Xtrender and TSI FusionXtrender and TSI Fusion Indicator
I created this indicator for myself. I was inspired by the indicators created by Bjorgum, Duyck and QuantTherapy and decided to create multiple indicators that either work well combined with their indicators or something new that applies some of their indicator concepts. I decided to share all of the indicator I have created because I believe in learning and earing together as a community. If you guys have any questions or suggestions write them.
Overview: The Xtrender and TSI Fusion Indicator is a powerful tool designed to help traders analyze market momentum, trends, and potential reversals. By combining Xtrender with the True Strength Index (TSI), this indicator provides a comprehensive view of market dynamics, making it easier to identify trading opportunities.
Image: Timeframe is set to daily
Features:
1.Xtrender Analysis:
Short-Term Xtrender: Visualizes short-term momentum using RSI-based calculations on EMA differences. This helps in identifying immediate market trends and pullbacks.
Image above: showcases Short-Term Xtrender
Xtrender T3: A smoothed version of the Xtrender that reduces noise and highlights significant trend changes.
Image above: showcases Xtrender T3 with Xtrender T3 color
2.TSI (True Strength Index):
TSI Value: Measures momentum by comparing price changes over two time periods, offering a clear view of trend strength.
TSI Signal Line: A smoothed version of the TSI value, used to generate buy and sell signals when crossed by the TSI.
Image: showcases TSI Value with TSI Signal Line
TSI Histogram: Shows the difference between the TSI and its signal line, highlighting potential reversals and trend continuations.
Image: showcases TSI Histogram
3.Color Coding and Visual Cues:
Trend Colors: The indicator uses dynamic colors to represent bullish or bearish conditions, making it easy to interpret market sentiment.
Background Color : The background changes color based on TSI signals, further aiding in visual trend analysis.
Image: showcases Background color and Zero line
How to Use
1.Xtrender Analysis:
Short-Term Xtrender: The short-term Xtrender is plotted as columns, changing color based on its direction and value. Green or lime indicates positive momentum, while red or maroon indicates negative momentum.
Xtrender T3: The Xtrender T3 line (black) represents a smoothed version of the short-term Xtrender, providing a clearer picture of the overall trend. The color of this line changes based on the Xtrender's value, helping you spot potential trend changes.
2.TSI (True Strength Index):
TSI Value and Signal Line: The TSI value is plotted as a line, with its color changing based on its relationship to the signal line. A crossover of the TSI above the signal line suggests a potential bullish move, while a crossover below indicates a bearish trend.
TSI Histogram: The histogram represents the difference between the TSI and its signal line. Positive values indicate bullish momentum, while negative values suggest bearish momentum.
3.Background Color:
The background color changes based on the TSI signal, with a greenish hue indicating bullish conditions and a reddish hue indicating bearish conditions. This provides a quick visual reference for market sentiment.
4.Zero Line:
A horizontal gray dotted line at the zero level helps you easily identify when the Xtrender or TSI crosses into positive or negative territory, signaling potential trend shifts.
Image above: Timeframe on daily with the individual elements combined
Example of Use:
•Trend Confirmation: Use the Xtrender and Xtrender T3 to confirm the direction of the trend. If both are aligned with the same color and direction, it increases the probability of a strong trend.
•Momentum Reversals: Watch for TSI crosses and histogram shifts to identify potential reversals. For example, a TSI crossover above its signal line with a corresponding change in the histogram from negative to positive could signal a buying opportunity.
•Pullbacks: Identify pullbacks within a trend by observing temporary shifts in the short-term Xtrender or TSI histogram. Use these signals to enter trades in the direction of the overall trend.
Image above: Showcases, Trend confirmation, reversal and pullbacks on daily timeframe.
Customization:
•TSI Speed: Choose between "Fast" and "Slow" TSI settings based on your trading style. Fast settings are more responsive to price changes, while slow settings offer smoother signals.
•Color Settings: Customize the colors for bullish, bearish, and neutral TSI conditions to match your personal preferences or chart theme.
This indicator is versatile and can be used for various trading strategies, from trend following to momentum trading, making it a valuable tool in any trader's arsenal.
My Scripts/Indicators/Ideas /Systems that I share are only for educational purposes
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Uptrick: RSI Histogram
1. **Introduction to the RSI and Moving Averages**
2. **Detailed Breakdown of the Uptrick: RSI Histogram**
3. **Calculation and Formula**
4. **Visual Representation**
5. **Customization and User Settings**
6. **Trading Strategies and Applications**
7. **Risk Management**
8. **Case Studies and Examples**
9. **Comparison with Other Indicators**
10. **Advanced Usage and Tips**
---
## 1. Introduction to the RSI and Moving Averages
### **1.1 Relative Strength Index (RSI)**
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder and introduced in his 1978 book "New Concepts in Technical Trading Systems." It is widely used in technical analysis to measure the speed and change of price movements.
**Purpose of RSI:**
- **Identify Overbought/Oversold Conditions:** RSI values range from 0 to 100. Traditionally, values above 70 are considered overbought, while values below 30 are considered oversold. These thresholds help traders identify potential reversal points in the market.
- **Trend Strength Measurement:** RSI also indicates the strength of a trend. High RSI values suggest strong bullish momentum, while low values indicate bearish momentum.
**Calculation of RSI:**
1. **Calculate the Average Gain and Loss:** Over a specified period (e.g., 14 days), calculate the average gain and loss.
2. **Compute the Relative Strength (RS):** RS is the ratio of average gain to average loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS))
### **1.2 Moving Averages (MA)**
Moving Averages are used to smooth out price data and identify trends by filtering out short-term fluctuations. Two common types are:
**Simple Moving Average (SMA):** The average of prices over a specified number of periods.
**Exponential Moving Average (EMA):** A type of moving average that gives more weight to recent prices, making it more responsive to recent price changes.
**Smoothed Moving Average (SMA):** Used to reduce the impact of volatility and provide a clearer view of the underlying trend. The RMA, or Running Moving Average, used in the USH script is similar to an EMA but based on the average of RSI values.
## 2. Detailed Breakdown of the Uptrick: RSI Histogram
### **2.1 Indicator Overview**
The Uptrick: RSI Histogram (USH) is a technical analysis tool that combines the RSI with a moving average to create a histogram that reflects momentum and trend strength.
**Key Components:**
- **RSI Calculation:** Determines the relative strength of price movements.
- **Moving Average Application:** Smooths the RSI values to provide a clearer trend indication.
- **Histogram Plotting:** Visualizes the deviation of the smoothed RSI from a neutral level.
### **2.2 Indicator Purpose**
The primary purpose of the USH is to provide a clear visual representation of the market's momentum and trend strength. It helps traders identify:
- **Bullish and Bearish Trends:** By showing how far the smoothed RSI is from the neutral 50 level.
- **Potential Reversal Points:** By highlighting changes in momentum.
### **2.3 Indicator Design**
**RSI Moving Average (RSI MA):** The RSI MA is a smoothed version of the RSI, calculated using a running moving average. This smooths out short-term fluctuations and provides a clearer indication of the underlying trend.
**Histogram Calculation:**
- **Neutral Level:** The histogram is plotted relative to the neutral level of 50. This level represents a balanced market where neither bulls nor bears have dominance.
- **Histogram Values:** The histogram bars show the difference between the RSI MA and the neutral level. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
## 3. Calculation and Formula
### **3.1 RSI Calculation**
The RSI calculation involves:
1. **Average Gain and Loss:** Calculated over the specified length (e.g., 14 periods).
2. **Relative Strength (RS):** RS = Average Gain / Average Loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS)).
### **3.2 Moving Average Calculation**
For the USH indicator, the RSI is smoothed using a running moving average (RMA). The RMA formula is similar to that of the EMA but is based on averaging RSI values over the specified length.
### **3.3 Histogram Calculation**
The histogram value is calculated as:
- **Histogram Value = RSI MA - 50**
**Plotting the Histogram:**
- **Positive Histogram Values:** Indicate that the RSI MA is above the neutral level, suggesting bullish momentum.
- **Negative Histogram Values:** Indicate that the RSI MA is below the neutral level, suggesting bearish momentum.
## 4. Visual Representation
### **4.1 Histogram Bars**
The histogram is plotted as bars on the chart:
- **Bullish Bars:** Colored green when the RSI MA is above 50.
- **Bearish Bars:** Colored red when the RSI MA is below 50.
### **4.2 Customization Options**
Traders can customize:
- **RSI Length:** Adjust the length of the RSI calculation to match their trading style.
- **Bull and Bear Colors:** Choose colors for histogram bars to enhance visual clarity.
### **4.3 Interpretation**
**Bullish Signal:** A histogram bar that moves from red to green indicates a potential shift to a bullish trend.
**Bearish Signal:** A histogram bar that moves from green to red indicates a potential shift to a bearish trend.
## 5. Customization and User Settings
### **5.1 Adjusting RSI Length**
The length parameter determines the number of periods over which the RSI is calculated and smoothed. Shorter lengths make the RSI more sensitive to price changes, while longer lengths provide a smoother view of trends.
### **5.2 Color Settings**
Traders can adjust:
- **Bull Color:** Color of histogram bars indicating bullish momentum.
- **Bear Color:** Color of histogram bars indicating bearish momentum.
**Customization Benefits:**
- **Visual Clarity:** Traders can choose colors that stand out against their chart’s background.
- **Personal Preference:** Adjust settings to match individual trading styles and preferences.
## 6. Trading Strategies and Applications
### **6.1 Trend Following**
**Identifying Entry Points:**
- **Bullish Entry:** When the histogram changes from red to green, it signals a potential entry point for long positions.
- **Bearish Entry:** When the histogram changes from green to red, it signals a potential entry point for short positions.
**Trend Confirmation:** The histogram helps confirm the strength of a trend. Strong, consistent green bars indicate robust bullish momentum, while strong, consistent red bars indicate robust bearish momentum.
### **6.2 Swing Trading**
**Momentum Analysis:**
- **Entry Signals:** Look for significant shifts in the histogram to time entries. A shift from bearish to bullish (red to green) indicates potential for upward movement.
- **Exit Signals:** A shift from bullish to bearish (green to red) suggests a potential weakening of the trend, signaling an exit or reversal point.
### **6.3 Range Trading**
**Market Conditions:**
- **Consolidation:** The histogram close to zero suggests a range-bound market. Traders can use this information to identify support and resistance levels.
- **Breakout Potential:** A significant move away from the neutral level may indicate a potential breakout from the range.
### **6.4 Risk Management**
**Stop-Loss Placement:**
- **Bullish Positions:** Place stop-loss orders below recent support levels when the histogram is green.
- **Bearish Positions:** Place stop-loss orders above recent resistance levels when the histogram is red.
**Position Sizing:** Adjust position sizes based on the strength of the histogram signals. Strong trends (indicated by larger histogram bars) may warrant larger positions, while weaker signals suggest smaller positions.
## 7. Risk Management
### **7.1 Importance of Risk Management**
Effective risk management is crucial for long-term trading success. It involves protecting capital, managing losses, and optimizing trade setups.
### **7.2 Using USH for Risk Management**
**Stop-Loss and Take-Profit Levels:**
- **Stop-Loss Orders:** Use the histogram to set stop-loss levels based on trend strength. For instance, place stops below support levels in bullish trends and above resistance levels in bearish trends.
- **Take-Profit Targets:** Adjust take-profit levels based on histogram changes. For example, lock in profits as the histogram starts to shift from green to red.
**Position Sizing:**
- **Trend Strength:** Scale position sizes based on the strength of histogram signals. Larger histogram bars indicate stronger trends, which may justify larger positions.
- **Volatility:** Consider market volatility and adjust position sizes to mitigate risk.
## 8. Case Studies and Examples
### **8.1 Example 1: Bullish Trend**
**Scenario:** A trader notices a transition from red to green histogram bars.
**Analysis:**
- **Entry Point:** The transition indicates a potential bullish trend. The trader decides to enter a long position.
- **Stop-Loss:** Set stop-loss below recent support levels.
- **Take-Profit:** Consider taking profits as the histogram moves back towards zero or turns red.
**Outcome:** The bullish trend continues, and the histogram remains green, providing a profitable trade setup.
### **8.2 Example 2: Bearish Trend**
**Scenario:** A trader observes a transition from green to red histogram bars.
**Analysis:**
- **Entry Point:** The transition suggests a potential
bearish trend. The trader decides to enter a short position.
- **Stop-Loss:** Set stop-loss above recent resistance levels.
- **Take-Profit:** Consider taking profits as the histogram approaches zero or shifts to green.
**Outcome:** The bearish trend continues, and the histogram remains red, resulting in a successful trade.
## 9. Comparison with Other Indicators
### **9.1 RSI vs. USH**
**RSI:** Measures momentum and identifies overbought/oversold conditions.
**USH:** Builds on RSI by incorporating a moving average and histogram to provide a clearer view of trend strength and momentum.
### **9.2 RSI vs. MACD**
**MACD (Moving Average Convergence Divergence):** A trend-following momentum indicator that uses moving averages to identify changes in trend direction.
**Comparison:**
- **USH:** Provides a smoothed RSI perspective and visual histogram for trend strength.
- **MACD:** Offers signals based on the convergence and divergence of moving averages.
### **9.3 RSI vs. Stochastic Oscillator**
**Stochastic Oscillator:** Measures the level of the closing price relative to the high-low range over a specified period.
**Comparison:**
- **USH:** Focuses on smoothed RSI values and histogram representation.
- **Stochastic Oscillator:** Provides overbought/oversold signals and potential reversals based on price levels.
## 10. Advanced Usage and Tips
### **10.1 Combining Indicators**
**Multi-Indicator Strategies:** Combine the USH with other technical indicators (e.g., Moving Averages, Bollinger Bands) for a comprehensive trading strategy.
**Confirmation Signals:** Use the USH to confirm signals from other indicators. For instance, a bullish histogram combined with a moving average crossover may provide a stronger buy signal.
### **10.2 Customization Tips**
**Adjust RSI Length:** Experiment with different RSI lengths to match various market conditions and trading styles.
**Color Preferences:** Choose histogram colors that enhance visibility and align with personal preferences.
### **10.3 Continuous Learning**
**Backtesting:** Regularly backtest the USH with historical data to refine strategies and improve accuracy.
**Education:** Stay updated with trading education and adapt strategies based on market changes and personal experiences.
Uptrick: Adaptive Trend Strength Index (ATSI)### **Adaptive Trend Strength Index (ATSI): Trend Detection Tool**
---
### Introduction
The **Adaptive Trend Strength Index (ATSI)** is a state-of-the-art indicator designed to offer traders an unparalleled view into market trends. By combining the principles of adaptive trend analysis with advanced volatility filtering, ATSI provides a powerful and visually intuitive method for identifying and following market trends. Its unique algorithm and customizable features make it an essential tool for traders across all markets—whether you're trading stocks, forex, commodities, or cryptocurrencies.
### The Purpose and Design Philosophy
At its core, the ATSI was built with the understanding that financial markets are dynamic, ever-changing entities influenced by a multitude of factors, including market sentiment, economic data, geopolitical events, and, critically, volatility. Traditional trend indicators often fall short by either over-smoothing price data (thus lagging behind the actual trend) or reacting too quickly to minor price fluctuations, resulting in false signals.
**ATSI solves this dilemma by adapting to market conditions in real-time.** It effectively filters out market noise while being sensitive enough to detect meaningful shifts in trend direction. The result is a trend line that is both responsive and smooth, providing traders with a clear, actionable view of the market's current trajectory.
### Key Features and Functionality
#### 1. **Adaptive Trend Calculation**
The heart of ATSI is its adaptive trend algorithm, which adjusts based on market conditions. It leverages a combination of price action analysis and volatility filtering to determine the strength and direction of the trend. Here’s how it works:
- **Volatility Sensitivity:** ATSI incorporates the Average True Range (ATR) to measure market volatility. This volatility measure is then adjusted by a user-defined sensitivity factor. This ensures that the indicator responds dynamically to different market environments—be it high-volatility breakouts or low-volatility consolidations.
- **Adaptive Smoothing:** The trend calculation is further enhanced by an exponential moving average (EMA) applied not just to the raw price data, but also to the resulting trend line itself. This dual-layer smoothing process helps to eliminate noise, resulting in a cleaner and more reliable trend line.
- **Real-Time Adaptation:** Unlike rigid indicators that require constant tweaking to stay relevant in changing market conditions, ATSI adapts in real-time. This adaptability makes it particularly valuable in fast-moving markets where conditions can change rapidly.
#### 2. **Visual Clarity**
In trading, visual clarity can make the difference between spotting a lucrative trend and missing out. ATSI excels in this regard by offering a clear, color-coded trend line that provides instant feedback on market conditions:
- **Thicker and Smoother Line:** ATSI’s trend line is designed to be visually prominent. By default, it is thicker than most standard indicators, making it easy to spot even in dense charts. Additionally, the smoothing applied to the line ensures that it flows smoothly, avoiding the jagged, noisy appearance that can plague other indicators.
- **Color-Coded Trends:** The trend line changes color based on the direction and strength of the trend:
- **Green Line**: Indicates a bullish trend, suggesting upward momentum in the market.
- **Red Line**: Indicates a bearish trend, signaling downward momentum.
- **Gold Line**: Represents a neutral or weak trend, where the market is consolidating or where there is no clear direction.
This color-coding is not just for aesthetics—it’s a critical feature that allows traders to quickly assess market conditions at a glance.
#### 3. **Customizable Parameters**
ATSI is built with the understanding that every trader’s strategy is unique. Whether you’re a day trader looking for short-term trends or a swing trader interested in catching longer moves, ATSI can be tailored to fit your needs:
- **Trend Length:** The length parameter controls how much historical data is considered in the trend calculation. A shorter length will make the indicator more sensitive to recent price changes, while a longer length will smooth out short-term fluctuations, focusing on the broader trend.
- **Smoothing Factor:** This parameter controls the level of smoothing applied to the trend line. A higher smoothing factor will result in a smoother, more stable trend line, while a lower factor will make the line more responsive to quick changes in price.
- **Volatility Sensitivity:** By adjusting the volatility sensitivity, you can control how reactive the indicator is to market volatility. A higher sensitivity makes the indicator more likely to detect trends in volatile markets, while a lower sensitivity helps to filter out noise in calmer markets.
- **Line Width:** ATSI allows you to adjust the thickness of the trend line, ensuring that it stands out on your chart. This is particularly useful when trading on charts with a lot of overlays or when you need a clear, bold line to guide your trading decisions.
- **Color Customization:** The colors for bullish, bearish, and neutral trends can be fully customized to match your personal preferences or to integrate seamlessly with your existing chart setup.
### Practical Applications
ATSI is a versatile indicator that can be applied to a wide range of trading strategies. Here’s how it can enhance your trading:
#### 1. **Trend Following**
For traders who thrive on catching and riding trends, ATSI is a game-changer. Its adaptive nature ensures that you stay in the trend for as long as possible without being shaken out by minor fluctuations. The clear color-coded line makes it easy to identify when a trend starts and ends, providing clear entry and exit signals.
#### 2. **Risk Management**
One of the biggest challenges in trading is managing risk, particularly in volatile markets. ATSI’s volatility sensitivity feature helps traders adjust their strategies based on current market conditions. For example, in a high-volatility environment, the indicator will become more sensitive, allowing you to tighten your stop losses or take profits earlier. Conversely, in a low-volatility market, the indicator will smooth out minor fluctuations, reducing the risk of being stopped out prematurely.
#### 3. **Trend Reversals and Consolidations**
ATSI is also highly effective in identifying trend reversals and periods of consolidation. The neutral (gold) line indicates periods where the market is undecided, which can often precede significant moves. Recognizing these periods can help you avoid getting caught in choppy markets and position yourself for the next big move.
#### 4. **Market Timing**
Timing the market is often seen as the holy grail of trading. While no indicator can predict the future with 100% accuracy, ATSI’s real-time adaptation gives you a significant edge. By responding to changes in market conditions as they happen, ATSI helps you make timely decisions, whether you’re entering a trade, exiting a position, or adjusting your risk parameters.
### Comparative Advantage
What sets ATSI apart from other trend indicators is its combination of adaptability, visual clarity, and ease of use:
- **Adaptability:** Most trend indicators are static—they apply the same calculations regardless of market conditions. ATSI, however, adapts to the market in real-time, ensuring that it remains relevant and reliable across different market environments.
- **Visual Clarity:** The thicker, smoother, color-coded line is not just aesthetically pleasing—it’s a functional design choice that helps you quickly interpret market conditions. Whether you’re glancing at your chart or conducting an in-depth analysis, the ATSI line stands out, providing immediate insight.
- **Ease of Use:** Despite its advanced features, ATSI is incredibly easy to use. The default settings are optimized for general use, but the indicator offers a high degree of customization for those who want to tailor it to their specific trading strategy.
### Conclusion
The **Adaptive Trend Strength Index (ATSI)** is more than just another trend indicator—it’s a comprehensive tool designed to give traders an edge in today’s fast-paced, volatile markets. By combining adaptive trend analysis with advanced volatility filtering, ATSI offers a unique blend of responsiveness and reliability. Its clear, color-coded visual representation of trends makes it easy to use, even for traders who are new to technical analysis, while its customizable parameters provide the flexibility that experienced traders demand.
Whether you’re looking to ride the next big trend, manage your risk more effectively, or simply get a clearer picture of the market’s current direction, ATSI is an invaluable addition to your trading toolkit. With its cutting-edge design and powerful functionality, ATSI is poised to become the go-to indicator for traders seeking to enhance their market analysis and improve their trading outcomes.
Relative Strength NSE:Nifty for TF CommunityThis is a modified version of the Relative Strength Indicator (No confusion with RSI) originally by in.tradingview.com/u/modhelius/ based on The indicator calculates the relative strength between a selected stock and a comparative symbol (typically a market index like NSE:NIFTY).
Relative strength (RS) compares the performance of two assets, typically a stock and a market index, by dividing their percentage changes over a specific period. This indicator oscillates around zero:
- Greater than 0: Indicates the stock has outperformed the comparative symbol.
- Less than 0: Indicates the stock has underperformed the comparative symbol.
Key Enhancements:
This Relative Strength Indicator offers practical features to automatically adjusts the comparison period based on the chart’s timeframe, whether daily, weekly, or monthly, so you don’t have to make manual changes.
Secondly, if the selected stock has fewer bars than the comparison period, the indicator uses the shorter period to ensure accurate results. The default colors are hardcoded so they look fine for both dark and white themes, but of course can be changed.
You can customise the settings to fit your needs. The default period is set to 50/52, and the comparative symbol is NSE:NIFTY, but both can be changed. There’s also an option to toggle a moving average on or off, providing a smoother visual representation.
RiskMetrics█ OVERVIEW
This library is a tool for Pine programmers that provides functions for calculating risk-adjusted performance metrics on periodic price returns. The calculations used by this library's functions closely mirror those the Broker Emulator uses to calculate strategy performance metrics (e.g., Sharpe and Sortino ratios) without depending on strategy-specific functionality.
█ CONCEPTS
Returns, risk, and volatility
The return on an investment is the relative gain or loss over a period, often expressed as a percentage. Investment returns can originate from several sources, including capital gains, dividends, and interest income. Many investors seek the highest returns possible in the quest for profit. However, prudent investing and trading entails evaluating such returns against the associated risks (i.e., the uncertainty of returns and the potential for financial losses) for a clearer perspective on overall performance and sustainability.
One way investors and analysts assess the risk of an investment is by analyzing its volatility , i.e., the statistical dispersion of historical returns. Investors often use volatility in risk estimation because it provides a quantifiable way to gauge the expected extent of fluctuation in returns. Elevated volatility implies heightened uncertainty in the market, which suggests higher expected risk. Conversely, low volatility implies relatively stable returns with relatively minimal fluctuations, thus suggesting lower expected risk. Several risk-adjusted performance metrics utilize volatility in their calculations for this reason.
Risk-free rate
The risk-free rate represents the rate of return on a hypothetical investment carrying no risk of financial loss. This theoretical rate provides a benchmark for comparing the returns on a risky investment and evaluating whether its excess returns justify the risks. If an investment's returns are at or below the theoretical risk-free rate or the risk premium is below a desired amount, it may suggest that the returns do not compensate for the extra risk, which might be a call to reassess the investment.
Since the risk-free rate is a theoretical concept, investors often utilize proxies for the rate in practice, such as Treasury bills and other government bonds. Conventionally, analysts consider such instruments "risk-free" for a domestic holder, as they are a form of government obligation with a low perceived likelihood of default.
The average yield on short-term Treasury bills, influenced by economic conditions, monetary policies, and inflation expectations, has historically hovered around 2-3% over the long term. This range also aligns with central banks' inflation targets. As such, one may interpret a value within this range as a minimum proxy for the risk-free rate, as it may correspond to the minimum rate required to maintain purchasing power over time.
The built-in Sharpe and Sortino ratios that strategies calculate and display in the Performance Summary tab use a default risk-free rate of 2%, and the metrics in this library's example code use the same default rate. Users can adjust this value to fit their analysis needs.
Risk-adjusted performance
Risk-adjusted performance metrics gauge the effectiveness of an investment by considering its returns relative to the perceived risk. They aim to provide a more well-rounded picture of performance by factoring in the level of risk taken to achieve returns. Investors can utilize such metrics to help determine whether the returns from an investment justify the risks and make informed decisions.
The two most commonly used risk-adjusted performance metrics are the Sharpe ratio and the Sortino ratio.
1. Sharpe ratio
The Sharpe ratio , developed by Nobel laureate William F. Sharpe, measures the performance of an investment compared to a theoretically risk-free asset, adjusted for the investment risk. The ratio uses the following formula:
Sharpe Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑎
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑎 = Standard deviation of the investment's returns (volatility)
A higher Sharpe ratio indicates a more favorable risk-adjusted return, as it signifies that the investment produced higher excess returns per unit of increase in total perceived risk.
2. Sortino ratio
The Sortino ratio is a modified form of the Sharpe ratio that only considers downside volatility , i.e., the volatility of returns below the theoretical risk-free benchmark. Although it shares close similarities with the Sharpe ratio, it can produce very different values, especially when the returns do not have a symmetrical distribution, since it does not penalize upside and downside volatility equally. The ratio uses the following formula:
Sortino Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑑
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑑 = Downside deviation (standard deviation of negative excess returns, or downside volatility)
The Sortino ratio offers an alternative perspective on an investment's return-generating efficiency since it does not consider upside volatility in its calculation. A higher Sortino ratio signifies that the investment produced higher excess returns per unit of increase in perceived downside risk.
█ CALCULATIONS
Return period detection
Calculating risk-adjusted performance metrics requires collecting returns across several periods of a given size. Analysts may use different period sizes based on the context and their preferences. However, two widely used standards are monthly or daily periods, depending on the available data and the investment's duration. The built-in ratios displayed in the Strategy Tester utilize returns from either monthly or daily periods in their calculations based on the following logic:
• Use monthly returns if the history of closed trades spans at least two months.
• Use daily returns if the trades span at least two days but less than two months.
• Do not calculate the ratios if the trade data spans fewer than two days.
This library's `detectPeriod()` function applies related logic to available chart data rather than trade data to determine which period is appropriate:
• It returns true if the chart's data spans at least two months, indicating that it's sufficient to use monthly periods.
• It returns false if the chart's data spans at least two days but not two months, suggesting the use of daily periods.
• It returns na if the length of the chart's data covers less than two days, signifying that the data is insufficient for meaningful ratio calculations.
It's important to note that programmers should only call `detectPeriod()` from a script's global scope or within the outermost scope of a function called from the global scope, as it requires the time value from the first bar to accurately measure the amount of time covered by the chart's data.
Collecting periodic returns
This library's `getPeriodicReturns()` function tracks price return data within monthly or daily periods and stores the periodic values in an array . It uses a `detectPeriod()` call as the condition to determine whether each element in the array represents the return over a monthly or daily period.
The `getPeriodicReturns()` function has two overloads. The first overload requires two arguments and outputs an array of monthly or daily returns for use in the `sharpe()` and `sortino()` methods. To calculate these returns:
1. The `percentChange` argument should be a series that represents percentage gains or losses. The values can be bar-to-bar return percentages on the chart timeframe or percentages requested from a higher timeframe.
2. The function compounds all non-na `percentChange` values within each monthly or daily period to calculate the period's total return percentage. When the `percentChange` represents returns from a higher timeframe, ensure the requested data includes gaps to avoid compounding redundant values.
3. After a period ends, the function queues the compounded return into the array , removing the oldest element from the array when its size exceeds the `maxPeriods` argument.
The resulting array represents the sequence of closed returns over up to `maxPeriods` months or days, depending on the available data.
The second overload of the function includes an additional `benchmark` parameter. Unlike the first overload, this version tracks and collects differences between the `percentChange` and the specified `benchmark` values. The resulting array represents the sequence of excess returns over up to `maxPeriods` months or days. Passing this array to the `sharpe()` and `sortino()` methods calculates generalized Information ratios , which represent the risk-adjustment performance of a sequence of returns compared to a risky benchmark instead of a risk-free rate. For consistency, ensure the non-na times of the `benchmark` values align with the times of the `percentChange` values.
Ratio methods
This library's `sharpe()` and `sortino()` methods respectively calculate the Sharpe and Sortino ratios based on an array of returns compared to a specified annual benchmark. Both methods adjust the annual benchmark based on the number of periods per year to suit the frequency of the returns:
• If the method call does not include a `periodsPerYear` argument, it uses `detectPeriod()` to determine whether the returns represent monthly or daily values based on the chart's history. If monthly, the method divides the `annualBenchmark` value by 12. If daily, it divides the value by 365.
• If the method call does specify a `periodsPerYear` argument, the argument's value supersedes the automatic calculation, facilitating custom benchmark adjustments, such as dividing by 252 when analyzing collected daily stock returns.
When the array passed to these methods represents a sequence of excess returns , such as the result from the second overload of `getPeriodicReturns()`, use an `annualBenchmark` value of 0 to avoid comparing those excess returns to a separate rate.
By default, these methods only calculate the ratios on the last available bar to minimize their resource usage. Users can override this behavior with the `forceCalc` parameter. When the value is true , the method calculates the ratio on each call if sufficient data is available, regardless of the bar index.
Look first. Then leap.
█ FUNCTIONS & METHODS
This library contains the following functions:
detectPeriod()
Determines whether the chart data has sufficient coverage to use monthly or daily returns
for risk metric calculations.
Returns: (bool) `true` if the period spans more than two months, `false` if it otherwise spans more
than two days, and `na` if the data is insufficient.
getPeriodicReturns(percentChange, maxPeriods)
(Overload 1 of 2) Tracks periodic return percentages and queues them into an array for ratio
calculations. The span of the chart's historical data determines whether the function uses
daily or monthly periods in its calculations. If the chart spans more than two months,
it uses "1M" periods. Otherwise, if the chart spans more than two days, it uses "1D"
periods. If the chart covers less than two days, it does not store changes.
Parameters:
percentChange (float) : (series float) The change percentage. The function compounds non-na values from each
chart bar within monthly or daily periods to calculate the periodic changes.
maxPeriods (simple int) : (simple int) The maximum number of periodic returns to store in the returned array.
Returns: (array) An array containing the overall percentage changes for each period, limited
to the maximum specified by `maxPeriods`.
getPeriodicReturns(percentChange, benchmark, maxPeriods)
(Overload 2 of 2) Tracks periodic excess return percentages and queues the values into an
array. The span of the chart's historical data determines whether the function uses
daily or monthly periods in its calculations. If the chart spans more than two months,
it uses "1M" periods. Otherwise, if the chart spans more than two days, it uses "1D"
periods. If the chart covers less than two days, it does not store changes.
Parameters:
percentChange (float) : (series float) The change percentage. The function compounds non-na values from each
chart bar within monthly or daily periods to calculate the periodic changes.
benchmark (float) : (series float) The benchmark percentage to compare against `percentChange` values.
The function compounds non-na values from each bar within monthly or
daily periods and subtracts the results from the compounded `percentChange` values to
calculate the excess returns. For consistency, ensure this series has a similar history
length to the `percentChange` with aligned non-na value times.
maxPeriods (simple int) : (simple int) The maximum number of periodic excess returns to store in the returned array.
Returns: (array) An array containing monthly or daily excess returns, limited
to the maximum specified by `maxPeriods`.
method sharpeRatio(returnsArray, annualBenchmark, forceCalc, periodsPerYear)
Calculates the Sharpe ratio for an array of periodic returns.
Callable as a method or a function.
Namespace types: array
Parameters:
returnsArray (array) : (array) An array of periodic return percentages, e.g., returns over monthly or
daily periods.
annualBenchmark (float) : (series float) The annual rate of return to compare against `returnsArray` values. When
`periodsPerYear` is `na`, the function divides this value by 12 to calculate a
monthly benchmark if the chart's data spans at least two months or 365 for a daily
benchmark if the data otherwise spans at least two days. If `periodsPerYear`
has a specified value, the function divides the rate by that value instead.
forceCalc (bool) : (series bool) If `true`, calculates the ratio on every call. Otherwise, ratio calculation
only occurs on the last available bar. Optional. The default is `false`.
periodsPerYear (simple int) : (simple int) If specified, divides the annual rate by this value instead of the value
determined by the time span of the chart's data.
Returns: (float) The Sharpe ratio, which estimates the excess return per unit of total volatility.
method sortinoRatio(returnsArray, annualBenchmark, forceCalc, periodsPerYear)
Calculates the Sortino ratio for an array of periodic returns.
Callable as a method or a function.
Namespace types: array
Parameters:
returnsArray (array) : (array) An array of periodic return percentages, e.g., returns over monthly or
daily periods.
annualBenchmark (float) : (series float) The annual rate of return to compare against `returnsArray` values. When
`periodsPerYear` is `na`, the function divides this value by 12 to calculate a
monthly benchmark if the chart's data spans at least two months or 365 for a daily
benchmark if the data otherwise spans at least two days. If `periodsPerYear`
has a specified value, the function divides the rate by that value instead.
forceCalc (bool) : (series bool) If `true`, calculates the ratio on every call. Otherwise, ratio calculation
only occurs on the last available bar. Optional. The default is `false`.
periodsPerYear (simple int) : (simple int) If specified, divides the annual rate by this value instead of the value
determined by the time span of the chart's data.
Returns: (float) The Sortino ratio, which estimates the excess return per unit of downside
volatility.
AdaptivePNLLibrary "Adaptive Profit And Loss"
Provide Take profit and Stop loss values depending on source.
TakeProfitPriceTypes()
Provides supported Take profit sources
Returns: Supported Take profit sources
StopLossPriceTypes()
Provides supported Take profit sources
Returns: Supported Take profit sources
Price(type)
Get price value by selected price type
Parameters:
type (string) : price type from @TakeProfitPriceTypes() or @StopLossPriceTypes()
Returns: Required price value.
LinearProfit(initPerc, stepPerc)
Lineary changed profit
Parameters:
initPerc (float) : Initial profit value in percent unit
stepPerc (float) : Amount of change per every bar since last entry. Posiitive value will decrease profit in time.
Returns: Profit value lineary increased/decreased since last entry. If there is no opened trade, value is NaN
AdaptedProfit(initPerc, stepPerc, source)
Profit adapted to lowest/highest value of given source and lineary changes after it
Parameters:
initPerc (float) : Initial profit value in percent unit
stepPerc (float) : Amount of change per every bar since last entry. Posiitive value will decrease profit in time.
source (float) : Source according to is profit adapted. If it reach high, profit is increased for long positions, same for low and short positions.
Returns: Profit value lineary increased/decreased and adjusted since last entry. If there is no active trade, value is NaN
LinearStopLoss(initPerc, stepPerc)
Lineary changed stop loss
Parameters:
initPerc (float) : Initial stop loss value in percent unit
stepPerc (float) : Amount of change per every bar since last entry. Posiitive value will increase stop loss in time.
Returns: Stop loss value lineary increased/decreased since last entry. If there is no opened trade, value is NaN
AdaptedStopLoss(initPerc, stepPerc, source)
Stop loss adapted to highest/lowest value of given source and lineary changes after it
Parameters:
initPerc (float) : Initial stop loss value in percent unit
stepPerc (float) : Amount of change per every bar since last entry. Posiitive value will increase stop loss in time.
source (float) : Source according to is stop loss adapted. If it reach high, stop loss is increased for long positions, same for low and short positions.
Returns: Stop loss value lineary increased/decreased and adjusted since last entry. If there is no active trade, value is NaN
Difference from Highest Price (Last N Candles)The output of this TradingView indicator is a label that appears below the latest candle on the chart. This label provides information about:
The highest high of the last N candles.
The highest close of the last N candles.
The current trading price.
The percentage difference between the highest high and the current trading price.
The percentage difference between the highest close and the current trading price.
The percentage change in price from the previous candle.
The N-day average percentage change.
This information is useful for traders to understand the relationship between the current price and recent price action, as well as to identify potential overbought or oversold conditions based on the comparison with recent highs and closes.
Here's a breakdown of what the code does:
It takes an input parameter for the number of days (or candles) to consider (input_days).
It calculates the highest high and highest close of the last N candles (highest_last_n_high and highest_last_n_close).
It calculates the difference between the close of the current candle and the close of the previous candle (diff), along with the percentage change.
It maintains an array of percentage changes of the last N days (percentage_changes), updating it with the latest percentage change.
It calculates the sum of percentage changes and the N-day average percentage change.
It calculates the difference between the highest high/highest close of the last N candles and the current trading price, along with their percentage differences.
Finally, it plots this information as a label below the candle for the latest bar.
Enio_SPX_Accumulation/DistributionThis indicator handles the same inputs used for classic Accumulation and Distribution indicators, but performs the calculations in a different way.
This indicator is used to compare the positive volume (up volume) and the number of advancing stocks against the negative volume (down volume) and the number of declining stocks.
This indicator only measures SPX market breadth (Advancing issues, Declining issues) and SPX volume (Up and down volume)so it is for use only with SPX, SPY or MES. It can also be used with ES, but data outside of regular trading hours is not provided, the indicator in those cases will print a block of the same height and same color as the last RTH bar.
When the histogram is positive or green, the bars change to a lighter color if the current bar is less than the average of the last 3 bars. A continued set of bars with a lighter color could mean that the trend is about to change.
When the histogram is negative or red, the bars change to a lighter color if the current bar is greater than the average of the last 3 bars. A continued set of bars with a lighter color could mean that the trend is about to change.
When the histogram height is low, could signal a choppy market (SPX).
The histogram can help indicate a trending market when the opening trend is maintained and the color of the bars does not change, for example, a solid green increasing histogram can indicate a bullish trending market, while a solid red decreasing histogram will indicate a strong bearish trend.
In intraday trading the indicator can signal if the SPX price changes are supported by volume and market breadth and also allows you to see when these changes or trend are weakening.
The change from green (positive) to red (negative) and vice versa should not be taken alone as a buy/sell signal but as a confirmation of signals from other indicators you trust.
Due to the great specific weight that some stocks have within the SPX price calculation, the divergences of this indicator with SPX, can be taken as warning signals, but should not become an element of trading decisions. . You could see a negative histogram while SPX is positive and vice versa.
Z-Score Based Momentum Zones with Advanced Volatility ChannelsThe indicator "Z-Score Based Momentum Zones with Advanced Volatility Channels" combines various technical analysis components, including volatility, price changes, and volume correction, to calculate Z-Scores and determine momentum zones and provide a visual representation of price movements and volatility based on multi timeframe highest high and lowest low values.
Note: THIS IS A IMPROVEMNT OF "Multi Time Frame Composite Bands" INDICATOR OF MINE WITH MORE EMPHASIS ON MOMENTUM ZONES CALULATED BASED ON Z-SCORES
Input Options
look_back_length: This input specifies the look-back period for calculating intraday volatility. correction It is set to a default value of 5.
lookback_period: This input sets the look-back period for calculating relative price change. The default value is 5.
zscore_period: This input determines the look-back period for calculating the Z-Score. The default value is 500.
avgZscore_length: This input defines the length of the momentum block used in calculations, with a default value of 14.
include_vc: This is a boolean input that, if set to true, enables volume correction in the calculations. By default, it is set to false.
1. Volatility Bands (Composite High and Low):
Composite High and Low: These are calculated by combining different moving averages of the high prices (high) and low prices (low). Specifically:
a_high and a_low are calculated as the average of the highest (ta.highest) and lowest (ta.lowest) high and low prices over various look-back periods (5, 8, 13, 21, 34) to capture short and long-term trends.
b_high and b_low are calculated as the simple moving average (SMA) of the high and low prices over different look-back periods (5, 8, 13) to smooth out the trends.
high_c and low_c are obtained by averaging a_high with b_high and a_low with b_low respectively.
IDV Correction Calulation : In this script the Intraday Volatility (IDV) is calculated as the simple moving average (SMA) of the daily high-low price range divided by the closing price. This measures how much the price fluctuates in a given period.
Composite High and Low with Volatility: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
Composite High and Low with Volatility Correction: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
2. Momentum Blocks Based on Z-Score:
Relative Price Change (RPC):
The Relative Price Change (rpdev) is calculated as the difference between the current high-low-close average (hlc3) and the previous simple moving average (psma_hlc3) of the same quantity. This measures the change in price over time.
Additionally, std_hlc3 is calculated as the standard deviation of the hlc3 values over a specified look-back period. The standard deviation quantifies the dispersion or volatility in the price data.
The rpdev is then divided by the std_hlc3 to normalize the price change by the volatility. This normalization ensures that the price change is expressed in terms of standard deviations, which is a common practice in quantitative analysis.
Essentially, the rpdev represents how many standard deviations the current price is away from the previous moving average.
Volume Correction (VC): If the include_vc input is set to true, volume correction is applied by dividing the trading volume by the previous simple moving average of the volume (psma_volume). This accounts for changes in trading activity.
Volume Corrected Relative Price Change (VCRPD): The vcrpd is calculated by multiplying the rpdev by the volume correction factor (vc). This incorporates both price changes and volume data.
Z-Scores: The Z-scores are calculated by taking the difference between the vcrpd and the mean (mean_vcrpd) and then dividing it by the standard deviation (stddev_vcrpd). Z-scores measure how many standard deviations a value is away from the mean. They help identify whether a value is unusually high or low compared to its historical distribution.
Momentum Blocks: The "Momentum Blocks" are essentially derived from the Z-scores (avgZScore). The script assigns different colors to the "Fill Area" based on predefined Z-score ranges. These colored areas represent different momentum zones:
Positive Z-scores indicate bullish momentum, and different shades of green are used to fill the area.
Negative Z-scores indicate bearish momentum, and different shades of red are used.
Z-scores near zero (between -0.25 and 0.25) suggest neutrality, and a yellow color is used.
Seasonal - Trading Day of MonthIndicator Description: Historical Comparative Price Analysis
The Historical Comparative Price Analysis indicator serves as a comprehensive tool for evaluating price changes over distinct trading periods. By configuring the date settings, the indicator captures the percentage change data for each individual day or month, facilitating a clear historical perspective. Each year is represented in a separate row, allowing for a side-by-side presentation of corresponding data for the same trading day or week.
Within the "Summary" row, the indicator calculates the average change for each selected trading day within a specified time frame. This calculation, rooted in Larry Williams' concept, considers trading days rather than calendar days. The "Summary" row provides a quick insight into whether the current price change exceeds or falls short of the average change within the chosen time frame.
The indicator's final row presents a comprehensive overview, including the maximum and minimum average changes. It showcases the closing price from the first column of the 10th row, aiding in distinguishing between the last trading day of the month and the first trading day, which varies due to different market opening times.
To enhance visual analysis, the indicator attempts to display the price average of the chosen time frame as a reference line on the chart. The maximum and minimum values are added or subtracted from the reference line to create an average price channel. The color of the candlesticks dynamically changes to indicate whether the current price change is above or below the average.
For optimal results, we recommend selecting the previous year's data and the current month's data from the 1st to the 31st day. In weekly charts, multiple months can be selected to provide a broader perspective on price trends.
Enhance your trading insights with the Historical Comparative Price Analysis indicator, and gain a deeper understanding of how current price changes relate to historical averages.
Note: This description is intended for educational and informational purposes and is not intended as financial advice. Always conduct your research and analysis before making trading decisions.
ATR DeltaThe ATR Delta indicator is based on the concept of Average True Range (ATR), which reflects the average price range over a specified period. By calculating the difference between current and previous ATR values, the ATR Delta provides valuable insights into volatility shifts in the market. This information can help traders identify periods of heightened or diminished price movement, enabling them to adjust their strategies accordingly.
The ATR Delta indicator consists of two main calculations:
-- ATR Calculation : The Average True Range (ATR) is calculated using the specified length parameter. It measures the average price range (including gaps) during that period. A larger ATR value indicates higher volatility, while a smaller value indicates lower volatility.
-- ATR Delta Calculation : The ATR Delta is calculated by subtracting the ATR value of the previous bar from the current ATR value. This calculation captures the change in volatility between the two periods, providing a measure of how volatility has evolved.
Positive ATR Delta values indicate an increase in volatility compared to the previous period. It suggests that price movements have expanded, potentially indicating a more active market. On the other hand, negative ATR Delta values indicate a decrease in volatility compared to the previous period. It suggests that price movements have contracted, potentially signaling a calmer or range-bound market.
The ATR Delta indicator uses coloration to visually represent the relationship between the ATR Delta, zero, and a signal line:
-- Green color is assigned when the ATR Delta is positive, above the signal line, and increasing. This coloration suggests a scenario of higher volatility, as the market is experiencing upward momentum in price swings.
-- Red color is assigned when the ATR Delta is negative, below the signal line, and decreasing. This coloration suggests a scenario of lower volatility, as the market is experiencing downward momentum in price swings.
-- Gray color is assigned for other cases when the ATR Delta and signal line relationship does not meet the above conditions.
These colors are reflected in the columns of the ATR Delta as well as the bar coloration.
The ATR Delta indicator includes a signal line, which acts as a reference for interpreting the ATR Delta values. The signal line is calculated as a moving average (EMA) of the ATR Delta over a specified length. It helps smooth out the ATR Delta fluctuations, providing a clearer indication of the underlying trend in volatility changes. When the ATR Delta crosses above the signal line, it may suggest a potential increase in volatility, indicating a market that is becoming more active. Conversely, when the ATR Delta crosses below the signal line, it may suggest a potential decrease in volatility, indicating a market that is becoming less active.
The coloration of the signal line in the ATR Delta indicator helps to differentiate between positive and negative values and provides further insight into market sentiment. When the signal line is positive, indicating increasing volatility, it is colored lime. This color choice reinforces the bullish sentiment and signifies potential opportunities for trend continuation or breakouts. On the other hand, when the signal line is negative, indicating decreasing volatility, it is colored fuchsia. This color choice highlights the bearish sentiment and suggests potential range-bound or consolidation periods. These colors are reflected in the background of the indicator.
The ATR Delta indicator offers several potential applications for traders:
-- Volatility Analysis : The ATR Delta is invaluable for understanding and analyzing volatility dynamics in the market. Traders can observe the changes in ATR Delta values and use them to assess the current level of price movement. This information can help determine the appropriate strategies and risk management approaches.
-- Breakout Strategies : Traders often use the ATR Delta to identify periods of increased volatility, which frequently accompany breakouts. By monitoring the ATR Delta, traders can anticipate potential price breakouts and adjust their entry and exit levels accordingly.
-- Trend Confirmation : Combining the ATR Delta with trend-following indicators allows traders to validate the strength of a trend. Higher ATR Delta values during an uptrend may indicate stronger momentum and a higher likelihood of continuation. Conversely, lower ATR Delta values during a downtrend may suggest a potential consolidation phase or trend reversal.
Limitations :
-- Lagging Indicator : The ATR Delta indicator is based on historical data and calculates the difference between current and previous ATR values. As a result, it may lag behind real-time market conditions. Traders should be aware of this delay and consider it when making trading decisions. It is advisable to combine the ATR Delta with other indicators or price action analysis for a more comprehensive assessment of market conditions.
-- Parameter Sensitivity : The ATR Delta indicator's effectiveness can be influenced by the selection of its parameters, such as the length of the ATR and signal line. Different market conditions may require adjustments to these parameters to better capture volatility changes. Traders should carefully test and optimize the indicator's parameters to align with the characteristics of the specific market or asset they are trading.
-- Market Regime Changes : The ATR Delta indicator assumes that volatility changes occur gradually. However, in rapidly changing market regimes or during news events, volatility can spike or drop abruptly, potentially rendering the indicator less effective. Traders should exercise caution and consider using additional tools or techniques to identify and adapt to such market conditions.
The ATR Delta indicator is a valuable tool for traders seeking to analyze and monitor volatility dynamics in the market. By calculating the difference between current and previous ATR values, it provides insights into changes in price movement and helps identify periods of increased or decreased volatility. Traders can leverage the ATR Delta to fine-tune their strategies, validate trend strength, and identify potential breakout opportunities. However, it is essential to recognize the limitations of the indicator, including its lagging nature and sensitivity to parameter selection. By combining the ATR Delta with other technical analysis tools and applying sound risk management practices, traders can enhance their decision-making process and potentially improve their trading outcomes.
Trend Correlation HeatmapHello everyone!
I am excited to release my trend correlation heatmap, or trend heatmap for short.
Per usual, I think its important to explain the theory before we get into the use of the indicator, so let's get into the theory!
The theory:
So what is a correlation?
Correlation is the relationship one variable has to another. Correlations are the basis of everything I do as a quantitative trader. From the correlation between the same variables (i.e. autocorrelation), the correlation between other variables (i.e. VIX and SPY, SPY High and SPY Low, DXY and ES1! close, etc.) and, as well, the correlation between price and time (time series correlation).
This may sound very familiar to you, especially if you are a user, observer or follower of my ideas and/or indicators. Ninety-five percent of my indicators are a function of one of those three things. Whether it be a time series based indicator (i.e.my time series indicator), whether it be autocorrelation (my autoregressive cloud indicator or my autocorrelation oscillator) or whether it be regressive in nature (i.e. my SPY Volume weighted close, or even my expected move which uses averages in lieu of regressive approaches but is foundational in regression principles. Or even my VIX oscillator which relies on the premise of correlations between tickers.) So correlation is extremely important to me and while its true I am more of a regression trader than anything, I would argue that I am more of a correlation trader, because correlations are the backbone of how I develop math models of stocks.
What I am trying to stress here is the importance of correlations. They really truly are foundational to any type of quantitative analysis for stocks. And as such, understanding the current relationship a stock has to time is pivotal for any meaningful analysis to be conducted.
So what is correlation to time and what does it tell us?
Correlation to time, otherwise known and commonly referred to as "Time Series", is the relationship a ticker's price has to the passing of time. It is displayed in the traditional Pearson Correlation Coefficient or R value and can be any value from -1 (strong negative relationship, i.e. a strong downtrend) to + 1 (i.e. a strong positive relationship, i.e. a strong uptrend). The higher or lower the value the stronger the up or downtrend is.
As such, correlation to time tells us two very important things. These are:
a) The direction of the stock; and
b) The strength of the trend.
Let's take a look at an example:
Above we have a chart of QQQ. We can see a trendline that seems to fit well. The questions we ask as traders are:
1. What is the likelihood QQQ breaks down from this trendline?
2. What is the likelihood QQQ continues up?
3. What is the likelihood QQQ does a false breakdown?
There are numerous mathematical approaches we can take to answer these questions. For example, 1 and 2 can be answered by use of a Cumulative Distribution Density analysis (CDDA) or even a linear or loglinear regression analysis and 3 can be answered, more or less, with a linear regression analysis and standard error ascertainment, or even just a general comparison using a data science approach (such as cosine similarity or Manhattan distance).
But, the reality is, all 3 of these questions can be visualized, at least in some way, by simply looking at the correlation to time. Let's look at this chart again, this time with the correlation heatmap applied:
If we look at the indicator we can see some pivotal things. These are:
1. We have 4, very strong uptrends that span both higher AND lower timeframes. We have a strong uptrend of 0.96 on the 5 minute, 50 candle period. We have a strong uptrend at the 300 candle lookback period on the 1 minute, we have a strong uptrend on the 100 day lookback on the daily timeframe period and we have a strong uptrend on the 5 minute on the 500 candle lookback period.
2. By comparison, we have 3 downtrends, all of which have correlations less than the 4 uptrends. All of the downtrends have a correlation above -0.8 (which we would want lower than -0.8 to be very strong), and all of the uptrends are greater than + 0.80.
3. We can also see that the uptrends are not confined to the smaller timeframes. We have multiple uptrends on multiple timeframes and both short term (50 to 100 candles) and long term (up to 500 candles).
4. The overall trend is strengthening to the upside manifested by a positive Max Change and a Positive Min change (to be discussed later more in-depth).
With this, we can see that QQQ is actually very strong and likely will continue at least some upside. If we let this play out:
We continued up, had one test and then bounced.
Now, I want to specify, this indicator is not a panacea for all trading. And in relation to the 3 questions posed, they are best answered, at least quantitatively, not only by correlation but also by the aforementioned methods (CDDA, etc.) but correlation will help you get a feel for the strength or weakness present with a stock.
What are some tangible applications of the indicator?
For me, this indicator is used in many ways. Let me outline some ways I generally apply this indicator in my day and swing trading:
1. Gauging the strength of the stock: The indictor tells you the most prevalent behavior of the stock. Are there more downtrends than uptrends present? Are the downtrends present on the larger timeframes vs uptrends on the shorter indicating a possible bullish reversal? or vice versa? Are the trends strengthening or weakening? All of these things can be visualized with the indicator.
2. Setting parameters for other indicators: If you trade EMAs or SMAs, you may have a "one size fits all" approach. However, its actually better to adjust your EMA or SMA length to the actual trend itself. Take a look at this:
This is QQQ on the 1 hour with the 200 EMA with 200 standard deviation bands added. If we look at the heatmap, we can see, yes indeed 200 has a fairly strong uptrend correlation of 0.70. But the strongest hourly uptrend is actually at 400 candles, with a correlation of 0.91. So what happens if we change the EMA length and standard deviation to 400? This:
The exact areas are circled and colour coded. You can see, the 400 offers more of a better reference point of supports and resistances as well as a better overall trend fit. And this is why I never advocate for getting married to a specific EMA. If you are an EMA 200 lover or 21 or 51, know that these are not always the best depending on the trend and situation.
Components of the indicator:
Ah okay, now for the boring stuff. Let's go over the functionality of the indicator. I tried to keep it simple, so it is pretty straight forward. If we open the menu here are our options:
We have the ability to toggle whichever timeframes we want. We also have the ability to toggle on or off the legend that displays the colour codes and the Max and Min highest change.
Max and Min highest change: The max and min highest change simply display the change in correlation over the previous 14 candles. An increasing Max change means that the Max trend is strengthening. If we see an increasing Max change and an increasing Min change (the Min correlation is moving up), this means the stock is bullish. Why? Because the min (i.e. ideally a big negative number) is going up closer to the positives. Therefore, the downtrend is weakening.
If we see both the Max and Min declining (red), that means the uptrend is weakening and downtrend is strengthening. Here are some examples:
Final Thoughts:
And that is the indicator and the theory behind the indicator.
In a nutshell, to summarize, the indicator simply tracks the correlation of a ticker to time on multiple timeframes. This will allow you to make judgements about strength, sentiment and also help you adjust which tools and timeframes you are using to perform your analyses.
As well, to make the indicator more user friendly, I tried to make the colours distinctively different. I was going to do different shades but it was a little difficult to visualize. As such, I have included a toggle-able legend with a breakdown of the colour codes!
That's it my friends, I hope you find it useful!
Safe trades and leave your questions, comments and feedback below!
Logarithmic VolatilityIntroducing the Logarithmic Volatility Indicator , an innovative trading indicator designed especially for trading in low volatility markets. This powerful indicator is aimed at traders of all levels, from beginners to experts, and is based on fundamental concepts of mathematics and statistics applied to the financial market. Its main objective is to provide you with a better understanding of price movements and help you make more accurate investment decisions, especially in low volatility environments.
The purpose of this indicator is to find a volatility estimator that depends on the difference between High and Low, taking into account that this measure is directly proportional to volatility. A first result was obtained by Parkinson (1980) which was later improved by Garman and Klass (1980), who improved the estimator by obtaining one of minimum variance. It is the simplified version (and recommended by them) of the Garman and Klass estimator that is used to calculate the daily volatility of the asset.
The Logarithmic Volatility Indicator is a unique smoothing indicator that uses logarithms and volatility calculation of the opening, high, low and closing prices. It combines these elements to obtain an accurate representation of market volatility in situations where volatility is low.
Features
This indicator has several outstanding features designed to enhance your trading analysis in low volatility environments:
• Intraday Volatility Calculation: This innovative feature allows you to view market volatility levels in real time, providing a clear view of market fluctuations even when volatility is low.
• EMA (Exponential Moving Average) Multi Length: The indicator incorporates three different EMA lengths (Fast, Medium and Slow). This gives you a deeper and more detailed analysis of market volatility, allowing you to detect subtle changes in volatility and make more accurate predictions.
• Visual color change: The indicator uses a color change between green and red to facilitate quick interpretation of the market. Green indicates a decrease in volatility, while red indicates an increase in volatility. This feature helps you quickly identify changes in market dynamics even in periods of low volatility.
• Histogram display: In addition to the colors, the indicator can also be displayed as a histogram. This intuitive representation allows you to visually observe changes in volatility over time and detect emerging patterns or trends in markets with low volatility.
Settings
The Logarithmic Volatility Indicator allows you to customize various settings to suit your specific trading needs:
• Slow EMA length: you can select the length of the slow exponential moving average according to your preferences and trading strategies.
• Fast EMA length: Similarly, you can choose the length of the fast exponential moving average to suit your trading style.
• Average EMA length: In addition to the two EMA lengths above, this indicator offers a third EMA length for even more detailed analysis. This additional feature is especially useful when trading in markets with low volatility, as it allows you to capture subtle changes in market dynamics.
Trading
The Logarithmic Volatility Indicator is designed not only to provide you with essential information about market volatility, but also to give you clear indications on when to trade. Here's how you can use the indicator's colors to guide your trading decisions:
- Long Trading: When the fast EMA has a smaller value than the slow EMA, the indicator will change to green. This is a signal to enter a long trade. That is, you can consider buying at this point, as an increase in price is anticipated due to decreasing volatility. With volatility declining, there is a greater likelihood that the price will continue in the current direction rather than fluctuate erratically.
- b]Short Trading: On the other hand, when the fast EMA has a higher value than the slow EMA, the indicator will turn red. This is a signal to enter a short trade. In other words, you may consider selling at this point, as a decline in price is anticipated due to rising volatility. With volatility on the rise, there is a greater risk of steeper price fluctuations.
It is important to remember that, as with any indicator, the Logarithmic Volatility Indicator does not guarantee 100% success. You should always use this indicator in combination with other analytical tools and good risk management. This tool provides you with an overview of market volatility and can help you identify trading opportunities in low volatility markets, but the final decision on when and how to trade should always be based on your own analysis and judgment.
In conclusion, the Logarithmic Volatility Indicator is an essential trading tool that every trader should have in their arsenal, especially when facing low volatility markets. With its accurate volatility calculation and easy-to-understand visualization, it will help you improve your trading decisions and maximize your profits even in situations where price movements are less pronounced. Try it today and take advantage of its efficiency in low volatility environments!
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Presentamos el Indicador de Volatilidad Logarítmica , un innovador indicador de trading diseñado especialmente para operar en mercados con baja volatilidad. Este poderoso indicador está dirigido a traders de todos los niveles, desde principiantes hasta expertos, y se basa en conceptos fundamentales de matemáticas y estadísticas aplicadas al mercado financiero. Su objetivo principal es proporcionarte una mejor comprensión de los movimientos de precios y ayudarte a tomar decisiones de inversión más precisas, especialmente en entornos de baja volatilidad.
Con este indicador se pretende encontrar un estimador de la volatilidad que dependa de la diferencia entre el High y el Low, teniendo en cuenta que esta medida es directamente proporcional a la volatilidad. Un primer resultado fue obtenido por Parkinson (1980) que posteriormente fue mejorado por Garman y Klass (1980), que mejoraron el estimador obteniendo uno de varianza mínima. Es la versión simplificada (y recomendada por ellos mismos) del estimador de Garman y Klass la que se utiliza para calcular la volatilidad diaria del activo.
El Indicador de Volatilidad Logarítmica es un indicador de suavizado único que utiliza logaritmos y el cálculo de la volatilidad de los precios de apertura, máximo, mínimo y cierre. Combina estos elementos para obtener una representación precisa de la volatilidad del mercado en situaciones donde la volatilidad es baja.
Características
Este indicador cuenta con varias características sobresalientes diseñadas para mejorar tu análisis de trading en entornos de baja volatilidad:
• Cálculo de la volatilidad intradía: Esta función innovadora te permite ver los niveles de volatilidad del mercado en tiempo real, lo que brinda una visión clara de las fluctuaciones del mercado incluso cuando la volatilidad es baja.
• EMA (Exponential Moving Average) Multi Longitud: El indicador incorpora tres longitudes diferentes de EMA (Rápida, Media y Lenta). Esto te proporciona un análisis más profundo y detallado de la volatilidad del mercado, permitiéndote detectar cambios sutiles en la volatilidad y realizar predicciones más precisas.
• Cambio de color visual: El indicador utiliza un cambio de color entre verde y rojo para facilitar la interpretación rápida del mercado. El verde indica una disminución de la volatilidad, mientras que el rojo indica un aumento de la volatilidad. Esta característica te ayuda a identificar rápidamente cambios en la dinámica del mercado incluso en períodos de baja volatilidad.
• Visualización Histograma: Además de los colores, el indicador también se puede visualizar como un histograma. Esta representación intuitiva te permite observar de manera visual los cambios en la volatilidad a lo largo del tiempo y detectar patrones o tendencias emergentes en mercados con baja volatilidad.
Ajustes
El Indicador de Volatilidad Logarítmica te permite personalizar varios ajustes para adaptarlos a tus necesidades de trading específicas:
• Longitud de EMA lenta: Puedes seleccionar la longitud de la media móvil exponencial lenta según tus preferencias y estrategias de trading.
• Longitud de EMA rápida: De manera similar, puedes elegir la longitud de la media móvil exponencial rápida para ajustarla a tu estilo de trading.
• Longitud de EMA media: Además de las dos longitudes de EMA anteriores, este indicador ofrece una tercera longitud de EMA para un análisis aún más detallado. Esta característica adicional es especialmente útil cuando operas en mercados con baja volatilidad, ya que te permite capturar cambios sutiles en la dinámica del mercado.
Operativa
El Indicador de Volatilidad Logarítmica está diseñado no solo para brindarte información esencial sobre la volatilidad del mercado, sino también para ofrecerte indicaciones claras sobre cuándo operar. Aquí te explicamos cómo puedes utilizar los colores del indicador para guiar tus decisiones de trading:
• Operativa en Largo: Cuando la EMA rápida tiene un valor más pequeño que la EMA lenta, el indicador cambiará a color verde. Esta es una señal para entrar en una operación en largo. Es decir, puedes considerar comprar en este punto, ya que se anticipa un aumento en el precio debido a la disminución de la volatilidad. Con la volatilidad en descenso, existe una mayor probabilidad de que el precio continúe en la dirección actual en lugar de fluctuar erráticamente.
• Operativa en Corto: Por otro lado, cuando la EMA rápida tiene un valor mayor que la EMA lenta, el indicador se tornará rojo. Esta es una señal para entrar en una operación en corto. En otras palabras, puedes considerar vender en este punto, ya que se anticipa una disminución en el precio debido al aumento de la volatilidad. Con la volatilidad en ascenso, existe un mayor riesgo de fluctuaciones de precio más pronunciadas.
Es importante recordar que, como con cualquier indicador, el Indicador de Volatilidad Logarítmica no garantiza un éxito del 100%. Siempre debes usar este indicador en combinación con otras herramientas de análisis y una buena gestión de riesgos. Esta herramienta te proporciona una visión general de la volatilidad del mercado y puede ayudarte a identificar oportunidades de trading en mercados con baja volatilidad, pero la decisión final de cuándo y cómo operar siempre deberá basarse en tu propio análisis y juicio.
En conclusión, el Indicador de Volatilidad Logarítmica es una herramienta de trading esencial que todo trader debe tener en su arsenal, especialmente cuando se enfrenta a mercados con baja volatilidad. Con su cálculo preciso de la volatilidad y su visualización fácil de entender, te ayudará a mejorar tus decisiones de trading y a maximizar tus ganancias incluso en situaciones donde los movimientos de precios son menos pronunciados. ¡Pruébalo hoy mismo y aprovecha su eficiencia en entornos de baja volatilidad!
DojiCandle body size RSI-SMMA filter MTF
DojiCandle body size RSI-SMMA filter MTF
Hi. I was inspired by a public script written by @ahmedirshad419, .
I thank him for his idea and hard work.
His script is the combination of RSI and Engulfing Pattern.
//------------------------------------------------------------
I decided to tweak it a bit with Open IA.
I have changed:
1) candle pattern to DojiCandle Pattern;
2) I added the ability for the user to change the size of the candlestick body;
3) Added SMMA 200;
4) Changed the colour of SMMA 200 depending on price direction;
5) Added a change in the colour of candlesticks, depending on the colour of the SMMA 200;
6) Added buy and sell signals with indicator name, ticker and close price;
7) Added ability to use indicator on multi time frame.
How it works
1. when RSI > 70 > SMMA 200 and form the bullish DojiCandle Pattern. It gives sell signal
2. when RSI < 30 < SMMA 200 and form the bearish DojiCandle Pattern. It gives buy signal
settings:
basic setting for RSI, SMMA 200 has been enabled in the script to set the levels accordingly to your trades
Enjoy
Order Blocks & Breaker Blocks [LuxAlgo]The Order Blocks & Breaker Blocks indicator detects order blocks that can be turned into breaker blocks on the chart automatically once mitigated.
Users can determine the amount of bullish and bearish order/breaker blocks that display on their chart from within the settings menu.
🔶 SETTINGS
Swing Lookback: Lookback period used for the detection of the swing points used to create order blocks.
Show Last Bullish OB: Number of the most recent bullish order/breaker blocks to display on the chart.
Show Last Bearish OB: Number of the most recent bearish order/breaker blocks to display on the chart.
Use Candle Body: Allows users to use candle bodies as order block areas instead of the full candle range.
🔹 Style
Show Historical Polarity Changes: Allows users to see labels indicating where a swing high/low previously occurred within a breaker block.
🔶 USAGE
We have published several scripts covering the detection of order blocks previously, however, the concept of breaker blocks was not yet introduced.
When price mitigates an order block, a breaker block is confirmed. We can eventually expect price to trade back to this breaker block offering a new trade opportunity.
We can see that this is similar to a change in polarity, where a support becomes a resistance after a breakout and vice versa.
This script highlights regular order blocks as solid extended areas on the chart and breaker blocks as dashed lines with dual-colored areas. The color change and dashed line starts at the location where the order block was mitigated.
Using a higher "Swing Lookback" setting will return longer term order/breaker blocks on the chart.
Users can optionally enable "Historical Polarity Changes" labels within the settings menu to see where breaker blocks might have provided an effective trade setup previously.
The "Historical Polarity Changes" setting is disabled by default & is most effective using replay mode as the labels are backpainted.
The order blocks & breaker blocks themselves can be used in real-time as they are detected based on the swing length & previous breaker blocks being mitigated.
Odd_mod Econ CalendarA modification of Economic Calendar Events: FOMC, CPI, and more written by jdehorty . Please send all tips his way as he is maintaining the underlying data for the Calendar and the original concept.
List of changes:
Optimized code, will only run once on initialization now(No random line in middle of screen on bar change)
Legend - Added short names
Legend - Removed header
Legend - Made repositionable with selectable top margins
Legend - Removed data name from legend when it is disabled
Legend - Removed border
Original Description by jdehorty :
This script plots major events from the Economic Calendar that often correspond to major pivot points in various markets. It also includes built-in logic to retroactively adjust larger time intervals (i.e. greater than 1 hour) to be correctly aligned with the interval during which the event occurred.
Events are taken from the Economic Calendar and will be updated periodically at the following library:
EconomicCalendar
The above library can be used to conveniently access date-related data for major Meetings, Releases, and Announcements as integer arrays, which can be used in other indicators. Currently, it has support for the following events:
FOMC Meetings
The FOMC meets eight times a year to determine the course of monetary policy . The FOMC's decisions are based on a review of economic and financial developments and its assessment of the likely effects of these developments on the economic outlook.
FOMC Minutes
The FOMC minutes are released three weeks after each FOMC meeting. The minutes provide a detailed account of the FOMC's discussion of economic and financial developments and its assessment of the likely effects of these developments on the economic outlook.
Producer Price Index (PPI) Releases
The Producer Price Index (PPI) measures changes in the price level of goods and services sold by domestic producers. The PPI is a weighted average of prices of a basket of goods and services, such as transportation, food, and medical care. PPI is a leading indicator of CPI .
Consumer Price Index ( CPI ) Releases
The Consumer Price Index ( CPI ) measures changes in the price level of goods and services purchased by households. The CPI is a weighted average of prices of a basket of consumer goods and services, such as transportation, food, and medical care. CPI is one of the most widely used measures of inflation .
Consumer Sentiment Index ( CSI ) Releases
The University of Michigan's Consumer Sentiment Index ( CSI ) is a measure of consumer attitudes about the economy. The CSI is based on a monthly survey of U.S. households and reflects the consumers' assessment of present and future economic conditions. The CSI is a leading indicator of consumer spending, which accounts for about two-thirds of U.S. economic activity.
Consumer Confidence Index ( CCI ) Releases
The Consumer Confidence Index is a survey that measures how optimistic or pessimistic consumers are regarding their expected financial situation.
Non-Farm Payroll (NFP) Releases
The Non-Farm Payroll (NFP) is a measure of the change in the number of employed persons, excluding farm workers and government employees. The NFP is a leading indicator of consumer spending, which accounts for about two-thirds of U.S. economic activity.
UFO + Realtime Divergences (UO x MFI)UFO + Realtime Divergences (UO x MFI) + Alerts
The UFO is a hybrid of two powerful oscillators - the Ultimate Oscillator (UO) and the Money Flow Index (MFI)
Features of the UFO include:
- Optional divergence lines drawn directly onto the oscillator in realtime.
- Configurable alerts to notify you when divergences occur, as well as centerline crossovers.
- Configurable lookback periods to fine tune the divergences drawn in order to suit different trading styles and timeframes.
- Background colouring option to indicate when the oscillator has crossed its centerline.
- Alternate timeframe feature allows you to configure the oscillator to use data from a different timeframe than the chart it is loaded on.
- 2x MTF triple-timeframe Stochastic RSI overbought and oversold confluence signals painted at the top of the panel for use as a confluence for reversal entry trades.
The core calculations of the UFO+ combine the factory settings of the Ultimate Oscillator and Money Flow Index, taking an average of their combined values for its output eg:
UO_Value + MFI_Value / 2
The result is a powerful oscillator capable of detecting high quality divergences, including on very low timeframes and highly volatile markets, it benefits from the higher weighting of the most recent price action provided by the Ultimate Oscillators calculations, as well as the calculation of the MFI, which incorporates volume data. The UFO and its incorporated 2x triple-timeframe MTF Stoch RSI overbought and oversold signals makes it well adapted for low timeframe scalping and regular divergence trades in particular.
The Ultimate Oscillator (UO)
Tradingview describes the Ultimate Oscillator as follows:
“The Ultimate Oscillator indicator (UO) is a technical analysis tool used to measure momentum across three varying timeframes. The problem with many momentum oscillators is that after a rapid advance or decline in price, they can form false divergence trading signals. For example, after a rapid rise in price, a bearish divergence signal may present itself, however price continues to rise. The Ultimate Oscillator attempts to correct this by using multiple timeframes in its calculation as opposed to just one timeframe which is what is used in most other momentum oscillators.”
You can read more about the UO and its calculations here
The Money Flow Index ( MFI )
Investopedia describes the True Strength Indicator as follows:
“The Money Flow Index ( MFI ) is a technical oscillator that uses price and volume data for identifying overbought or oversold signals in an asset. It can also be used to spot divergences which warn of a trend change in price. The oscillator moves between 0 and 100. Unlike conventional oscillators such as the Relative Strength Index ( RSI ), the Money Flow Index incorporates both price and volume data, as opposed to just price. For this reason, some analysts call MFI the volume-weighted RSI .”
You can read more about the MFI and its calculations here
The Stochastic RSI (relating to the built-in MTF Stoch RSI feature)
The popular oscillator has been described as follows:
“The Stochastic RSI is an indicator used in technical analysis that ranges between zero and one (or zero and 100 on some charting platforms) and is created by applying the Stochastic oscillator formula to a set of relative strength index ( RSI ) values rather than to standard price data. Using RSI values within the Stochastic formula gives traders an idea of whether the current RSI value is overbought or oversold. The Stochastic RSI oscillator was developed to take advantage of both momentum indicators in order to create a more sensitive indicator that is attuned to a specific security's historical performance rather than a generalized analysis of price change.”
You can read more about the Stochastic RSI and its calculations here
How do traders use overbought and oversold levels in their trading?
The oversold level, that is when the Stochastic RSI is above the 80 level is typically interpreted as being 'overbought', and below the 20 level is typically considered 'oversold'. Traders will often use the Stochastic RSI at an overbought level as a confluence for entry into a short position, and the Stochastic RSI at an oversold level as a confluence for an entry into a long position. These levels do not mean that price will necessarily reverse at those levels in a reliable way, however. This is why this version of the Stoch RSI employs the triple timeframe overbought and oversold confluence, in an attempt to add a more confluence and reliability to this usage of the Stoch RSI .
What are divergences?
Divergence is when the price of an asset is moving in the opposite direction of a technical indicator, such as an oscillator, or is moving contrary to other data. Divergence warns that the current price trend may be weakening, and in some cases may lead to the price changing direction.
There are 4 main types of divergence, which are split into 2 categories;
regular divergences and hidden divergences. Regular divergences indicate possible trend reversals, and hidden divergences indicate possible trend continuation.
Regular bullish divergence: An indication of a potential trend reversal, from the current downtrend, to an uptrend.
Regular bearish divergence: An indication of a potential trend reversal, from the current uptrend, to a downtrend.
Hidden bullish divergence: An indication of a potential uptrend continuation.
Hidden bearish divergence: An indication of a potential downtrend continuation.
How do traders use divergences in their trading?
A divergence is considered a leading indicator in technical analysis , meaning it has the ability to indicate a potential price move in the short term future.
Hidden bullish and hidden bearish divergences, which indicate a potential continuation of the current trend are sometimes considered a good place for traders to begin, since trend continuation occurs more frequently than reversals, or trend changes.
When trading regular bullish divergences and regular bearish divergences, which are indications of a trend reversal, the probability of it doing so may increase when these occur at a strong support or resistance level . A common mistake new traders make is to get into a regular divergence trade too early, assuming it will immediately reverse, but these can continue to form for some time before the trend eventually changes, by using forms of support or resistance as an added confluence, such as when price reaches a moving average, the success rate when trading these patterns may increase.
Typically, traders will manually draw lines across the swing highs and swing lows of both the price chart and the oscillator to see whether they appear to present a divergence, this indicator will draw them for you, quickly and clearly, and can notify you when they occur.
Setting alerts.
With this indicator you can set alerts to notify you when any/all of the above types of divergences occur, on any chart timeframe you choose.
Configurable pivot period.
You can adjust the default pivot lookback values to suit your prefered trading style and timeframe. If you like to trade a shorter time frame, lowering the default lookback values will make the divergences drawn more sensitive to short term price action.
Disclaimer: This script includes code from the stock UO and MFI by Tradingview as well as the Divergence for Many Indicators v4 by LonesomeTheBlue.
Modified QQE-ZigZag [Non Repaint During Candle Building]V V V V V V V Please Read V V V V V V V
I ask Peter and he is fine, that im published this script
Tell me if you have some ideas or criticism about that sricpt
>>>>>>>>>> This is a modified Version of Peter_O's Momentum Based ZigZag <<<<<<<<<<<
This is only a test, and i want to share it with the community
It works like other ZigZags
Because Peters_O's original Version is only non repaint on closed historical Data ,
during a Candle building process it can still repaint (signal appears / 21 seconds later signal disapears / 42 seconds later signal appears again in the same candle / etc.),
but that isnt important for backtesting, its only important for realtime PivotPoints during a candle.
My goal for this zigzag was to make it absolute non repaint neither during a candle building process (current candle),
so once the signal is shown there is no chance that it disapers and shown a few seconds later again on that same candle, it can only show up one time per candle an thats it,
and that makes it absolute non repaint in all time frames.
Credits to:
==> Thanks to @glaz , for bringing the QQE to Tradingview <3
==> Thanks to @Peter_O , for sharing his idea to use the QQE as base for a Zigzag
and for sharing his MTF RSI with the Community <3
Changes:
- I changed the MTF RSI a little bit, you can choose between two version
- I changed the QQE a little bit, its now using the MTF RSI , and its using High and Low values as Source to make it absolute non repaint during a candle is building
- I added a little Divergence Calculation beween price and the MTF RSI that is used for the ZigZag
Colors :
- Green for HH / HL Continuation
- Red for LL / LH Continuation
- Yellow for Positive Divergence
- Purple for Negative Divergence
Important:
It is not possible to backtest this script correctly with historical Data, its only possible in Realtime,
because the QQE is using crossunders with RSILowSource and the QQE Line to find the Tops and,
because the QQE is using crossovers with RSIHighSource and the QQE Line to find the Bottoms,
and that means it is not possible to find the correct Time/Moment when that crossovers / crossunders happens in historical Data
=============> So please be sure you understand the Calculation and Backtest it in Realtime when you want to use it,
because i didn't published this script for real trading
=============> Im not a financial advisor and youre using this script at your own risk
=============> Please do your own research
Edward PriceAction
This is an updated version of my previous script, I have added a few extra Patterns and some patterns specs have chnaged over those specified by "Price Action Battle Station by theforexguy".
Because this script has diverted from the original specification of "theforexguy", I have decided to release it as a new version. Improvements have been made to some of the pattern finding calculations, for example Hammer and Shooting Stars are now special Pin Bars, they now must have preceding and succeeding confirm bars, so they do not occur very often.
NOTE: All the identification of PA candles is disabled by default.
Changes made in Version 2.0 :
Added Forex Morning and Evening Stars (the centre small candle is not a specific color).
Abbreviated text names for less cluttered look.
Change minimum/maximum bar sizes to be a % of current ATR, rather than pips, this makes relative sizing independent on Time Frame, and make the script work better with non-currency assets like stocks and commodities .
Change definition of Hammer and shooting Star so the the previous candle is part of a trend and is followed by a confirm candle.
Added some precendence test to reduce multiple action labels.
版本注释: After some feedback from fellow traders I have made the following changes:
Definition for Outside Bar now does not require the previous bar to be opposite Colour (this the same as Inside Bars), but added a requirement for minimum size ratio compared to previous Bar (set to 1.1 by default). If you require previous Bar to be opposite colour, you could use Engulfing candles with Outside Bar option enabled.
Added Maximum size ratio requirement for Inside Bars (set to 0.9 by default).
版本注释: Minor Update.
Added OverSized candle Pattern, the pattern is labelled when candle is some ratio (default 5) bigger than current ATR of chart time frame.
Added Option to Change ATR Length.
版本注释: Patch
Correct Polarity of Oversize Bar labelling.
中文解释：
价格行为交易，此指标能够显示出来K线所代表的意思，比如PB就是PINBAR的意思 就是倒锤头线，反转概率大于延续概率。
OB就是吞没的意思，不管是阴吞没还是阳吞没 我们根据PA入场就行，标准是回撤50%入场。而ODJI就是黄昏星，启明星的意思。
这个指标在添加的时候是空白的，需要人工去点设置，把需要使用的功能打上钩钩确认。这样就能够在图表上面显示出来了。
如果不希望显示彩色K线同样也可以设置哈！
数值和样式都 可以设置，在不懂指标的前提下推荐使用默认设置。只负责打勾勾就行。确认后就能够看到图表上面显示的指标了。
FX Meter ScriptA while ago, we wrote* about the usefulness of using a currency strength meter and how you can build one from scratch.
See here: www.globalprime.com.au
Now we've taken this little project to the next level by visually spotting, via color signals in a dashboard and alerts, when a potential new trend might be developing in a currency pair.
*It's critical that you first read that article before you jump into reading this one or else you could get easily lost.
The script gives a trigger every time two currencies show diverging flows via opposing moving average slopes.
The signals originate from a first chart where currency indexes can be found, calculated through a formula, in various thin lines. Then a moving average to each currency index is applied so that it can smooth out the lines (what I call Micro moving averages – thicker lines -) and is usually a 4-5 period MA, with the key input to pay attention being the slope. One can perform their own tests on what works best for their particular trading style. The smaller the period in the moving average, the more responsive to changes in biases but the downside is that you will get a greater number of false moves. In the windows below the 1st chart, the stochRSI is calculated for each currency index (these values originate from the currency index and not from the applied MA). By default, a 25-period is applied to both RSI and Stoch length.
A 2nd chart that looks at the same logic is also accounted for to build this script, but instead of checking the micro trend, it applies a 25MA to the currency index, so it looks at what I call the slope of the macro trend. In this case, by default, a 125-period is applied to both RSI and Stoch length.
We had in mind to transition from just eye-balling and monitoring these charts manually to build a script via Tradingview that makes calculations real time (whenever the change in the moving average slope first occurs, and not when the bar/line closes), so that one can decide whether or not its a signal worth trading as part of a new trend emerging. Note, this is not so much a signal-triggering indicator but rather a tool to constantly be on the lookout monitoring what currencies might start to develop trends.
The actual script consists of a dashboard with different colored rectangles being triggered depending on the quality of the signal.
We will be happy to discuss it further with anyone who is interested in exploiting all the benefits that it can offer.
The way you add the script into your Tradingview chart is by first copy everything in the txt file. Then go to Pine editor (bottom middle-left) in your tradingview chart, delete everything there, then Paste the script. Then click Add to Chart (top right of the pine editor).
Note, you should add via the Anchored Text function the following list of pairs below, in this alphabetic order, on the right-hand side of the chart, as demonstrated above:
AUDCAD
AUDJPY
AUDNZD
AUDUSD
CADJPY
EURAUD
EURJPY
EURCAD
EURNZD
EURGBP
EURUSD
GBPAUD
GBPCAD
GBPJPY
GBPNZD
GBPUSD
NZDCAD
NZDJPY
NZDUSD
USDCAD
USDJPY
There are only 2 rules for the script to trigger a signal (see below). However, as I will elaborate further down, there are up to 6 different colors we can grade a signal
RULE 1 -> 2 moving averages, which are a calculation applied to a currency index as shown in the micro trend above, exhibit slopes in the opposite direction.
RULE 2 -> The Stoch RSI cannot be in overbought conditions if the slope of the moving average points higher or in oversold if the slope points lower.
Note 1: Even if the chart is a 60m timeframe by default (can be changed to any timeframe(, one gets the signal the moment the change of slope is identified, which means the indicator monitors changes in price tick by tick, and not on a candle close, otherwise one would get the trigger too late.
As an example of the highest-graded signal triggering (in green), a few hours ago we were given the visual cue that GBPCAD was experiencing a change of behavior. If we crosscheck the time the green-colored trigger was given with the actual GBPCAD chart, this is what we can observe. The pair is 30p higher since the trigger.
HOW TO SETUP ALERTS
One can easily setup a notification window each time the above rules are met, for example, if the EUR MA slope changes to bullish, and the AUD MA slope changes to bearish, and none of the 2 currency index values corresponding to these 2 moving averages (EUR and AUD) show a stoch RSI in overbought (above 80) in the case of the EUR, or oversold (below 20) in the case of the AUD, then the notification pop up would show a customized line: Long EURAUD
Note 1: Recording the slope of the macro moving average, which is usually a 25period MA applied to the currency index, is not included as part of the rules to trigger a signal, but it is taken into account to grade the quality of each signal.
Note 2: I recommend each signal to be triggered once or if you prefer, simply monitor the chart visually on the change of colors via the dashboard. The calculation resets and can appear again the moment that the slope changes to the opposite direction, so it’s a very dynamic indicator that will alert you the second a pair of currencies starts trending.
Note 3: When the signal is triggered, the indicator draws a colored rectangle. Each signal notification should be colored based on the following logic below.
LOGIC TO QUALIFY SIGNALS
-> Any long micro position with Macro MA in full agreement (ie/ Long EURAUD, Macro EUR up, Macro AUD down) is highlighted with green color
-> Any long micro position with macro moving averages in partial agreement (for example Long EURAUD, Macro EUR up AUD up) is highlighted with blue color
-> Any long micro position with macro moving averages in full disagreement (for example Long EURAUD, Macro EUR down AUD up) is highlighted with magenta color
-> Any short micro position with macro moving averages in full agreement (for example Short EURAUD, Macro EUR down AUD up) is highlighted with red color
-> Any short micro position with macro moving averages in partial agreement (for example Short EURAUD, Macro EUR up AUD up) is highlighted with orange color
-> Any short micro position with macro moving averages in full disagreement (for example Short EURAUD, Macro EUR up AUD down) is highlighted with purple color
PARAMETERS IN THE SCRIPT SETTINGS
Overbought/oversold: One can modify the stoch RSI level from which the indicator considers the value to be in overbought or oversold conditions. As a rule of thumb, consider 20/30 for oversold and 70/80 for oversold.
Slopes micro/macro MAs: One can edit the slope of the micro MA period (rule of thumb 4-5) and the macro MA (by default 25).
Value StochRSI: The default inputs are K 3, D 3, RSI Length 25, Stoch Length 25 for the micro and 125 period for the macro.
Change colors: One can edit the assigned colors in the signals dashboard.
Timeframe applied: The indicator has the flexibility to be applied to any timeframe, not just the 60m by default. Simply change the timeframe temporality.
CURRENCY INDEXES FORMULAS
It is the responsibility of the user to keep the values of the indexes updated. Find a recent sample below, as per values in early April. What this means is that at least once a week, in order to not let the values outdated, you should update the script with the latest valuations in the denominator.
NZD INDEX -> FX_IDC:NZDAUD/0.96+FX:NZDJPY/75.81+FX:NZDUSD/0.68+FX_IDC:NZDEUR/0.6+FX_IDC:NZDGBP/0.52+FX:NZDCHF/0.69+FX:NZDCAD/0.9
EUR INDEX -> FX:EURUSD/1.13+FX:EURJPY/125.5+FX:EURGBP/0.87+FX:EURCHF/1.135+FX:EURCAD/1.49+FX:EURNZD/1.655+FX:EURAUD/1.59
JPY INDEX -> 1/(FX:USDJPY/110.5+FX:EURJPY/125.5+FX:AUDJPY/79+FX:NZDJPY/75.5+FX:GBPJPY/144.5+FX:CHFJPY/110.5+FX:CADJPY/84)
USD INDEX -> FX_IDC:USDEUR/0.88+FX:USDJPY/110.5+FX_IDC:USDGBP/0.77+FX:USDCHF+FX:USDCAD/1.315+FX_IDC:USDNZD/1.46+FX_IDC:USDAUD/1.4
CAD INDEX-> FX_IDC:CADAUD/1.07+FX_IDC:CADNZD/1.11+FX:CADJPY/84.27+FX_IDC:CADUSD/0.76+FX_IDC:CADEUR/0.67+FX:CADCHF/0.76+FX_IDC:CADGBP/0.58
GBP INDEX -> FX:GBPAUD/1.83+FX:GBPNZD/1.91+FX:GBPJPY/144.5+FX_IDC:GBPEUR/1.15+FX:GBPCHF/1.31+FX:GBPUSD/1.31+FX:GBPCAD/1.71
Remember, I have provided a manual on how to build a currency strength meter. That’s what you will need to do first if you want to obtain the actual currency indexes other than just the indicator, which is just the visual cue to get you alerted when the slopes turn.
Once you’ve created your indexes via tradingview, you then apply a moving average to each index. Then apply the stochrsi 25 period to each index. For the macro trend, I make the same calculations, but the period of the MA is 25 instead of 4, while the stoch rsi is 125 periods vs 25 periods.
FINAL NOTE
This is a tool that should be interpreted as visual assistance, via the dashboard, to get that first cue when opposing micro slopes via the FX meter occur. However, you still need to check the technical context of the pair (levels marked, proj reached, etc.) but that first cue is a major time saver to constantly spot what's trending in FX. The permutations u can play with, as part of this script, are significant. You can tweak the timeframes you use, the periods of the moving averages, etc. I find the micro and macro trend combos when either a green or red signals is triggered the most reliable, with positions to be exploited via 15m and hourly under the right technical context.
By Traders For TradersThis is an updated version of my previous script, I have added a few extra Patterns and some patterns specs have chnaged over those specified by "Price Action Battle Station by theforexguy".
Because this script has diverted from the original specification of "theforexguy", I have decided to release it as a new version. Improvements have been made to some of the pattern finding calculations, for example Hammer and Shooting Stars are now special Pin Bars, they now must have preceding and succeeding confirm bars, so they do not occur very often.
NOTE: All the identification of PA candles is disabled by default.
Changes made in Version 2.0 :
Added Forex Morning and Evening Stars (the centre small candle is not a specific color).
Abbreviated text names for less cluttered look.
Change minimum/maximum bar sizes to be a % of current ATR, rather than pips, this makes relative sizing independent on Time Frame, and make the script work better with non-currency assets like stocks and commodities .
Change definition of Hammer and shooting Star so the the previous candle is part of a trend and is followed by a confirm candle.
Added some precendence test to reduce multiple action labels.
版本注释: After some feedback from fellow traders I have made the following changes:
Definition for Outside Bar now does not require the previous bar to be opposite Colour (this the same as Inside Bars), but added a requirement for minimum size ratio compared to previous Bar (set to 1.1 by default). If you require previous Bar to be opposite colour, you could use Engulfing candles with Outside Bar option enabled.
Added Maximum size ratio requirement for Inside Bars (set to 0.9 by default).
版本注释: Minor Update.
Added OverSized candle Pattern, the pattern is labelled when candle is some ratio (default 5) bigger than current ATR of chart time frame.
Added Option to Change ATR Length.
版本注释: Patch
Correct Polarity of Oversize Bar labelling.
Correlative Move IndicatorEDIT: When loading this indicator it uses a default symbol for comparison of SPX. On Tradingview SPX is a Daily price (unless you buy real time) so you will see "Loading ..." and never see data. Move out to a daily time frame -or- switch the symbol to something available intraday. /EDIT
Correlates the movement of the price you are graphing to the price of someting else that you pick (default is SPX, see EDIT above)
Comments in code explain what I did. If correlations are too tight for CC to show anything but a flat line try this.
Please comment / improve.
=====================
// A simple indicator that looks complex (impress your friends)
// Provides rate of change in the propensity of something
// to move in correlation with whatever you are graphing.
// Inputs are:
// "Compared symbol" - standard Trading View symbol input. You can input ratios & formulas if you like; Defaults to SPX
// "Invert?" - by default the indicator shows the item you have charted as numerator and the "Compared symbol"
// the denominator. So if you graphed "UVXY" and open this indicator with default compared symbol "SPX" then
// the base relationship is UVXY/SPX. Click the box if you want SPX/UVXY (for example) instead.
// "Fast EMA Period" - the period for the fast EMA (white line). default = 7
// "Slow EMA Period" - the period for the slow EMA (black line). default = 27. Important: the bakground color of the indicator
// changes based on this EMA hitting threshold values below.
// "+ threshold" - > threshold for green background. default = 1.0
// "- threshold" - < threshold for red background. default = 0.99
// "BBand Period" - number of periods back for BBand (1 std deviation) calculation. default = 15
// Does not measure correlation per se - it measures change in that correlation.
// If two things do not correlate well in the first place then you will see a lot of noise
// and I wish you much luck in interpreting it.
// However, if two things do correlate well (like VXX and VIX) then this will help you detect
// circumstances where that correlation is unstable. Such instability can signal change in direction.
// I developed it to track real time changes in contango / backwardation in various VIX futures instruments which I trade.
// Tip - always try invert - sometimes the correlation changes become clearer. That can be because the threshold bias
// towards "+" with the defaults here, so think about what the "logical" relationship is and adjust the thresholds, or invert,
// or do both. Just remember - the indicator is below the item you are charting, so the default "source"/"compared"
// relationship is intuitive as you look at the screen. Volatility traders, however, will find "invert" useful with default
// thresholds signalling "green" for contango and "red" for backwardation.
// Short and long ema trends added for smoothing and trend change indications.
// Background color changes to green when correlation changing "positively" and red when "negatively" and white when near 1.
// Think of the value "1" as representing the base "1 to 1" correlation between two things. That doesn't mean same price -
// it means same rate and direction in change in price.
// 1 std deviation is used to build a basic Bollinger Band in blue. The number of periods for calculating that is an input.
// You may find a change in correlation signal outside a Bollinger Band signals a direction change. TV alerts can be
// set for such events.
Adaptive Z-Score Oscillator [QuantAlgo]🟢 Overview
The Adaptive Z-Score Oscillator transforms price action into statistical significance measurements by calculating how many standard deviations the current price deviates from its moving average baseline, then dynamically adjusting threshold levels based on historical distribution patterns. Unlike traditional oscillators that rely on fixed overbought/oversold levels, this indicator employs percentile-based adaptive thresholds that automatically calibrate to changing market volatility regimes and statistical characteristics. By offering both adaptive and fixed threshold modes alongside multiple moving average types and customizable smoothing, the indicator provides traders and investors with a robust framework for identifying extreme price deviations, mean reversion opportunities, and underlying trend conditions through the visualization of price behavior within a statistical distribution context.
🟢 How It Works
The indicator begins by establishing a dynamic baseline using a user-selected moving average type applied to closing prices over the specified length period, then calculates the standard deviation to measure price dispersion:
basis = ma(close, length, maType)
stdev = ta.stdev(close, length)
The core Z-Score calculation quantifies how many standard deviations the current price sits above or below the moving average basis, creating a normalized oscillator that facilitates cross-asset and cross-timeframe comparisons:
zScore = stdev != 0 ? (close - basis) / stdev : 0
smoothedZ = ma(zScore, smooth, maType)
The adaptive threshold mechanism employs percentile calculations over a historical lookback period to determine statistically significant extreme zones. Rather than using fixed levels like ±2.0, the indicator identifies where a specified percentage of historical Z-Score readings have fallen, automatically adjusting to market regime changes:
upperThreshold = adaptive ? ta.percentile_linear_interpolation(smoothedZ, percentilePeriod, upperPercentile) : fixedUpper
lowerThreshold = adaptive ? ta.percentile_linear_interpolation(smoothedZ, percentilePeriod, lowerPercentile) : fixedLower
The visualization architecture creates a four-tier coloring system that distinguishes between extreme conditions (beyond the adaptive thresholds) and moderate conditions (between the midpoint and threshold levels), providing visual gradation of statistical significance through opacity variations and immediate recognition of distribution extremes.
🟢 How to Use This Indicator
▶ Overbought and Oversold Identification:
The indicator identifies potential overbought conditions when the smoothed Z-Score crosses above the upper threshold, indicating that price has deviated to a statistically extreme level above its mean. Conversely, oversold conditions emerge when the Z-Score crosses below the lower threshold, signaling statistically significant downward deviation. In adaptive mode (default), these thresholds automatically adjust to the asset's historical behavior, i.e., during high volatility periods, the thresholds expand to accommodate wider price swings, while during low volatility regimes, they contract to capture smaller deviations as significant. This dynamic calibration reduce false signals that plague fixed-level oscillators when market character shifts between volatile and ranging conditions.
▶ Mean Reversion Trading Applications:
The Z-Score framework excels at identifying mean reversion opportunities by highlighting when price has stretched too far from its statistical equilibrium. When the oscillator reaches extreme bearish levels (below the lower threshold with deep red coloring), it suggests price has become statistically oversold and may snap back toward the mean, presenting potential long entry opportunities for mean reversion traders. Symmetrically, extreme bullish readings (above the upper threshold with bright green coloring) indicate potential short opportunities or long exit points as price becomes statistically overbought. The moderate zones (lighter colors between midpoint and threshold) serve as early warning areas where traders can prepare for potential reversals, while exits from extreme zones (crossing back inside the thresholds) often provide confirmation that mean reversion is underway.
▶ Trend and Distribution Analysis:
Beyond discrete overbought/oversold signals, the histogram's color pattern and shape reveal the underlying trend structure and distribution characteristics. Sustained periods where the Z-Score oscillates primarily in positive territory (green bars) indicate a bullish trend where price consistently trades above its moving average baseline, even if not reaching extreme levels. Conversely, predominant negative readings (red bars) suggest bearish trend conditions. The distribution shape itself provides insight into market behavior, e.g., a narrow, centered distribution clustering near zero indicates tight ranging conditions with price respecting the mean, while a wide distribution with frequent extreme readings reveals volatile trending or choppy conditions. Asymmetric distributions skewed heavily toward one side demonstrate persistent directional bias, whereas balanced distributions suggest equilibrium between bulls and bears.
▶ Built-in Alerts:
Seven alert conditions enable automated monitoring of statistical extremes and trend transitions. Enter Overbought and Enter Oversold alerts trigger when the Z-Score crosses into extreme zones, providing early warnings of potential reversal setups. Exit Overbought and Exit Oversold alerts signal when price begins reverting from extremes, offering confirmation that mean reversion has initiated. Zero Cross Up and Zero Cross Down alerts identify transitions through the neutral line, indicating shifts between above-mean and below-mean price action that can signal trend changes. The Extreme Zone Entry alert fires on any extreme threshold penetration regardless of direction, allowing unified monitoring of both overbought and oversold opportunities.
▶ Color Customization:
Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and aesthetic preferences, ensuring optimal contrast and readability across trading platforms. The bar transparency control (0-90%) allows fine-tuning of visual prominence, with minimal transparency creating bold, attention-grabbing bars for primary analysis, while higher transparency values produce subtle background context when using the oscillator alongside other indicators. The extreme and moderate zone coloring system uses automatic opacity variation to create instant visual hierarchy, with darkest colors highlight the most statistically significant deviations demanding immediate attention, while lighter shades mark developing conditions that warrant monitoring but may not yet justify action. Optional candle coloring extends the Z-Score color scheme directly to the price candles on the main chart, enabling traders to instantly recognize statistical extremes and trend conditions without needing to reference the oscillator panel, creating a unified visual experience where both price action and statistical analysis share the same color language.
