Rate of Change HistogramExplanation of Modifications
Converting ROC to Histogram:
Original ROC: The ROC is calculated as roc = 100 * (source - source ) / source , plotted as a line oscillating around zero.
Modification: Instead of plotting roc as a line, it’s now plotted as a histogram using style=plot.style_columns. This makes the ROC values visually resemble the MACD histogram, with bars extending above or below the zero line based on momentum.
Applying MACD’s Four-Color Scheme:
Logic: The histogram’s color is determined by:
Above Zero (roc >= 0): Bright green (#26A69A) if ROC is rising (roc > roc ), light green (#B2DFDB) if falling (roc < roc ).
Below Zero (roc < 0): Bright red (#FF5252) if ROC is falling (roc < roc ), light red (#FFCDD2) if rising (roc > roc ).
Implementation: Used the exact color logic and hex codes from the MACD code, applied to the ROC histogram. This highlights momentum ebbs (falling ROC, fading waves) and flows (rising ROC, strengthening waves).
Removing Signal Line:
Unlike the previous attempt, no signal line is added. The histogram is purely the ROC value, ensuring it directly reflects price change momentum without additional smoothing, making it faster and more responsive to pulse waves, as you indicated ROC performs better than other oscillators.
Alert Conditions:
Added alerts to match the MACD’s logic, triggering when the ROC histogram crosses the zero line:
Rising to Falling: When roc >= 0 and roc < 0, signaling a potential wave peak (e.g., end of Wave 3 or C).
Falling to Rising: When roc <= 0 and roc > 0, indicating a potential wave bottom (e.g., start of Wave 1 or rebound).
These alerts help identify transitions in 3-4 wave pulse patterns.
Plotting:
Histogram: Plotted as columns (plot.style_columns) with the four-color scheme, directly representing ROC momentum.
Zero Line: Kept the gray zero line (#787B86) for reference, consistent with the MACD.
Removed ROC Line/Signal Line: Since you want the ROC to act as the histogram itself, no additional lines are plotted.
Inputs:
Retained the original length (default 9) and source (default close) inputs for consistency.
Removed signal-related inputs (e.g., signal_length, sma_signal) as they’re not needed for a pure ROC histogram.
How This ROC Histogram Works for Wave Pulses
Wave Alignment:
Above Zero (Bullish Momentum): Positive ROC bars indicate flows (e.g., impulse Waves 1, 3, or rebounds in Wave B/C). Bright green bars show accelerating momentum (strong pulses), while light green bars suggest fading momentum (potential wave tops).
Below Zero (Bearish Momentum): Negative ROC bars indicate ebbs (e.g., corrective Waves 2, 4, A, or C). Bright red bars show increasing bearish momentum (strong pullbacks), while light red bars suggest slowing declines (potential wave bottoms).
3-4 Wave Pulses:
In a 3-wave A-B-C correction: Wave A (down) shows bright red bars (falling ROC), Wave B (up) shows bright/light green bars (rising ROC), and Wave C (down) shifts back to red bars.
In a 4-wave consolidation: Alternating green/red bars highlight the rhythmic ebbs and flows as momentum oscillates.
Timing:
Zero-line crossovers mark wave transitions (e.g., from Wave 2 to Wave 3).
Color changes (e.g., bright to light green) signal momentum shifts within waves, helping identify pulse peaks/troughs.
Advantages Over MACD:
The ROC histogram is more responsive than the MACD histogram because ROC directly measures price change percentage, while MACD relies on moving average differences, which introduce lag. This makes the ROC histogram better for capturing rapid 3-4 wave pulses, as you noted.
Example Usage
For a stock with 3-4 wave pulses on a 5-minute chart:
Wave 1 (Flow): ROC rises above zero, histogram turns bright green (rising momentum), indicating a strong bullish pulse.
Wave 2 (Ebb): ROC falls below zero, histogram shifts to bright red (falling momentum), signaling a corrective pullback.
Wave 3 (Flow): ROC crosses back above zero, histogram becomes bright green again, confirming a powerful pulse.
Wave 4 (Ebb): ROC dips slightly, histogram turns light green (falling momentum above zero) or light red (rising momentum below zero), indicating consolidation.
Alerts trigger on zero-line crosses (e.g., from Wave 2 to Wave 3), helping time trades.
Settings Recommendations
Default (length=9): Works well for most time frames, balancing sensitivity and smoothness.
Intraday Pulses: Use length=5 or length=7 for faster signals on 5-minute or 15-minute charts.
Daily Charts: Try length=12 or length=14 for broader wave cycles.
Testing: Apply to a stock with clear wave patterns (e.g., tech stocks like AAPL or TSLA) and adjust length to match the pulse frequency you observe.
Notes
Confirmation: Pair the ROC histogram with price action (e.g., Fibonacci retracements, support/resistance) to validate wave counts, as momentum oscillators can be noisy in choppy markets.
Divergences: Watch for divergences (e.g., price makes a higher high, but ROC histogram bars are lower) to spot wave reversals, especially at Wave 3 or C ends.
Comparison to MACD: The ROC histogram is faster and more direct, making it ideal for short-term pulse waves, but it may be more volatile, so use with technical levels for precision.
Cari dalam skrip untuk "bar"
H4 3-Candle Pattern (Persistent Signals)Below is an example in Pine Script v5 that detects a pattern using the last three completed 4H candles and then plots a permanent arrow on the fourth candle (i.e. on the current bar) when the conditions are met. The arrow stays on that bar even after new bars form.
In this version, the pattern is evaluated as follows on each bar (when there are enough candles):
Bullish Pattern:
The candle three bars ago (oldest of the three) is bullish (its close is greater than its open).
The candle two bars ago closes above the high of that older candle.
The last completed candle (one bar ago) closes at or above the low of the candle two bars ago.
Bearish Pattern:
The candle three bars ago is bearish (its close is less than its open).
The candle two bars ago closes below the low of that older candle.
The last completed candle closes at or below the high of the candle two bars ago.
When the conditions are met the script draws a green up arrow below the current (fourth) candle for a bullish pattern and a red down arrow above the current candle for a bearish pattern. These arrows are drawn as regular plot symbols and remain on the chart permanently.
Copy and paste the code into TradingView’s Pine Script Editor:
Volume Predictor [PhenLabs]📊 Volume Predictor
Version: PineScript™ v6
📌 Description
The Volume Predictor is an advanced technical indicator that leverages machine learning and statistical modeling techniques to forecast future trading volume. This innovative tool analyzes historical volume patterns to predict volume levels for upcoming bars, providing traders with valuable insights into potential market activity. By combining multiple prediction algorithms with pattern recognition techniques, the indicator delivers forward-looking volume projections that can enhance trading strategies and market analysis.
🚀 Points of Innovation:
Machine learning pattern recognition using Lorentzian distance metrics
Multi-algorithm prediction framework with algorithm selection
Ensemble learning approach combining multiple prediction methods
Real-time accuracy metrics with visual performance dashboard
Dynamic volume normalization for consistent scale representation
Forward-looking visualization with configurable prediction horizon
🔧 Core Components
Pattern Recognition Engine : Identifies similar historical volume patterns using Lorentzian distance metrics
Multi-Algorithm Framework : Offers five distinct prediction methods with configurable parameters
Volume Normalization : Converts raw volume to percentage scale for consistent analysis
Accuracy Tracking : Continuously evaluates prediction performance against actual outcomes
Advanced Visualization : Displays actual vs. predicted volume with configurable future bar projections
Interactive Dashboard : Shows real-time performance metrics and prediction accuracy
🔥 Key Features
The indicator provides comprehensive volume analysis through:
Multiple Prediction Methods : Choose from Lorentzian, KNN Pattern, Ensemble, EMA, or Linear Regression algorithms
Pattern Matching : Identifies similar historical volume patterns to project future volume
Adaptive Predictions : Generates volume forecasts for multiple bars into the future
Performance Tracking : Calculates and displays real-time prediction accuracy metrics
Normalized Scale : Presents volume as a percentage of historical maximums for consistent analysis
Customizable Visualization : Configure how predictions and actual volumes are displayed
Interactive Dashboard : View algorithm performance metrics in a customizable information panel
🎨 Visualization
Actual Volume Columns : Color-coded green/red bars showing current normalized volume
Prediction Columns : Semi-transparent blue columns representing predicted volume levels
Future Bar Projections : Forward-looking volume predictions with configurable transparency
Prediction Dots : Optional white dots highlighting future prediction points
Reference Lines : Visual guides showing the normalized volume scale
Performance Dashboard : Customizable panel displaying prediction method and accuracy metrics
📖 Usage Guidelines
History Lookback Period
Default: 20
Range: 5-100
This setting determines how many historical bars are analyzed for pattern matching. A longer period provides more historical data for pattern recognition but may reduce responsiveness to recent changes. A shorter period emphasizes recent market behavior but might miss longer-term patterns.
🧠 Prediction Method
Algorithm
Default: Lorentzian
Options: Lorentzian, KNN Pattern, Ensemble, EMA, Linear Regression
Selects the algorithm used for volume prediction:
Lorentzian: Uses Lorentzian distance metrics for pattern recognition, offering excellent noise resistance
KNN Pattern: Traditional K-Nearest Neighbors approach for historical pattern matching
Ensemble: Combines multiple methods with weighted averaging for robust predictions
EMA: Simple exponential moving average projection for trend-following predictions
Linear Regression: Projects future values based on linear trend analysis
Pattern Length
Default: 5
Range: 3-10
Defines the number of bars in each pattern for machine learning methods. Shorter patterns increase sensitivity to recent changes, while longer patterns may identify more complex structures but require more historical data.
Neighbors Count
Default: 3
Range: 1-5
Sets the K value (number of nearest neighbors) used in KNN and Lorentzian methods. Higher values produce smoother predictions by averaging more historical patterns, while lower values may capture more specific patterns but could be more susceptible to noise.
Prediction Horizon
Default: 5
Range: 1-10
Determines how many future bars to predict. Longer horizons provide more forward-looking information but typically decrease accuracy as the prediction window extends.
📊 Display Settings
Display Mode
Default: Overlay
Options: Overlay, Prediction Only
Controls how volume information is displayed:
Overlay: Shows both actual volume and predictions on the same chart
Prediction Only: Displays only the predictions without actual volume
Show Prediction Dots
Default: false
When enabled, adds white dots to future predictions for improved visibility and clarity.
Future Bar Transparency (%)
Default: 70
Range: 0-90
Controls the transparency of future prediction bars. Higher values make future bars more transparent, while lower values make them more visible.
📱 Dashboard Settings
Show Dashboard
Default: true
Toggles display of the prediction accuracy dashboard. When enabled, shows real-time accuracy metrics.
Dashboard Location
Default: Bottom Right
Options: Top Left, Top Right, Bottom Left, Bottom Right
Determines where the dashboard appears on the chart.
Dashboard Text Size
Default: Normal
Options: Small, Normal, Large
Controls the size of text in the dashboard for various display sizes.
Dashboard Style
Default: Solid
Options: Solid, Transparent
Sets the visual style of the dashboard background.
Understanding Accuracy Metrics
The dashboard provides key performance metrics to evaluate prediction quality:
Average Error
Shows the average difference between predicted and actual values
Positive values indicate the prediction tends to be higher than actual volume
Negative values indicate the prediction tends to be lower than actual volume
Values closer to zero indicate better prediction accuracy
Accuracy Percentage
A measure of how close predictions are to actual outcomes
Higher percentages (>70%) indicate excellent prediction quality
Moderate percentages (50-70%) indicate acceptable predictions
Lower percentages (<50%) suggest weaker prediction reliability
The accuracy metrics are color-coded for quick assessment:
Green: Strong prediction performance
Orange: Moderate prediction performance
Red: Weaker prediction performance
✅ Best Use Cases
Anticipate upcoming volume spikes or drops
Identify potential volume divergences from price action
Plan entries and exits around expected volume changes
Filter trading signals based on predicted volume support
Optimize position sizing by forecasting market participation
Prepare for potential volatility changes signaled by volume predictions
Enhance technical pattern analysis with volume projection context
⚠️ Limitations
Volume predictions become less accurate over longer time horizons
Performance varies based on market conditions and asset characteristics
Works best on liquid assets with consistent volume patterns
Requires sufficient historical data for pattern recognition
Sudden market events can disrupt prediction accuracy
Volume spikes may be muted in predictions due to normalization
💡 What Makes This Unique
Machine Learning Approach : Applies Lorentzian distance metrics for robust pattern matching
Algorithm Selection : Offers multiple prediction methods to suit different market conditions
Real-time Accuracy Tracking : Provides continuous feedback on prediction performance
Forward Projection : Visualizes multiple future bars with configurable display options
Normalized Scale : Presents volume as a percentage of maximum volume for consistent analysis
Interactive Dashboard : Displays key metrics with customizable appearance and placement
🔬 How It Works
The Volume Predictor processes market data through five main steps:
1. Volume Normalization:
Converts raw volume to percentage of maximum volume in lookback period
Creates consistent scale representation across different timeframes and assets
Stores historical normalized volumes for pattern analysis
2. Pattern Detection:
Identifies similar volume patterns in historical data
Uses Lorentzian distance metrics for robust similarity measurement
Determines strength of pattern match for prediction weighting
3. Algorithm Processing:
Applies selected prediction algorithm to historical patterns
For KNN/Lorentzian: Finds K nearest neighbors and calculates weighted prediction
For Ensemble: Combines multiple methods with optimized weighting
For EMA/Linear Regression: Projects trends based on statistical models
4. Accuracy Calculation:
Compares previous predictions to actual outcomes
Calculates average error and prediction accuracy
Updates performance metrics in real-time
5. Visualization:
Displays normalized actual volume with color-coding
Shows current and future volume predictions
Presents performance metrics through interactive dashboard
💡 Note:
The Volume Predictor performs optimally on liquid assets with established volume patterns. It’s most effective when used in conjunction with price action analysis and other technical indicators. The multi-algorithm approach allows adaptation to different market conditions by switching prediction methods. Pay special attention to the accuracy metrics when evaluating prediction reliability, as sudden market changes can temporarily reduce prediction quality. The normalized percentage scale makes the indicator consistent across different assets and timeframes, providing a standardized approach to volume analysis.
Enhanced VSA Volume & Candle Colors with MA SelectionOverview:
This script aims to enhance the visualization of volume spikes and price action by coloring volume bars and price candles dynamically based on the volume behavior. It allows traders to customize the type of volume moving average (SMA, EMA, or VWMA) used and apply various color schemes to highlight high, low, and extreme volume conditions. Additionally, alerts are generated when extreme or low-volume conditions occur.
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Key Features:
Customizable Volume Lookback Period:
The script allows users to define the period for calculating the moving average of volume (default: 200).
Volume Multiplier Settings:
High and low volume thresholds are defined using multipliers. Users can adjust these to customize how volume is categorized (default multipliers: 1.5 for high volume, 0.5 for low volume).
Percentile-Based Extreme Volume Detection:
The script calculates a percentile threshold for extreme volume (default: 90th percentile) based on the volume data, highlighting exceptionally high volume spikes.
Moving Average Selection:
Users can choose between Simple Moving Average (SMA), Exponential Moving Average (EMA), or Volume Weighted Moving Average (VWMA) to track volume trends over the selected lookback period.
Volume-Based Price Bar Coloring:
Price bars can be colored according to the volume conditions (high, low, or extreme). This feature can be toggled on or off.
Dynamic Transparency and Color Customization:
The script allows users to set custom colors for different volume conditions (high, low, neutral, extreme) and adjusts the transparency of volume bars based on the relative size of the volume.
Alerts:
Alerts can be set for when extreme volume spikes or low volume conditions are detected.
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Script Components:
Volume Histogram Plot:
Displays the volume bars with dynamic coloring based on the volume condition (high, low, or extreme). The color of the bars adjusts for clarity, with transparency based on volume levels.
Moving Average Plot:
Plots the selected volume moving average (SMA, EMA, or VWMA) to visualize the trend of volume over the chosen lookback period.
Smoothed Average Volume (EMA of Volume):
A smoothed EMA line is plotted to provide a clear representation of volume trends over time.
Price Bar Coloring:
If enabled, price bars are colored according to the current volume condition, providing immediate visual feedback to the trader.
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How It Can Be Used:
Volume Analysis for Entry/Exit Points: Traders can use the volume conditions (high, low, and extreme) to identify potential entry or exit points. High-volume bars often signal strong market activity, while low-volume bars may indicate consolidation or indecision.
Volume Confirmation for Trend Reversal: Extreme volume spikes can sometimes precede significant price movements. Traders can monitor these spikes for potential trend reversal signals.
Customizing Alerts: Alerts based on volume conditions help traders stay updated on important volume events without constantly monitoring the chart.
Color-Coded Price Action: The dynamic coloring of price bars makes it easier to identify periods of strong or weak market participation, allowing traders to make informed decisions quickly.
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Compliance with TradingView's House Rules:
No Promotion of Financial Products: The script does not promote any specific financial instruments or products, ensuring compliance with TradingView’s content guidelines.
Clear Functionality: The script provides clear, functional analysis tools without making unsupported claims about predicting market movements.
No Automated Trading: The script does not include any automated trading or order execution features, which complies with TradingView’s policy on non-automated scripts.
This breakdown ensures clarity on the script’s purpose, features, and how it might be used by traders. It's written in a way that fits TradingView's content guidelines, keeping the focus on providing valuable analytical tools rather than making promises or promoting any financial product.
Advanced Support and Resistance Levels[MAP]Advanced Support and Resistance Levels Indicator
Author
Developed by:
Overview
The "Advanced Support and Resistance Levels" indicator, created, is a sophisticated tool designed for TradingView's Pine Script v6 platform. It identifies and plots key support and resistance levels on a price chart, enhancing technical analysis by incorporating pivot strength, volume weighting, and level decay. The indicator overlays lines, zones, and labels on the chart, providing a visual representation of significant price levels where the market has historically reversed or consolidated.
Purpose
This indicator, authored by , aims to:
Detect significant pivot points (highs and lows) with customizable strength requirements.
Track and rank support/resistance levels based on their recency, volume, and number of touches.
Display these levels as lines and optional zones, with strength-based visual cues (e.g., line thickness and opacity).
Offer flexibility through user-configurable settings to adapt to different trading styles and market conditions.
Features
Pivot Detection:
Identifies high and low pivots using a strength parameter, requiring a specified number of bars on either side where no higher highs or lower lows occur.
Incorporates closing price checks and SMA-based trend confirmation to filter out noise and ensure pivots align with the broader market direction.
Level Management:
Maintains a dynamic array of levels with attributes: price, type (support/resistance), bars since last touch, strength, and volume.
Merges nearby levels within a tolerance percentage, updating prices with a strength-weighted average.
Prunes weaker or older levels when exceeding the maximum allowed, prioritizing those with higher calculated strength.
Strength Calculation:
Combines the number of touches (strength), volume (if enabled), and age decay (if enabled) into a single metric.
Volume weighting uses a logarithmic scale to emphasize high-volume pivots without over-amplifying extreme values.
Age decay reduces the importance of older levels over time, ensuring relevance to current price action.
Visualization:
Draws horizontal lines at each level, with thickness reflecting the number of touches (up to a user-defined maximum).
Optional price zones around levels, sized as a percentage of the price, to indicate areas of influence.
Labels display the level type (S for support, R for resistance), price, and strength score, with position (left or right) customizable.
Line opacity varies with strength, providing a visual hierarchy of level significance.
Plots small triangles at detected pivot points for reference.
Inputs
Lookback Period (lookback, default: 20): Number of bars to consider for trend confirmation via SMA. Range: 5–100.
Pivot Strength (strength, default: 2): Number of bars required on each side of a pivot to confirm it. Range: 1–10.
Price Tolerance % (tolerance, default: 0.5): Percentage range for merging similar levels. Range: 0.1–5.
Max Levels to Show (maxLevels, default: 10): Maximum number of levels displayed. Range: 2–50.
Zone Size % (zoneSizePercent, default: 0.1): Size of the S/R zone as a percentage of the price. Range: 0–1.
Line Width (lineWidth, default: 1): Maximum thickness of level lines. Range: 1–5.
Show Labels (showLabels, default: true): Toggle visibility of level labels.
Label Position (labelPos, default: "Right"): Position of labels ("Left" or "Right").
Level Strength Decay (levelDecay, default: true): Enable gradual reduction in strength for older levels.
Volume Weighting (volumeWeight, default: true): Incorporate volume into level strength calculations.
Support Color (supportColor, default: green): Color for support levels.
Resistance Color (resistColor, default: red): Color for resistance levels.
How It Works
Pivot Detection:
Checks for pivots only after enough bars (2 * strength) have passed.
A high pivot requires strength bars before and after with no higher highs or closes, and a short-term SMA above a long-term SMA.
A low pivot requires strength bars before and after with no lower lows or closes, and a short-term SMA below a long-term SMA.
Level Tracking:
New pivots create levels with initial strength and volume.
Existing levels within tolerance are updated: strength increases, volume takes the maximum value, and price adjusts via a weighted average.
Levels older than lookback * 4 bars with strength below 0.5 are removed.
If the number of levels exceeds maxLevels, the weakest (by calculated strength) are pruned using a selection sort algorithm.
Drawing:
Updates on the last confirmed bar or in real-time.
Lines extend lookback bars left and right from the current bar, with thickness based on touches.
Zones (if enabled) are drawn symmetrically around the level price.
Labels show detailed info, with opacity tied to strength.
Usage
Add to Chart: Apply the indicator to any TradingView chart via the Pine Script editor, as designed by .
Adjust Settings: Customize inputs to match your trading strategy (e.g., increase strength for stronger pivots, adjust tolerance for tighter level merging).
Interpret Levels: Focus on thicker, less transparent lines for stronger levels; use zones to identify potential reversal areas.
Combine with Other Tools: Pair with trend indicators or oscillators for confluence in trading decisions.
Notes
Performance: The indicator uses arrays and sorting, which may slow down on very long charts with many levels. Keep maxLevels reasonable for efficiency.
Accuracy: Enhanced by trend confirmation and volume weighting, making it more reliable than basic S/R indicators, thanks to 's design.
Limitations: Real-time updates may shift levels as new pivots form; historical levels are more stable.
Example Settings
For day trading: lookback=10, strength=1, tolerance=0.3, maxLevels=5.
For swing trading: lookback=50, strength=3, tolerance=0.7, maxLevels=10.
Credits
Author: – Creator of this advanced support and resistance tool, blending precision and customization for traders.
Cumulative Price Change AlertCumulative Price Change Alert
Version: 1.0
Author: QCodeTrader 🚀
Overview 🔍
The Cumulative Price Change Alert indicator analyzes the percentage change between the current and previous open prices and sums these changes over a user-defined number of bars. It then generates visual buy and sell signals using arrows and labels on the chart, helping traders spot cumulative price momentum and potential trading opportunities.
Key Features ⚙️
Customizable Timeframe 🕒:
Use a custom timeframe or default to the chart's timeframe for price data.
User-Defined Summation 🔢:
Specify the number of bars to sum, allowing you to analyze cumulative price changes.
Custom Buy & Sell Conditions 🔔:
Set individual percentage change thresholds and cumulative sum thresholds to tailor signals for
your strategy.
Visual Alerts 🚀:
Displays green upward arrows for buy signals and red downward arrows for sell signals directly
on the chart.
Informative Labels 📝:
Provides labels with formatted percentage change and cumulative sum details for the analyzed
bars.
Versatile Application 📊:
Suitable for stocks, forex, crypto, commodities, and more.
How It Works ⚡
Price Change Calculation ➗:
The indicator calculates the percentage change between the current bar's open price and the
previous bar's open price.
Cumulative Sum ➕:
It then sums these percentage changes over the last N bars (as specified by the user).
Signal Generation 🚦:
Buy Signal 🟢: When both the individual percentage change and the cumulative sum exceed
their respective buy thresholds, a green arrow and label are displayed.
Sell Signal 🔴: Conversely, if the individual change and cumulative sum fall below the sell
thresholds, a red arrow and label are shown.
How to Use 💡
Add the Indicator ➕:
Apply the indicator to your chart.
Customize Settings ⚙️:
Set a custom timeframe if desired.
Define the number of bars to sum.
Adjust the buy/sell percentage change and cumulative sum thresholds to match your trading
strategy.
Interpret Visual Cues 👀:
Monitor the chart for green or red arrows and corresponding labels that signal potential buy or
sell opportunities based on cumulative price movements.
Settings Explained 🛠️
Custom Timeframe:
Select an alternative timeframe for analysis, or leave empty to use the current chart's timeframe.
Number of Last Bars to Sum:
Determines how many bars are used to compute the cumulative percentage change.
Buy Condition - Min % Change:
The minimum individual percentage change required to consider a buy signal.
Buy Condition - Min Sum of Bars:
The minimum cumulative percentage change over the defined bars needed for a buy signal.
Sell Condition - Max % Change:
The maximum individual percentage change threshold for a sell signal.
Sell Condition - Max Sum of Bars:
The maximum cumulative percentage change over the defined bars for triggering a sell signal.
Best Use Cases 🎯
Momentum Identification 📈:
Quickly spot strong cumulative price movements and momentum shifts.
Entry/Exit Signals 🚪:
Use the visual signals to determine potential entry and exit points in your trading.
Versatile Strategy Application 🔄:
Effective for scalping, swing trading, and longer-term analysis across various markets.
UPD: uncheck labels for better performance
Time Change Indicator-AYNETDetailed Scientific Explanation of the Time Change Indicator Code
This Pine Script code implements a financial indicator designed to measure and visualize the percentage change in the closing price of an asset over a specified timeframe. It uses historical data to calculate changes and displays them as a histogram for intuitive analysis. Below is a comprehensive scientific breakdown of the code:
1. User Inputs
The script begins by defining user-configurable parameters, enabling flexibility in analysis:
timeframe: The user selects the timeframe for measuring price changes (e.g., 1 hour, 1 day). This determines the granularity of the analysis.
positive_color and negative_color: Users choose the colors for positive and negative changes, enhancing visual interpretation.
2. Data Retrieval
The script employs request.security to fetch closing price data (close) for the specified timeframe. This function ensures that the indicator adapts to different timeframes, providing consistent results regardless of the chart's base timeframe.
Current Closing Price (current_close):
current_close
=
request.security(syminfo.tickerid, timeframe, close)
current_close=request.security(syminfo.tickerid, timeframe, close)
Retrieves the closing price for the defined timeframe.
Previous Closing Price (prev_close): The script uses a variable (prev_close) to store the previous closing price. This variable is updated dynamically as new data is processed.
3. Price Change Calculation
The script calculates both the absolute and percentage change in closing price:
Absolute Price Change (price_change):
price_change
=
current_close
−
prev_close
price_change=current_close−prev_close
Measures the difference between the current and previous closing prices.
Percentage Change (percent_change):
percent_change
=
price_change
prev_close
×
100
percent_change=
prev_close
price_change
×100
Normalizes the change relative to the previous closing price, making it easier to compare changes across different assets or timeframes.
4. Conditional Logic for Visualization
The script uses a conditional statement to determine the color of each histogram bar:
Positive Change: If price_change > 0, the bar is assigned the user-defined positive_color.
Negative Change: If price_change < 0, the bar is assigned the negative_color.
This differentiation provides a clear visual cue for understanding price movement direction.
5. Visualization
The script visualizes the percentage change using a histogram and enhances the chart with dynamic labels:
Histogram (plot.style_histogram):
Each bar represents the percentage change for a given timeframe.
Bars above the zero line indicate positive changes, while bars below the zero line indicate negative changes.
Zero Line (hline(0)): A reference line at zero provides a baseline for interpreting changes.
Dynamic Labels (label.new):
Each bar is annotated with its exact percentage change value.
The label's position and color correspond to the bar, improving clarity.
6. Algorithmic Flow
Data Fetching: Retrieve the current and previous closing prices for the specified timeframe.
Change Calculation: Compute the absolute and percentage changes between the two prices.
Bar Coloring: Determine the color of the histogram bar based on the change's direction.
Plotting: Visualize the changes as a histogram and add labels for precise data representation.
7. Applications
This indicator has several practical applications in financial analysis:
Volatility Analysis: By visualizing percentage changes, traders can assess the volatility of an asset over specific timeframes.
Trend Identification: Positive and negative bars highlight periods of upward or downward momentum.
Cross-Asset Comparison: Normalized percentage changes enable the comparison of price movements across different assets, regardless of their nominal values.
Market Sentiment: Persistent positive or negative changes may indicate prevailing bullish or bearish sentiment.
8. Scientific Relevance
This script applies fundamental principles of data visualization and time-series analysis:
Statistical Normalization: Percentage change provides a scale-invariant metric for comparing price movements.
Dynamic Data Processing: By updating the prev_close variable with real-time data, the script adapts to new market conditions.
Visual Communication: The use of color and labels improves the interpretability of quantitative data.
Conclusion
This indicator combines advanced Pine Script functions with robust financial analysis techniques to create an effective tool for evaluating price changes. It is highly adaptable, providing users with the ability to tailor the analysis to their specific needs. If additional features, such as smoothing or multi-timeframe analysis, are required, the code can be further extended.
Price Action All In OneThis indicator represents the most advanced level of price action indicators, incorporating six useful features: traditional gaps, shadow gaps, bar counting, moving averages, previous values, and IO pattern matching .
When I refer to price action, I mean the teachings of Dr. Al Brooks.
While you can find these features in other indicators, mine is more advanced. The default settings are designed to work on a 5-minute timeframe, but you can also use this indicator on other time periods if you prefer.
Gaps
Traditional Gaps: Occurs when the lowest price of a bar is higher than the highest price of the previous bar, or the highest price of a bar is lower than the lowest price of the previous bar.
Shadow/Tail Gaps: Occurs when the lowest price of a bar is higher than the highest price of the second last bar, or the highest price of a bar is lower than the lowest price of the second last bar.
Gaps indicate strength, and consecutive gaps in one direction are characteristic of a strong trend. They offer a perspective on the strength of a trend, signifying that limit orders on one side are at a loss with no opportunity to exit at breakeven. Can bulls or bears create gaps? Are the gaps they create filled, or do they remain open?
Traditional Gaps & Shadow/Tail Gaps
Bar Counting
The ability to use different timeframes (e.g., to determine the minute within an hour or the hour within a week).
Consistent display of 1; in other indicators, if you set intervals to 2, you see 2, 4, 6, etc., or 1, 2, 4, 6. In my indicator, you will see 1, 3, 5, etc.
In intraday trading, certain specific times are more important than others. For example, a form of reversal is more likely to occur at the midpoint of the trading day (if there are 80 candles in a day, the midpoint is at the 40th candle).
This doesn't mean you should make reversal trades at the 40th candle. The bar count feature simply reminds you of the current time, helping you gauge how long until the trading day ends. For instance, if there are 80 candles in a day and you're an intraday trader, you probably shouldn't make a swing trade at the 70th candle because there are only 10 candles left until the close—likely not enough time for a swing to develop.
Additionally, if you trade on a 5-minute timeframe, seeing candles numbered 3, 6, 9, etc. indicates the close of a 15-minute candle. This means that in addition to 5-minute timeframe traders, 15-minute timeframe traders will also pay attention to these candles, making them more significant. For the same reason, the 12th candle is crucial, as its close also marks the close of an hourly candle.
Day Time Frame & Week Time Frame
Moving Averages
Provides three EMAs. You can set different timeframes and choose between continuous or discrete modes.
Moving averages are excellent tools for determining trends. The 20 EMA is particularly popular, which increases its significance. Traders using different timeframes, such as 5-minute, 15-minute, and 1-hour, all utilize the 20 EMA. This indicator allows you to see what traders on 15-minute and 1-hour timeframes are observing, even when you're on a 5-minute timeframe.
Once again, the default settings of this indicator assume that the user is trading intraday on a 5-minute timeframe. However, if that's not the case, you can easily adjust the moving average periods. For instance, if you trade on a 1-hour timeframe and want to display the 4-hour and daily moving averages on your chart, this can be done effortlessly.
5m 20, 15m 20 & 1h 20
Previous Values
Features three previous value displays. You can set their sources and timeframes independently and define the range for all previous values.
For intraday trading, marking the previous day's high, low, and close prices can be crucial. While some other indicators provide this feature, mine does it better. You can set different timeframes and choose various sources. For example, you might want to display the average of (O+H+L+C)/4 for the last week.
In addition to setting the timeframe and source, you can also configure the display range:
All: This will show the data in all positions. For example, you can see the high price from two days ago on yesterday's chart.
Today: This will only display the previous day's high price on the current day's chart.
Timeframe: This will display the data based on the specified timeframe you set.
Last Week High, Last Day Close & Low(Timeframe Display)
IO Pattern Matching
More advanced than other IO pattern matching indicators. For adjacent IIs, it merges to display as III, IIII, and so on. The same applies to OO patterns. Additionally, it automatically merges adjacent IOI and II into IOII, and adjacent OO and IOI into IIOI.
II Pattern: This refers to two consecutive inside bar candles. On a lower timeframe, the II pattern forms a converging triangle, which is a breakout pattern. The II pattern could also potentially become a final flag, which is the last flag in a trend.
OO Pattern: This refers to two consecutive outside bar candles. On a lower timeframe, the OO pattern forms an expanding triangle. You can use the OO pattern similarly to how you would use an expanding triangle.
IOI Pattern: This pattern occurs when the first candle is contained within the second candle, and the third candle is also contained within the second candle. This is a breakout pattern and could similarly represent a terminal flag in a trend.
The appearance of II, OO, or IOI patterns does not necessarily mean you should make a reversal trade. These patterns are meant to mark potential moves in a lower timeframe within the current cycle, providing a new perspective on the market and reminding you to stay vigilant.
You shouldn't look for IO patterns in a tight trading range. There are many IO patterns in a tight trading range, but they don't hold much significance.
II, OO & IOI
Common Volume Spike Indicator with Price Color on SpikeIndicator Name: Common Volume Spike Indicator with Price Color on Spike
Description:
The “Common Volume Spike Indicator with Price Color on Spike” is designed to detect significant volume spikes and highlight them on the chart. It not only identifies moments when the trading volume exceeds a certain threshold but also colors the price bars based on price movement during these spikes.
Key Features:
• Volume Spike Detection: Detects volume spikes when the current volume exceeds a specified multiple of the average volume over a user-defined lookback period.
• Dynamic Volume Break: Highlights bars where the volume exceeds a threshold, dynamically calculated as a multiple of the average volume (default is 10x the average volume).
• Price Color on Volume Spike: When a volume spike occurs, bars are colored green if the price closes higher than the previous bar, and red if the price closes lower. This feature helps traders easily identify significant price movements during high-volume periods.
• Customizable Parameters:
• Threshold Multiplier: Adjust the sensitivity of volume spike detection.
• Lookback Period: Define the period over which the average volume is calculated.
• Volume Break Multiplier: Set a multiplier for the average volume to identify extreme volume breaks.
This indicator is suitable for traders who want to quickly spot critical market events driven by significant increases in volume. It helps to visualize both the volume activity and the corresponding price movement, providing an additional layer of market insight.
How to Use:
1. Green Bars: When the volume spike condition is met and the price closes higher than the previous bar, the bar is colored green.
2. Red Bars: When the volume spike condition is met and the price closes lower than the previous bar, the bar is colored red.
3. Blue Bars: Indicates a significant volume break, where the current volume exceeds a specified multiple of the average volume (default: 10x).
Ideal for intraday and swing traders who rely on volume and price action for market entries and exits. This indicator works well across different asset classes, including stocks, forex, and cryptocurrencies.
You can adjust the input parameters to fit your specific trading strategy and timeframe.
Disclaimer: This indicator is a tool to help with market analysis and should not be considered financial advice. Always perform your own due diligence before making any trading decisions.
This description outlines the key functionality and how the indicator can benefit traders on TradingView.
VWAP with Trend Alerts [CrossTrade]The VWAP with Trend Alerts indicator is designed to provide a comprehensive visual and analytical tool for traders using the Volume Weighted Average Price (VWAP) along with additional features like custom bar coloring and trend-based signal alerts.
Key Components and Functionalities:
1. VWAP Calculation: The core of this indicator is the VWAP, which represents the average price of an asset, weighted by volume. It's a popular tool among traders to identify the general direction and strength of a trend, and for assessing entry and exit points.
2. Standard Deviation Bands: Surrounding the VWAP are multiple bands calculated based on standard deviation values. These bands serve as dynamic support and resistance levels. The script allows up to three bands, each with customizable multipliers, giving insights into price volatility and potential breakout or reversal points.
3. Bar Coloring Options:
- Color All Bars: When enabled, all bars on the chart are colored based on whether they close above (green) or below (red) the VWAP.
- Trend Bars Only: This option, when selected, colors only the bars that close beyond the second standard deviation band. It helps in identifying stronger trends and significant market movements.
4. Buy and Sell Signal Conditions: The script includes conditions for buy and sell signals specifically tailored for trend bars. A buy signal is generated when a bar closes above both the VWAP and the upper second standard deviation band, indicating a potential strong uptrend. Conversely, a sell signal is triggered when a bar closes below both the VWAP and the lower second standard deviation band, suggesting a strong downtrend.
5. Alert Conditions: To aid in timely decision-making, the script features alert conditions corresponding to the buy and sell signals.
Usage and Application:
- For Trend Identification: The VWAP and its bands can help identify the prevailing market trend. Bars closing consistently above the VWAP suggest an uptrend, while those closing below indicate a downtrend.
- Volatility Assessment: The standard deviation bands provide a visual representation of market volatility. Narrower bands suggest low volatility, while wider bands indicate high volatility.
- Signal Alerts for Trading: The buy and sell signals, especially those filtered by the trend bars condition, can be valuable for traders looking for strong movement confirmations.
Flexibility and Customization:
This indicator is highly customizable and builds off of the core logic found in standard VWAP indicators. By allowing traders to adjust the standard deviation multipliers and choose their preferred bar coloring strategy. It caters to various trading styles, whether focusing on the broader market trend or pinpointing significant trend-based movements.
Moving average to price cloudHi all!
This indicator shows when the price crosses the defined moving average. It plots a green or red cloud (depending on trend) and the moving average. It also plots an arrow when the trend changes (this can be disabled in 'style'->'labels' in the settings).
The moving average itself can be used as dynamic support/resistance. The trend will change based on your settings (described below). By default the trend will change when the whole bar is above/below the moving average for 2 bars (that's closed). This can be changed by "Source" and "Bars".
Settings
• Length (choose the length of the moving average. Defaults to 21)
• Type (choose what type of moving average).
- "SMA" (Simple Moving Average)
- "EMA" (Exponential Moving Average)
- "HMA" (Hull Moving Average)
- "WMA" (Weighted Moving Average)
- "VWMA" (Volume Weighted Moving Average)
- "DEMA" (Double Exponential Moving Average)
Defaults to"EMA".
• Source (Define the price source that must be above/below the moving average for the trend to change. Defaults to 'High/low (passive)')
- 'Open' The open of the bar has to cross the moving average
- 'Close' The close of the bar has to cross the moving average
- 'High/low (passive)' In a down trend: the low of the bar has to cross the moving average
- 'High/low (aggressive)' In a down trend: the high of the bar has to cross the moving average
• Source bar must be close. Defaults to 'true'.
• Bars (Define the number bars whose value (defined in 'Source') must be above/below the moving average. All the bars (defined by this number) must be above/below the moving average for the trend to change. Defaults to 2.)
Let me know if you have any questions.
Best of trading luck!
Uptrick: Volume StrengthPurpose:
The "Uptrick: Volume Strength" indicator, known by its short title 'VolStrength,' is meticulously designed to evaluate the strength of volume activity within a market, providing traders with valuable insights into liquidity dynamics. By visualizing volume bars and comparing them to a predefined threshold, traders can gauge the intensity of buying or selling pressure, thereby assessing market liquidity and potential price movements.
Explanation:
Input Parameters:
Traders benefit from the ability to customize the threshold for high volume, allowing them to adapt the indicator to varying market conditions and trading strategies.
The calculation of the average volume over a specified period adds depth to the analysis, offering traders a reference point for assessing current volume levels relative to historical averages and evaluating liquidity trends.
Volume Analysis:
The script discerns between bars where the closing price exceeds the opening price (up bars) and bars where the closing price is lower than the opening price (down bars), facilitating the identification of bullish or bearish market sentiment.
High-volume bars that surpass the predefined threshold are prominently highlighted, serving as indicators of increased trading activity and enhanced liquidity levels.
Average Volume Visualization:
A line representing the average volume over the specified period is plotted on the chart, providing traders with a visual reference for evaluating current volume levels against historical averages. This aids in assessing the overall liquidity conditions in the market.
Volume Bar Representation:
The colorization of volume bars is contingent upon their direction (up or down) and whether they exceed the high volume threshold.
Up bars, symbolizing buying pressure, are typically depicted in green, while down bars, indicative of selling pressure, are rendered in red.
Notably, when volume surpasses the high volume threshold, the respective bar color is applied, accentuating significant volume spikes and their potential impact on liquidity and price dynamics.
Through its meticulous design and comprehensive features, the "Uptrick: Volume Strength" indicator equips traders with actionable insights into market liquidity dynamics. By integrating volume analysis into their trading strategies, traders can effectively assess liquidity conditions, identify potential price movements, and make informed trading decisions.
Median RSI**Description:**
The "Median RSI with Buy/Sell Signals and Bar Color" indicator on TradingView calculates the median Relative Strength Index (RSI) alongside buy and sell signals and customizable bar colors. RSI is a momentum oscillator that measures the speed and change of price movements. This indicator provides traders with insights into the relative strength of a security by comparing its recent gains to its recent losses.
**How it Works:**
1. **RSI Calculation:** The script computes the RSI using a specified length parameter. This RSI value indicates whether a security is overbought or oversold, helping traders identify potential reversal points.
2. **Median RSI Calculation:** It calculates the highest and lowest RSI values over a certain period and finds the median value. This median RSI acts as a benchmark, guiding traders in assessing the relative strength of a security compared to its recent performance.
3. **Bar Color Customization:** The script allows users to customize the bar color based on the relationship between the RSI and the median RSI. Bars are colored differently to visually represent whether the RSI is above, below, or equal to the median RSI. Additionally, the script highlights bars when they cross the median RSI, providing visual cues for potential shifts in market momentum.
**Benefits:**
- **RSI Insights:** Provides insights into the relative strength of a security by comparing its recent gains to its recent losses.
- **Buy/Sell Signals:** Generates buy and sell signals based on the RSI crossing above or below the median RSI, aiding traders in timing their trades.
- **Customizable Bar Colors:** Allows traders to customize bar colors based on the relationship between the RSI and the median RSI, facilitating quick visual analysis.
- **Visual Representation:** Visualizes the RSI median RSI, and bar color on the price chart for easy interpretation.
**Ideal Usage:**
- **Trend Confirmation:** Traders can use the indicator to confirm the direction of the trend before entering trades.
- **Reversal Signals:** Changes in RSI direction, indicated by crosses above or below the median RSI, can signal potential reversals in market momentum.
- **Combination with Other Indicators:** It can be used in conjunction with other technical indicators to enhance trading strategies, providing additional confirmation signals.
**Warnings:**
- **False Signals:** Like any technical indicator, false signals may occur, especially during periods of low volume or choppy market conditions. Additional analysis and risk management techniques should be used to avoid potential losses.
- **Parameter Sensitivity:** Traders should test different parameter settings and consider market conditions when using the indicator, as adjustments may affect its sensitivity to price movements.
By providing insights into RSI dynamics, and offering customizable bar colors, the "Median RSI with Buy/Sell Signals and Bar Color" indicator equips traders with valuable tools for technical analysis and decision-making in the financial markets.
Kaufman Efficiency Ratio-Based Risk PercentageOVERVIEW
The Kaufman Efficiency Ratio-Based Exposure Management indicator uses the Kaufman Efficiency Ratio (KER) to calculate how much you should risk per trade.
If KER is high, then the indicator will tell you to risk more per trade.
A high KER value indicates a trending market, so if you are a trend trader, it makes sense to risk more during these times.
If KER is low, then the indicator will tell you to risk less per trade.
A low KER value indicates a trending market, so if you are a trend trader, it makes sense to risk less during these times.
CONCEPTS
The Kaufman Efficiency Ratio (also known as the Efficiency Ratio, KER, or ER) is a separate indicator developed by Perry J. Kaufman and first published in Kaufman's book, "New Trading Systems and Methods" in 1987.
The KER used to measure the efficiency of a financial instrument's price movement. It is calculated as follows:
KER = (change in price over x bars) / (sum of absolute price changes over x bars)
The first part of the formula, "change in price over x bars" measures the difference between the current close price and the close price x bars ago. The second part of the formula "sum of absolute price changes over x bars" measures the sum of the |open-close| range of each bar between now and x bars ago.
If there is a high change in price over x bars relative to the sum of absolute price changes over x bars, a trending/volatile market is likely in place.
If there is a low change in price over x bars relative to the sum of absolute price changes over x bars, a ranging/choppy market is likely in place.
If you are a trend trader, you can assume that entries taken during high KER periods are more likely to lead to a trend. This indicator helps capitalize on that assumption by increasing risk % per trade during high KER periods, and decreasing risk % per trade during low KER periods.
It uses the following formulas to calculate a KER-adjusted risk % per trade:
Linearly-increasing risk % = min risk + (KER * (max risk - min risk))
Exponentially-increasing risk % = min risk + ((KER^n) * (max risk - min risk))
min risk = the smallest amount you'd be willing to risk on a trade
max risk = the largest amount you'd be willing to risk on a trade
KER = the current Kaufman Efficiency Ratio value
n = an exponent factor used to control the rate of increase of the risk %
Here is an example of how these formulas work:
Assuming that min risk is 0.5%, max risk is 2%, and KER is 0.8 (indicating a trending market), we can calculate the following risk per trade amounts:
Linearly-increasing risk % = 0.5 + (0.8 * (2 - 0.5)) = 1.7%
Exponentially-increasing risk % = 0.5 + ((0.8^3) * (2 - 0.5)) = 1.27%
Now, lets do the same calculations with a lower KER of 0.2 , which indicates a choppy market:
Linearly-increasing risk % = 0.5 + (0.2 * (2 - 0.5)) = 0.8%
Exponentially-increasing risk % = 0.5 + ((0.2^3) * (2 - 0.5)) = 0.51%
With a high KER, we risk more per trade to capitalize on the higher chance of a trending market. With a lower KER, we risk less per trade to protect ourselves from the higher chance of a choppy market.
MACDh with divergences & impulse system (overlayed on prices)-----------------------------------------------------------------
General Description:
This indicator ( the one on the top panel above ) consists on some lines, arrows and labels drawn over the price bars/candles indicating the detection of regular divergences between price and the classic MACD histogram (shown on the low panel). This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra features" Impulse System and Keltner Channels, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
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Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
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Some cool features included in this indicator:
1. This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Price bars are colored blue when conditions for a Red Price Bar or Green Price Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green price bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red price bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue price bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
2. Another "extra feature" included here is the " Keltner Channels ". Keltner Channels are volatility-based envelopes set above and below an exponential moving average.
3. It were also included a couple of EMAs.
Everything can be removed from the chart any time.
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Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*Shows a pair of EMAs.
*Shows Keltner Channels (using ATR)
Keltner Channels are volatility-based envelopes set above and below an exponential moving average.
*This indicator also has the option to show the Impulse System over the price bars/candles.
MACDh with divergences & impulse system-----------------------------------------------------------------
General Description:
This indicator ( the one on the low panel ) is a classic MACD that also shows regular divergences between its histogram and the prices. This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra feature" Impulse System, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
-----------------------------------------------------------------
Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
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Extra feature: Impulse System
This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars or macd histogram bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Histogram bars are colored blue when conditions for a Red Histogram Bar or Green Histogram Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green histogram bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red histogram bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue histogram bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
The impulse system can be removed from the chart any time.
-----------------------------------------------------------------
Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*This indicator also has the option to show the Impulse System over the MACD histogram bars
RSI Xray + VolumeRSI Analysis:
The indicator calculates the Relative Strength Index (RSI) using a user-defined length (default: 14).
It colors the bars based on RSI levels to identify potential overbought and oversold conditions.
Bars exceeding the overbought level (default: 70) are colored, while bars below the oversold level (default: 30) are colored too.
This helps traders identify potential trend reversals or market exhaustion points.
Midpoint Analysis:
The indicator calculates the midpoint of each bar, which is the average of the high and low prices.
It colors the bars based on their relation to the midpoint.
Bars above the midpoint are colored, indicating potential bullish momentum.
Bars below the midpoint are colored, suggesting potential bearish momentum.
Volume Analysis:
The indicator offers the ability to analyze volume changes and identify high volume bars.
It colors the bars when the volume exceeds a user-defined threshold.
This feature helps traders identify potential areas of market interest and increased participation.
Moving Average (SMA):
The indicator plots a Simple Moving Average (SMA) line of the closing price over a user-defined period (default: 9).
This moving average line helps traders identify potential trends and spot areas of support or resistance.
RSI Extreme Conditions:
The indicator identifies extreme RSI conditions by comparing the current RSI value with the highest and lowest RSI values calculated from a user-defined number of previous bars (default: 10).
When the RSI exceeds the overbought level but is lower than the highest RSI value within the specified range, the bar color changes to a customizable color (default: blue).
Conversely, when the RSI falls below the oversold level but is higher than the lowest RSI value within the specified range, the bar color changes to the same customizable color.
This feature helps traders identify potential RSI-based trading opportunities and market turning points.
Customization:
The indicator offers customizable settings for colors, RSI levels, SMA length, volume thresholds, RSI extreme levels, and RSI label color.
Traders can modify these settings based on their preferences and trading strategies.
Overall, the 'RSI Xray + Volume' indicator provides a comprehensive view of RSI levels, market momentum, volume changes, and RSI extreme conditions. Traders can use this information to identify potential trade setups, validate market trends, and make more informed trading decisions. It can be applied to various timeframes and instruments, making it a valuable tool for both short-term and long-term traders.
Sushi Trend [HG]🍣 The Sushi Roll, a trading concept conceived at a restaurant by Mark Fisher.
While the indicator itself goes by Sushi Trend, it is completely backed by the idea of Mark Fisher's Sushi Roll Reversal Pattern. No, it has nothing to do with raw fish, it just so happens that somebody was ordering sushi during the discussion of the idea, and that's how it got its name.
📝 Origin
First mentioned in his book, The Logical Trader --- the idea of the Sushi Roll is to serve as an early warning system to identify reversals in the market. Fisher defines the pattern as a series of 10 bars, split into two different sections, seen as 5 and 5. In order for the pattern to be emitted, the 5 bars to the right must completely engulf the 5 bars to the left. It's not a super complex system and is in fact extremely simple to grasp.
📈 Supertrend Similarities
Instead of displaying the pattern in the way Fisher meant for it to be portrayed (as seen in the photo above), I instead turned it into an indicator similar to that of Supertrend while also inheriting the same concepts from the pattern. I did this because the pattern itself has inconsistencies which can be quite noticeable when trading with it after a while. For example, these patterns can occur even during consolidating periods, and even though the pattern is meant to be recognized during trending markets, the engulfing bars can sometimes be left with indecisive directions.
➡️ The Result
Here is the result, visualized to be better in a trending format. (The indicator will not contain the boxes.)
While Fisher does mention the pattern to include 10 bars, you can actually use this pattern with any number of bars. At the end of the day, it's a concept derived from a discussion at a Japanese restaurant, and a pattern that has been around for years that has seen results. Due to this, I added an input option to control the series of bars for right-bar engulf detection.
To reassure the meaning of the pattern --> "A series of 10 bars" means 5 left bars and 5 right bars. So if you want to check if 5 right bars are engulfing the previous 5 bars (as seen in the photo above), you would want to select 5 in the input settings.
You can learn more about it from the following links
Market Reversals and the Sushi Roll Technique
The Logical Trader
libKageMiscLibrary "libKageMisc"
Kage's Miscelaneous library
print(_value)
Print a numerical value in a label at last historical bar.
Parameters:
_value : (float) The value to be printed.
Returns: Nothing.
barsBackToDate(_year, _month, _day)
Get the number of bars we have to go back to get data from a specific date.
Parameters:
_year : (int) Year of the specific date.
_month : (int) Month of the specific date. Optional. Default = 1.
_day : (int) Day of the specific date. Optional. Default = 1.
Returns: (int) Number of bars to go back until reach the specific date.
bodySize(_index)
Calculates the size of the bar's body.
Parameters:
_index : (simple int) The historical index of the bar. Optional. Default = 0.
Returns: (float) The size of the bar's body in price units.
shadowSize(_direction)
Size of the current bar shadow. Either "top" or "bottom".
Parameters:
_direction : (string) Direction of the desired shadow.
Returns: (float) The size of the chosen bar's shadow in price units.
shadowBodyRatio(_direction)
Proportion of current bar shadow to the bar size
Parameters:
_direction : (string) Direction of the desired shadow.
Returns: (float) Ratio of the shadow size per body size.
bodyCloseRatio(_index)
Proportion of chosen bar body size to the close price
Parameters:
_index : (simple int) The historical index of the bar. Optional. Default = 0.()
Returns: (float) Ratio of the body size per close price.
lastDayOfMonth(_month)
Returns the last day of a month.
Parameters:
_month : (int) Month number.
Returns: (int) The number (28, 30 or 31) of the last day of a given month.
nameOfMonth(_month)
Return the short name of a month.
Parameters:
_month : (int) Month number.
Returns: (string) The short name ("Jan", "Feb"...) of a given month.
pl(_initialValue, _finalValue)
Calculate Profit/Loss between two values.
Parameters:
_initialValue : (float) Initial value.
_finalValue : (float) Final value = Initial value + delta.
Returns: (float) Profit/Loss as a percentual change.
gma(_Type, _Source, _Length)
Generalist Moving Average (GMA).
Parameters:
_Type : (string) Type of average to be used. Either "EMA", "HMA", "RMA", "SMA", "SWMA", "WMA" or "VWMA".
_Source : (series float) Series of values to process.
_Length : (simple int) Number of bars (length).
Returns: (float) The value of the chosen moving average.
xFormat(_percentValue, _minXFactor)
Transform a percentual value in a X Factor value.
Parameters:
_percentValue : (float) Percentual value to be transformed.
_minXFactor : (float) Minimum X Factor to that the conversion occurs. Optional. Default = 10.
Returns: (string) A formated string.
isLong()
Check if the open trade direction is long.
Returns: (bool) True if the open position is long.
isShort()
Check if the open trade direction is short.
Returns: (bool) True if the open position is short.
lastPrice()
Returns the entry price of the last openned trade.
Returns: (float) The last entry price.
barsSinceLastEntry()
Returns the number of bars since last trade was oppened.
Returns: (series int)
getBotNameFrosty()
Return the name of the FrostyBot Bot.
Returns: (string) A string containing the name.
getBotNameZig()
Return the name of the FrostyBot Bot.
Returns: (string) A string containing the name.
getTicksValue(_currencyValue)
Converts currency value to ticks
Parameters:
_currencyValue : (float) Value to be converted.
Returns: (float) Value converted to minticks.
getSymbol(_botName, _botCustomSymbol)
Formats the symbol string to be used with a bot
Parameters:
_botName : (string) Bot name constant. Either BOT_NAME_FROSTY or BOT_NAME_ZIG. Optional. Default is empty string.
_botCustomSymbol : (string) Custom string. Optional. Default is empy string.
Returns: (string) A string containing the symbol for the bot. If all arguments are empty, the current symbol is returned in Binance format.
showProfitLossBoard()
Calculates and shows a board of Profit/Loss through the years.
Returns: Nothing.
AntaresLibrary "Antares"
this library contains some utility functions that I use in my open source scripts including moving average helpers, candlstick helpers, money management, formatters, convertors, webhook integration, analysis, filters and drawing helpers
ma(type, length, source)
Wraps all ma functions
Parameters:
type : Either SMA or EMA or RMA or WMA or VWMA
length : Number of bars (length).
source : Series of values to process.
Returns: Moving average of `source` for `length` bars back by the of MA.
bb(ma, length, mult, source)
Overwrites `ta.bb` duo to limitations of simple int.float mult. Bollinger Bands. A Bollinger Band is a technical analysis tool defined by a set of lines plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of the security's price, but can be adjusted to user preferences.
Parameters:
ma : Either SMA or EMA or RMA or WMA or VWMA
length : Number of bars (length).
mult : Standard deviation factor.
source : Series of values to process.
Returns: Bollinger Bands.
atr(length, h, l, c)
Overwrites `ta.atr` duo to limitations of simple int length. Function atr (average true range) returns the RMA of true range. True range is max(high - low, abs(high - close ), abs(low - close )).
Parameters:
length : Number of bars (length).
h : High price high price.
l : low price.
c : Close price close price.
Returns: Average true range.
rsi(length, source)
Overwrites `ta.rsi` duo to limitations of simple int length. Relative strength index. It is calculated using the `ta.rma()` of upward and downward changes of `source` over the last `length` bars.
Parameters:
length : Number of bars (length).
source : Series of values to process.
Returns: Relative strength index.
lowest(length, source, start)
Lowest value for a given number of bars back.
Parameters:
length : Number of bars (length).
source : Series of values to process.
start : Series number of bars that should be skipped before process.
Returns: Lowest value in the series.
highest(length, source, start)
Highest value for a given number of bars back.
Parameters:
length : Number of bars (length).
source : Series of values to process.
start : Series number of bars that should be skipped before process.
Returns: Highest value in the series.
atr_multiplier(rsi, atr_max_multiplier)
Dynamic atr multiplier calculated by RSI.
Parameters:
rsi : Relative strength index.
atr_max_multiplier : The maximum multiplier of atr
Returns: Dynamic multiplier of ATR
offset(atr, atr_multiplier)
Safe dynamic offset you need to use in your stoploss, stop buy/sell, etc.
Parameters:
atr : Average true range.
atr_multiplier : ATR multiplier got from `atr_multiplier(rsi, atr_max_multiplier)`
Returns: Dynamic offset
rsi_emotional(rsi, bottom, top)
Tells you if RSI is in emotional zone.
Parameters:
rsi : Relative Strength Index
bottom : The zone that below it market reacts emotionally
top : The zone that above it market reacts emotionally
Returns: false if RSI was between `bottom` and `top` otherwise true
rsi_signal(rsi, bottom, top)
Tells you if RSI is in good point to check your other strategy conditions.
Parameters:
rsi : Relative Strength Index
bottom : The zone that below it market reacts emotionally
top : The zone that above it market reacts emotionally
Returns: 1 if RSI crossed out 30, 50 or 70. -1 if RSI crossed under 70, 50, 30. otherwise is 0
Lagging Session Regression ChannelHello Traders !
Note :
This is my very first published script on trading view & from brainstorming an idea to developing to the finched product it was imperative to me for the indiactor and every one of its features to be of some meaningfull use. If you like the idea of statsitics being able to predict future prices in the market then this indicator may be usefull in your trading arsenal.
Introduction :
Lagging Session Regression Channel (LSRC) is a statistical trend analysis indicator that "laggs" the market by the user defined session, by defualt a day, by doing so the indicator leverges the ability of simple linear regression to predict future asset price.(This can be used on any asset in any market in any time frame)
Options & inputs :
- Bar regression lookback :
The value of bars back from the lats session change, if the seesion time is equivelnt to the the chart timefrmae then the regression line will not lag price, i.e it will act as a stantdard lineer regression channel chnaging on evrey last confimred bar.
- Standard Deviation lookback :
The value of bars from the last session change to cacluate the unbiased standard deviation, The lookback can be set to > or < the regression lookback to cauture > or < less asset volatility. (note this is the same as the residual standard deviation)
- Predicted price at nth bar :
if you whant to know the predicted close price value at any given point in the regression and to the RHS of the regression.
- Regression Line colors group :
Changes the colors of each plotted line.
- OLS Line color : is only changeable when trend color is set to false / unticked.
- Visable deviations group :
Plots the lines that you want on chart, e.g if "Show DEV1" and "Sow DEV SUB1" are the only inputs ticked then they will be the only lines ploted along with the simple linear regression line.
- Regression Line Dynamics group :
All inputs in this group change the regressions calculations given the bar lookback is constant / the same.
- Trend color : if set too true, when the close of the proceding real time bar is greater than the simple linear regression line from the last confimred session the line will be colored green, if otherwise the close is below the simple linear regression line the line will be colored red.
- Extend regression line :
This is the same chart image as seen on the publication chart image but with Extend regression line set to true, this allows the trader to test the valdity of the regression and how well it predicts future price, as seen on the M15 chart of BTCUSD above the indicator was pritty good at doing this.
- Standard deviation channel source :
Source for standard deviation to be calculated on. note if this is set to a varible other than the close then this will no longer be the resdiaul standard deviation, as of now "LSRC 1.0" the regression uses only the close for y / predicted values.
- Time elasped unitl next regression calculation :
The session time until the next LSRC will be calculated and plotted
Label LSRC stats :
- STAN DEV : the standard deviation used to cacluateed the deviation channels
- MIN : The lowest price across the regression
- MAX : The highest price across the regression
- n bars above dev 1 : The number of bars that closed above the first standard deviation channel across the entire regression calculation
- n bars below sub dev1 : The number of bars that closed below the first standard deviation channel.
- Regression Price : The output of "Predicted price at nth bar" input.
Hope you find this usefull !
I will continue too try improve this script and update it accordingly.
Triple ThreatThis indicator provides buy and sell signals for Bitcoin based on confluence from well-known momentum, volatility, and trend indicators. It has successfully captured the major directional trends on Bitcoin's daily chart since 2018, and the settings are currently optimized for this chart in particular. This indicator implements RSI to gauge momentum, BBWP to gauge volatility, and an EMA to gauge trend. Maximum confluence signals are represented by horizontal bars in the indicator's pane, where the tallest green bar is a confirmed buy signal, and the tallest red bar is a confirmed sell signal. The shortest bar represents a momentum-only signal, and the second-shortest bar represents a volatility signal in confluence with the previously given momentum signal.
To track momentum, the RSI is plotted to the indicator plane against a moving average of the RSI. A momentum signal is generated when the RSI crosses over its moving average, retests/approaches the moving average, and then continues in the crossover direction (i.e., it fails to cross the moving average to the opposite side, creating a successful retest). The settings that affect this trigger are the "Crossover Threshold," which specifies how much the RSI should exceed the moving average to be considered a crossover, and the "Retest threshold," which specifies how closely the RSI should approach the moving average to be considered a retest. A momentum signal is ALSO generated if the RSI or its moving average exceed their counterpart by a certain threshold. For example, if the threshold was set at 10, a BUY signal would be generated when the RSI exceeds the moving average by 10, or a SELL signal would be generated when the moving average exceeds the RSI by 10. This threshold can be set using the "Instant Signal Threshold" setting. Either type of momentum signal will be plotted on the pane as the shortest horizontal bar, with its color indicating the signal's direction.
Volatility is primarily measured using the Bollinger Band Width Percentile (BBWP) indicator, which was created by The_Caretaker. BBWP plots the volatility of the asset's price, given by Bollinger Band width, relative to past volatility by assigning the volatility readings into percentiles. The indicator also includes a moving average of the BBWP itself, where a crossover to the upside represents expanding volatility and a crossover to the downside represents contracting volatility. This indicator is used to confirm a signal given by the momentum indicators - a momentum signal that is given during a period of expanding volatility has a greater likelihood of success. Therefore, when the BBWP crosses above its moving average by a given threshold, a previously triggered momentum signal is considered to be "confirmed." The threshold for this crossover can be set using the "BBWP Confirmation Threshold" setting. However, it is also relevant that periods of extreme volatility often accompany an extremity in price action (a "top" or "bottom"), in which case the BBWP is likely to contract after price reaches such an extremity. This phenomenon is captured by also using "extreme reads" on the momentum indicator to signal that there has already been enough volatility to confirm a momentum signal. If the RSI gives an "extreme read" before triggering a signal, the momentum signal is also considered to be confirmed. For example, if the RSI is above 80, breaks below 80, and then gives a SELL signal, this sell signal is considered to be confirmed without requiring the BBWP to crossover its moving average to the upside. The threshold that would confirm a SELL signal can be set with the "Overbought" setting, and the threshold that would confirm a BUY signal can be set with the "Oversold" setting. Whenever a volatility signal confirms a momentum signal, a medium-sized horizontal bar will be plotted on the pane in the same directional color as the momentum signal. Note that a momentum signal may trigger at the exact same time as the volatility signal which confirms it; in this case, only the medium-sized bar will be visible on the pane, but its direction can still be identified by its color.
Lastly, to reduce the likelihood of "false signals," a trend indicator is used to confirm the direction of the signal. This is typically an exponential moving average. If a confirmed volatility SELL signal is given, and the closing price is below the moving average, then the SELL signal is also confirmed by the trend. Likewise, if a confirmed volatility BUY signal is given, and the closing price is above the moving average, then the BUY signal is confirmed by the trend. The type and length of the moving average used to verify the trend can be set using the "Moving Average Type" and "Moving Average Length" settings found below the momentum/volatility settings. A trend signal is plotted on the pane as a tall horizontal bar, and is more deeply colored than the momentum and volatility signals.
For maximum confluence, it is recommended that the trend signal, given by the tallest bar, is the one that forms the basis of trades executed while using the Triple Threat indicator. It is possible to enter more aggressive trades with better entries by using only the volatility signal, given by the medium-sized bar, however this entails greater risk and should only be done in confluence with an additional trading strategy of your own discretion. Backtesting has shown that using the volatility signal alone underperforms using the volatility signal in confluence with the trend signal.
Please also be advised that the default setting are optimized for Bitcoin's daily chart only. The indicator is still applicable to other timeframes and asset classes, but the settings may need to be modified. I have a list of settings for other Bitcoin timeframes, and I would be happy to share them upon request.
I hope you can find this indicator to be of some use to your trading strategies. I'd be happy to hear any feedback from the community, so please don't hesitate to reach out. Stay safe, and happy trading.
MovingAveragesLibrary "MovingAverages"
Contains utilities for generating moving average values including getting a moving average by name and a function for generating a Volume-Adjusted WMA.
sma(_D, _len) Simple Moving Avereage
Parameters:
_D : The series to measure from.
_len : The number of bars to measure with.
ema(_D, _len) Exponential Moving Avereage
Parameters:
_D : The series to measure from.
_len : The number of bars to measure with.
rma(_D, _len) RSI Moving Avereage
Parameters:
_D : The series to measure from.
_len : The number of bars to measure with.
wma(_D, _len) Weighted Moving Avereage
Parameters:
_D : The series to measure from.
_len : The number of bars to measure with.
vwma(_D, _len) volume-weighted Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
alma(_D, _len) Arnaud Legoux Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
cma(_D, _len, C, compound) Coefficient Moving Avereage (CMA) is a variation of a moving average that can simulate SMA or WMA with the advantage of previous data.
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
C : The coefficient to use when averaging. 0 behaves like SMA, 1 behaves like WMA.
compound : When true (default is false) will use a compounding method for weighting the average.
dema(_D, _len) Double Exponential Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
zlsma(_D, _len) Arnaud Legoux Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
zlema(_D, _len) Arnaud Legoux Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
get(type, len, src) Generates a moving average based upon a 'type'.
Parameters:
type : The type of moving average to generate. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
len : The number of bars to measure with.
src : The series to measure from. Default is 'close'.
Returns: The moving average series requested.
