Momentum Matrix (BTC-COIN)The Momentum Matrix (BTC-COIN) indicator analyzes the momentum relationship between Coinbase stock ( NASDAQ:COIN ) and Bitcoin ( CRYPTOCAP:BTC ). By combining RSI, correlation, and dominance metrics, it identifies bullish and bearish macro trends to align trades with market momentum.
How It Works
Price Inputs: Pulls weekly price data for CRYPTOCAP:BTC and NASDAQ:COIN for macro analysis.
Metrics Calculated:
• RSI Divergence: Measures momentum differences between CRYPTOCAP:BTC and $COIN.
• Price Ratio: Tracks the $COIN/ CRYPTOCAP:BTC relationship relative to its long-term average (SMA).
• Correlation: Analyzes price co-movement between CRYPTOCAP:BTC and $COIN.
• Dominance Impact: Incorporates CRYPTOCAP:BTC dominance for broader crypto trends.
Composite Momentum Score: Combines these metrics into a smoothed macro momentum value.
Thresholds for Trend Detection: Upper and lower thresholds dynamically adapt to market conditions.
Signals and Visualization:
• Buy Signal: Momentum exceeds the upper threshold, indicating bullish trends.
• Sell Signal: Momentum falls below the lower threshold, indicating bearish trends.
• Background Colors: Green (bullish), Red (bearish).
Strengths
Integrates multiple metrics for robust macro analysis.
Dynamic thresholds adapt to market conditions.
Effective for identifying macro momentum shifts.
Limitations
Lag in high volatility due to smoothing.
Less effective in choppy, sideways markets.
Assumes CRYPTOCAP:BTC dominance drives NASDAQ:COIN momentum, which may not always hold true.
Improvements
Multi-Timeframe Analysis: Add daily or monthly data for precision.
Volume Filters: Include volume thresholds for signal validation.
Additional Metrics: Consider MACD or Stochastics for further confirmation.
Complementary Tools
Volume Indicators: OBV or cumulative delta for confirmation.
Trend-Following Systems: Pair with moving averages for timing.
Market Breadth Metrics: Combine with CRYPTOCAP:BTC dominance trends for context.
震盪指標
Gradient Stochastic RSI CyclesThe Gradient Stochastic RSI Cycles indicator combines several key technical concepts into one, providing a unique perspective compared to the traditional RSI (Relative Strength Index) and other indicators typically used . Here's a breakdown of the specific features that make this indicator stand out:
1. Stochastic RSI (StochRSI):
The Stochastic RSI is a momentum indicator that applies the Stochastic Oscillator formula to the RSI. While RSI alone measures overbought and oversold conditions based on the price's relative strength, StochRSI refines this by measuring the position of RSI relative to its own range over a specified period.
This approach helps identify overbought and oversold conditions more dynamically, and it can be a leading indicator compared to the traditional RSI, which may lag in certain market conditions.
2. Key Differences from Traditional RSI:
RSI (Traditional): The RSI directly compares the average gains and losses of the price over a set period (typically 14 periods). It outputs a value between 0 and 100, where values above 70 indicate overbought conditions and values below 30 suggest oversold conditions.
Stochastic RSI: Instead of being calculated from price itself, the StochRSI is derived from the RSI, which adds an additional layer of smoothness and filtering. This makes it more responsive to changes in market momentum, often producing faster signals, especially in volatile markets.
Key Advantage: The Stochastic RSI often generates more timely signals by incorporating both RSI and Stochastic Oscillator principles. This leads to clearer identification of trend reversals or continuation signals, especially in strongly trending or choppy markets.
3. Smoothing and Signal Generation:
%K and %D Smoothing: The indicator uses two key smoothing steps for generating signals: the %K line (stochastic RSI itself) and the %D line (a smoothed version of %K). These are typical of Stochastic indicators but applied to the RSI, making it more sophisticated and adaptive to market cycles.
The moving average of %K (denoted as the "MA Line") further refines the trend signals by smoothing the price action of the %K line. This allows for better trend recognition, reducing false signals in sideways markets.
Key Advantage: The added smoothing steps from the %K, %D, and MA Line help in producing less erratic signals, enabling smoother and more accurate trend-following behavior. The MA line is especially useful in filtering out noise in the Stochastic RSI.
4. Trend Direction (Bullish vs Bearish):
Bullish/Bearish Conditions: The indicator includes a clear trend identification mechanism, where the indicator is considered bullish when the %K line is above the %D line and bearish when it is below.
This distinction is visually represented with gradient colors, where the bullish condition is highlighted with a green color (often associated with upward momentum) and bearish with a red color (indicating downward pressure).
Key Advantage: By distinguishing the trend direction visually and dynamically, this feature adds a layer of market interpretation that is not present in the traditional RSI. It offers clarity in identifying bullish or bearish cycles within market movements, making it easier for traders to align their positions with prevailing market trends.
5. Gradient Colors and Visualization:
The indicator uses gradient colors to visually represent the market condition. The color changes dynamically based on whether the market is in a bullish or bearish state, providing immediate feedback to the trader on the momentum of the asset.
This color gradient approach adds a clear visual reference compared to the traditional line-based RSI indicators, where traders have to infer trend direction based on multiple readings or conditions.
Key Advantage: The color gradient not only serves as a trend indicator but also makes the signal more visually accessible and easier to interpret in real-time.
6. Threshold Levels and Overbought/Oversold Conditions:
Horizontal Lines at 15 and 85: These thresholds are used to mark oversold and overbought levels, similar to how the 30 and 70 levels function in the traditional RSI. The key difference here is that the Stochastic RSI is more sensitive to price movements, and thus these levels can be more dynamic and precise in identifying extreme market conditions.
Key Advantage: The Stochastic RSI's threshold levels offer more precise markers for overbought and oversold conditions in comparison to the RSI, providing better actionable insights during volatile market phases.
7. Gradient Fill between %K and Midline:
The indicator fills the area between the %K line and the Midline (50) based on whether the trend is bullish or bearish, with different opacities depending on the trend.
Key Advantage: This visual fill enhances the clarity of market cycles and trend phases, making it easier for traders to spot potential trend reversals or trend-following opportunities. The fill acts as a dynamic background to reinforce the current market sentiment.
Advanced Trend Following: Unlike basic RSI or Stochastic indicators, the Gradient Stochastic RSI Cycles indicator integrates trend-following principles with stochastic analysis applied to RSI, creating a powerful hybrid for capturing market momentum.
Dynamic Visual Feedback: The gradient color effect and fill based on trend direction give this indicator a unique visual aspect that makes market conditions more intuitive and easier to analyze at a glance. This is not available in traditional RSI or most common stochastic oscillators.
Enhanced Overbought/Oversold Signals: By utilizing the Stochastic RSI, this indicator offers more responsive overbought and oversold levels, often leading to earlier signals compared to the conventional RSI.
Smooth and Adaptive: The multiple smoothing steps used in the indicator (with %K, %D, and the MA line) provide a more adaptive approach to trend filtering, reducing false signals that often occur with basic indicators.
In summary, the Gradient Stochastic RSI Cycles indicator is an advanced, adaptive tool that combines RSI, Stochastic Oscillator, and moving averages to provide traders with more accurate, timely, and visually accessible market signals. Its design helps overcome many of the limitations associated with traditional RSI or stochastic-based indicators, offering a more refined analysis of price momentum.
Double RSIDouble RSI (DRSI) Indicator
The Double RSI (DRSI) is a technical analysis tool designed to provide traders with enhanced buy and sell signals by identifying uptrend and downtrend thresholds. It refines traditional RSI-based signals by applying a "double calculation" to the Relative Strength Index (RSI), improving precision in detecting trend changes.
Key Concepts Behind the Indicator
1. Double RSI Calculation
The DRSI indicator takes the standard RSI (calculated using the closing price over a specified length) and applies a second RSI calculation to it. This creates a smoother, more refined RSI value, making it more effective at highlighting the general trend of the market.
RSI: Measures the strength of recent price movements, ranging from 0 to 100.
Double RSI (DRSI): Applies the RSI formula to the RSI values themselves, smoothing out fluctuations and generating clearer signals.
How Does the Indicator Work?
The DRSI identifies uptrends and downtrends using two user-defined thresholds:
Uptrend Threshold (Default = 59): A value above this threshold signals a potential shift into an uptrend.
Downtrend Threshold (Default = 52): A value below this threshold signals a potential shift into a downtrend.
Signal Generation
Buy Signal: A crossover occurs when the DRSI value crosses above the Downtrend Threshold, signaling the beginning of an upward movement.
Sell Signal: A crossunder occurs when the DRSI value crosses below the Uptrend Threshold, signaling the beginning of a downward movement.
Customizable Inputs
The indicator offers customizable settings for increased flexibility:
DRSI Length (Default = 13): Determines the lookback period for RSI calculations. A shorter length increases sensitivity, while a longer length smooths the signals.
Uptrend Threshold (Default = 59): Sets the level above which an uptrend is confirmed.
Downtrend Threshold (Default = 52): Sets the level below which a downtrend is confirmed.
Bar Color and Glow Effects: Traders can enable colored candles or glowing DRSI lines for better visual representation.
Why is This Indicator Useful for Traders?
1. Noise Reduction
By applying a second RSI calculation, the DRSI smooths out minor fluctuations and highlights the overall trend.
2. Clear Uptrend and Downtrend Signals
The indicator provides intuitive buy (green arrow) and sell (red arrow) markers, simplifying decision-making.
3. Customizable Thresholds
Traders can adjust the thresholds and length to better suit specific trading strategies or market conditions.
4. Bar Coloring
Bars are color-coded to indicate the trend:
Green (Above Uptrend Threshold): Indicates an uptrend.
Red (Below Downtrend Threshold): Indicates a downtrend.
How the Indicator Appears on the Chart
DRSI Line: A smooth line derived from the double RSI calculation.
Threshold Lines: Two horizontal lines (green for the Uptrend Threshold, red for the Downtrend Threshold) to visualize trend changes.
Colored Candles: Candlesticks dynamically change color based on the trend direction (green for uptrends, red for downtrends).
Buy/Sell Markers:
Buy Signal: A green upward triangle below the bar, marking the start of an uptrend.
Sell Signal: A red downward triangle above the bar, marking the start of a downtrend.
In Summary
The Double RSI (DRSI) indicator is a powerful tool for identifying uptrends and downtrends with:
Smoothed trend detection using double-calculated RSI values.
Clear, actionable buy and sell signals.
Customizable settings to match different trading styles.
By focusing on trend thresholds rather than overbought or oversold levels, the DRSI provides traders with precise, noise-free signals to optimize their trading decisions.
RSI Divergence - Left Candles Onlyrsi
The **RSI Divergence** indicator in this script is designed to highlight **divergence** between the **Relative Strength Index (RSI)** and **price action** on a chart. Divergence can be a key signal for potential trend reversals or continuation in technical analysis.
### **Key Components of the Indicator:**
1. **RSI Calculation:**
- The **Relative Strength Index (RSI)** is calculated using a typical 14-period length, but the user can customize this input.
- RSI is a momentum oscillator that measures the speed and change of price movements, oscillating between 0 and 100. Values above 70 indicate overbought conditions, and values below 30 indicate oversold conditions.
2. **Divergence Logic:**
- **Bullish Divergence:** Occurs when the price forms a **lower low**, but the RSI forms a **higher low**. This suggests that despite price continuing to drop, momentum (RSI) is strengthening, which may indicate a potential price reversal to the upside.
- **Bearish Divergence:** Occurs when the price forms a **higher high**, but the RSI forms a **lower high**. This indicates that even though price is rising, the momentum (RSI) is weakening, which could signal a price reversal to the downside.
3. **Pivot Identification:**
- The script identifies **pivot points** (local highs and lows) on both price and RSI.
- **Bullish Divergence:** A lower price low with a higher RSI low.
- **Bearish Divergence:** A higher price high with a lower RSI high.
4. **Lookback Periods:**
- **Lookback Left (lookbackLeft):** Defines the number of bars to look back for pivot confirmation. This allows for adjusting the sensitivity of the divergence.
- The **divergence range** is constrained by two parameters:
- **Minimum range (rangeLower):** The minimum number of bars for divergence to be considered.
- **Maximum range (rangeUpper):** The maximum number of bars for divergence to be considered.
5. **Signal Generation and Plotting:**
- When a **bullish divergence** is detected, a **green label** is plotted below the bar where the divergence occurs.
- When a **bearish divergence** is detected, a **red label** is plotted above the bar.
- The script uses **`plotshape()`** to plot these labels on the chart.
6. **Alerts:**
- Alerts are configured for both **bullish** and **bearish divergences** so that you can be notified when a divergence signal occurs.
---
### **How the Indicator Works:**
- The RSI and price action are compared using **pivots**: The script checks whether the price and RSI are forming new highs or lows within the specified **lookback period**.
- If the conditions for divergence (higher/lower RSI pivot vs price pivot) are met, a signal is plotted on the chart.
- The script helps to visually identify potential reversal points and allows users to set alerts for these divergence signals.
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### **Use Case:**
- This script is useful for traders looking to trade potential trend reversals based on **divergence** between price and RSI.
- **Bullish divergence** can indicate a **buy** opportunity, while **bearish divergence** can suggest a **sell** opportunity.
- The indicator works best in **volatile markets** and when combined with other technical analysis tools for confirmatio
Polyphase MACD (PMACD)The Polyphase MACD (PMACD) uses polyphase decimation to create a continuous estimate of higher timeframe MACD behavior. The number of phases represents the timeframe multiplier - for example, 3 phases approximates a 3x higher timeframe.
Traditional higher timeframe MACD indicators update only when each higher timeframe bar completes, creating stepped signals that can miss intermediate price action. The PMACD addresses this by maintaining multiple phase-shifted MACD calculations and combining them with appropriate anti-aliasing filters. This approach eliminates the discrete jumps typically seen in higher timeframe indicators, though the resulting signal may sometimes deviate from the true higher timeframe values due to its estimative nature.
The indicator processes price data through parallel phase calculations, each analyzing a different time-offset subset of the data. These phases are filtered and combined to prevent aliasing artifacts that occur in simple timeframe conversions. The result is a smooth, continuous signal that begins providing meaningful values immediately, without requiring a warm-up period of higher timeframe bars.
The PMACD maintains the standard MACD components - the MACD line (fast MA - slow MA), signal line, and histogram - while providing a more continuous view of higher timeframe momentum. Users can select between EMA and SMA calculations for both the oscillator and signal components, with all calculations benefiting from the same polyphase processing technique.
Polyphase Stochastic RSI (PSRSI)The Polyphase Stochastic RSI (PSRSI) provides a continuous estimate of higher timeframe Stochastic RSI behavior by using polyphase decimation. The number of phases represents the timeframe multiplier - for example, 3 phases approximates a 3x higher timeframe.
While traditional higher timeframe indicators only update at the completion of each higher timeframe bar, the PSRSI creates a continuous signal by maintaining multiple phase-shifted calculations and combining them with appropriate anti-aliasing filters. This approach eliminates the gaps and discontinuities typically seen in higher timeframe indicators, though the resulting signal may sometimes deviate from the true higher timeframe values due to its estimative nature.
The indicator processes data through parallel phase calculations, each handling a different subset of price data offset in time. These phases are then filtered and combined to prevent aliasing artifacts that occur in simple timeframe conversions. The result is a smooth, continuous signal that starts providing meaningful values immediately, without requiring a warm-up period of higher timeframe bars.
Users can choose between RSI and Stochastic RSI modes, with both benefiting from the same polyphase processing technique. The indicator maintains the standard interpretation of overbought and oversold conditions while providing a more continuous view of higher timeframe momentum.
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview
The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions.
Understanding RSI
What is RSI?
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset.
How RSI Works:
Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods.
Range: The RSI oscillates between 0 and 100.
Interpretation:
Key Features of RSI:
Momentum Indicator: RSI helps identify the momentum of price movements.
Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals.
Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50.
Understanding Bollinger Bands
What is Bollinger Bands?
Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines:
Upper Band: SMA + (Standard Deviation × Multiplier)
Middle Band (Basis): SMA
Lower Band: SMA - (Standard Deviation × Multiplier)
How Bollinger Bands Work:
Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility.
Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands.
Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels.
Key Features of Bollinger Bands:
Volatility Indicator: Bollinger Bands help traders understand the volatility of the market.
Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands.
Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout.
Combining RSI and Bollinger Bands
Strategy Overview:
The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are:
RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe.
RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes.
Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band.
Strategy Details:
RSI Calculation:
Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes.
Check if the RSI crosses above 60 on the 15-minute timeframe.
Ensure the RSI is above 60 on the 1-hour and 1-day timeframes.
Bollinger Bands Calculation:
Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations.
Check if the price is above the 20-period moving average or walking on the upper Bollinger Band.
Entry and Exit Signals:
Long Signal: When all the above conditions are met, consider a long entry.
Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit.
Example Usage
Setup:
Add the indicator to your TradingView chart.
Configure the inputs as per your requirements.
Monitoring:
Look for the long signal on the chart.
Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes.
Check that the price is above the 20-period moving average or walking on the upper Bollinger Band.
Trading:
Enter a long position when the criteria are met.
Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules.
Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average.
House Rules Compliance
No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis.
TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines.
Conclusion
This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
[blackcat] L1 Enveloped Oscillator█ OVERVIEW
The script is an indicator named “ L1 Enveloped Oscillator” (L1 EO) designed to plot various trend and oscillator values on a separate chart pane. It calculates multiple indicators such as trend, adjusted trend, oscillator, directional strength, and normalized oscillator, and uses these to detect potential buy and sell signals based on trend contractions, expansions, and divergences.
█ LOGICAL FRAMEWORK
Structure:
1 — Input Parameters: None are explicitly defined, but the script is parameterized within the function with fixed values for levels and periods.
2 — Calculations: The calculate_l1_enveloped_oscillator function computes multiple values including price bases, trend, oscillator, and adjusted trends. This function uses built-in Pine Script functions like ta.highest, ta.lowest, ta.ema, ta.sma, and math.max.
3 — Plotting: The calculated values are plotted on the chart using the plot function, with different colors and styles for visual distinction.
4 — Signal Detection: The script detects and labels potential buy and sell signals based on trend contractions, expansions, and divergences between the price and oscillator.
5 — Conditional Statements: Multiple if statements are used to determine when to place labels for buy and sell signals.
█ CUSTOM FUNCTIONS
• calculate_l1_enveloped_oscillator(high, low, close, open): Calculates various trend and oscillator values based on the input price data.
— Parameters: high, low, close, open (price data).
— Return Values: A tuple containing top_level, bottom_level, middle_level, adjusted_trend, trend, oscillator, directional_strength, normalized_oscillator, and adjusted_candle_trend.
█ KEY POINTS AND TECHNIQUES
• Advanced Pine Script Features: Utilizes built-in functions for technical analysis (ta.highest, ta.lowest, ta.ema, ta.sma, ta.crossover, ta.crossunder).
• Optimization Techniques: Uses fixed periods and levels for calculations, which can be adjusted for different market conditions.
• Best Practices: Clearly separates calculations and plotting, making the script modular and easier to maintain.
• Unique Approaches: Combines multiple indicators (trend, oscillator, directional strength) to detect complex market conditions like divergences and contractions/expansions.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: Users can modify the levels (top_level, bottom_level, middle_level) and periods used in calculations to better suit specific asset classes or market conditions.
• Extensions: The script can be extended to include additional indicators or signals, such as RSI or MACD, to enhance its predictive power.
• Application Scenarios: Similar techniques can be applied in other trading strategies involving trend analysis and divergence detection, such as momentum trading or mean reversion strategies.
• Related Concepts: Users can explore other Pine Script concepts like alerts, backtesting, and optimization to fine-tune strategies based on historical data.
LRI Momentum Cycles [AlgoAlpha]Discover the LRI Momentum Cycles indicator by AlgoAlpha, a cutting-edge tool designed to identify market momentum shifts using trend normalization and linear regression analysis. This advanced indicator helps traders detect bullish and bearish cycles with enhanced accuracy, making it ideal for swing traders and intraday enthusiasts alike.
Key Features :
🎨 Customizable Appearance : Set personalized colors for bullish and bearish trends to match your charting style.
🔧 Dynamic Trend Analysis : Tracks market momentum using a unique trend normalization algorithm.
📊 Linear Regression Insight : Calculates real-time trend direction using linear regression for better precision.
🔔 Alert Notifications : Receive alerts when the market switches from bearish to bullish or vice versa.
How to Use :
🛠 Add the Indicator : Favorite and apply the indicator to your TradingView chart. Adjust the lookback period, linear regression source, and regression length to fit your strategy.
📊 Market Analysis : Watch for color changes on the trend line. Green signals bullish momentum, while red indicates bearish cycles. Use these shifts to time entries and exits.
🔔 Set Alerts : Enable notifications for momentum shifts, ensuring you never miss critical market moves.
How It Works :
The LRI Momentum Cycles indicator calculates trend direction by applying linear regression on a user-defined price source over a specified period. It compares historical trend values, detecting bullish or bearish momentum through a dynamic scoring system. This score is normalized to ensure consistent readings, regardless of market conditions. The indicator visually represents trends using gradient-colored plots and fills to highlight changes in momentum. Alerts trigger when the momentum state changes, providing actionable trading signals.
Trend Strength/DirectionThis is a really good, though complex indicator, so I will add two different explanations so to appease both the laymen and those who take the time to read thoroughly.
Simple Explanation
This indicator utilizes 6HMA's to display their angles
The greater the angle ---> the stronger the trend
If more angles are positive, then trend is very strong
If more are negative, then very negative
Comprehensive Explanation
6 angles, each of a different time frame are used to represent direction and trend strength. Angles are used because they intrinsically represent momentum and speed. An angle of 45 represents a perfect balance between something that can cover the furthest distance without compensating for speed. 1 of the 6 angles is intended(though customizable) to represent the 5 hma's angle. This is because the 5hma is very good at representing very near term price action.
Angle Levels
Its important to understand what the angle levels mean for the underlying hma's. The 0 level represents a hma that is horizontal. This is important because this is the point at which it decides to be bullish or bearish. +/- 45, as noted before, represent bullishness/bearishness that represent strong trends without compensating for speed. A continuous increase/decrease and or a cross of these levels generally indicate significant change in sentiment, of which trades may be taken.
Strategy
You should weigh your decision by those angles that represent the longer time frame. If more angles represent a certain sentiment, it is obviously unwise to fight against that long term sentiment. The purpose of this indicator was to provide a proper representation of trend direction and strength, but also solve the problem of when you should 'dip' buy.
For an example: if all angles are increase or decreasing, then you may use the 5hma's angle to find the proper points at which you will enter a position.
***NOTE: I dont think the +/- 45 bands should indicate 'overbought' or 'oversold' zones that some might assume. Instead you should wait for a crossing of this zone.
RSI BandsOverview
The RSI Bands indicator is a tool designed to calculate and display overbought, oversold, and middle bands based on the Relative Strength Index (RSI).
Its primary purpose is to provide traders with a clue on whether to place limit buy or limit sell orders, or to set stop-loss orders effectively. The bands represent the price levels the asset must reach for the RSI to align with specific thresholds:
Overbought Band: Displays the upper band representing the price level the asset must reach for the RSI to become overbought.
Oversold Band: Displays the lower band representing the price level the asset must reach for the RSI to become oversold.
Middle Band: Displays the middle band representing the price level the asset must reach for the RSI to hit the middle level. It uses both traditional RSI calculations and a dynamic period adjustment mechanism for improved adaptability to market conditions. The script also offers smoothing options for the bands.
Features
Calculates overbought, oversold, and middle bands using RSI values.
Dynamically adjusts the RSI period based on pivot points if enabled.
Offers smoothing options for the bands: EMA, SMA, or None.
Customizable input parameters for flexibility.
Inputs
Source Value: Selects the data source (e.g., close price) for RSI calculation.
Period: Sets the static RSI calculation period. Used if dynamic period is disabled.
Use Dynamic Period?: Toggles the use of a dynamic RSI period.
Pivot Left/Right Length: Determines the range of bars for pivot detection when using dynamic periods.
Dynamic Period Multiplier: Scales the dynamically calculated RSI period.
Overbought Level: RSI level that marks the overbought threshold.
Oversold Level: RSI level that marks the oversold threshold.
Middle Level: RSI level used as a midpoint reference.
Smoothing Type: Specifies the smoothing method for the bands (EMA, SMA, or None).
Smoothing Length: Length used for the selected smoothing method.
Key Calculations
RSI Calculation:
Computes RSI using gains and losses over the specified period (dynamic or static).
Incorporates a custom function for calculating RSI with dynamic periods.
Dynamic Period Adjustment:
Uses pivot points to determine an adaptive RSI period.
Multiplies the base dynamic period by the Dynamic Period Multiplier.
Band Calculation:
Calculates price changes (deltas) required to achieve the overbought, oversold, and middle RSI levels.
The price changes (deltas) are determined using an iterative approximation technique. For each target RSI level (overbought, oversold, or middle), the script estimates the required change in price by adjusting a hypothetical delta value until the calculated RSI aligns with the target RSI. This approximation ensures precise calculation of the price levels necessary for the RSI to reach the specified thresholds.
Computes the upper (overbought), lower (oversold), and middle bands by adding these deltas to the source price.
Smoothing:
Applies the selected smoothing method (EMA or SMA) to the calculated bands.
Plots
Overbought Band: Displays the upper band representing the price level the asset must reach for the RSI to become overbought.
Oversold Band: Displays the lower band representing the price level the asset must reach for the RSI to become oversold.
Middle Band: Displays the middle band representing the price level the asset must reach for the RSI to hit the middle level.
Usage
Choose the source value (e.g., close price).
Select whether to use a dynamic RSI period or a static one.
Adjust pivot lengths and multipliers for dynamic period calculation as needed.
Set the overbought, oversold, and middle RSI levels based on your analysis.
Configure smoothing options for the bands.
Observe the plotted bands and use them to identify potential overbought and oversold market conditions.
Market Anomaly Detector (MAD)Market Anomaly Detector (MAD) Indicator - Detailed Description:
The Market Anomaly Detector (MAD) Indicator is a unique tool designed to identify potential market anomalies by combining several price action-based and momentum indicators. This indicator is especially useful for traders who seek to identify significant market shifts and anomalies before they become visible in conventional technical indicators.
Key Features of the MAD Indicator:
1. Z-Score Threshold for Anomaly Detection:
• The Z-Score measures how far a current price is from its average over a defined period, normalized by standard deviation. This allows the MAD indicator to detect outliers or anomalies in price movements.
• By adjusting the Z-Score Threshold, traders can tune the sensitivity of the indicator to capture only the most significant price deviations, filtering out noise and reducing false signals.
2. Volume and Liquidity Filter:
• Volume is a key indicator of market participation and sentiment. The MAD Indicator uses a volume multiplier to assess when price movements are supported by sufficient trading volume.
• A volume spike is identified when the current volume exceeds the average volume by a certain multiplier. This ensures that only high-confidence signals are generated, particularly useful for spotting trend reversals and breakout opportunities.
3. Signal Cooldown Period:
• To prevent overfitting and reduce false signals, a signal cooldown period is implemented. Once a buy or sell signal is triggered, the indicator waits for a specified number of bars (e.g., 5) before triggering another signal, even if the price action meets the criteria for a new signal. This helps maintain a cleaner trading environment and avoids confusion when the market is volatile.
4. Upper and Lower Bands for Trend Confirmation:
• The MAD Indicator uses bands based on the mean price and standard deviation, similar to Bollinger Bands. These upper and lower bands help to define the expected price range for a given period, indicating overbought or oversold conditions.
• The combination of Z-Score, volume, and band analysis helps pinpoint when the price breaks out of expected ranges, providing early warning signs for potential market shifts.
5. Trend Confirmation from Higher Timeframes:
• The MAD Indicator includes a multi-timeframe approach to trend confirmation, using the 50-period EMA on a higher timeframe (e.g., 1-hour chart). This ensures that signals are aligned with the overall market trend, enhancing the reliability of buy and sell signals.
How It Works:
• The MAD Indicator continuously monitors price action, volume, and statistical anomalies, using the Z-Score to determine when the price is significantly deviating from its historical average.
• When the price breaks above the upper band and a bullish anomaly is detected, a buy signal is generated. (Green Background)
• Similarly, when the price breaks below the lower band and a bearish anomaly is detected, a sell signal is triggered. (Red Background
• By filtering signals based on volume and using the cooldown period, the MAD Indicator ensures that only high-quality trades are signaled.
How to Use the MAD Indicator:
• Buy Signal: Occurs when the price breaks above the upper band and there is a significant deviation from the mean (bullish anomaly).
• Sell Signal: Occurs when the price breaks below the lower band and there is a significant deviation from the mean (bearish anomaly).
• Volume Confirmation: Ensure that the buy/sell signals are supported by a volume spike, indicating strong market participation.
• Signal Cooldown Period: After a signal is triggered, the indicator waits for the cooldown period to avoid triggering multiple signals in quick succession.
Why It’s Worth Paying For:
The MAD Indicator combines advanced statistical analysis (Z-Score), price action, and volume analysis to identify market anomalies and breakouts before they are visible on standard indicators. By leveraging the power of mean reversion and statistical anomalies, this tool provides traders with high-confidence signals that can lead to profitable trades, especially in volatile markets. The integration of a multi-timeframe trend filter ensures that signals are aligned with the overall market trend, reducing the likelihood of false breakouts.
This indicator is ideal for trend-following traders looking for high-probability entries and mean-reversion traders aiming to capture price deviations. The signal cooldown period and volume filter provide an additional layer of precision, ensuring that you only act on the strongest market signals.
Adaptive Price Zone Oscillator [QuantAlgo]Adaptive Price Zone Oscillator 🎯📊
The Adaptive Price Zone (APZ) Oscillator by QuantAlgo is an advanced technical indicator designed to identify market trends and reversals through adaptive price zones based on volatility-adjusted bands. This sophisticated system combines typical price analysis with dynamic volatility measurements to help traders and investors identify trend direction, potential reversals, and market volatility conditions. By evaluating both price action and volatility together, this tool enables users to make informed trading decisions while adapting to changing market conditions.
💫 Dynamic Zone Architecture
The APZ Oscillator provides a unique framework for assessing market trends through a blend of smoothed typical prices and volatility-based calculations. Unlike traditional oscillators that use fixed parameters, this system incorporates dynamic volatility measurements to adjust sensitivity automatically, helping users determine whether price movements are significant relative to current market conditions. By combining smoothed price trends with adaptive volatility zones, it evaluates both directional movement and market volatility, while the smoothing parameters ensure stable yet responsive signals. This adaptive approach allows users to identify trending conditions while remaining aware of volatility expansions and contractions, enhancing both trend-following and mean-reversion strategies.
📊 Indicator Components & Mechanics
The APZ Oscillator is composed of several technical components that create a dynamic trending system:
Typical Price: Utilizes HLC3 (High, Low, Close average) as a balanced price representation
Volatility Measurement: Computes exponential moving average of price changes to determine dynamic zones
Smoothed Calculations: Applies additional smoothing to reduce noise while maintaining responsiveness
Trend Detection: Evaluates price position relative to adaptive zones to determine market direction
📈 Key Indicators and Features
The APZ Oscillator utilizes typical price with customizable length and threshold parameters to adapt to different trading styles. Volatility calculations are applied to determine zone boundaries, providing context-aware levels for trend identification. The trend detection component evaluates price action relative to the adaptive zones, helping validate trends and identify potential reversals.
The indicator also incorporates multi-layered visualization with:
Color-coded trend representation (bullish/bearish)
Clear trend state indicators (+1/-1)
Mean reversion signals with distinct markers
Gradient fills for better visual clarity
Programmable alerts for trend changes
⚡️ Practical Applications and Examples
✅ Add the Indicator : Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
👀 Monitor Trend State : Watch the oscillator's position relative to the zero line to identify trend direction and potential reversals. The step-line visualization with diamonds makes trend changes clearly visible.
🎯 Track Signals : Pay attention to the mean reversion markers that appear above and below the price chart:
→ Upward triangles (⤻) signal potential bullish reversals
→ X crosses (↷) indicate potential bearish reversals
🔔 Set Alerts : Configure alerts for trend changes in both bullish and bearish directions, ensuring you can act on significant technical developments promptly.
🌟 Summary and Tips
The Adaptive Price Zone Oscillator by QuantAlgo is a versatile technical tool, designed to support both trend following and mean reversion strategies across different market environments. By combining smoothed typical price analysis with dynamic volatility-based zones, it helps traders and investors identify significant trend changes while measuring market volatility, providing reliable technical signals. The tool's adaptability through customizable length, threshold, and smoothing parameters makes it suitable for various trading timeframes and styles, allowing users to capture opportunities while maintaining awareness of changing market conditions.
Key parameters to optimize for your trading style:
APZ Length: Adjust for more or less sensitivity to price changes
Threshold: Fine-tune the volatility multiplier for wider or narrower zones
Smoothing: Balance noise reduction with signal responsiveness
Super Oscillator with Alerts by BigBlueCheeseSuper Oscillator with Alerts (by BigBlueCheese)
I got sick of eyeballing multiple oscillators generating output on different scales and interpreting them on the fly, so I picked 4 of my favs, 2 fisher transforms (fast & slow) The Squeeze & my own Market Rhythm Oscillator & made the Super Oscillator with Alerts which combines multiple indicators and oscillators to analyze market conditions and generate actionable trading signals.
The output is buy/sell/neutral signals and a color coded table summarizing indicator states (strong buy to strong sell etc). The color legend can be disabled once you get used to the color codes. The user can choose to watch the table output and its changing output, OR unclutter their screen by toggling the table off & just watching for the signals SO+ (buy), SO-(sell), SO?(neutral)
The combined signals are run through a scoring and weighting scheme that utilizes each indicators Z-scores, Min-Max normalization, and raw values which are all used in different parts of the scoring process.
A velocity filter (for more immediate/sensitive response) is available for the user to toggle on/off. The raw indicator values are classified into categories reflecting their current strength and are assigned momentum points.
Z-scores measure how far each oscillator's current value deviates from its mean in terms of standard deviations. Basically, the Z-scores focus on relative behavior, while momentum captures directional trends. Together, they provide a more nuanced view of market conditions. Large Z-scores increase the likelihood of stronger signals. The idea is to are amplify influence in extreme conditions whereas low Z scores will have minimal impact on the cumulative score, making signals less prone to noise.
Inputs and Their Contributions
1. Momentum: Controlled by the raw oscillator values and thresholds.
2. Min-Max: Automatically calculated based on the historical range of oscillators.
3. Velocity: Input: useVelocity (true/false) toggle. Weights: User-defined weights for velocity contribution.
4. Z-Score: Input: useZScore (true/false) toggle. Weights: User-defined weights for Z-score contribution.
The system combines momentum, Min-Max normalization, (and if enabled) velocity, and Z-scores, to generate dynamic and actionable trading signals that appear as markers on the chart indicating buy, sell, and neutral signals.
Alerts can also be triggered based on these signals.
Users can customize the weighting and inclusion of velocity and Z-scores to align the scoring system with their trading strategy and preferences.
If there is enough interest for some other preferred oscillator, I will substitute it for out my Market Rhythm Oscillator & republish with the code. LMK
For the curious out there, the Market Rhythm Oscillator (MRO) is a custom oscillator that analyzes price dynamics using a combination of weighted volatility-based calculations. It helps measure price momentum and potential exhaustion levels by identifying high and low volatility regions.
• Purpose: The MRO is particularly effective at identifying market trends and potential reversals by analyzing price extremes and their behavior over a defined lookback period.
• Calculation Components might include:
o Waveform Volatility Factor (WVF): Measures the price's deviation from its highest or lowest values within a given period.
o Bands and Smoothing:
Upper and lower bands based on standard deviations of WVF.
Smoothing is applied to the WVF for better trend clarity.
o Exhaustion Levels: Uses the MRO's trend length to calculate when the price action may become overextended.
Happy hunting but as always, not a trade recommendation, past results not indicative of future results, DYOR!
Coinbase Premium Index (Any Symbol)The Coinbase Premium Index provides a valuable insight into market dynamics by calculating the price premium between Coinbase (USD pairs) and Binance (USDT pairs). A positive premium typically indicates heavy buying pressure on Coinbase, often coinciding with upward price trends on lower timeframes. Conversely, a negative premium suggests selling pressure or weaker demand on Coinbase compared to Binance.
** Key Features: **
**Dynamic Symbol Detection**: Automatically detects the current chart symbol and adapts the premium calculation accordingly.
**Customizable Moving Averages**:
Select between SMA (Simple Moving Average) or EMA (Exponential Moving Average).
Adjust the moving average period to suit your trading strategy (default: SMA with 50 periods).
**Error Handling for Missing Data**:
Displays "Symbol not on Coinbase" when the cryptocurrency is unavailable on Coinbase.
Plots zero-value columns in light grey for unsupported symbols.
**Visual Representation**:
Premium values are displayed as columns: green for positive premiums, red for negative premiums.
A moving average line in light grey helps highlight trends.
Zero Line: A horizontal dashed line is included as a reference point.
** Why Use This Script?**
The Coinbase Premium Index helps traders identify moments of increased buying pressure among U.S. investors, often indicative of bullish momentum on lower timeframes. Use this tool to monitor premium dynamics and gain a clearer understanding of market sentiment across major exchanges.
** How to Use: **
Add this script to your TradingView chart.
Adjust the moving average type and period through the input menu.
Use the premium columns and moving averages to identify potential price trends and validate exchange-specific trading opportunities.
GMO (Gyroscopic Momentum Oscillator) GMO
Overview
This indicator fuses multiple advanced concepts to give traders a comprehensive view of market momentum, volatility, and potential turning points. It leverages the Gyroscopic Momentum Oscillator (GMO) foundation and layers on IQR-based bands, dynamic ATR-adjusted OB/OS levels, torque filtering, and divergence detection. The outcome is a versatile tool that can assist in identifying both short-term squeezes and long-term reversal zones while detecting subtle shifts in momentum acceleration.
Key Components:
Gyroscopic Momentum Oscillator (GMO) – A physics-inspired metric capturing trend stability and momentum by treating price dynamics as “angle,” “angular velocity,” and “inertia.”
IQR Bands – Highlight statistically typical oscillation ranges, providing insight into short-term squeezes and potential near-term trend shifts.
ATR-Adjusted OB/OS Levels – Dynamic thresholds for overbought/oversold conditions, adapting to volatility, aiding in identifying long-term potential reversal zones.
Torque Filtering & Scaling – Smooths and thresholds torque (the rate of change of momentum) and visually scales it for clarity, indicating sudden force changes that may precede volatility adjustments.
Divergence Detection – Highlights potential reversal cues by comparing oscillator swings against price swings, revealing regular and hidden bullish/bearish divergences.
Conceptual Insights
IQR Bands (Short-Term Squeeze & Trend Direction):
Short-Term Momentum and Squeeze: The IQR (Interquartile Range) bands show where the oscillator tends to “live” statistically. When the GMO line hovers within compressed IQR bands, it can signal a momentum squeeze phase. Exiting these tight ranges often correlates with short-term breakout opportunities.
Trend Reversals: If the oscillator pushes beyond these IQR ranges, it may indicate an emerging short-term trend change. Traders can watch for GMO escaping the IQR “comfort zone” to anticipate a new directional move.
Dynamic OB/OS Levels (Long-Term Reversal Zones):
ATR-Based Adaptive Thresholds: Instead of static overbought/oversold lines, this tool uses ATR to adjust OB/OS boundaries. In calm markets, these lines remain closer to ±90. As volatility rises, they approach ±100, reflecting greater permissible swings.
Long-Term Trend Reversal Potential: If GMO hits these dynamically adjusted OB/OS extremes, it suggests conditions ripe for possible long-term trend reversals. Traders seeking major inflection points may find these adaptive levels more reliable than fixed thresholds.
Torque (Sudden Force & Directional Shifts):
Momentum Acceleration Insight: Torque represents the second derivative of momentum, highlighting how quickly momentum is changing. High positive torque suggests a rapidly strengthening bullish force, while high negative torque warns of sudden bearish pressure.
Early Warning & Stability/Volatility Adjustments: By monitoring torque spikes, traders can anticipate momentum shifts before price fully confirms them. This can signal imminent changes in stability or increased volatility phases.
Indicator Parameters and Usage
GMO-Related Inputs:
lenPivot (Default 100): Length for calculating the pivot line (slow market axis).
lenSmoothAngle (Default 200): Smooths the angle measure, reducing noise.
lenATR (Default 14): ATR period for scaling factor, linking price changes to volatility.
useVolatility (Default true): If true, volatility (ATR) influences inertia, adjusting momentum calculations.
useVolume (Default false): If true, volume affects inertia, adding a liquidity dimension to momentum.
lenVolSmoothing (Default 50): Smooths volume calculations if useVolume is enabled.
lenMomentumSmooth (Default 20): EMA smoothing of GMO for a cleaner oscillator line.
normalizeRange (Default true): Normalizes GMO to a fixed range for consistent interpretation.
lenNorm (Default 100): Length for normalization window, ensuring GMO’s scale adapts to recent extremes.
IQR Bands Settings:
iqrLength (Default 14): Period to compute the oscillator’s statistical IQR.
iqrMult (Default 1.5): Multiplier to define the upper and lower IQR-based bands.
ATR-Adjusted OB/OS Settings:
baseOBLevel (Fixed at 90) and baseOSLevel (Fixed at 90): Base lines for OB/OS.
atrPeriodForOBOS (Default 50): ATR length for adjusting OB/OS thresholds dynamically.
atrScaling (Default 0.2): Controls how strongly volatility affects OB/OS lines.
Torque Filtering & Visualization:
torqueSmoothLength (Default 10): EMA length to smooth raw torque values.
atrPeriodForTorque (Default 14): ATR period to determine torque threshold.
atrTorqueScaling (Default 0.5): Scales ATR for determining torque’s “significant” threshold.
torqueScaleFactor (Default 10.0): Multiplies the torque values for better visual prominence on the chart.
Divergence Inputs:
showDivergences (Default true): Toggles divergence signals.
lbR, lbL (Defaults 5): Pivot lookback periods to identify swing highs and lows.
rangeUpper, rangeLower: Bar constraints to validate potential divergences.
plotBull, plotHiddenBull, plotBear, plotHiddenBear: Toggles for each divergence type.
Visual Elements on the Chart
GMO Line (Blue) & Zero Line (Gray):
GMO line oscillates around zero. Positive territory hints bullish momentum, negative suggests bearish.
IQR Bands (Teal Lines & Yellow Fill):
Upper/lower bands form a statistical “normal range” for GMO. The median line (purple) provides a central reference. Contraction near these bands indicates a short-term squeeze, expansions beyond them can signal emerging short-term trend changes.
Dynamic OB/OS (Red & Green Lines):
Red line near +90 to +100: Overbought zone (dynamic).
Green line near -90 to -100: Oversold zone (dynamic).
Movement into these zones may mark significant, longer-term reversal potential.
Torque Histogram (Colored Bars):
Plotted below GMO. Green bars = torque above positive threshold (bullish acceleration).
Red bars = torque below negative threshold (bearish acceleration).
Gray bars = neutral range.
This provides early warnings of momentum shifts before price responds fully.
Precession (Orange Line):
Scaled for visibility, adds context to long-term angular shifts in the oscillator.
Divergence Signals (Shapes):
Circles and offset lines highlight regular or hidden bullish/bearish divergences, offering potential reversal signals.
Practical Interpretation & Strategy
Short-Term Opportunities (IQR Focus):
If GMO compresses within IQR bands, the market might be “winding up.” A break above/below these bands can signal a short-term trade opportunity.
Long-Term Reversal Zones (Dynamic OB/OS):
When GMO approaches these dynamically adjusted extremes, conditions may be ripe for a major trend shift. This is particularly useful for swing or position traders looking for significant turnarounds.
Monitoring Torque for Acceleration Cues:
Torque spikes can precede price action, serving as an early catalyst signal. If torque turns strongly positive, anticipate bullish acceleration; strongly negative torque may warn of upcoming bearish pressure.
Confirm with Divergences:
Divergences between price and GMO reinforce potential reversal or continuation signals identified by IQR, OB/OS, or torque. Use them to increase confidence in setups.
Tips and Best Practices
Combine with Price & Volume Action:
While the indicator is powerful, always confirm signals with actual price structure, volume patterns, or other trend-following tools.
Adjust Lengths & Periods as Needed:
Shorter lengths = more responsiveness but more noise. Longer lengths = smoother signals but greater lag. Tune parameters to match your trading style and timeframe.
Use ATR and Volume Settings Wisely:
If markets are highly volatile, consider useVolatility to refine momentum readings. If liquidity is key, enable useVolume.
Scaling Torque:
If torque bars are hard to read, increase torqueScaleFactor further. The scaling doesn’t affect logic—only visibility.
Conclusion
The “GMO + IQR Bands + ATR-Adjusted OB/OS + Torque Filtering (Scaled)” indicator presents a holistic framework for understanding market momentum across multiple timescales and conditions. By interpreting short-term squeezes via IQR bands, long-term reversal zones via adaptive OB/OS, and subtle acceleration changes through torque, traders can gain advanced insights into when to anticipate breakouts, manage risk around potential reversals, and fine-tune timing for entries and exits.
This integrated approach helps navigate complex market dynamics, making it a valuable addition to any technical analysis toolkit.
Multi-Indicator Signal with TableThis indicator is a versatile multi-indicator tool designed for traders who want to combine signals from various popular indicators into a single framework. It not only visualizes buy and sell signals but also provides a clear, easy-to-read table that summarizes the included indicators and their respective signal colors.
Key Features:
RSI (Relative Strength Index):
Buy Signal: RSI falls below the oversold level (default: 30).
Sell Signal: RSI rises above the overbought level (default: 70).
Signal Color: Green.
MACD (Moving Average Convergence Divergence):
Buy Signal: MACD line crosses above the signal line.
Sell Signal: MACD line crosses below the signal line.
Signal Color: Blue.
MA Crossover (Moving Average Crossover):
Buy Signal: Short EMA (default: 7) crosses above Long SMA (default: 14).
Sell Signal: Short EMA crosses below Long SMA.
Signal Color: Purple.
Stochastic Oscillator:
Buy Signal: Stochastic %K falls below 20 and crosses above %D.
Sell Signal: Stochastic %K rises above 80 and crosses below %D.
Signal Color: Yellow.
TSI (True Strength Index):
Buy Signal: TSI crosses above the zero line.
Sell Signal: TSI crosses below the zero line.
Signal Color: Red.
Dynamic Signal Table:
A clean, compact table displayed at the top-right corner of the chart, summarizing the indicators and their respective signal colors for quick reference.
Customization:
All indicator parameters are fully adjustable, allowing users to fine-tune settings to match their trading strategy.
Signal colors and table design ensure a visually intuitive experience.
Usage:
This tool is ideal for traders who prefer a multi-indicator approach for generating buy/sell signals.
The combination of different indicators helps to filter out noise and increase the accuracy of trade setups.
Notes:
Signals appear only after the confirmation of the current bar to avoid false triggers.
This indicator is designed for educational purposes and should be used in conjunction with proper risk management strategies.
SIM Trend Strength OscillatorTrend Strength Oscillator
The UNIQUE Trend Strength Oscillator is a non-overlayed indicator designed to help traders identify the strength and direction of market trends. This indicator uses Average True Range (ATR) bands to determine trend conditions and provides a visual representation of trend strength through a smoothed oscillator line.
Add the indicator to favorites for easy access
Key Features:
ATR Bands: Utilizes ATR bands to define trend conditions, with options to use either EMA or SMA for smoothing.
Trend Conditions: Identifies moderate and strong uptrends and downtrends, as well as sideways movements.
Trend Strength Calculation: Assigns normalized trend strength values based on the identified trend conditions.
Smoothing: Smoothes the trend strength values over a specified number of confirmation candles to provide a clearer trend signal.
Visualization: Displays the trend strength as a colored oscillator line and background, making it easy to interpret trend strength and direction at a glance.
Inputs:
Use EMA for ATR: Toggle to use EMA instead of SMA for ATR bands.
ATR Period: Period for ATR calculation.
ATR Mean Length: Length for the SMA of ATR.
Trend Confirmation Candles: Number of candles for trend confirmation.
Usage:
Trend Identification: Use the oscillator to identify the strength and direction of the current trend.
Trend Confirmation: Ensure that the trend condition has been true for the specified number of confirmation candles for more reliable signals.
Visual Cues: The colored oscillator line and background provide quick visual cues for trend strength and direction.
The Trend Strength Oscillator is a valuable tool for traders looking to gain insights into market trends and make more informed trading decisions.
Buy me a Coffee (ETH): 0x34539E9D183B427DC14376158C8Fa9f619B03eEa
Stochastic Oscillator-Time & Frequency StatsThe Stochastic Oscillator Time & Frequency Statistics indicator is a tool designed to enhance your trading decisions by combining the traditional Stochastic Oscillator with additional metrics and visual aids. Although the Stochastic Oscillator is typically used to indicate trend direction and overbought/oversold conditions, the %K and %D lines can cross over and under multiple times while in the critical zones. The statistics added to this indicator allow traders to assess the probability of multiple crossover signals occurring on an asset or within various time frames. Signal levels and definitions of critical zones can be adjusted while the statistics are automatically updated to the relevant ticker, time frame and thresholds. Visual preferences such as colors and signal shapes can also be customized.
The Stochastic Oscillator is a commonly used momentum indicator developed by George Lane. It measures the position of the current closing price relative to the asset's recent high-low range over a set period. This advanced version calculates various probability and frequency statistics to better understand the oscillator’s behaviour and guide our strategies and risk management. Some key questions that this indicator intends to address are:
How long does the average momentum last in a trend?; How long does the oscillator remain in the critical zones?; How many times could one expect crossovers/unders' to occur in critical zones before momentum changes?; And, at what price does the candle need to close for the k & d lines to cross and signal a momentum shift?
Statistics & Probabilities:
The indicator calculates important time and frequency-based metrics that provide deeper insight into the behavior of the Stochastic Oscillator. These are displayed in a text box on the indicator panel, including:
Avg Long: The average number of bars between the last long signal before exiting the critical oversold zone and the next short signal in the overbought critical zone, including the standard deviation and the sample size within the relevant time frame.
Avg Short: The average number of bars between the last short signal in the overbought critical zone and the next long signal in the oversold critical zone, including the standard deviation and the sample size within the relevant time frame.
Time in Oversold: The average time (in bars/candle sticks) that the Stochastic Oscillator's %K & %D lines both spend in the oversold region (below the buy signal level) after entering and before departing the oversold region, along with the standard deviation.
Time in Overbought: The average time (in bars/candle sticks) that the Stochastic Oscillator's %K & %D lines both spend in the overbought region (above the sell signal level), after entering and before departing the overbought region, along with the standard deviation.
Signal Frequency: It calculates the percentage of long or short signals that occur consecutively within the critical zone before the opposing signal occurs (e.g., 1Long: 40.54%, 2 Long: 28.55%, 3Long: 17.4%, >3 Long: 13.51%, 1Short: 36.15%, 2Short: 30.41%, 3Short: 17.57%, >3Short: 15.88%). This is calculated for 1 through 6 consecutive occurrences and summarised for more than 6 consecutive signals
Key Features:
Oversold: Typically When the Stochastic Oscillator is below 20, it indicates that the asset may be oversold, potentially signalling a buying opportunity. The threshold for "overbought" and "oversold" extreme regions can be adjusted
Overbought: When the Stochastic Oscillator is above 80, it suggests the asset may be overbought, and a downturn might be near.
Stochastic Slope: The slope of the Stochastic Oscillator indicates the prominent trend direction within the selected time period.
Customizable Buy/Sell Signal Levels: The indicator allows customizable levels for detecting oversold (typically below 20-25) and overbought (typically above 75-80) conditions, helping one spot potential reversal zones for initiating long or short trades.
Crossover Alerts: The indicator tracks crossovers between the %K and %D lines, generating:
Long signals: When a crossover occurs below the buy signal level (indicating oversold conditions).
Short signals: when a crossunder occurs above the sell signal level (indicating overbought conditions).
The signals are visualized as labels on the chart:
- **L** for potential long (buy) signals: Marked below the bars when the %K line crosses above the %D line.
- **S** for potential short (sell) signals: Marked above the bars when the %K line crosses below the %D line.
Disclaimers:
No Guarantees: The indicator is provided "as-is" without any warranties or guarantees of accuracy, completeness, or fitness for a particular purpose. The outcomes or performance of trades executed using this indicator are not guaranteed to be successful or profitable.
User Responsibility: You are solely responsible for any trading decisions you make based on the use of this indicator. All trading and investment activities involve risk, and it is essential to conduct your own research, analysis, and due diligence before making any financial decisions.
No Liability: The creator of this indicator is not responsible for any financial losses, direct or indirect, incurred as a result of using this indicator. This includes, but is not limited to, loss of profits, loss of capital, or any other negative financial outcomes.
Market Risks: Markets are volatile, and prices may fluctuate significantly. Trading and investing carry inherent risks, and there is always the potential for loss. You should only trade with capital that you can afford to lose.
Independent Advice: This indicator and the content generated by its creator does not constitute financial advice and is for entertainment purposes only. It is strongly recommended that you seek independent financial advice from a qualified and licensed professional before making any trading or investment decisions based on the use of this indicator.
By using this indicator, you acknowledge that you fully understand and accept the risks involved, and you agree to indemnify and hold harmless the creator of this indicator from any claims, damages, or liabilities arising from its use.
The author of this script has made every effort to ensure that the code is an original interpretation and application of the open-source **Stochastic Oscillator**, as developed by George Lane. The script reflects a unique adaptation aimed at enhancing trading strategies through advanced statistical analysis and trade management features. The author does not claim any proprietary rights over the foundational concepts of the **Stochastic Oscillator** and does not intend to infringe upon any existing copyrights. Should any copyright infringement be identified, the author commits to removing the indicator immediately and forfeits any rights to further or intended financial gain from its use.
Universal Forex Strength Index - UFSIUniversal Forex Strength Index: A Comprehensive Guide for Traders
The Universal Forex Strength Index (UFSI) is a powerful technical analysis tool designed to help traders assess the strength of various currency pairs in the Forex market. This guide will walk you through the functionality of the UFSI, how to interpret its signals, and how to utilize it effectively in your trading strategy.
Understanding the Components of UFSI
1. Relative Strength Index (RSI)
The UFSI utilizes the Relative Strength Index (RSI), a momentum oscillator that measures the speed and change of price movements. The RSI ranges from 0 to 100 and is typically used to identify overbought or oversold conditions:
Above 70: Overbought condition
Below 30: Oversold condition
2. Exponential Moving Averages (EMA)
The indicator also incorporates two Exponential Moving Averages:
EMA 21: A short-term trend indicator.
EMA 50: A longer-term trend indicator.
The difference between these two EMAs is normalized to create a value that reflects market momentum.
3. Strength Index Calculation
The UFSI combines the RSI and the normalized EMA difference to produce a composite strength index. This index ranges from 0 to 100 and provides insights into the overall strength of a currency pair.
4. EMA of the Strength Index
A 50-period EMA of the strength index is calculated to smooth out fluctuations and provide a clearer trend direction.
Color Coding System
The UFSI employs a dynamic color-coding scheme that helps traders quickly assess market conditions:
Strength Index Colors
Green Shades: Indicates a strong bullish trend.
Dark Green (#006400) to Light Green (#008000): Strong bullish momentum.
Orange Shades: Indicates a potential reversal or uncertainty.
Orange (#FFA500) to Gold (#FFD700): Bullish but losing momentum.
Red Shades: Indicates a strong bearish trend.
Dark Red (#FF4500) to Bright Red (#FF0000): Strong bearish momentum.
Blue Shades: Indicates neutral or indecisive market conditions.
Light Blue (#1E90FF) to Dark Blue (#0000FF): No clear trend.
EMA Gradient Color
The color of the 50 EMA of the Strength Index changes based on its value:
Above 50: Indicates bullish sentiment, transitioning from light green to dark green as strength increases.
Below 50: Indicates bearish sentiment, transitioning from red to orange as strength decreases.
How to Use the Universal Forex Strength Index in Trading
Step-by-Step Trading Strategy
Identify Market Conditions
Look at the color of the strength index line:
If it’s predominantly green, consider looking for buying opportunities.
If it’s predominantly red, consider looking for selling opportunities.
If it’s blue, be cautious as there may be no clear trend.
Confirm with EMA
Check the position of the strength index relative to its EMA:
If the strength index is above its EMA and both are above 50, this confirms a strong bullish trend.
If the strength index is below its EMA and both are below 50, this confirms a strong bearish trend.
Set Entry and Exit Points
Use traditional support and resistance levels or other indicators (like moving averages or Fibonacci retracement levels) for setting entry and exit points.
Consider entering trades when there’s a crossover between the strength index and its EMA, especially when confirmed by color changes.
Risk Management
Always use stop-loss orders to protect against unexpected market movements.
Adjust your position size based on your risk tolerance and account size.
Conclusion
The Universal Forex Strength Index is an invaluable tool for traders seeking to gauge market sentiment and make informed trading decisions. By understanding its components, interpreting its color-coded signals, and integrating it into your trading strategy, you can enhance your ability to navigate the complexities of the Forex market successfully.
Feel free to share this guide on TradingView or use it as part of your trading toolkit! Happy trading!
[blackcat] L1 Main life line oscillator█ OVERVIEW
The Pine Script provided is an indicator named " L1 Main life line oscillator." Its primary function is to calculate and plot two oscillators: the Main Force and the Life Line. These oscillators are derived from smoothed price data, and the script also detects and labels crossovers and crossunders between the two lines, which can be used to generate buy and sell signals.
█ FEATURES
Key Features:
• Input Parameters: Users can define the period (n) and the weight for the oscillators.
• Custom Function: A function calculate_life_line_oscillator is defined to compute the Main Force and Life Line oscillators.
• Advanced Calculations: The script uses an adaptive moving average (ALMA) and exponential moving average (EMA) to smooth the price data and calculate the oscillators.
• Crossover and Crossunder Detection: Built-in functions ta.crossover and ta.crossunder are used to identify signal points.
• Label Drawing: Custom labels are drawn on the chart to indicate buy ("B") and sell ("S") signals.
█ HOW TO USE
1 — Configure Input Parameters: Adjust the period (n) and weight to suit your trading strategy.
2 — Interpret the Oscillators: Observe the Main Force and Life Line on the chart.
3 — Act on Signals: Look for crossovers and crossunders to generate buy and sell signals. Buy signals are indicated by the label "B" and sell signals by "S".
█ LIMITATIONS
• Lag in Signals: While the use of ALMA and EMA reduces lag, some delay may still occur, especially in volatile markets.
• False Signals: Crossovers and crossunders can sometimes produce false signals, so it is advisable to use this indicator in conjunction with other tools for confirmation.
█ NOTES
Advanced Pine Script Features:
• Adaptive Moving Average (ALMA): Provides a more responsive and adaptive oscillator.
• Exponential Moving Average (EMA): Smooths the price range and Main Force values.
• Crossover and Crossunder Detection: Utilizes built-in functions for signal identification.
• Label Drawing: Enhances visual signaling with custom labels.
Optimization Techniques:
• The use of ALMA and EMA helps in reducing lag and improving the responsiveness of the oscillators.
• The custom function encapsulates complex calculations, making the main script cleaner and more maintainable.
Unique Approaches:
• The combination of ALMA and EMA to create the Main Force oscillator provides a unique smoothing method.
• The Life Line is calculated using a weighted average of the previous and current Main Force values, adding an additional layer of smoothing and responsiveness.
█ THANKS
Thank you for using the " L1 Main life line oscillator." If you have any questions or suggestions, please feel free to reach out in the comments or on the TradingView or my Discord channel.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
Potential Modifications:
• Additional Indicators: Extend the script to include other technical indicators (e.g., RSI, MACD) for a more comprehensive trading signal system.
• Customizable Colors and Styles: Allow users to customize the colors and styles of the plotted lines and labels.
• Alerts: Implement alerts for crossovers and crossunders to notify users in real-time.
Application Scenarios:
• Intraday Trading: The responsiveness of the oscillators makes this script suitable for intraday trading, where quick buy and sell signals are crucial.
• Long-Term Analysis: By adjusting the period n, the script can be used for long-term trend analysis and strategic trades.
• Backtesting: The script can be modified into a strategy to backtest the performance of the oscillator-based signals against historical data.
Related Pine Script Concepts:
• Strategy Development: Understanding how to convert indicators into strategies for backtesting and live trading.
• Advanced Plotting: Exploring more advanced plotting techniques, such as using different styles and customizing plot appearances.
• Signal Validation: Techniques for validating and filtering signals to reduce false positives and improve trade accuracy.
Multi-Period CorrelationDescription:
The “Correlation Coefficient - Multi Periods” indicator allows you to analyze the correlation between the price of the chart’s asset and another specified asset across multiple time periods simultaneously. It provides a visual representation of how closely the two assets move in relation to each other over user-defined lengths, helping traders and analysts identify relationships, diversification opportunities, and potential hedging strategies.
Features:
• Multi-Period Correlation: Input multiple periods (e.g., 20, 50, 100) to see correlations across different timeframes on the same chart.
• Customizable Asset: Choose any symbol to compare against the current asset.
• Dynamic Visualization: Each correlation is plotted with a unique color for easy distinction.
• Validation: Warns the user if invalid inputs are provided for the lengths, ensuring accuracy.
• Reference Lines: Horizontal lines at 1, 0, and -1 for quick interpretation:
• 1: Perfect positive correlation.
• 0: No correlation.
• -1: Perfect negative correlation.
Use Cases:
• Portfolio Analysis: Evaluate how an asset correlates with another to assess diversification.
• Market Analysis: Identify trends and relationships between stocks, indices, or other financial instruments.
• Risk Management: Understand correlation to optimize hedging strategies and reduce portfolio risk.
This indicator is ideal for traders and investors seeking to make informed decisions by understanding inter-market relationships and their dynamics over time.
[blackcat] L4 Dynamic Trend Analysis█ OVERVIEW
The script implements a dynamic trend analysis indicator named L4 Dynamic Trend Analysis (L4 DTA). It uses a combination of Exponential Moving Averages (EMA), Relative Strength Index (RSI), and custom functions to determine the trend direction and strength. The primary function is to visually represent the trend conditions and potential entry points on the chart.
█ FEATURES
• Initializes a gradient color array and populates it with a spectrum of colors. This gradient is used for coloring the power trend line based on the RSI value.
• Calculates the Average Linear Moving Average (ALMA) of the closing price.
• Computes the RSI of the ALMA value.
• Retrieves a color from the gradient array based on the RSI value.
• Defines a custom function dynamic_trend_analysis that calculates various trend indicators.
• Utilizes the plot function to display different trend conditions and signals on the chart.
• Adds labels to indicate short ('S') and long ('B') signals based on the trend conditions.
█ HOW TO USE
The script begins by defining the gradient color array.
It then calculates the ALMA and RSI values.
The dynamic_trend_analysis function is called, which computes several trend indicators.
Based on these indicators, the script plots different signals and trend lines on the chart.
Labels are added to indicate short and long signals when specific conditions are met.
█ CUSTOM FUNCTIONS
1 — xrf(values, length)
• Purpose: Retrieves the most recent non-NaN value from an array within a specified length.
• Parameters: values (array of float values), length (integer).
• Return Value: The most recent non-NaN value from the array within the specified length.
2 — xbs(cond, lkb)
• Purpose: Checks a condition over a specified lookback period and returns a boolean value.
• Parameters: cond (boolean condition), lkb (lookback period).
• Return Value: Boolean value indicating whether the condition was met over the lookback period.
3 — dynamic_trend_analysis(high, low, close)
• Purpose: Computes several trend indicators including short-side and long-side prices, crossovers, trend strength, and power trend.
• Parameters: high, low, close (price series).
• Return Value: An array containing trend strength (cc), moving average (ma1), trend (trend), and power trend (power_trend).
█ NOTES
• Gradient Color Array: The script uses a gradient color array to dynamically color the power trend line based on the RSI value, providing a visual indication of momentum.
• Custom Functions: The use of custom functions (xrf, xbs, dynamic_trend_analysis) encapsulates complex logic, making the script modular and easier to maintain.
• Trend Analysis: The script combines multiple indicators (EMA, RSI) to create a comprehensive trend analysis, providing multiple signals for trading decisions.
• Efficient Plotting: The script uses conditional plotting to display signals only when specific conditions are met, reducing clutter on the chart.
• Modifications: The script can be modified to include additional indicators or adjust the parameters of existing ones to better suit different trading styles or market conditions.
• Extensions: The dynamic trend analysis function can be extended to include more sophisticated trend following or reversal strategies.
• Alternative Uses: Similar techniques can be applied to other types of technical analysis, such as volatility analysis or momentum strategies.
• Related Concepts: Understanding of Pine Script functions like array.push, ta.ema, ta.rsi, and plot is beneficial for enhancing and customizing the script. Additionally, knowledge of conditional plotting and label creation can help in refining the visual output.
