• On intraday charts most visuals are hidden by design.
⸻
Good practice and limitations
• This is a research indicator, not a trading system.
• The fixed Cap = 20 keeps a common scale, extreme moves will be clipped.
• Relative mode depends on the ratio symbol / benchmark, ensure both legs have data for your feed.
⸻
Credits
Concept inspired by Robert Carver’s forecast methodology in Advanced Futures Trading Strategies. Implementation details, parameters, and visuals are specific to this script.
⸻
Changelog
• First version
⸻
Disclaimer
For education and research only, not financial advice. Always test on your market and data feed, consider costs and slippage before using any indicator in live decisions.
