Uptrick: MultiTrend Squeeze System**Uptrick: MultiTrend Squeeze System Indicator: The Ultimate Trading Tool for Precision and Versatility 📈🔥**
### Introduction
The MultiTrend Squeeze System is a powerful, multi-faceted trading indicator designed to provide traders with precise buy and sell signals by combining the strengths of multiple technical analysis tools. This script isn't just an indicator; it's a comprehensive trading system that merges the power of SuperTrend, RSI, Volume Filtering, and Squeeze Momentum to give you an unparalleled edge in the market. Whether you're a day trader looking for short-term opportunities or a swing trader aiming to catch longer-term trends, this indicator is tailored to meet your needs.
### Key Features and Unique Aspects
1. **SuperTrend with Dynamic Adjustments 📊**
- **Adaptive SuperTrend Calculation:** The SuperTrend is a popular trend-following indicator that adjusts dynamically based on market conditions. It uses the Average True Range (ATR) to calculate upper and lower bands, which shift according to market volatility. This script takes it further by combining it with the RSI and Volume filtering to provide more accurate signals.
- **Direction Sensitivity:** The SuperTrend here is not static. It adjusts based on the direction of the previous SuperTrend value, ensuring that the indicator remains relevant even in choppy markets.
2. **RSI Integration for Overbought/Oversold Conditions 💹**
- **RSI Calculation:** The Relative Strength Index (RSI) is incorporated to identify overbought and oversold conditions, adding an extra layer of precision. This helps in filtering out false signals and ensuring that trades are taken only in optimal conditions.
- **Customizable RSI Settings:** The RSI settings are fully customizable, allowing traders to adjust the RSI length and the overbought/oversold levels according to their trading style and market.
3. **Volume Filtering for Enhanced Signal Confirmation 📉**
- **Volume Multiplier:** This unique feature integrates volume analysis, ensuring that signals are only generated when there is sufficient market participation. The Volume Multiplier can be adjusted to filter out weak signals that occur during low-volume periods.
- **Optional Volume Filtering:** Traders have the flexibility to turn the volume filter on or off, depending on their preference or market conditions. This makes the indicator versatile, allowing it to be used across different asset classes and market conditions.
4. **Squeeze Momentum Indicator (SMI) for Market Pressure Analysis 💥**
- **Squeeze Detection:** The Squeeze Momentum Indicator detects periods of market compression and expansion. This script goes beyond the traditional Bollinger Bands and Keltner Channels by incorporating true range calculations, offering a more nuanced view of market momentum.
- **Customizable Squeeze Settings:** The lengths and multipliers for both Bollinger Bands and Keltner Channels are customizable, giving traders the flexibility to fine-tune the indicator based on their specific needs.
5. **Visual and Aesthetic Customization 🎨**
- **Color-Coding for Clarity:** The indicator is color-coded to make it easy to interpret signals. Bullish trends are marked with a vibrant green color, while bearish trends are highlighted in red. Neutral or unconfirmed signals are displayed in softer tones to reduce noise.
- **Histogram Visualization:** The primary trend direction and strength are displayed as a histogram, making it easy to visualize the market's momentum at a glance. The height and color of the bars provide immediate feedback on the strength and direction of the trend.
6. **Alerts for Real-Time Trading 🚨**
- **Custom Alerts:** The script is equipped with custom alerts that notify traders when a buy or sell signal is generated. These alerts can be configured to send notifications through various channels, including email, SMS, or directly to the trading platform.
- **Immediate Reaction:** The alerts are triggered based on the confluence of SuperTrend, RSI, and Volume signals, ensuring that traders are notified only when the most robust trading opportunities arise.
7. **Comprehensive Input Customization ⚙️**
- **SuperTrend Settings:** Adjust the ATR length and factor to control the sensitivity of the SuperTrend. This allows you to adapt the indicator to different market conditions, whether you're trading a volatile cryptocurrency or a more stable stock.
- **RSI Settings:** Customize the RSI length and thresholds for overbought and oversold conditions, enabling you to tailor the indicator to your specific trading strategy.
- **Volume Settings:** The Volume Multiplier and the option to toggle the volume filter provide an additional layer of customization, allowing you to fine-tune the indicator based on market liquidity and participation.
- **Squeeze Momentum Settings:** The lengths and multipliers for Bollinger Bands and Keltner Channels can be adjusted to detect different levels of market compression, providing flexibility for both short-term and long-term traders.
### How It Works: A Deep Dive Into the Mechanics 🛠️
1. **SuperTrend Calculation:**
- The SuperTrend is calculated using the ATR, which measures market volatility. The indicator creates upper and lower bands around the price, adjusting these bands based on the current level of market volatility. The direction of the trend is determined by the position of the price relative to these bands.
- The script enhances the standard SuperTrend by ensuring that the bands do not flip-flop too quickly, reducing the chances of false signals in a choppy market. The direction is confirmed by checking the position of the close relative to the previous band, making the trend detection more reliable.
2. **RSI Integration:**
- The RSI is calculated over a customizable length and compared to user-defined overbought and oversold levels. When the RSI crosses below the oversold level, and the SuperTrend indicates a bullish trend, a buy signal is generated. Conversely, when the RSI crosses above the overbought level, and the SuperTrend indicates a bearish trend, a sell signal is triggered.
- The combination of RSI with SuperTrend ensures that trades are only taken when there is a strong confluence of signals, reducing the chances of entering trades during weak or indecisive market phases.
3. **Volume Filtering:**
- The script calculates the average volume over a 20-period simple moving average. The volume filter ensures that buy and sell signals are only valid when the current volume exceeds a multiple of this average, which can be adjusted by the user. This feature helps filter out weak signals that might occur during low-volume periods, such as just before a major news event or during after-hours trading.
- The volume filter is particularly useful in markets where volume spikes are common, as it ensures that signals are only generated when there is significant market interest in the direction of the trend.
4. **Squeeze Momentum:**
- The Squeeze Momentum Indicator (SMI) adds a layer of market pressure analysis. The script calculates Bollinger Bands and Keltner Channels, detecting when the market is in a "squeeze" — a period of low volatility that typically precedes a significant price move.
- When the Bollinger Bands are inside the Keltner Channels, the market is in a squeeze (compression phase). This is often a precursor to a breakout or breakdown. The script colors the histogram bars black during this phase, indicating a potential for a strong move. Once the squeeze is released, the bars are colored according to the direction of the SuperTrend, signaling a potential entry point.
5. **Integration and Signal Generation:**
- The script brings together the SuperTrend, RSI, Volume, and Squeeze Momentum to generate highly accurate buy and sell signals. A buy signal is triggered when the SuperTrend is bullish, the RSI indicates oversold conditions, and the volume filter confirms strong market participation. Similarly, a sell signal is generated when the SuperTrend is bearish, the RSI indicates overbought conditions, and the volume filter is met.
- The combination of these elements ensures that the signals are robust, reducing the likelihood of entering trades during weak or indecisive market conditions.
### Practical Applications: How to Use the MultiTrend Squeeze System 📅
1. **Day Trading:**
- For day traders, this indicator provides quick and reliable signals that can be used to enter and exit trades multiple times within a day. The volume filter ensures that you are trading during the most liquid times of the day, increasing the chances of successful trades. The Squeeze Momentum aspect helps you catch breakouts or breakdowns, which are common in intraday trading.
2. **Swing Trading:**
- Swing traders can use the MultiTrend Squeeze System to identify longer-term trends. By adjusting the ATR length and factor, you can make the SuperTrend more sensitive to catch longer-term moves. The RSI and Squeeze Momentum aspects help you time your entries and exits, ensuring that you get in early on a trend and exit before it reverses.
3. **Scalping:**
- For scalpers, the quick signals provided by this system, especially in combination with the volume filter, make it easier to take small profits repeatedly. The histogram bars give you a clear visual cue of the market's momentum, making it easier to scalp effectively.
4. **Position Trading:**
- Even position traders can benefit from this indicator by using it to confirm long-term trends. By adjusting the settings to less sensitive parameters, you can ensure that you are only entering trades when a strong trend is confirmed. The Squeeze Momentum indicator will help you stay in the trade during periods of consolidation, waiting for the next big move.
### Conclusion: Why the MultiTrend Squeeze System is a Game-Changer 🚀
The MultiTrend Squeeze System is not just another trading indicator; it’s a comprehensive trading strategy encapsulated within a single script. By combining the power
of SuperTrend, RSI, Volume Filtering, and Squeeze Momentum, this indicator provides a robust and versatile tool that can be adapted to various trading styles and market conditions.
**Why is it Unique?**
- **Multi-Dimensional Analysis:** Unlike many other indicators that rely on a single data point or calculation, this script incorporates multiple layers of analysis, ensuring that signals are based on a confluence of factors, which increases their reliability.
- **Customizability:** The vast range of input settings allows traders to tailor the indicator to their specific needs, whether they are trading forex, stocks, cryptocurrencies, or commodities.
- **Visual Clarity:** The color-coded bars, labels, and signals make it easy to interpret the market conditions at a glance, reducing the time needed to make trading decisions.
Whether you are a novice trader or an experienced market participant, the MultiTrend Squeeze System offers a powerful toolset to enhance your trading strategy, reduce risk, and maximize your potential returns. With its combination of trend analysis, momentum detection, and volume filtering, this indicator is designed to help you trade with confidence and precision in any market condition.
M-oscillator
Uptrick: Adaptive Cloud Oscillator (ACO)### **Uptrick: Adaptive Cloud Oscillator (ACO)**
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### Introduction
The **Uptrick: Adaptive Cloud Oscillator (ACO)** is an advanced technical analysis tool designed to empower traders with precise trend detection and visual clarity in dynamic market conditions. By seamlessly integrating adaptive trend analysis, volatility filtering, and cloud-based support and resistance levels, the ACO provides traders with the actionable insights needed to navigate complex markets with confidence.
This indicator is highly customizable, allowing traders to tailor its functionality to their specific trading style and preferences. Whether you're a trend follower, swing trader, or looking to identify key support and resistance zones, the **Uptrick: ACO** is an indispensable tool that can adapt to a variety of market conditions.
### Indicator Purpose and Functionality
#### 1. **Adaptive Trend Detection**
At the heart of the **Uptrick: ACO** lies its adaptive trend detection algorithm. Unlike traditional moving averages that may lag in volatile markets or react too slowly to rapid changes, this adaptive method uses a smoothing technique that dynamically adjusts based on market conditions. By doing so, it provides a more responsive trend line that captures meaningful price movements while filtering out minor fluctuations.
- **How It Works:** The trend line is calculated using an adaptive smoothing factor, making it responsive to recent price actions while maintaining a level of stability that prevents whipsaw signals. This ensures that traders are always in tune with the prevailing market trend, whether bullish, bearish, or neutral.
#### 2. **Dynamic Cloud Support and Resistance**
The **Uptrick: ACO** features a dynamic "cloud" that serves as a key element in its analysis. This cloud is constructed using a moving average combined with the Average True Range (ATR), which adjusts based on the market’s volatility. The cloud provides dynamic support and resistance levels, essential for identifying potential reversal zones or confirming trend continuations.
- **Cloud Displacement:** The cloud is displaced forward by a user-defined number of bars, offering a predictive view of where future support and resistance levels may lie. This forward-looking feature helps traders anticipate potential price movements, making the ACO a powerful tool for planning trades ahead of time.
#### 3. **Versatile Visualization Options**
The **Uptrick: ACO** is designed with flexibility in mind, allowing users to choose between two distinct display modes:
- **Buy/Sell Signals:** In this mode, the indicator generates clear buy and sell signals based on crossovers of the trend line and the cloud boundaries. These signals are visualized directly on the chart with up and down labels, making it easy for traders to identify potential entry and exit points.
- **Cloud Fill Only:** For traders who prefer a cleaner chart, this mode removes the buy/sell signals and instead focuses on coloring the area between the upper and lower cloud boundaries. The color of the cloud fill changes based on the trend direction, providing a visual representation of the market's momentum.
- **Optional EMA Line:** An Exponential Moving Average (EMA) line can be optionally displayed on the chart. The EMA serves as an additional trend filter, helping traders further refine their entries and exits. The length, color, and thickness of the EMA are fully customizable to fit individual trading strategies.
### Practical Applications
#### 1. **Trend Following and Reversals**
The **Uptrick: ACO** excels in identifying and following trends. By analyzing the relationship between the trend line and the cloud, traders can determine the strength and direction of the current market trend. The cloud’s dynamic nature means it can adapt to both trending and ranging markets, providing consistent insights regardless of market conditions.
- **Example:** If the trend line crosses above the upper cloud boundary, it signals a potential buy opportunity. Conversely, a cross below the lower cloud boundary suggests a sell opportunity. Traders can use these signals to enter trades aligned with the prevailing trend.
#### 2. **Support and Resistance Identification**
The forward-displaced cloud acts as a predictive support and resistance zone. Traders can use these zones to set stop-loss levels, determine take-profit targets, or identify potential reversal points.
- **Example:** When the price approaches the upper cloud boundary from below, the boundary may act as resistance, indicating a potential reversal or pullback. If the price breaks through this level, it may signal a continuation of the bullish trend.
#### 3. **Volatility-Based Analysis**
By incorporating ATR into its calculations, the **Uptrick: ACO** provides a built-in mechanism to adapt to varying levels of market volatility. This makes it particularly useful in markets prone to sudden spikes in volatility, such as during major economic announcements or geopolitical events.
- **Example:** In a high-volatility environment, the cloud widens, allowing for greater price fluctuations within the trend. Traders can use this information to adjust their risk management strategies, such as widening stop-loss levels during volatile periods to avoid being stopped out prematurely.
### Customization and Flexibility
The **Uptrick: ACO** is designed to be highly customizable, ensuring it can meet the needs of traders with different strategies and preferences. Key customization options include:
- **Cloud and Trend Settings:** Traders can adjust the length of the cloud, the smoothing factor for the trend line, and the displacement of the cloud to optimize the indicator for their specific market and timeframe.
- **Display Modes:** With a simple dropdown selection, traders can choose whether to display buy/sell signals or focus solely on the cloud fill, providing flexibility in how the indicator is visualized.
- **Color and Style Customization:** The colors for bullish and bearish trends, cloud fill, buy/sell signals, and the EMA line can all be customized, allowing traders to integrate the **Uptrick: ACO** seamlessly into their existing chart setups.
### Conclusion
The **Uptrick: Adaptive Cloud Oscillator (ACO)** is more than just a trend indicator—it's a comprehensive market analysis tool that provides traders with a deep understanding of market dynamics. Its combination of adaptive trend analysis, dynamic support and resistance levels, and versatile visualization options makes it an essential tool for traders looking to gain an edge in any market environment.
Whether you're a seasoned trader or just starting, the **Uptrick: ACO** offers the insights and flexibility needed to make informed trading decisions. By helping you identify trends, anticipate reversals, and adapt to changing market conditions, the **Uptrick: ACO** can significantly enhance your trading strategy and improve your overall trading performance.
Bitcoin Power Law Oscillator [InvestorUnknown]The Bitcoin Power Law Oscillator is a specialized tool designed for long-term mean-reversion analysis of Bitcoin's price relative to a theoretical midline derived from the Bitcoin Power Law model (made by capriole_charles). This oscillator helps investors identify whether Bitcoin is currently overbought, oversold, or near its fair value according to this mathematical model.
Key Features:
Power Law Model Integration: The oscillator is based on the midline of the Bitcoin Power Law, which is calculated using regression coefficients (A and B) applied to the logarithm of the number of days since Bitcoin’s inception. This midline represents a theoretical fair value for Bitcoin over time.
Midline Distance Calculation: The distance between Bitcoin’s current price and the Power Law midline is computed as a percentage, indicating how far above or below the price is from this theoretical value.
float a = input.float (-16.98212206, 'Regression Coef. A', group = "Power Law Settings")
float b = input.float (5.83430649, 'Regression Coef. B', group = "Power Law Settings")
normalization_start_date = timestamp(2011,1,1)
calculation_start_date = time == timestamp(2010, 7, 19, 0, 0) // First BLX Bitcoin Date
int days_since = request.security('BNC:BLX', 'D', ta.barssince(calculation_start_date))
bar() =>
= request.security('BNC:BLX', 'D', bar())
int offset = 564 // days between 2009/1/1 and "calculation_start_date"
int days = days_since + offset
float e = a + b * math.log10(days)
float y = math.pow(10, e)
float midline_distance = math.round((y / btc_close - 1.0) * 100)
Oscillator Normalization: The raw distance is converted into a normalized oscillator, which fluctuates between -1 and 1. This normalization adjusts the oscillator to account for historical extremes, making it easier to compare current conditions with past market behavior.
float oscillator = -midline_distance
var float min = na
var float max = na
if (oscillator > max or na(max)) and time >= normalization_start_date
max := oscillator
if (min > oscillator or na(min)) and time >= normalization_start_date
min := oscillator
rescale(float value, float min, float max) =>
(2 * (value - min) / (max - min)) - 1
normalized_oscillator = rescale(oscillator, min, max)
Overbought/Oversold Identification: The oscillator provides a clear visual representation, where values near 1 suggest Bitcoin is overbought, and values near -1 indicate it is oversold. This can help identify potential reversal points or areas of significant market imbalance.
Optional Moving Average: Users can overlay a moving average (either SMA or EMA) on the oscillator to smooth out short-term fluctuations and focus on longer-term trends. This is particularly useful for confirming trend reversals or persistent overbought/oversold conditions.
This indicator is particularly useful for long-term Bitcoin investors who wish to gauge the market's mean-reversion tendencies based on a well-established theoretical model. By focusing on the Power Law’s midline, users can gain insights into whether Bitcoin’s current price deviates significantly from what historical trends would suggest as a fair value.
Trading Channel Index (TCI)Overview:
The Trading Channel Index (TCI) is a technical analysis tool designed to identify cyclical trends in financial markets by smoothing out price movements and reducing volatility compared to traditional oscillators, like the Commodity Channel Index (CCI). The TCI helps traders pinpoint overbought and oversold conditions, as well as gauge the strength and direction of market trends.
Calculation:
The TCI is calculated through a multi-step process:
Typical Price (Xt): The typical price is computed as the average of the high, low, and close prices for each bar:
Xt = (High + Low + Close) / 3
Exponential Average (Et): This step smooths the typical price over a specified number of bars (TCI Channel Length) using an exponential moving average (EMA). The smoothing factor alpha is derived from the channel length:
Et = alpha * Xt + (1 - alpha) * Et
Where alpha = 2 / (TCI Channel Length + 1).
Average Deviation (Dt): The average deviation measures how much the typical price deviates from the exponential average over time. This is also smoothed using the EMA:
Dt = alpha * abs(Et - Xt) + (1 - alpha) * Dt
Channel Index (CI): The Channel Index is calculated by normalizing the difference between the typical price and the exponential average by the average deviation:
CI = (Xt - Et) / (0.15 * Dt)
Trading Channel Index (TCI): Finally, the TCI is generated by applying additional smoothing to the Channel Index using another EMA over the specified number of bars (TCI Average Length). The smoothing factor beta is derived from the average length:
TCI = beta * CI + (1 - beta) * TCI
Indicator Variables:
TCI Channel Length:
- Description: This variable sets the number of historical bars used to calculate the Channel Index (CI). A shorter length results in a more sensitive CI that responds quickly to price changes, while a longer length produces a smoother and less volatile CI.
- Default Value: 21
TCI Average Length:
-Description: This variable determines the number of bars over which the Channel Index (CI) is smoothed to produce the TCI. A shorter length makes the TCI more responsive to recent price changes, whereas a longer length further smooths the TCI, reducing its sensitivity to short-term fluctuations.
-Default Value: 10
Usage:
Overbought and Oversold Conditions: The TCI often uses levels such as +100 and -100 to identify potential reversal points. When the TCI crosses above +100, it might indicate an overbought condition, signaling a potential sell. Conversely, when it crosses below -100, it could indicate an oversold condition, suggesting a potential buy.
Trend Identification: Sustained values above 0 typically indicate a bullish trend, while values below 0 suggest a bearish trend. The TCI's smoothness helps traders stay in trends longer by reducing the impact of short-term market noise.
Conclusion:
The Trading Channel Index (TCI) is a versatile and powerful tool for traders who wish to capture cyclical price movements with a reduced level of noise. By adjusting the TCI Channel Length and TCI Average Length, traders can tailor the indicator to suit different market conditions, making it applicable across various timeframes and asset classes.
Commitment of Trader %RThis script is a TradingView Pine Script that creates a custom indicator to analyze Commitment of Traders (COT) data. It leverages the TradingView COT library to fetch data related to futures and options markets, processes this data, and then applies the Williams %R indicator to the COT data to assist in trading decisions. Here’s a detailed explanation of its components and functionality:
Importing and Configuration:
The script imports the COT library from TradingView and sets up tooltips to explain different input options to the user.
It allows the user to choose the mode for fetching COT data, which can be based on the root of the symbol, base currency, or quote currency.
Users can also input a specific CFTC code directly, instead of relying on automatic code generation.
Inputs and Parameters:
The script provides inputs to select the type of data (futures, options, or both), the type of COT data to display (long positions, short positions, etc.), and thresholds for the Williams %R indicator.
It also allows setting the period for the Williams %R calculation.
Data Request and Processing:
The dataRequest function fetches COT data for large traders, small traders, and commercial hedgers.
The script calculates the Williams %R for each type of trader, which measures overbought and oversold conditions.
Visualization:
The script uses background colors to highlight when the Williams %R crosses the specified thresholds for commercial hedgers.
It plots the COT data and Williams %R on the chart, with different colors representing large traders, small traders, and commercial hedgers.
Horizontal lines are drawn to indicate the upper and lower thresholds.
Display Information:
A table is displayed on the chart’s lower left corner showing the current COT data and CFTC code used.
Use of COT Report in Futures Trading
The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides insights into the positions held by different types of traders in the futures markets. This information is valuable for traders as it shows:
Market Sentiment: By analyzing the positions of commercial traders (often considered to be more informed), non-commercial traders (speculative traders), and small traders, traders can gauge market sentiment and potential future movements.
Contrarian Indicators: Large shifts in positions, especially when non-commercial traders hold extreme positions, can signal potential reversals or trends.
Research on COT Data and Price Movements
Several academic studies have examined the relationship between COT data and price movements in financial markets. Here are a few key works:
"The Predictive Power of the Commitment of Traders Report" by Jacob J. (2009):
This paper explores how changes in the positions of different types of traders in the COT report can predict future price movements in futures markets.
Citation: Jacob, J. (2009). The Predictive Power of the Commitment of Traders Report. Journal of Futures Markets.
"A New Look at the Commitment of Traders Report" by Mitchell, C. (2010):
Mitchell analyzes the efficacy of using COT data as a trading signal and its impact on trading strategies.
Citation: Mitchell, C. (2010). A New Look at the Commitment of Traders Report. Financial Analysts Journal.
"Market Timing Using the Commitment of Traders Report" by Kirkpatrick, C., & Dahlquist, J. (2011):
This study investigates the use of COT data for market timing and the effectiveness of various trading strategies based on the report.
Citation: Kirkpatrick, C., & Dahlquist, J. (2011). Market Timing Using the Commitment of Traders Report. Technical Analysis of Stocks & Commodities.
These studies provide insights into how COT data can be utilized for forecasting and trading decisions, reinforcing the utility of incorporating such data into trading strategies.
Breadth Thrust Indicator by Zweig (NYSE Data with Volume)The Breadth Thrust Indicator, based on Zweig's methodology, is used to gauge the strength of market breadth and potential bullish signals. This indicator evaluates the breadth of the market by analyzing the ratio of advancing to declining stocks and their associated volumes.
Usage:
Smoothing Length: Adjusts the smoothing period for the combined ratio of breadth and volume.
Low Threshold: Defines the threshold below which the smoothed combined ratio should fall to consider a bullish signal.
High Threshold: Sets the upper threshold that the smoothed combined ratio must exceed to confirm a bullish Breadth Thrust signal.
Signal Interpretation:
Bullish Signal: A background color change to green indicates that the Breadth Thrust condition has been met. This occurs when the smoothed combined ratio crosses above the high threshold after being below the low threshold. This signal suggests strong market breadth and potential bullish momentum.
By using this indicator, traders can identify periods of strong market participation and potential upward price movement, helping them make informed trading decisions.
Approximate Spectral Entropy-Based Market Momentum (SEMM)Overview
The Approximate Spectral Entropy-Based Market Momentum (SEMM) indicator combines the concepts of spectral entropy and traditional momentum to provide traders with insights into both the strength and the complexity of market movements. By measuring the randomness or predictability of price changes, SEMM helps traders understand whether the market is in a trending or consolidating state and how strong that trend or consolidation might be.
Key Features
Entropy Measurement: Calculates the approximate spectral entropy of price movements to quantify market randomness.
Momentum Analysis: Integrates entropy with rate-of-change (ROC) to highlight periods of strong or weak momentum.
Dynamic Market Insight: Provides a dual perspective on market behavior—both the trend strength and the underlying complexity.
Customizable Parameters: Adjustable window length for entropy calculation, allowing for fine-tuning to suit different market conditions.
Concepts Underlying the Calculations
The indicator utilizes Shannon entropy, a concept from information theory, to approximate the spectral entropy of price returns. Spectral entropy traditionally involves a Fourier Transform to analyze the frequency components of a signal, but due to Pine Script limitations, this indicator uses a simplified approach. It calculates log returns over a rolling window, normalizes them, and then computes the Shannon entropy. This entropy value represents the level of disorder or complexity in the market, which is then multiplied by traditional momentum measures like the rate of change (ROC).
How It Works
Price Returns Calculation: The indicator first computes the log returns of price data over a specified window length.
Entropy Calculation: These log returns are normalized and used to calculate the Shannon entropy, representing market complexity.
Momentum Integration: The calculated entropy is then multiplied by the rate of change (ROC) of prices to generate the SEMM value.
Signal Generation: High SEMM values indicate strong momentum with higher randomness, while low SEMM values indicate lower momentum with more predictable trends.
How Traders Can Use It
Trend Identification: Use SEMM to identify strong trends or potential trend reversals. Low entropy values can indicate a trending market, whereas high entropy suggests choppy or consolidating conditions.
Market State Analysis: Combine SEMM with other indicators or chart patterns to confirm the market's state—whether it's trending, ranging, or transitioning between states.
Risk Management: Consider high SEMM values as a signal to be cautious, as they suggest increased market unpredictability.
Example Usage Instructions
Add the Indicator: Apply the "Approximate Spectral Entropy-Based Market Momentum (SEMM)" indicator to your chart.
Adjust Parameters: Modify the length parameter to suit your trading timeframe. Shorter lengths are more responsive, while longer lengths smooth out the signal.
Analyze the Output: Observe the blue line for entropy and the red line for SEMM. Look for divergences or confirmations with price action to guide your trades.
Combine with Other Tools: Use SEMM alongside moving averages, support/resistance levels, or other indicators to build a comprehensive trading strategy.
RSI - ARIEIVhe RSI MAPPING - ARIEIV is a powerful technical indicator based on the Relative Strength Index (RSI) combined with moving averages and divergence detection. This indicator is designed to provide a clear view of overbought and oversold conditions, as well as identifying potential reversals and signals for market entries and exits.
Key Features:
Customizable RSI:
The indicator offers flexibility in adjusting the RSI length and data source (closing price, open price, etc.).
The overbought and oversold lines can be customized, allowing the RSI to signal critical market zones according to the trader’s strategy.
RSI-Based Moving Averages (MA):
Users can enable a moving average based on the RSI with support for multiple types such as SMA, EMA, WMA, VWMA, and SMMA (RMA).
For those who prefer Bollinger Bands, there’s an option to use the moving average with standard deviation to detect market volatility.
Divergence Detection:
Detects both regular and hidden divergences (bullish and bearish) between price and RSI, which can indicate potential market reversals.
These divergences can be customized with specific colors for easy identification on the chart, allowing traders to quickly spot significant market shifts.
Zone Mapping:
The script maps zones of buying and selling strength, filling the areas between the overbought and oversold levels with specific colors, highlighting when the market is in extreme conditions.
Strength Tables:
At the end of each session, a table appears on the right side of the chart, displaying the "Buying Strength" and "Selling Strength" based on calculated RSI levels. This allows for quick analysis of the dominant pressure in the market.
Flexible Settings:
Many customization options are available, from adjusting the number of decimal places to the choice of colors and the ability to toggle elements on or off within the chart.
RSI Slope Filtered Signals [UAlgo]The "RSI Slope Filtered Signals " is a technical analysis tool designed to enhance the accuracy of RSI (Relative Strength Index) signals by incorporating slope analysis. This indicator not only considers the RSI value but also analyzes the slope of the RSI over a specified number of bars, providing a more refined signal that accounts for the momentum and trend strength. By utilizing both positive and negative slope arrays, the indicator dynamically adjusts its thresholds, ensuring that signals are responsive to changing market conditions. This tool is particularly useful for traders looking to identify overbought and oversold conditions with a higher degree of precision, filtering out noise and providing clear visual cues for potential market reversals.
🔶 Key Features
Dynamic Slope Analysis: Measures the slope of RSI over a customizable number of bars, offering insights into the momentum and trend direction.
Adaptive Thresholds: Uses historical slope data to calculate dynamic thresholds, adjusting signal sensitivity based on market conditions.
Normalized Slope Calculation: Normalizes the slope values to provide a consistent measure across different market conditions, making the indicator more versatile.
Clear Signal Visualization: The indicator plots both positive and negative normalized slopes with color gradients, visually representing the strength of the trend.
Overbought and Oversold Signals: Plots overbought and oversold signals directly on the chart when the calculated value reaches the user-specified threshold, helping traders identify potential reversal points.
Customizable Settings: Allows users to adjust the RSI length, slope measurement bars, and lookback periods, providing flexibility to tailor the indicator to different trading strategies.
🔶 Interpreting the Indicator
The "RSI Slope Filtered Signals " indicator is designed to be easy to interpret. Here's how you can use it:
Normalized Slope: The indicator plots the normalized slope of the RSI, with values above zero indicating positive momentum and values below zero indicating negative momentum. A higher positive slope suggests a strong upward trend, while a deeper negative slope indicates a strong downward trend.
Reversal Signals: The indicator plots several horizontal lines at different thresholds (+3, +2, +1, 0, -1, -2, -3). These levels are used to gauge the strength of the momentum based on the normalized slope. For example, a normalized slope crossing above the +2 threshold may indicate a strong bullish trend, while crossing below the -2 threshold may suggest a strong bearish trend. These thresholds help in understanding the intensity of the current trend and provide context for interpreting the indicator's signals.
This indicator generates overbought and oversold signals not solely based on the RSI entering extreme levels (above 70 for overbought and below 30 for oversold), but also by considering the behavior of the normalized slope relative to specific thresholds. Specifically, the Overbought Signal (🔽) is triggered when the RSI is above 70 and the normalized slope from the previous bar is greater than or equal to the upper threshold, with the current slope being lower than the previous slope, indicating a potential bearish reversal as momentum may be slowing down.
Similarly, the Oversold Signal (🔼) is generated when the RSI is below 30 and the normalized slope from the previous bar is less than or equal to the lower threshold, with the current slope being higher than the previous slope, signaling a potential bullish reversal as the downward momentum may be weakening.
Area Plots: The indicator also plots the positive and negative slopes as filled areas, providing a quick visual cue for the strength and direction of the trend. Green areas represent positive slopes (upward momentum), while red areas represent negative slopes (downward momentum).
By combining these elements, the "RSI Slope Filtered Signals " provides a comprehensive view of the market's momentum, helping traders make more informed decisions by filtering out false signals and focusing on the significant trends.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Average of CBO and CBO divergence histogramShort Description:
This indicator combines a Custom Bias Oscillator (CBO) with its Divergence Histogram and computes their average for use to assess the market's bias based on candlestick analysis, from the aforementioned CBO indicator.
Full Description:
Overview:
This indicator integrates two powerful analytical tools into a single script: a Custom Bias Oscillator (CBO) and its Divergence Histogram. This indicator provides traders with a comprehensive view of market bias and divergence between price movements and volume, enhanced by an optional signal line derived from the combined average of these metrics.
Key Features:
Custom Bias Oscillator (CBO):
The CBO is calculated based on the body and wick biases of candlesticks, normalized by the Average True Range (ATR) to account for market volatility.
The CBO is scaled by the divergence between the Rate of Change (ROC) of volume and the ROC of the adjusted bias, ensuring it reflects potential reversals or continuations in the market.
Divergence Histogram:
The Divergence Histogram is derived from the difference between the CBO and its signal line.
This difference is normalized and plotted to provide visual cues for potential divergences, which may indicate trend exhaustion or the beginning of a new trend.
Combined Average with Signal Line:
The indicator calculates the average of the CBO and the normalized divergence, creating a combined signal that offers a more rounded perspective on market conditions.
A signal line, generated by smoothing the combined average, is plotted to help traders identify potential buy or sell signals based on crossovers.
Customization:
The indicator includes customizable parameters for the periods of the oscillator, signal line, ATR, ROC, and the combined signal line, allowing traders to tailor the indicator to different market conditions and timeframes.
How to Use:
Buy Signal: Consider a long position when the combined average crosses above the signal line, indicating potential bullish momentum.
Sell Signal: Consider a short position when the combined average crosses below the signal line, indicating potential bearish momentum.
Divergence Analysis: Use the Divergence Histogram to identify areas where price movements may be diverging from volume, signaling potential reversals or corrections.
Disclaimer:
This indicator is designed for educational and informational purposes only. It is not financial advice. Always perform your own analysis before making any investment decisions. Past performance is not indicative of future results.
Normalized Willspread IndicatorNot sure to call it as willspread or not, because i take this idea from Larry William's original willspread indicator and did some modifications which found out to be more effective in my opinion, which is by subtracting 21 and 3 ma, this indicator is found on Trade_Stocks_and_Commodities_With_the_Insiders page155. Feel free to find out.
Here's what I modified, instead of using the subtraction between two ma, I use one ma only, I find more accurate in spotting oversold and overbought value. This indicator is useful for metals. It basically compares the value between two assets, let's say u are watching gold, u can select compare it to dxy, us30Y or gold, let's say u choose to compare to dxy, and the indicator shows the the index is overvalued which is above 80 levels, then it is suggesting that gold is overvalued, the same logic apply to undervalued as well which is 20 levels. This is not a entry or exit tool but as additional confluence, u can use any entry method u want like supply and demand and use this indicator to validate your idea, not sure whether it works on forex or not, so far i think it works well on metals.
The bar colour corresponding to the index when it is overbought or oversold. U can switch off it if you dont need it. Do note that this is a repainting indicator, so u must refer to previous week close.
EMA Crossover Buy/Sell IndicatorScript Overview
This script is a trading indicator designed to identify potential buy and sell signals based on the crossover of two Exponential Moving Averages (EMAs):
Indicator Title and Setup:
The script is named "EMA Crossover Buy/Sell Indicator" and is plotted directly on the price chart.
EMAs Calculation:
It calculates two EMAs: a 20-period EMA and a 50-period EMA. These are used to analyze the market trends over different time frames.
Plotting EMAs:
The 20-period EMA is shown on the chart in blue.
The 50-period EMA is shown in orange.
These lines help visualize the current trend and potential points of interest where the moving averages intersect.
Generating Signals:
A buy signal is triggered when the 20-period EMA crosses above the 50-period EMA.
A sell signal is triggered when the 20-period EMA crosses below the 50-period EMA.
These signals suggest potential buying or selling opportunities based on the crossover of the EMAs.
Displaying Signals:
Buy signals are marked with green labels below the bars on the chart.
Sell signals are marked with red labels above the bars on the chart.
This visual representation helps traders quickly identify potential trading opportunities.
Alerts:
Alerts are set up to notify the trader when a buy or sell signal occurs.
The alert messages specify whether the signal is a buying opportunity or a selling opportunity based on the EMA crossovers.
Altcoin Total Average Divergence (YavuzAkbay)The "Average Price and Divergence" indicator is a strong tool built exclusively for cryptocurrency traders who understand the significance of comparing altcoins to Bitcoin (BTC). While traditional research frequently focusses on the value of cryptocurrencies against fiat currencies such as the US dollar, this indicator switches the focus to the value of altcoins against Bitcoin itself, allowing you to detect potential market opportunities and divergences.
The indicator allows you to compare the price of an altcoin to Bitcoin (e.g., ETHBTC, SOLBTC), which is critical for determining how well an altcoin performs against the main cryptocurrency. This is especially important for investors who expect Bitcoin's price will continue to rise logarithmically and want to ensure that their altcoin holdings retain or expand in market capitalisation compared to Bitcoin.
The indicator computes the average price of the chosen cryptocurrency relative to Bitcoin over the viewable portion of the chart. This average acts as a benchmark, indicating the normal value around which the altcoin's price moves.
The primary objective of this indicator is to calculate and plot the divergence, which is the difference between the altcoin's current price relative to Bitcoin and its average value. This divergence can reveal probable overbought or oversold conditions, allowing traders to make better decisions about entry and exit points.
The divergence is represented as a histogram, with bars representing the magnitude of the difference between the current and average prices. Positive values indicate that the altcoin is trading above its average value in comparison to Bitcoin, whereas negative values indicate that it is trading below its average.
The indicator automatically adjusts to the chart's visible range, ensuring that the average price and divergence are always calculated using the most relevant data. This makes the indicator extremely sensitive to changes in the chart view and market conditions.
How to Use:
A significant positive divergence may imply that the cryptocurrency is overbought in comparison to Bitcoin and is headed for a correction. A significant negative divergence, on the other hand, may indicate that the cryptocurrency has been oversold and is cheap in comparison to Bitcoin.
Tracking how an altcoin's price deviates from its average relative to Bitcoin can provide insights about the market's opinion towards that altcoin. Persistent positive divergence may suggest high market confidence, whilst constant negative divergence may imply a lack of interest or eroding fundamentals.
Use divergence data to better time your trades, either by entering when a cryptocurrency is discounted in comparison to its average (negative divergence) or departing when it is overpriced (positive divergence). This allows you to capture value as the price returns to its mean.
Ideal For:
Cryptocurrency Traders who want to understand how altcoins are performing relative to Bitcoin rather than just against fiat currencies.
Long-term Investors looking to ensure their altcoin investments are maintaining or growing their value relative to Bitcoin.
Market Analysts interested in identifying potential reversals or continuations in altcoin prices based on divergence from their average value relative to Bitcoin.
Price Oscillator TR### Summary: How to Use the Price Oscillator with EMA Indicator
The **Price Oscillator with EMA** is a custom technical analysis tool designed to help traders identify potential buying and selling opportunities based on price momentum. Here's how to use it:
1. **Understanding the Oscillator**:
- The oscillator is calculated by normalizing the current price relative to the highest high and lowest low over a specified lookback period. It fluctuates between -70 and +70.
- When the oscillator is near +70, the price is close to the recent highs, indicating potential overbought conditions. Conversely, when it’s near -100, the price is close to recent lows, indicating potential oversold conditions.
2. **Exponential Moving Average (EMA)**:
- The indicator includes an EMA of the oscillator to smooth out price fluctuations and provide a clearer signal.
- The EMA helps to filter out noise and confirm trends.
3. **Trading Signals**:
- **Bullish Signal**: A potential buying opportunity is signaled when the oscillator crosses above its EMA. This suggests increasing upward momentum.
- **Bearish Signal**: A potential selling opportunity is signaled when the oscillator crosses below its EMA. This indicates increasing downward momentum.
4. **Visual Aids**:
- The indicator includes horizontal lines at +70, 0, and -70 to help you quickly assess overbought, neutral, and oversold conditions.
- The blue line represents the oscillator, while the orange line represents the EMA of the oscillator.
### How to Use:
- **Set your parameters**: Adjust the lookback period and EMA length to fit your trading strategy and time frame.
- **Watch for Crossovers**: Monitor when the oscillator crosses the EMA. A crossover from below to above suggests a buy, while a crossunder from above to below suggests a sell.
- **Confirm with Other Indicators**: For more reliable signals, consider using this indicator alongside other technical tools like volume analysis, trend lines, or support/resistance levels.
This indicator is ideal for traders looking to capture momentum-based trades in various market conditions.
MACD Trail | Flux Charts💎 GENERAL OVERVIEW
Introducing our new MACD Trail indicator! Moving average convergence/divergence (MACD) is a well-known indicator among traders. It's a trend-following indicator that uses the relationship between two exponential moving averages (EMAs). This indicator aims to use MACD to generate a trail that follows the current price of the ticker, which can act as a support / resistance zone. More info about the process in the "How Does It Work" section.
Features of the new MACD Trail Indicator :
A Trail Generated Using MACD Calculation
Customizable Algorithm
Customizable Styling
📌 HOW DOES IT WORK ?
First of all, this indicator calculates the current MACD of the ticker using the user's input as settings. Let X = MACD Length setting ;
MACD ~= X Period EMA - (X * 2) Period EMA
Then, two MACD Trails are generated, one being bullish and other being bearish. Let ATR = 30 period ATR (Average True Range)
Bullish MACD Trail = Current Price + MACD - (ATR * 1.75)
Bearish MACD Trail = Current Price + MACD + (ATR * 1.75)
The indicator starts by rendering only the Bullish MACD Trail. Then if it's invalidated (candlestick closes below the trail) it switches to Bearish MACD Trail. The MACD trail switches between bullish & bearish as they get invalidated.
The trail type may give a hint about the current trend of the price action. The trail itself also can act as a support / resistance zone, here is an example :
🚩 UNIQUENESS
While MACD is one of the most used indicators among traders, this indicator aims to add another functionality to it by rendering a trail based on it. This trail may act as a support / resistance zone as described above, and gives a glimpse about the current trend. The indicator also has custom MACD Length and smoothing options, as well as various style options.
⚙️ SETTINGS
1. General Configuration
MACD Length -> This setting adjusts the EMA periods used in MACD calculation. Increasing this setting will make MACD more responseive to longer trends, while decreasing it may help with detection of shorter trends.
Smoothing -> The smoothing of the MACD Trail. Increasing this setting will help smoothen out the MACD Trail line, but it can also make it less responsive to the latest changes.
Moments Functions
This script is a TradingView Pine Script (version 5) for calculating and plotting statistical moments of a financial series. Here's a breakdown of what it does:
Script Overview
Purpose:
The script calculates and visualizes moments such as Mean, Variance, Skewness, and Kurtosis of a price series.
It also provides the option to display log returns and various statistical bands.
Inputs:
Moments Selection: Choose from Mean, Variance, Skewness, or Excess Kurtosis.
Source Settings: Define the lookback period and source data (e.g., closing price or log returns).
Plot Settings: Control visibility and styling of plots, bands, and information panels.
Colors Settings: Customize colors for different plot elements.
Functions:
f_va(): Computes sample variance.
f_sd(): Computes sample standard deviation.
f_skew(): Computes sample skewness.
f_kurt(): Computes sample kurtosis.
seskew(): Calculates the standard error of skewness.
sekurt(): Calculates the standard error of kurtosis.
skewcv(): Computes critical values for skewness.
kurtcv(): Computes critical values for kurtosis.
Outputs:
Plots:
Moment values (Mean, Variance, Skewness, Kurtosis).
Log Returns (if selected).
Standard Deviation Bands (if selected).
Critical Values for Skewness and Kurtosis (if selected).
Information Panel: Displays current statistical values and their significance.
Customization:
Users can customize appearance and behavior of the script through various input options, including colors, line thickness, and background settings.
Key Variables and Constants
Constants:
zscoreS and zscoreL: Z-scores for confidence intervals based on sample size.
skewrv and kurtrv: Reference values for skewness and excess kurtosis.
Sample Functions:
f_va() and f_sd(): Custom functions to calculate sample variance and standard deviation.
f_skew() and f_kurt(): Custom functions to calculate skewness and kurtosis.
Critical Values:
Functions skewcv() and kurtcv() calculate critical values used to assess statistical significance of skewness and kurtosis.
Plotting
Plot Types:
Mean, variance, skewness, and excess kurtosis are plotted based on user selection.
Log returns are plotted if enabled.
Standard deviation bands and critical values are plotted if enabled.
Labels:
Information panel labels display mean, variance/standard deviation, skewness, and kurtosis values along with their significance.
Example Usage
To use this script:
Add it to a TradingView chart.
Adjust inputs to configure which statistical moments to display, the source data, and the appearance of the plots.
Review the plotted data and labels to analyze the statistical properties of the selected price series.
This script is useful for traders and analysts looking to perform advanced statistical analysis on financial data directly within TradingView.
When comparing two stock prices over a period of time, the statistical moments—mean, variance, skewness, and kurtosis—can provide a deep insight into the behavior of the stock prices and their distributions. Here’s what each moment signifies in this context:
1. Mean
Definition: The mean (or average) is the sum of the stock prices over the period divided by the number of data points. It represents the central value of the price series.
Interpretation: When comparing two stocks, the mean tells you the average price level of each stock over the period. A higher mean indicates that, on average, the stock price is higher compared to another stock with a lower mean.
Comparison Insight: If Stock A has a higher mean price than Stock B, it implies that Stock A's prices are generally higher than those of Stock B over the given period.
2. Variance
Definition: Variance measures the dispersion or spread of the stock prices around the mean. It is the average of the squared differences from the mean.
Interpretation: A higher variance indicates that the stock prices fluctuate more widely from the mean, implying greater volatility. Conversely, a lower variance indicates more stable and predictable prices.
Comparison Insight: Comparing the variances of two stocks helps in assessing which stock has more price volatility. If Stock A has a higher variance than Stock B, it means Stock A's prices are more volatile and less predictable compared to Stock B.
3. Skewness
Definition: Skewness measures the asymmetry of the distribution of stock prices around the mean. It can be positive, negative, or zero:
Positive Skewness: The distribution has a long right tail, with more frequent small returns and fewer large positive returns.
Negative Skewness: The distribution has a long left tail, with more frequent small returns and fewer large negative returns.
Zero Skewness: The distribution is symmetric around the mean.
Interpretation: Skewness tells you about the direction of outliers in the stock price distribution. Positive skewness means a higher probability of large positive returns, while negative skewness means a higher probability of large negative returns.
Comparison Insight: By comparing skewness, you can understand the nature of extreme returns for two stocks. For example, if Stock A has positive skewness and Stock B has negative skewness, Stock A might have more frequent large gains, whereas Stock B might have more frequent large losses.
4. Kurtosis
Definition: Kurtosis measures the "tailedness" of the distribution of stock prices. It indicates how much of the distribution is in the tails versus the center. High kurtosis means more outliers (extreme returns), while low kurtosis means fewer outliers.
Interpretation:
High Kurtosis: Indicates a higher likelihood of extreme price movements (both high and low) compared to a normal distribution.
Low Kurtosis: Indicates that extreme price movements are less common.
Comparison Insight: Comparing kurtosis between two stocks shows which stock has more extreme returns. If Stock A has higher kurtosis than Stock B, it means Stock A has more frequent extreme price changes, suggesting more risk or opportunities for large gains or losses.
Summary
Mean: Compares average price levels.
Variance: Compares price volatility.
Skewness: Compares the asymmetry of price movements.
Kurtosis: Compares the likelihood of extreme price changes.
By analyzing these statistical moments, you can gain a comprehensive view of how the two stocks behave relative to each other, which can inform investment decisions based on risk, return expectations, and the nature of price movements.
Gabriel's Relative Unrealized Profit with Dynamic MVRV Histogram
Certainly! Here’s an enhanced description of the Gabriel's Relative Unrealized Profit with Dynamic MVRV Histogram indicator with detailed usage instructions and explanations of why it's effective:
Gabriel's Relative Unrealized Profit with Dynamic MVRV Histogram
Description:
The Gabriel's Relative Unrealized Profit with Dynamic MVRV Histogram is an advanced trading indicator designed to offer in-depth insights into asset profitability and market valuation. By integrating Relative Unrealized Profit (RUP) and the Market Value to Realized Value (MVRV) Ratio, this indicator provides a nuanced view of an asset's performance and potential trading signals.
Key Components:
SMA Length and Volume Indicator:
SMA Length: Defines the period for the Simple Moving Average (SMA) used to calculate the entry price, defaulted to 14 periods. This smoothing technique helps estimate the average historical price at which the asset was acquired.
Volume Indicator: Allows selection between "volume" and "vwap" (Volume-Weighted Average Price) for calculating entry volume. The choice impacts the calculation of entry volume, either based on standard trading volume or a weighted average price.
Realized Price Calculation:
Computes the average price over a specified period (default of 30 periods) to establish the realized price. This serves as a benchmark for evaluating the cost basis of the asset.
MVRV Calculation:
Current Price: The most recent closing price of the asset, representing its market value.
Total Cost: Calculated as the product of the entry price and entry volume, reflecting the total investment made.
Unrealized Profit: The difference between the current price and the entry price, multiplied by entry volume, indicating profit or loss that has yet to be realized.
Relative Unrealized Profit: Expressed as a percentage of the total cost, showing how much profit or loss exists relative to the initial investment.
Market Value and Realized Value: Market Value is the current price multiplied by entry volume, while Realized Value is the realized price multiplied by entry volume. The MVRV Ratio is obtained by dividing Market Value by Realized Value.
Normalization:
Normalizes both Relative Unrealized Profit and MVRV Ratio to a standardized range of -100 to 100. This involves calculating the minimum and maximum values over a 100-period window to ensure comparability and relevance.
Histogram Calculation:
The histogram is derived from the difference between the normalized Relative Unrealized Profit and the normalized MVRV Ratio. It visually represents the disparity between the two metrics, highlighting potential trading signals.
Plotting and Alerts:
Plots:
Normalized Relative Unrealized Profit (Blue Line): Plotted in blue, this line shows the scaled measure of unrealized profit. Positive values indicate potential gains, while negative values suggest potential losses.
Normalized MVRV Ratio (Red Line): Plotted in red, this line represents the scaled MVRV Ratio. Higher values suggest that the asset’s market value significantly exceeds its realized value, indicating potential overvaluation, while lower values suggest potential undervaluation.
Histogram (Green Bars): Plotted in green, this histogram displays the difference between the normalized Relative Unrealized Profit and the normalized MVRV Ratio. Positive bars indicate that the asset’s profitability is exceeding its market valuation, while negative bars suggest the opposite.
Alerts:
High Histogram Alert: Activated when the histogram value exceeds 50. This condition signals a strong positive divergence, indicating that the asset's profitability is outperforming its market valuation. It may suggest a buying opportunity or indicate that the asset is undervalued relative to its potential profitability.
Low Histogram Alert: Triggered when the histogram value falls below -50. This condition signals a strong negative divergence, indicating that the asset's profitability is lagging behind its market valuation. It may suggest a selling opportunity or indicate that the asset is overvalued relative to its profitability.
How to Use the Indicator:
Setup: Customize the SMA Length, Volume Indicator, and Realized Price Length based on your trading strategy and asset volatility. These parameters allow you to tailor the indicator to different market conditions and asset types.
Interpretation:
Blue Line (Normalized Relative Unrealized Profit): Monitor this line to gauge the profitability of holding the asset. Significant positive values suggest that the asset is currently in a profitable position relative to its purchase price.
Red Line (Normalized MVRV Ratio): Use this line to assess whether the asset is trading at a premium or discount relative to its cost basis. Higher values may indicate overvaluation, while lower values suggest undervaluation.
Green Bars (Histogram): Observe the histogram for deviations between RUP and MVRV Ratio. Large positive bars indicate that the asset's profitability is strong relative to its valuation, signaling potential buying opportunities. Large negative bars suggest that the asset's profitability is weak relative to its valuation, signaling potential selling opportunities.
Trading Strategy:
Bullish Conditions: When the histogram shows large positive values, it suggests that the asset’s profitability is strong compared to its valuation. Consider this as a potential buying signal, especially if the histogram remains consistently positive.
Bearish Conditions: When the histogram displays large negative values, it indicates that the asset’s profitability is weak compared to its valuation. This may signal a potential selling opportunity or caution, particularly if the histogram remains consistently negative.
Why This Indicator is Effective:
Integrated Metrics: Combining Relative Unrealized Profit and MVRV Ratio provides a comprehensive view of asset performance. This integration allows traders to evaluate both profitability and market valuation in one cohesive tool.
TICK Price Label Colors[Salty]The ticker symbol for the NYSE CUMULATIVE Tick Index is TICK. The Tick Index is a short-term indicator that shows the number of stocks trading up minus the number of stocks trading down. Traders can use this ratio to make quick trading decisions based on market movement. For example, a positive tick index can indicate market optimism, while readings of +1,000 and -1,000 can indicate overbought or oversold conditions.
This script is used to color code the price label of the Symbol values zero or above in Green(default), and values below zero in red(default). For a dynamic symbol like the TICK this tells me the market is bullish when Green or Bearish when Red. I was previously using the baseline style with a Base level of 50 to accomplish this view of the symbol, but it was always difficult to maintain the zero level at the zero TICK value. This indicator is always able to color code the price label properly. Also, it has the benefit of setting the timeframe to 1 second(default) that is maintained even when the chart timeframe is changed.
Update: Added the ability to show the TICK Symbol to support viewing multiple TICK tickers at once as shown.
25-Day Momentum IndexDescription:
The 25-Day Momentum Index (25D MI) is a technical indicator designed to measure the strength and direction of price movements over a 25-day period. Inspired by classic momentum analysis, this indicator helps traders identify trends and potential reversal points in the market.
How It Works:
Momentum Calculation: The 25D MI calculates momentum as the difference between the current closing price and the closing price 25 days ago. This difference provides insights into the market's recent strength or weakness.
Plotting: The indicator plots the Momentum Index as a blue line, showing the raw momentum values. A zero line is also plotted in gray to serve as a reference point for positive and negative momentum.
Highlighting Zones:
Positive Momentum: When the Momentum Index is above zero, it is plotted in green, highlighting positive momentum phases.
Negative Momentum: When the Momentum Index is below zero, it is plotted in red, highlighting negative momentum phases.
Usage:
A rising curve means an increase in upward momentum - if it is above the zero line. A rising curve below the zero line signifies a decrease in downward momentum. By the same token, a falling curve means an increase in downward momentum below the zero line, a decrease in upward momentum above the zero line.
This indicator is ideal for traders looking to complement their strategy with a visual tool that captures the essence of market momentum over a significant period. Use it to enhance your technical analysis and refine your trading decisions.
Ultimate Bands [BigBeluga]Ultimate Bands
The Ultimate Bands indicator is an advanced technical analysis tool that combines elements of volatility bands, oscillators, and trend analysis. It provides traders with a comprehensive view of market conditions, including trend direction, momentum, and potential reversal points.
🔵 KEY FEATURES
● Ultimate Bands
Consists of an upper band, lower band, and a smooth middle line
Based on John Ehler's SuperSmoother algorithm for reduced lag
Bands are calculated using Root Mean Square Deviation (RMSD) for adaptive volatility measurement
Helps identify potential support and resistance levels
● Ultimate Oscillator
Derived from the price position relative to the Ultimate Bands
Oscillates between overbought and oversold levels
Provides insights into potential reversals and trend strength
● Trend Signal Line
Based on a Hull Moving Average (HMA) of the Ultimate Oscillator
Helps identify the overall trend direction
Color-coded for easy trend interpretation
● Heatmap Visualization
Displays the current state of the oscillator and trend signal
Provides an intuitive visual representation of market conditions
Shows overbought/oversold status and trend direction at a glance
● Breakout Signals
Optional feature to detect and display breakouts beyond the Ultimate Bands
Helps identify potential trend reversals or continuations
Visualized with arrows on the chart and color-coded candles
🔵 HOW TO USE
● Trend Identification
Use the color and position of the Trend Signal Line to determine the overall market trend
Refer to the heatmap for a quick visual confirmation of trend direction
● Entry Signals
Look for price touches or breaks of the Ultimate Bands for potential entry points
Use oscillator extremes in conjunction with band touches for stronger signals
Consider breakout signals (if enabled) for trend-following entries
● Exit Signals
Use opposite band touches or breakouts as potential exit points
Monitor the oscillator for divergences or extreme readings as exit signals
● Overbought/Oversold Analysis
Use the Ultimate Oscillator and heatmap to identify overbought/oversold conditions
Look for potential reversals when the oscillator reaches extreme levels
● Confirmation
Combine Ultimate Bands, Oscillator, and Trend Signal for stronger trade confirmation
Use the heatmap for quick visual confirmation of market conditions
🔵 CUSTOMIZATION
The Ultimate Bands indicator offers several customization options:
Adjust the main calculation length for bands and oscillator
Modify the number of standard deviations for band calculation
Change the signal line length for trend analysis
Toggle the display of breakout signals and candle coloring
By fine-tuning these settings, traders can adapt the Ultimate Bands indicator to various market conditions and personal trading strategies.
The Ultimate Bands indicator provides a multi-faceted approach to market analysis, combining volatility-based bands, oscillator analysis, and trend identification in one comprehensive tool. Its adaptive nature and visual cues make it suitable for both novice and experienced traders across various timeframes and markets. The integration of multiple analytical elements offers traders a rich set of data points to inform their trading decisions.
Market Structure Oscillator [LuxAlgo]The Market Structure Oscillator indicator analyzes and synthesizes short-term, intermediate-term, and long-term market structure shifts and breaks, visualizing the output as oscillators and graphical representations of real-time market structures on the main price chart.
The oscillator presentation of the detected market structures helps traders visualize trend momentum and strength, identifying potential trend reversals, and providing different perspectives to enhance the analysis of classic market structures.
🔶 USAGE
A market structure shift signals a potential change in market sentiment or direction, while a break of structure indicates a continuation of the current trend. Detecting these events in real-time helps traders recognize both trend changes and continuations. The market structure oscillator translates these concepts visually, offering deeper insights into market momentum and strength. It aids traders in identifying overbought or oversold conditions, potential trend reversals, and confirming trend direction.
Oscillators often generate signals based on crossing certain thresholds or diverging from price movements, providing cues for traders to enter or exit positions.
The weights determine the influence of each period (short-term, intermediate-term, long-term) on the final oscillator value. By changing the weights, traders can emphasize or de-emphasize the importance of each period. Higher weights increase their respective market structure's influence on the oscillator value. For example, if the weight for the short-term period is set to 0, the final value of the oscillator will be calculated using only the intermediate-term and long-term market structures.
The indicator features a Cycle Oscillator component, which uses the market structure oscillator values to generate a histogram and provide further insights into market cycles and potential signals. The Cycle Oscillator aids in timing by allowing traders to more easily see the median length of an oscillation around the average point, helping them identify both favorable prices and favorable moments for trading.
Users can also display detected market structures on the price chart by enabling the corresponding market structure toggle from the "Market Structures on Chart" settings group.
🔶 DETAILS
The script initiates its analysis by detecting swing levels, which form the fundamental basis for its operations. It begins by identifying short-term swing points, automatically detected solely based on market movements without any reliance on user-defined input. Short-Term Swing Highs (STH) are peaks in price surrounded by lower highs on both sides, while Short-Term Swing Lows (STL) are troughs surrounded by higher lows.
To identify intermediate-term and long-term swing points, the script uses previously detected short-term swing points as reference points. It examines these points to determine intermediate-term swings and further analyzes intermediate-term swings to identify long-term swing points. This method ensures a thorough and unbiased evaluation of market dynamics, providing traders with reliable insights into market structures.
Once swing levels are detected, the process continues with the analysis of Market Structure Shifts (MSS) and Breaks of Structure (BoS). A Market Structure Shift, also known as a Change of Character (CHoCH), is a critical event in price action analysis that suggests a potential shift in market sentiment or direction. It occurs when the price reverses from an established trend, indicating that the current trend may be losing momentum and a reversal could be imminent.
On the other hand, a Break of Structure signifies the continuation of the existing market trend. This event occurs when the price decisively moves beyond a previous swing high or low, confirming the strength and persistence of the prevailing trend.
The indicator analyzes price patterns using a pure price action approach and identifies market structures for short-term, intermediate-term, and long-term periods. The collected data is then normalized and combined using specified weights to calculate the final Market Structure Oscillator value.
🔶 SETTINGS
The indicator incorporates user-defined settings, allowing users to tailor it according to their preferences and trading strategies.
🔹 Market Structure Oscillator
Market Structure Oscillator: Toggles the visibility of the market structures oscillator.
Short Term Weight: Defines the weight for the short-term market structure.
Intermediate Term Weight: Defines the weight for the intermediate-term market structure.
Long Term Weight: Defines the weight for the long-term market structure.
Oscillator Smoothing: Determines the smoothing factor for the oscillator.
Gradient Colors: Allows customization of bullish and bearish gradient colors.
Market Structure Oscillator Crosses: Provides signals based on market structure oscillator equilibrium level crosses.
🔹 Cycle Oscillator
Cycle Oscillator - Histogram: Toggles the visibility of the cycle oscillator.
Cycle Signal Length: Defines the length of the cycle signal.
Cycle Oscillator Crosses: Provides signals based on cycle oscillator crosses.
🔹 Market Structures on Chart
Market Structures: Allows plotting of market structures (short, intermediate, and long term) on the chart.
Line, Label, and Color: Options to display lines and labels for different market structures with customizable colors.
🔹 Oscillator Components
Oscillators: Separately plots short-term, intermediate-term, and long-term oscillators. Provides options to display these oscillators with customizable colors.
🔶 RELATED SCRIPTS
Market-Structures-(Intrabar)
Regression Indicator [BigBeluga]Regression Indicator
Indicator Overview:
The Regression Indicator is designed to help traders identify trends and potential reversals in price movements. By calculating a regression line and a normalized regression indicator, it provides clear visual signals for market direction, aiding in making informed trading decisions. The indicator dynamically updates with the latest market data, ensuring timely and relevant signals.
Key Features:
⦾ Calculations
Regression Indicator: Calculates the linear regression coefficients (slope and intercept) and derives the normalized distance close from the regression line.
// @function regression_indicator is a Normalized Ratio of Regression Lines with close
regression_indicator(src, length) =>
sum_x = 0.0
sum_y = 0.0
sum_xy = 0.0
sum_x_sq = 0.0
distance = 0.0
// Calculate Sum
for i = 0 to length - 1 by 1
sum_x += i + 1
sum_y += src
sum_xy += (i + 1) * src
sum_x_sq += math.pow(i + 1, 2)
// Calculate linear regression coefficients
slope = (length * sum_xy - sum_x * sum_y)
/ (length * sum_x_sq - math.pow(sum_x, 2))
intercept = (sum_y - slope * sum_x) / length
// Calculate Regression Indicator
y1 = intercept + slope
distance := (close - y1)
distance_n = ta.sma((distance - ta.sma(distance, length1))
/ ta.stdev(distance, length1), 10)
⦿ Reversion Signals:
Marks potential trend reversal points.
⦿ Trend Identification:
Highlights when the regression indicator crosses above or below the zero line, signaling potential trend changes.
⦿ Color-Coded Candles:
Changes candle colors based on the regression indicator's value.
⦿ Arrow Markers:
Indicate trend directions on the chart.
⦿ User Inputs
Regression Length: Defines the period for calculating the regression line.
Normalization Length: Period used to normalize the regression indicator.
Signal Line: Length for averaging the regression indicator to generate signals.
Main Color: Color used for plotting the regression line and signals.
The Regression Indicator is a powerful tool for analyzing market trends and identifying potential reversal points. With customizable inputs and clear visual aids, it enhances the trader's ability to make data-driven decisions. The dynamic nature of the indicator ensures it remains relevant with up-to-date market information, making it a valuable addition to any trading strategy."
Oscillator Scatterplot Analysis [Trendoscope®]In this indicator, we demonstrate how to plot oscillator behavior of oversold-overbought against price movements in the form of scatterplots and perform analysis. Scatterplots are drawn on a graph containing x and y-axis, where x represent one measure whereas y represents another. We use the library Graph to collect the data and plot it as scatterplot.
Pictorial explanation of components is defined in the chart below.
🎲 This indicator performs following tasks
Calculate and plot oscillator
Identify oversold and overbought areas based on various methods
Measure the price and bar movement from overbought to oversold and vice versa and plot them on the chart.
In our example,
The x-axis represents price movement. The plots found on the right side of the graph has positive price movements, whereas the plots found on the left side of the graph has negative price movements.
The y-axis represents the number of bars it took for reaching overbought to oversold and/or oversold to overbought. Positive bars mean we are measuring oversold to overbought, whereas negative bars are a measure of overbought to oversold.
🎲 Graph is divided into 4 equal quadrants
Quadrant 1 is the top right portion of the graph. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from oversold to overbought
Quadrant 2 is the top left portion of the graph. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from oversold to overbought.
Quadrant 3 is the bottom left portion of the chart. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from overbought to oversold.
Quadrant 4 is the bottom right portion of the chart. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from overbought to oversold.
🎲 Indicator components in Detail
Let's dive deep into the indicator.
🎯 Oscillator Selection
Select the Oscillator and define the overbought oversold conditions through input settings
Indicator - Oscillator base used for performing analysis
Length - Loopback length on which the oscillator is calculated
OB/OS Method - We use Bollinger Bands, Keltener Channel and Donchian channel to calculate dynamic overbought and oversold levels instead of static 80-10. This is also useful as other type of indicators may not be within 0-100 range.
Length and Multiplier are used for the bands for calculating Overbought/Oversold boundaries.
🎯 Define Graph Properties
Select different graph properties from the input settings that will instruct how to display the scatterplot.
Type - this can be either scatterplot or heatmap. Scatterplot will display plots with specific transparency to indicate the data, whereas heatmap will display background with different transparencies.
Plot Color - this is the color in which the scatterplot or heatmap is drawn
Plot Size - applicable mainly for scatterplot. Since the character we use for scatterplot is very tiny, the large at present looks optimal. But, based on the user's screen size, we may need to select different sizes so that it will render properly.
Rows and Columns - Number of rows and columns allocated per quadrant. This means, the total size of the chart is 2X rows and 2X columns. Data sets are divided into buckets based on the number of available rows and columns. Hence, changing this can change the appearance of the overall chart, even though they are representing the same data. Also, please note that tables can have max 10000 cells. If we increase the rows and columns by too much, we may get runtime errors.
Outliers - this is used to exclude the extreme data. 20% outlier means, the chart will ignore bottom 20% and top 20% when defining the chart boundaries. However, the extreme data is still added to the boundaries.
