Supertrend + MACD + HMAIndicator Description: Supertrend + MACD + HMA
General Summary
It is a composite technical indicator that combines three analysis tools to generate buy and sell signals in institutional trading. It uses confirmation from multiple indicators to increase the precision of market entries.
Components
1. Supertrend (ST)
Function: Identifies the main market trend (bullish or bearish)
Parameters: ATR Length 10, Factor 3.0
Visualization:
Green line = Bullish trend
Red line = Bearish trend
Semi-transparent green/red background that fills the area according to direction
How it works: Uses ATR (Average True Range) to calculate dynamic support and resistance bands
2. MACD (Moving Average Convergence Divergence)
Function: Measures price momentum and direction
Parameters: Fast 18, Slow 144, Signal Smoothing 9
Components:
MACD Line (orange): Difference between two EMAs
Signal Line (purple): EMA of the MACD
Histogram (green/red columns): Difference between MACD and its signal
Green = Positive histogram (bullish momentum)
Red = Negative histogram (bearish momentum)
3. HMA 100 (Hull Moving Average)
Function: Identifies support/resistance level and price direction
Parameters: Length 100
Visualization: Blue thick line
Characteristics:
Less lag than traditional moving averages
Price > HMA = Bullish trend
Price < HMA = Bearish trend
Signal Logic
🟢 BUY SIGNAL
Generated when ANY of these conditions is met:
Total Confluence:
MACD positive (histogram > 0)
Price above HMA 100
Supertrend in Bullish mode
Supertrend Change:
Supertrend changes from Bearish to Bullish
MACD remains positive
Price above HMA
Price Crossover:
Price crosses above HMA (at candle close)
Supertrend is in Bullish mode
MACD is positive
🔴 SELL SIGNAL
Generated when ANY of these conditions is met:
Total Confluence:
MACD negative (histogram < 0)
Price below HMA 100
Supertrend in Bearish mode
Supertrend Change:
Supertrend changes from Bullish to Bearish
MACD remains negative
Price Crossover:
Price crosses below HMA (at candle close)
Supertrend is in Bearish mode
MACD is negative
Important Features
✅ Single Signal Per Type
Once a BUY is generated, no other BUY is generated until a SELL appears
Avoids multiple entries in the same direction
✅ Crossover Detection
The indicator generates signals at candle close when price crosses HMA
Allows capturing quick market moves
✅ Trend Changes
Detects when Supertrend changes direction
Provides early exits from the market
✅ Automatic Alerts
Push notifications when BUY or SELL is generated
Ideal for automated trading
Tìm kiếm tập lệnh với "change"
Moving Average ProjectionDisplays 2-5 moving averages (solid lines) and projects their future trajectory (dashed lines) based on current trend momentum. This helps you anticipate where key MAs are heading and identify potential future support/resistance levels.
Important: Projections show where MAs would move IF the current trend continues—they're not predictions. Market conditions change, so use projections as planning tools, not trading signals.
General Settings
Number of MAs (2-5) controls how many moving averages display on your chart. Start with 2-3 to avoid clutter. Projection Bars (1-100) determines how far into the future to project—use 10-20 for intraday charts and 20-40 for daily charts. Lookback for Slope (2-100) sets the number of bars used to calculate trend slope, where shorter lookbacks are more responsive and longer ones are smoother. The default of 20 works well for most situations.
Individual MA Settings (MA 1-5)
Each MA has four settings: Length sets the period for the MA (common values are 9, 20, 50, 100, and 200), Type lets you choose between SMA, EMA, WMA, HMA, VWMA, or RMA (EMA is most popular), Color sets the historical MA line color, and Projection Color sets the projected line color (usually a lighter or transparent version of the main color).
MA Types Quick Reference: EMA is most popular and responsive to recent prices. SMA gives equal weight to all periods and is the smoothest. HMA is very responsive with low lag. VWMA incorporates volume data.
Quick Setup Examples
Day Trading: 3 MAs (9/21/50 EMA), 10-15 projection bars, 10-15 lookback
Swing Trading: 2 MAs (50/200 EMA), 20-30 projection bars, 20 lookback
Scalping: 2 MAs (9/20 EMA), 5-10 projection bars, 5-10 lookback
How to Use
Trend Identification: An uptrend shows price above rising MAs with projections pointing up. A downtrend shows price below falling MAs with projections pointing down. Consolidation appears as flat MAs with horizontal projections.
Support & Resistance: Rising MA projections act as future dynamic support levels, while falling MA projections act as future dynamic resistance levels.
Anticipating Changes: Watch for projected MA crossovers before they happen. When projections converge, expect volatility or consolidation. Steep projections suggest unsustainable trends, so be cautious. Flat projections indicate ranging markets.
Trade Planning: Check the current trend using MA alignment, then look at projections to gauge trend continuation likelihood. Use projected MA levels for potential targets or stop placement.
Important Tips
When Projections Work Best: Projections are most reliable in stable trending markets with consistent momentum, low volatility environments, and away from major news events.
When to Be Cautious: Use caution during high volatility or choppy price action, around major economic releases, when projections show extreme or parabolic angles, and during trend transitions.
Combine With Other Analysis: Don't trade projections alone. Use them alongside price action, volume, support and resistance levels, and other indicators for confirmation.
Best Practices
Start with 2-3 MAs to avoid chart clutter. Match your projection and lookback bars to your trading timeframe. Use consistent color schemes for quick interpretation. Adjust settings as market conditions change. Always use proper risk management—projections are planning tools, not guarantees.
Troubleshooting
Projections not showing: Check that Projection Bars > 0 and you're viewing the most recent bar
Chart too cluttered: Reduce number of MAs or increase projection color transparency
Projections too volatile: Increase lookback bars or switch to EMA/SMA from HMA
Can't see certain MAs: Verify "Number of MAs" setting includes them (MA 3 won't show if set to 2)
Volume Weighted Average Price Dynamic Slope [sgbpulse]VWAP Dynamic Slope: A Comprehensive Indicator for Trend Identification and Smart Trading
Introducing VWAP Dynamic Slope, an innovative TradingView indicator that harnesses the power of Volume Weighted Average Price (VWAP) and enhances it with immediate visual feedback. The indicator colors the VWAP line based on its slope, allowing you to quickly and easily identify the direction and strength of the current trend for the asset, providing advanced tools for in-depth analysis.
What is VWAP and Why is it so Important?
VWAP (Volume Weighted Average Price) is an indicator that represents the average price at which an asset has traded, weighted by the volume traded at each price level. Unlike a simple moving average, VWAP gives greater weight to trades executed with high volume, making it a reliable measure of the asset's "true" or "fair" price within a given period. Many institutional traders use VWAP as a central reference point for evaluating the effectiveness of entries and exits. An asset trading above its VWAP is considered to have bullish momentum, and below it – bearish momentum.
How it Works: Dynamic VWAP Slope Analysis
VWAP Dynamic Slope analyzes the inclination of the VWAP line and displays it using an intuitive color scheme:
Positive Slope (Uptrend): When the VWAP points upwards, signaling positive momentum, the default color will be green.
Negative Slope (Downtrend): When the VWAP points downwards, signaling negative momentum, the default color will be orange.
Trend Change (CHG): When a change in the VWAP's trend direction occurs, a "CHG" label will be displayed. The label's color will be green if the change is to an uptrend, and orange if the change is to a downtrend.
Identifying Steep Slopes for Increased Momentum:
The indicator's uniqueness lies in its ability to identify "steep" slopes – rapid and particularly strong changes in the VWAP's direction. This indicates exceptionally strong momentum:
Steep Positive Slope: The VWAP color will change to dark green, indicating significant buying pressure.
Steep Negative Slope: The VWAP color will change to dark red, indicating significant selling pressure.
Dynamic Momentum Strength Label: In situations of steep slope (positive or negative), a dynamic label will be displayed with the change value of the VWAP at that point. This label allows you to monitor momentum strength, intensification, or weakening in real-time.
Advanced Analytical Tools for Complete Control
VWAP Dynamic Slope provides you with unprecedented flexibility through a variety of customizable tools:
Multiple VWAP Anchors and Visual Marking:
Common Time Anchors: Choose whether the VWAP resets at the beginning of each Session (daily), Week, Month, Quarter, Year, Decade, or Century.
Advanced Intraday Anchors: Within the Session, you can choose to calculate VWAP specifically for Pre-Market, Regular Hours, and Post-Market hours. This option is particularly crucial for intraday traders.
Important Event Anchors: The indicator allows for VWAP resets at significant milestones such as Earnings, Dividends, and Splits, for analyzing the market's immediate reaction.
Visual Anchor Marking: To enhance clarity and orientation, a Label ⚓ can be displayed at each selected anchor point, helping to immediately identify the start point of the VWAP calculation in the chosen context.
Customizable Bands (Up to Three on Each Side):
Add up to three Bands above and below the VWAP to identify areas of deviation and excursion from the average price. You have two calculation options:
Standard Deviation: Based on volatility and statistical distance from the VWAP.
Percentage: Defines fixed percentage-based bands from the VWAP.
Key Pre-Market Levels (Pre-Market High/Low):
Display the Pre-Market High and Low levels as separate lines on the chart. These lines often serve as important psychological support and resistance zones, allowing you to see how the VWAP behaves near them.
Full Customization and Precise Control:
VWAP Source Selection: Determine which price data type will be used for the VWAP calculation. The default is HLC3 (average of High, Low, and Close), but any other relevant data source available in TradingView can be selected.
Offset: Set an offset for the VWAP line, allowing you to shift it left or right on the time axis by a chosen number of bars.
Customizable Colors: Choose your preferred colors for each slope state, Pre-Market High/Low lines, and Bands.
Setting the "Steepness" Threshold (Per-mille Price Change Per Minute ‱/min with Auto-Adjustment): Determine the sensitivity for identifying a steep slope by setting the required change threshold in VWAP in terms of per-mille price change per minute (‱/min). The indicator performs smart adjustment for any timeframe you select on the chart (e.g., 30 seconds, 1 minute, 5 minutes, 10 minutes, etc.), ensuring that the "steepness" setting maintains consistency and relevance.
Examples for Setting the Steepness Threshold:
Suppose you set the steepness threshold to 0.3‱/min (per-mille price change per minute).
On a 30-second chart: The indicator will check if the VWAP changed by 0.15 ‱/min (half of the per-minute threshold) within a single bar. If so, the slope will be considered steep. Explanation: Since 30 seconds is half a minute, the indicator looks for a change that is half of the threshold set for a full minute.
On a 1-minute chart: The indicator will check if the VWAP changed by 0.3 ‱/min (the full per-minute threshold) within a single bar. If so, the slope will be considered steep. Explanation: Here, the bar represents a full minute, so we check the full threshold.
On a 5-minute chart: The indicator will check if the VWAP changed by 1.5 ‱/min (5 times the per-minute threshold) within a single bar. If so, the slope will be considered steep. Explanation: A 5-minute bar contains 5 minutes, so the cumulative change in VWAP needs to be 5 times greater to be considered "steep" on the same scale.
In summary, this setting allows you to precisely and uniformly control the sensitivity of steep slope detection across all timeframes, providing immense flexibility in analyzing the asset's momentum.
Advantages of Using Per-mille Price Change Per Minute (‱/min)
Using per-mille price change per minute (‱/min) offers several key advantages for your indicator:
Normalized and Objective Measurement: It provides a uniform scale for the VWAP's rate of change, regardless of the asset's price or nominal value. A 0.1 per-mille change per minute always carries the same relative significance.
Comparison Across Different Asset Prices: Using per-mille allows for direct comparison of VWAP movement strength between assets trading at very different prices (e.g., a $100 asset versus a $1 asset), enabling an understanding of true momentum without bias from the nominal price.
Smart Timeframe Agnostic Adjustment: This is a critical capability. The indicator automatically adjusts the per-mille per minute threshold you set to any chart timeframe (30 seconds, 1 minute, 5 minutes, etc.), maintaining consistency in "steepness" detection without manual recalibration.
Precise Momentum Identification: This measurement precisely identifies when the VWAP's rate of change becomes significant, and when momentum strengthens or weakens, contributing to more informed trading decisions.
In short, per-mille change per minute (‱/min) provides accuracy, consistency, and flexibility in identifying VWAP momentum changes, with smart adaptation across all timeframes.
Who is this Indicator For?
VWAP Dynamic Slope is a powerful tool for:
Intraday Traders: For quick identification of intraday trend directions and momentum across any timeframe, with specific consideration for Pre-Market, Regular Hours, or Post-Market VWAP, and incorporating key pre-market levels.
Swing Traders and Long-Term Investors: For analyzing longer-term trends based on periodic and event-driven VWAP anchors.
Beginner Traders: As an excellent visual aid for understanding the relationship between price, volume, and trend direction, and how different anchor points, pre-market levels, and data sources influence price behavior.
Experienced Traders: For integration with existing strategies, gaining additional confirmation for trend strength identification, and highly precise and flexible parameter calibration.
VWAP Dynamic Slope provides a rich, multi-dimensional layer of information about the VWAP, helping you make more informed trading decisions in real-time, within the context of your chosen asset.
LB | SB | OH | OL (Auto Futures OI)This indicator is for trading purposes, particularly in futures markets given the inclusion of open interest (OI) data.
Indicator Name and Overlay: The indicator is named "LB | SB | OH | OL" and is set to overlay on the price chart (overlay=true).
Override Symbol Input: Users can input a symbol to override the default symbol for analysis.
Open Interest Data Retrieval: It retrieves open interest data for the specified symbol and time frame. If no data is found, it generates a runtime error.
Dashboard Configuration: Users can choose to display a dashboard either at the top right, bottom right, or bottom left of the chart.
Calculations:
It calculates the percentage change in open interest (oi_change).
It calculates the percentage change in price compared to the previous day's close (price_change).
Build Up Conditions:
Long Build Up: When there's a significant increase in open interest (OIChange threshold) and price rises (PriceChange threshold).
Short Build Up: When there's a significant increase in open interest (OIChange threshold) and price falls (PriceChange threshold).
Display Table:
It creates a table on the chart showing the build-up conditions, open interest change percentage, and price change percentage.
Labeling:
It allows for the labeling of buy and sell conditions based on price movements.
Overall, this indicator provides a visual representation of open interest and price movements, helping traders identify potential trading opportunities based on build-up conditions and price behavior.
The "LB | SB | OH | OL" indicator is a tool designed to assist traders in analyzing price movements and open interest (OI) changes in FNO markets. This indicator combines various elements to provide insights into long build-up (LB), short build-up (SB), open-high (OH), and open-low (OL) scenarios.
Key features of the indicator include:
Override Symbol Input: Traders can override the default symbol and input their preferred symbol for analysis.
Open Interest Data: The indicator retrieves open interest data for the selected symbol and time frame, facilitating analysis based on changes in open interest.
Dashboard: The indicator features a customizable dashboard that displays key information such as build-up conditions, OI change, and price change.
Build-Up Conditions: The indicator identifies long build-up and short build-up scenarios based on user-defined thresholds for OI change and price change percentages.
Customization Options: Traders have the flexibility to customize various aspects of the indicator, including colors for long build-up, short build-up, positive OI change, negative OI change, positive price change, and negative price change.
Label Plots: Buy and sell labels are plotted on the chart to highlight potential trading opportunities. Traders can customize the colors and text colors of these labels based on their preferences.
Overall, the "LB | SB | OH | OL" indicator offers traders a comprehensive tool for analyzing price movements and open interest changes, helping them make informed trading decisions in the FNO markets.
Topological Market Stress (TMS) - Quantum FabricTopological Market Stress (TMS) - Quantum Fabric
What Stresses The Market?
Topological Market Stress (TMS) represents a revolutionary fusion of algebraic topology and quantum field theory applied to financial markets. Unlike traditional indicators that analyze price movements linearly, TMS examines the underlying topological structure of market data—detecting when the very fabric of market relationships begins to tear, warp, or collapse.
Drawing inspiration from the ethereal beauty of quantum field visualizations and the mathematical elegance of topological spaces, this indicator transforms complex mathematical concepts into an intuitive, visually stunning interface that reveals hidden market dynamics invisible to conventional analysis.
Theoretical Foundation: Topology Meets Markets
Topological Holes in Market Structure
In algebraic topology, a "hole" represents a fundamental structural break—a place where the normal connectivity of space fails. In markets, these topological holes manifest as:
Correlation Breakdown: When traditional price-volume relationships collapse
Volatility Clustering Failure: When volatility patterns lose their predictive power
Microstructure Stress: When market efficiency mechanisms begin to fail
The Mathematics of Market Topology
TMS constructs a topological space from market data using three key components:
1. Correlation Topology
ρ(P,V) = correlation(price, volume, period)
Hole Formation = 1 - |ρ(P,V)|
When price and volume decorrelate, topological holes begin forming.
2. Volatility Clustering Topology
σ(t) = volatility at time t
Clustering = correlation(σ(t), σ(t-1), period)
Breakdown = 1 - |Clustering|
Volatility clustering breakdown indicates structural instability.
3. Market Efficiency Topology
Efficiency = |price - EMA(price)| / ATR
Measures how far price deviates from its efficient trajectory.
Multi-Scale Topological Analysis
Markets exist across multiple temporal scales simultaneously. TMS analyzes topology at three distinct scales:
Micro Scale (3-15 periods): Immediate structural changes, market microstructure stress
Meso Scale (10-50 periods): Trend-level topology, medium-term structural shifts
Macro Scale (50-200 periods): Long-term structural topology, regime-level changes
The final stress metric combines all scales:
Combined Stress = 0.3×Micro + 0.4×Meso + 0.3×Macro
How TMS Works
1. Topological Space Construction
Each market moment is embedded in a multi-dimensional topological space where:
- Price efficiency forms one dimension
- Correlation breakdown forms another
- Volatility clustering breakdown forms the third
2. Hole Detection Algorithm
The indicator continuously scans this topological space for:
Hole Formation: When stress exceeds the formation threshold
Hole Persistence: How long structural breaks maintain
Hole Collapse: Sudden topology restoration (regime shifts)
3. Quantum Visualization Engine
The visualization system translates topological mathematics into intuitive quantum field representations:
Stress Waves: Main line showing topological stress intensity
Quantum Glow: Surrounding field indicating stress energy
Fabric Integrity: Background showing structural health
Multi-Scale Rings: Orbital representations of different timeframes
4. Signal Generation
Stable Topology (✨): Normal market structure, standard trading conditions
Stressed Topology (⚡): Increased structural tension, heightened volatility expected
Topological Collapse (🕳️): Major structural break, regime shift in progress
Critical Stress (🌋): Extreme conditions, maximum caution required
Inputs & Parameters
🕳️ Topological Parameters
Analysis Window (20-200, default: 50)
Primary period for topological analysis
20-30: High-frequency scalping, rapid structure detection
50: Balanced approach, recommended for most markets
100-200: Long-term position trading, major structural shifts only
Hole Formation Threshold (0.1-0.9, default: 0.3)
Sensitivity for detecting topological holes
0.1-0.2: Very sensitive, detects minor structural stress
0.3: Balanced, optimal for most market conditions
0.5-0.9: Conservative, only major structural breaks
Density Calculation Radius (0.1-2.0, default: 0.5)
Radius for local density estimation in topological space
0.1-0.3: Fine-grained analysis, sensitive to local changes
0.5: Standard approach, balanced sensitivity
1.0-2.0: Broad analysis, focuses on major structural features
Collapse Detection (0.5-0.95, default: 0.7)
Threshold for detecting sudden topology restoration
0.5-0.6: Very sensitive to regime changes
0.7: Balanced, reliable collapse detection
0.8-0.95: Conservative, only major regime shifts
📊 Multi-Scale Analysis
Enable Multi-Scale (default: true)
- Analyzes topology across multiple timeframes simultaneously
- Provides deeper insight into market structure at different scales
- Essential for understanding cross-timeframe topology interactions
Micro Scale Period (3-15, default: 5)
Fast scale for immediate topology changes
3-5: Ultra-fast, tick/minute data analysis
5-8: Fast, 5m-15m chart optimization
10-15: Medium-fast, 30m-1H chart focus
Meso Scale Period (10-50, default: 20)
Medium scale for trend topology analysis
10-15: Short trend structures
20-25: Medium trend structures (recommended)
30-50: Long trend structures
Macro Scale Period (50-200, default: 100)
Slow scale for structural topology
50-75: Medium-term structural analysis
100: Long-term structure (recommended)
150-200: Very long-term structural patterns
⚙️ Signal Processing
Smoothing Method (SMA/EMA/RMA/WMA, default: EMA) Method for smoothing stress signals
SMA: Simple average, stable but slower
EMA: Exponential, responsive and recommended
RMA: Running average, very smooth
WMA: Weighted average, balanced approach
Smoothing Period (1-10, default: 3)
Period for signal smoothing
1-2: Minimal smoothing, noisy but fast
3-5: Balanced, recommended for most applications
6-10: Heavy smoothing, slow but very stable
Normalization (Fixed/Adaptive/Rolling, default: Adaptive)
Method for normalizing stress values
Fixed: Static 0-1 range normalization
Adaptive: Dynamic range adjustment (recommended)
Rolling: Rolling window normalization
🎨 Quantum Visualization
Fabric Style Options:
Quantum Field: Flowing energy visualization with smooth gradients
Topological Mesh: Mathematical topology with stepped lines
Phase Space: Dynamical systems view with circular markers
Minimal: Clean, simple display with reduced visual elements
Color Scheme Options:
Quantum Gradient: Deep space blue → Quantum red progression
Thermal: Black → Hot orange thermal imaging style
Spectral: Purple → Gold full spectrum colors
Monochrome: Dark gray → Light gray elegant simplicity
Multi-Scale Rings (default: true)
- Display orbital rings for different time scales
- Visualizes how topology changes across timeframes
- Provides immediate visual feedback on cross-scale dynamics
Glow Intensity (0.0-1.0, default: 0.6)
Controls the quantum glow effect intensity
0.0: No glow, pure line display
0.6: Balanced, recommended setting
1.0: Maximum glow, full quantum field effect
📋 Dashboard & Alerts
Show Dashboard (default: true)
Real-time topology status display
Current market state and trading recommendations
Stress level visualization and fabric integrity status
Show Theory Guide (default: true)
Educational panel explaining topological concepts
Dashboard interpretation guide
Trading strategy recommendations
Enable Alerts (default: true)
Extreme stress detection alerts
Topological collapse notifications
Hole formation and recovery signals
Visual Logic & Interpretation
Main Visualization Elements
Quantum Stress Line
Primary indicator showing topological stress intensity
Color intensity reflects current market state
Line style varies based on selected fabric style
Glow effect indicates stress energy field
Equilibrium Line
Silver line showing average stress level
Reference point for normal market conditions
Helps identify when stress is elevated or suppressed
Upper/Lower Bounds
Red upper bound: High stress threshold
Green lower bound: Low stress threshold
Quantum fabric fill between bounds shows stress field
Multi-Scale Rings
Aqua circles : Micro-scale topology (immediate changes)
Orange circles: Meso-scale topology (trend-level changes)
Provides cross-timeframe topology visualization
Dashboard Information
Topology State Icons:
✨ STABLE: Normal market structure, standard trading conditions
⚡ STRESSED: Increased structural tension, monitor closely
🕳️ COLLAPSE: Major structural break, regime shift occurring
🌋 CRITICAL: Extreme conditions, reduce risk exposure
Stress Bar Visualization:
Visual representation of current stress level (0-100%)
Color-coded based on current topology state
Real-time percentage display
Fabric Integrity Dots:
●●●●● Intact: Strong market structure (0-30% stress)
●●●○○ Stressed: Weakening structure (30-70% stress)
●○○○○ Fractured: Breaking down structure (70-100% stress)
Action Recommendations:
✅ TRADE: Normal conditions, standard strategies apply
⚠️ WATCH: Monitor closely, increased vigilance required
🔄 ADAPT: Change strategy, regime shift in progress
🛑 REDUCE: Lower risk exposure, extreme conditions
Trading Strategies
In Stable Topology (✨ STABLE)
- Normal trading conditions apply
- Use standard technical analysis
- Regular position sizing appropriate
- Both trend-following and mean-reversion strategies viable
In Stressed Topology (⚡ STRESSED)
- Increased volatility expected
- Widen stop losses to account for higher volatility
- Reduce position sizes slightly
- Focus on high-probability setups
- Monitor for potential regime change
During Topological Collapse (🕳️ COLLAPSE)
- Major regime shift in progress
- Adapt strategy immediately to new market character
- Consider closing positions that rely on previous regime
- Wait for new topology to stabilize before major trades
- Opportunity for contrarian plays if collapse is extreme
In Critical Stress (🌋 CRITICAL)
- Extreme market conditions
- Significantly reduce risk exposure
- Avoid new positions until stress subsides
- Focus on capital preservation
- Consider hedging existing positions
Advanced Techniques
Multi-Timeframe Topology Analysis
- Use higher timeframe TMS for regime context
- Use lower timeframe TMS for precise entry timing
- Alignment across timeframes = highest probability trades
Topology Divergence Trading
- Most powerful at regime boundaries
- Price makes new high/low but topology stress decreases
- Early warning of potential reversals
- Combine with key support/resistance levels
Stress Persistence Analysis
- Long periods of stable topology often precede major moves
- Extended stress periods often resolve in regime changes
- Use persistence tracking for position sizing decisions
Originality & Innovation
TMS represents a genuine breakthrough in applying advanced mathematics to market analysis:
True Topological Analysis: Not a simplified proxy but actual topological space construction and hole detection using correlation breakdown, volatility clustering analysis, and market efficiency measurement.
Quantum Aesthetic: Transforms complex topology mathematics into an intuitive, visually stunning interface inspired by quantum field theory visualizations.
Multi-Scale Architecture: Simultaneous analysis across micro, meso, and macro timeframes provides unprecedented insight into market structure dynamics.
Regime Detection: Identifies fundamental market character changes before they become obvious in price action, providing early warning of structural shifts.
Practical Application: Clear, actionable signals derived from advanced mathematical concepts, making theoretical topology accessible to practical traders.
This is not a combination of existing indicators or a cosmetic enhancement of standard tools. It represents a fundamental reimagining of how we measure, visualize, and interpret market dynamics through the lens of algebraic topology and quantum field theory.
Best Practices
Start with defaults: Parameters are optimized for broad market applicability
Match timeframe: Adjust scales based on your trading timeframe
Confirm with price action: TMS shows market character, not direction
Respect topology changes: Reduce risk during regime transitions
Use appropriate strategies: Adapt approach based on current topology state
Monitor persistence: Track how long topology states maintain
Cross-timeframe analysis: Align multiple timeframes for highest probability trades
Alerts Available
Extreme Topological Stress: Market fabric under severe deformation
Topological Collapse Detected: Regime shift in progress
Topological Hole Forming: Market structure breakdown detected
Topology Stabilizing: Market structure recovering to normal
Chart Requirements
Recommended Markets: All liquid markets (forex, stocks, crypto, futures)
Optimal Timeframes: 5m to Daily (adaptable to any timeframe)
Minimum History: 200 bars for proper topology construction
Best Performance: Markets with clear regime characteristics
Academic Foundation
This indicator draws from cutting-edge research in:
- Algebraic topology and persistent homology
- Quantum field theory visualization techniques
- Market microstructure analysis
- Multi-scale dynamical systems theory
- Correlation topology and network analysis
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice or provide direct buy/sell signals. Topological analysis reveals market structure characteristics, not future price direction. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of topology. Trade the structure, not the noise.
Bringing advanced mathematics to practical trading through quantum-inspired visualization.
Trade with insight. Trade with structure.
— Dskyz , for DAFE Trading Systems
Supertrend with Volume Filter AlertSupertrend with Volume Filter Alert - Indicator Overview
What is the Supertrend Indicator?
The Supertrend indicator is a popular trend-following tool used by traders to identify the direction of the market and potential entry/exit points. It is based on the Average True Range (ATR), which measures volatility, and plots a line on the chart that acts as a dynamic support or resistance level. When the price is above the Supertrend line, it signals an uptrend (bullish), and when the price is below, it indicates a downtrend (bearish). The indicator is particularly effective in trending markets but can generate false signals during choppy or sideways conditions.
How This Script Works
The "Supertrend with Volume Filter Alert" enhances the classic Supertrend indicator by adding a customizable volume filter to improve signal reliability.
Here's how it functions:
Supertrend Calculation:The Supertrend is calculated using the ATR over a user-defined period (default: 55) and a multiplier (default: 1.85). These parameters control the sensitivity of the indicator:A higher ATR period smooths out volatility, making the indicator less reactive to short-term price fluctuations.The multiplier determines the distance of the Supertrend line from the price, affecting how quickly it responds to trend changes.The script plots the Supertrend line in cyan for uptrends and red for downtrends, making it easy to visualize the market direction.
Volume Filter:A key feature of this script is the volume filter, which helps filter out false signals in choppy markets. The filter compares the current volume to the average volume over a lookback period (default: 20) and only triggers signals if the volume exceeds the average by a specified multiplier (default: 2.0).This ensures that trend changes are accompanied by significant market participation, increasing the likelihood of a genuine trend shift.
Signals and Alerts:
Buy signals (cyan triangle below the bar) are generated when the price crosses above the Supertrend line (indicating an uptrend) and the volume condition is met.Sell signals (red triangle above the bar) are generated when the price crosses below the Supertrend line (indicating a downtrend) and the volume condition is met.Alerts are set up for both buy and sell signals, notifying traders only when the volume filter confirms the trend change.
Customizable Settings for Multiple Markets
The default settings in this script (ATR Period: 55, ATR Multiplier: 1.85, Volume Lookback Period: 20, Volume Multiplier: 2.0) were carefully chosen to provide a balance of sensitivity and reliability across various markets, including stocks, indices (like the S&P 500), forex, and cryptocurrencies.
Here's why these settings work well:
ATR Period (55): A longer ATR period smooths out volatility, making the indicator less prone to whipsaws in volatile markets like crypto or forex, while still being responsive enough for trending markets like indices.
ATR Multiplier (1.85): This multiplier strikes a balance between capturing early trend changes and avoiding noise. A smaller multiplier would make the indicator too sensitive, while a larger one might miss early opportunities.
Volume Lookback Period (20): A 20-bar lookback for volume averaging provides a robust baseline for identifying significant volume spikes, adaptable to both short-term (e.g., daily charts) and longer-term (e.g., weekly charts) timeframes.
Volume Multiplier (2.0): Requiring volume to be at least 2x the average ensures that only high-conviction moves trigger signals, which is crucial for markets with varying liquidity levels.
These parameters are fully customizable, allowing traders to adjust the indicator to their specific market, timeframe, or trading style. For example, you might reduce the ATR period for faster-moving markets or increase the volume multiplier for more conservative signal filtering.
How the Volume Filter Reduces Bad Trades in Choppy Markets
One of the main drawbacks of the Supertrend indicator is its tendency to generate false signals during choppy or ranging markets, where price fluctuates without a clear trend. The volume filter in this script addresses this issue by ensuring that trend changes are backed by significant market activity:
In choppy markets, price movements often lack strong volume, leading to false breakouts or reversals. By requiring volume to be a multiple (default: 2x) of the average volume over the lookback period, the script filters out these low-volume, low-conviction moves.This reduces the likelihood of taking bad trades during sideways markets, as only trend changes with strong volume confirmation will trigger signals. For example, on a daily chart of the S&P 500, a buy signal will only fire if the price crosses above the Supertrend line and the volume on that day is at least twice the 20-day average, indicating genuine buying pressure.
Usage Tips
Markets and Timeframes: This indicator is versatile and can be used on various assets (stocks, indices, forex, crypto) and timeframes (1-minute, 1-hour, daily, etc.). Adjust the settings based on the market's volatility and your trading strategy.
Combine with Other Indicators: While the volume filter improves reliability, consider using additional indicators like RSI or MACD to confirm trends, especially in ranging markets.
Backtesting: Test the indicator on historical data for your chosen market to optimize the settings and ensure they align with your trading goals.
Alerts: Set up alerts for buy and sell signals to stay informed of high-probability trend changes without constantly monitoring the chart.
ConclusionThe "Supertrend with Volume Filter Alert" is a powerful tool for trend-following traders, combining the simplicity of the Supertrend indicator with a volume-based filter to enhance signal accuracy. Its customizable settings make it adaptable to multiple markets, while the volume filter helps reduce false signals in choppy conditions, allowing traders to focus on high-probability trades. Whether you're trading stocks, indices, forex, or crypto, this indicator can help you identify trends with greater confidence.
Aggregated Open Interest [Alpha Extract]The Aggregated Open Interest indicator provides a comprehensive view of open interest across multiple cryptocurrency exchanges, allowing traders to monitor institutional positioning and market sentiment. By aggregating data from major exchanges like Binance, BitMEX, and Kraken, this indicator offers valuable insights into potential price movements and market shifts.
🔶 CALCULATION
The indicator processes open interest data through multiple analytical methods:
Exchange Aggregation: Collects and normalizes open interest data from multiple exchanges (Binance, BitMEX, Kraken) with proper currency normalization.
Multi-Mode Analysis: Calculates various metrics including raw open interest values, OI change, OI delta, volume-weighted delta, and OI RSI.
Divergence Detection: Uses pivot point analysis to identify divergences between price action and open interest movements.
Activity Assessment: Tracks bullish and bearish activity patterns by correlating open interest changes with price movements.
Formula:
Aggregate OI = Sum of normalized open interest from selected exchanges
OI Change = Current OI - Previous OI
OI Delta = Net change in open interest across timeframes
OI Delta × Volume = OI Delta weighted by relative volume
OI RSI = Relative Strength Index applied to open interest values
OI Heatmap = Multi-timeframe visualization of OI changes across 7 distinct periods
🔶 DETAILS
Visual Features:
Open Interest: Candlestick representation of aggregated open interest
OI Change: Histogram showing period-to-period changes
OI Delta: Histogram displaying net OI movements
OI Delta × Volume: Volume-weighted OI delta for enhanced signals
OI RSI: Oscillator showing overbought/oversold OI conditions
OI Heatmap: Multi-timeframe visualization showing OI changes across 7 periods (3, 5, 8, 13, 21, 34, and 55 days)
Divergence Detection: Color-coded markers (teal for bullish, red for bearish) highlighting significant divergences between price and open interest
Analysis Table: Real-time summary of key metrics including aggregate OI, recent changes, and bullish/bearish activity.
Interpretation:
Increasing Open Interest + Rising Price: Strong bullish trend confirmation
Increasing Open Interest + Falling Price: Strong bearish trend confirmation
Decreasing Open Interest + Rising Price: Weak bullish trend (potential reversal)
Decreasing Open Interest + Falling Price: Weak bearish trend (potential reversal)
Divergences: Signal potential trend exhaustion and reversals when price moves in one direction while open interest moves in the opposite direction
Heatmap: Provides at-a-glance insight into open interest trends across multiple timeframes, with green bars indicating rising OI and red bars indicating falling OI
🔶 EXAMPLES
Trend Confirmation: Rising open interest accompanying a price increase confirms strong bullish momentum with institutional backing.
Example: During January-February 2025, rising OI during price advances confirms institutional participation in the uptrend.
Bearish Divergence: Price makes a higher high while open interest makes a lower high, signaling potential trend reversal.
Example: Red markers appear at market tops where price continues higher but open interest fails to confirm, preceding significant corrections.
Bullish Divergence : Price makes a lower low while open interest makes a higher low, indicating potential bottoming.
Example: Teal markers appear at market bottoms where price continues lower but open interest fails to confirm, preceding significant rallies.
OI Heatmap Analysis : Multiple timeframes showing consistent red signals across short to long-term periods indicate strong institutional selling pressure.
Example: When all 7 periods (3-55 days) show red during a price uptrend, this signals institutional selling into retail strength, often preceding major corrections.
🔶 SETTINGS
Customization Options:
Data Sources: Toggle different exchanges (Binance USDT/USD/BUSD, BitMEX USD/USDT, Kraken USD)
Display Mode: Choose between Open Interest, OI Change, OI Delta, OI Delta × Volume, OI RSI, and OI Heatmap
Currency Units: Display in USD or base cryptocurrency (COIN)
Analysis Tools: Moving Average (length and color), RSI (length and color)
Divergence Detection: Enable/disable signals, adjust lookback period and threshold percentage, customize bullish/bearish divergence colors
OI Heatmap Colors: Customize bullish (green) and bearish (red) signal colors for the multi-timeframe heatmap visualization
The Aggregated Open Interest indicator provides traders with comprehensive insights into institutional positioning across major exchanges, helping identify potential trend continuations, reversals, and key market turning points driven by smart money movements. The addition of the OI Heatmap feature enables traders to quickly visualize open interest trends across multiple timeframes, providing valuable context for institutional positioning over different market cycles.
Smart Adaptive Signal SystemSmart Adaptive Signal System
Description: The Smart Adaptive Signal System is a sophisticated indicator that generates intelligent buy/sell signals by dynamically adapting to market conditions. It predicts target prices based on momentum and volatility, providing more accurate and reliable trading opportunities.
How It Works:
Dynamic Signal Generation: The system predicts target prices by considering factors such as volatility and momentum. This allows it to react instantly to trend changes and market fluctuations.
Adaptive Thresholds: Buy and sell signals are triggered with adaptive thresholds, adjusting according to market volatility. This ensures flexibility in the face of sudden market changes.
Trend-Based Reset: Users can choose to reset threshold values based on a time interval or trend change. This feature helps the system re-adapt to current market conditions for greater accuracy.
Target Price Prediction: Target prices are calculated using momentum and volatility, helping the system predict future price movements.
How to Use:
Buy/Sell Signals: The indicator generates buy and sell signals based on market conditions. Look for a "down arrow" for a buy signal and an "up arrow" for a sell signal on the chart.
Target Price Lines: Along with buy and sell signals, the system draws target price lines. This helps you visualize potential future price levels.
Flexible Settings: Users can customize analysis periods, minimum change percentages, and other parameters to fit their needs.
Features:
Dynamic buy and sell signals
Target price predictions
Volatility and momentum-based analysis
User-friendly and flexible settings
Trend-based adaptive resetting
Alerts: The Smart Adaptive Signal System responds quickly to sudden market changes, but always use it in conjunction with other indicators like support and resistance levels. Signal accuracy may vary depending on market conditions.
Trendilo ARTrendilo AR is a custom trading indicator designed to identify market trends using advanced techniques such as the Arnaud Legoux Moving Average (ALMA), volume confirmations, and dynamic volatility bands. This indicator provides a clear visualization of trends, including significant changes and custom alerts.
Review of Indicators Used
1. ALMA
Description:
ALMA is a moving average that applies an advanced filter to smooth price data, reducing noise and focusing on actual trends.
Usage in the Indicator:
Used to calculate the smoothed percentage price change and determine trend direction. Customizable parameters include:
- Length: Defines the number of bars to consider.
- Offset: Adjusts sensitivity toward recent prices.
- Sigma: Controls the degree of smoothing.
Advantages:
- Reduced lag in trend detection.
- Resistance to market noise.
2. ATR
Description:
ATR measures the market’s average volatility by considering the range between high and low prices over a given period.
Usage in the Indicator:
ATR is used to calculate "dynamic smoothing", adjusting the indicator’s sensitivity based on current market volatility.
Advantages:
- Adapts to high or low volatility conditions.
- Helps define dynamic support and resistance levels.
3. SMA
Description:
SMA calculates the average of prices or volume over a specific time period.
Usage in the Indicator:
Used to calculate the volume moving average (Volume SMA) to confirm whether the current volume supports the detected trend.
Advantages:
- Easy to understand and calculate.
- Provides volume-based trend confirmation.
4. RMS Bands
Description:
RMS Bands calculate the standard deviation of percentage price changes, creating upper and lower levels that act as overbought and oversold indicators.
Usage in the Indicator:
- Define the range within which the market is considered neutral.
- Crosses above or below the bands indicate trend changes.
Advantages:
- Visual identification of strong trends.
- Helps filter false signals.
Colors and Visuals Used in the Indicator
1. ALMA Line
Colors:
- Green: Indicates a confirmed uptrend (with sufficient volume).
- Red: Indicates a confirmed downtrend (with sufficient volume).
- Gray: Indicates a neutral phase or insufficient volume to confirm a trend.
2. RMS Bands
- Upper and Lower Lines:
- Purple (with transparency): These lines represent the RMS bands (upper and lower) and
adjust opacity based on trend strength.
- Stronger trends result in less transparency (more solid colors).
3. Highlighted Background (Strong Trends)
- Color:
- Light Green (transparent): Highlights a strong trend when the smoothed percentage change (ALMA) exceeds 1.5 times the RMS.
4. Horizontal Lines
- Baseline (0):
- Dark Gray: Serves as a central reference to identify the directionality of percentage changes.
- Additional Line (0.1):
- Blue: A customizable line to mark user-defined key levels.
5. Bar Colors
- Bar Colors:
- Green: When the price is in a confirmed uptrend.
- Red: When the price is in a confirmed downtrend.
- No color: When there is insufficient volume or no clear trend.
How to Use the Indicator
1. Initial Setup
1. Add the Indicator to Your Chart: Copy the code into the Pine Editor on TradingView and apply it to your chart.
2. Customize Parameters: Adjust values based on your trading strategy:
- Smoothing: Controls the level of smoothing for percentage changes.
- Lookback Length: Defines the observation period for calculations.
- Band Multiplier: Adjusts the width of RMS bands.
2. Signal Interpretation
1. Indicator Colors:
- Green: Confirmed uptrend.
- Red: Confirmed downtrend.
- Gray: No clear trend or insufficient volume.
2. RMS Bands:
- If the ALMA line (smoothed percentage change) crosses above the upper RMS band, it signals a potential uptrend.
- If it crosses below the lower RMS band, it signals a potential downtrend.
3. Volume Confirmation:
- The indicator's color activates only if the current volume exceeds the Volume SMA.
3. Alerts and Decisions
1. Trend Change Alerts:
- The indicator automatically triggers alerts when an uptrend or downtrend is detected.
- Configure these alerts to receive real-time notifications.
2. Strong Trend Signals:
- When the magnitude of the percentage change exceeds 1.5 times the RMS, the chart background highlights the strong trend.
4. Trading Strategies
1. Buy:
- Enter long positions when:
- The indicator turns green.
- Volume confirms the trend.
- Consider placing a stop-loss just below the lower RMS band.
2. Sell:
- Enter short positions when:
- The indicator turns red.
- Volume confirms the trend.
- Consider placing a stop-loss just above the upper RMS band.
3. Neutral:
- Avoid trading when the indicator is gray, as no clear trend or insufficient volume is present.
Disclaimer: As this is my first published indicator, please use it with caution. Feedback is highly appreciated to improve its performance.
Happy Trading!
DCA Valuation & Unrealized GainsThis Pine Script for TradingView calculates and visualizes the relationship between a Dollar Cost Average (DCA) price and the All-Time High (ATH) price for over 50 different cryptocurrencies. Here's what it does:
1. Inputs for DCA Prices:
- Users can manually input DCA prices for specific cryptocurrencies (e.g., BTC, ETH, BNB).
2. Dynamic ATH Calculation:
- Dynamically calculates the ATH price for the current asset using the highest price in the chart's loaded data and persists this value across bars.
3. Percentage Change from DCA to ATH:
- Computes the percentage gain from the DCA price to the ATH price.
4. Visualizations:
- Draws a line at the DCA price and the ATH price, both extended to the right.
- Adds an arrow pointing from the DCA price to the ATH, offset by 10 bars into the future.
- Displays labels for:
- The percentage gain from DCA to ATH.
- "No DCA Configured" if no valid DCA price is set for the asset.
5. Color Coding:
- Labels and arrows are color-coded to indicate positive or negative percentage changes:
- Green for gains.
- Red for losses.
6. Adaptability:
- The script dynamically adjusts to the current asset based on its ticker and uses the corresponding DCA price.
This functionality provides traders with clear insights into their investment's performance relative to its ATH, aiding in decision-making.
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To add a new asset to the script:
1. Define the DCA Input: Add a new input for the asset's DCA price using the `input.float` function. For example:
dcaPriceNEW = input.float(title="NEW DCA Price", defval=0.1, tooltip="Set the DCA price for NEW")
2. Add the Asset Logic: Include a conditional check for the new asset in the ticker matching logic:
if str.contains(currentAsset, "NEW") and dcaPriceNEW != 0
dcaPrice := dcaPriceNEW
Where NEW is the ticker symbol of the asset you're adding.
NOTE: SOLO had to be put before SOL because otherwise the indicator was pulling the DCA price from SOL even on the SOLO chart. If you have a similar issue, try that fix.
Adding an asset requires only these two changes. Once done, the script dynamically incorporates the new asset into its calculations and visualizations.
Direction Coefficient Indicator# Direction Coefficient Indicator with Advanced Volume & Volatility Adjustments
The Direction Coefficient Indicator represents an advanced technical analysis tool that combines price momentum analysis with sophisticated volume and volatility adjustments. This versatile indicator measures market direction while adapting to various trading conditions, making it valuable for both trend following and momentum trading strategies.
At its core, the indicator employs a unique approach to price analysis by establishing a dynamic reference period for calculations. It processes price data through an EMA smoothing mechanism to reduce market noise and presents results as percentage-based measurements, ensuring universal applicability across different markets and timeframes.
One of the indicator's standout features is its volume integration system. When enabled, this system implements volume-weighted calculations that provide enhanced accuracy during significant market moves while effectively reducing false signals during low-volume periods. This volume weighting mechanism proves particularly valuable in highly liquid markets where volume plays a crucial role in price movement validation.
The volatility adjustment feature sets this indicator apart from traditional momentum tools. By incorporating smart volatility normalization, the indicator adapts seamlessly to changing market conditions. This adjustment helps maintain consistent signals across different volatility regimes, preventing excessive noise during highly volatile periods while remaining sensitive enough during calmer market phases.
Direction change detection forms another crucial component of the indicator. The system continuously monitors momentum shifts and provides early warning signals for potential trend reversals. This feature helps traders avoid late exits from positions and offers valuable insights for potential market turning points. When the indicator detects significant changes in momentum, it displays a warning symbol (⚠) alongside its regular signals.
The visual presentation of the indicator utilizes an intuitive color-coded system. Green labels indicate positive momentum, while red labels signify negative momentum. The display system includes customizable label sizes and positions, allowing traders to adapt the visual elements to their specific chart setup and preferences. Label distance from candles, color schemes, and reference lines can all be adjusted to create an optimal visual experience.
For practical application, the indicator offers several parameter settings that traders can adjust. The time period parameters include adjustable lookback periods and EMA length, while advanced calculation options allow for enabling or disabling volume weighting and volatility adjustment features. These parameters can be fine-tuned based on specific trading timeframes and market conditions.
In trend following scenarios, traders can use the coefficient direction for trend confirmation while monitoring warning signals for potential exits. The volume weighting feature adds another layer of confirmation for trend strength. For momentum trading, strong coefficient readings can signal entry points, while warning signals help identify potential exit timing.
Risk management becomes more systematic with this indicator. Warning signals can guide stop loss placement, while the volatility adjustment feature assists in position sizing decisions. The volume weighting component helps traders evaluate the significance of price moves, contributing to more informed entry timing decisions.
The indicator performs optimally when traders start with default settings and gradually adjust parameters based on their specific needs. For longer-term trades, increasing the lookback period often provides more stable signals. In highly liquid markets, enabling volume weighting can enhance signal quality. The volatility adjustment feature proves particularly valuable during unstable market conditions.
The Direction Coefficient Indicator stands as a comprehensive solution for traders seeking a sophisticated yet practical approach to market analysis. By combining multiple analytical components into a single, customizable tool, it provides valuable insights while remaining accessible to traders of various experience levels.
For optimal results, traders should consider using this indicator in conjunction with other technical analysis tools while paying attention to its warning signals and volume-weighted insights. Regular parameter adjustment based on changing market conditions and specific trading styles will help maximize the indicator's effectiveness in various trading scenarios.
Indicateur de Coefficient Directeur
L'Indicateur de Coefficient Directeur représente un outil d'analyse technique avancé qui combine l'analyse de momentum des prix avec des ajustements sophistiqués de volume et de volatilité. Cet indicateur polyvalent mesure la direction du marché tout en s'adaptant à diverses conditions de trading, le rendant précieux tant pour le suivi de tendance que pour les stratégies de trading momentum.
À sa base, l'indicateur emploie une approche unique de l'analyse des prix en établissant une période de référence dynamique pour les calculs. Il traite les données de prix à travers un mécanisme de lissage EMA pour réduire le bruit du marché et présente les résultats sous forme de mesures en pourcentage, assurant une applicabilité universelle à travers différents marchés et temporalités.
L'une des caractéristiques distinctives de l'indicateur est son système d'intégration du volume. Lorsqu'il est activé, ce système met en œuvre des calculs pondérés par le volume qui fournissent une précision accrue pendant les mouvements significatifs du marché tout en réduisant efficacement les faux signaux pendant les périodes de faible volume. Ce mécanisme de pondération du volume s'avère particulièrement valuable dans les marchés très liquides où le volume joue un rôle crucial dans la validation des mouvements de prix.
La fonction d'ajustement de la volatilité distingue cet indicateur des outils de momentum traditionnels. En incorporant une normalisation intelligente de la volatilité, l'indicateur s'adapte parfaitement aux conditions changeantes du marché. Cet ajustement aide à maintenir des signaux cohérents à travers différents régimes de volatilité, empêchant le bruit excessif pendant les périodes très volatiles tout en restant suffisamment sensible pendant les phases de marché plus calmes.
La détection des changements de direction forme une autre composante cruciale de l'indicateur. Le système surveille continuellement les changements de momentum et fournit des signaux d'avertissement précoces pour les potentiels renversements de tendance. Cette fonctionnalité aide les traders à éviter les sorties tardives des positions et offre des aperçus précieux des potentiels points de retournement du marché. Lorsque l'indicateur détecte des changements significatifs de momentum, il affiche un symbole d'avertissement (⚠) à côté de ses signaux réguliers.
La présentation visuelle de l'indicateur utilise un système intuitif codé par couleurs. Les étiquettes vertes indiquent un momentum positif, tandis que les étiquettes rouges signifient un momentum négatif. Le système d'affichage inclut des tailles et positions d'étiquettes personnalisables, permettant aux traders d'adapter les éléments visuels à leur configuration spécifique de graphique et leurs préférences. La distance des étiquettes par rapport aux bougies, les schémas de couleurs et les lignes de référence peuvent tous être ajustés pour créer une expérience visuelle optimale.
Pour l'application pratique, l'indicateur offre plusieurs paramètres de réglage que les traders peuvent ajuster. Les paramètres de période temporelle incluent des périodes de référence ajustables et la longueur de l'EMA, tandis que les options de calcul avancées permettent d'activer ou de désactiver les fonctionnalités de pondération du volume et d'ajustement de la volatilité. Ces paramètres peuvent être affinés en fonction des temporalités de trading spécifiques et des conditions de marché.
Dans les scénarios de suivi de tendance, les traders peuvent utiliser la direction du coefficient pour la confirmation de tendance tout en surveillant les signaux d'avertissement pour les sorties potentielles. La fonction de pondération du volume ajoute une couche supplémentaire de confirmation pour la force de la tendance. Pour le trading momentum, des lectures fortes du coefficient peuvent signaler des points d'entrée, tandis que les signaux d'avertissement aident à identifier le timing potentiel de sortie.
La gestion du risque devient plus systématique avec cet indicateur. Les signaux d'avertissement peuvent guider le placement des stops loss, tandis que la fonction d'ajustement de la volatilité aide aux décisions de dimensionnement des positions. La composante de pondération du volume aide les traders à évaluer l'importance des mouvements de prix, contribuant à des décisions de timing d'entrée plus éclairées.
L'indicateur fonctionne de manière optimale lorsque les traders commencent avec les paramètres par défaut et ajustent progressivement les paramètres en fonction de leurs besoins spécifiques. Pour les trades à plus long terme, l'augmentation de la période de référence fournit souvent des signaux plus stables. Dans les marchés très liquides, l'activation de la pondération du volume peut améliorer la qualité des signaux. La fonction d'ajustement de la volatilité s'avère particulièrement précieuse pendant les conditions de marché instables.
L'Indicateur de Coefficient Directeur s'impose comme une solution complète pour les traders recherchant une approche sophistiquée mais pratique de l'analyse de marché. En combinant plusieurs composantes analytiques en un seul outil personnalisable, il fournit des aperçus précieux tout en restant accessible aux traders de différents niveaux d'expérience.
Pour des résultats optimaux, les traders devraient envisager d'utiliser cet indicateur en conjonction avec d'autres outils d'analyse technique tout en prêtant attention à ses signaux d'avertissement et ses aperçus pondérés par le volume. L'ajustement régulier des paramètres basé sur les conditions changeantes du marché et les styles de trading spécifiques aidera à maximiser l'efficacité de l'indicateur dans divers scénarios de trading.
Lsma ATR | viResearchLsma ATR | viResearch
Conceptual Foundation and Innovation
The "Lsma ATR" indicator from viResearch combines the power of the Least Squares Moving Average (LSMA) with the Average True Range (ATR) to offer traders a dynamic approach to trend analysis and volatility management. The LSMA is highly regarded for its ability to fit a linear regression line to price data, providing a smooth and precise trend line with minimal lag. When paired with the ATR, which measures market volatility, this indicator not only tracks trend direction but also adapts to changes in volatility. The integration of both elements allows traders to identify potential trend reversals and assess the strength of trends in the context of market volatility. This combination makes the "Lsma ATR" a versatile tool for following trends while managing risk, as it responds quickly to changes in price direction while accounting for shifts in market volatility.
Technical Composition and Calculation
The "Lsma ATR" script consists of two primary components: the Least Squares Moving Average (LSMA) and the Average True Range (ATR). The LSMA is calculated over a user-defined length, providing a smoothed representation of the market trend based on linear regression. The ATR, also user-defined, is used to measure market volatility by calculating the average range between high and low prices over a specified period. By adding and subtracting the ATR from the LSMA, the indicator creates upper and lower boundaries that help define the market's current volatility-adjusted range. The script monitors for price crossovers with these boundaries to generate trend signals. When the price crosses above the upper boundary, it signals a potential upward trend. Conversely, when the price crosses below the lower boundary, it signals a possible downward trend. These boundaries dynamically adjust based on volatility, providing more accurate signals as market conditions change.
Features and User Inputs
The "Lsma ATR" script offers several customizable inputs, allowing traders to fine-tune the indicator to their trading preferences. The LSMA Length controls the lookback period for the LSMA, determining how smooth or responsive the trend line is. The ATR Length defines the period used for calculating the average volatility, affecting the width of the volatility-adjusted range. Additionally, the indicator includes alert conditions that notify traders when a trend shift occurs, either to the upside or downside.
Practical Applications
The "Lsma ATR" indicator is designed for traders who want to follow market trends while accounting for changes in volatility. The LSMA provides a clear, smoothed trend line that helps identify the direction of the market, while the ATR adjusts the boundaries based on the current volatility level. This combination makes the indicator particularly effective for detecting trend reversals, as the LSMA tracks the overall trend direction and price crossovers with the ATR boundaries provide early signals of potential trend changes. It also helps manage risk by understanding market volatility, allowing traders to adjust their strategies based on the strength of price movements. The indicator improves trend-following strategies by combining LSMA’s trend detection with ATR’s volatility adjustment, offering a nuanced approach in various market conditions.
Advantages and Strategic Value
The "Lsma ATR" script offers significant value by integrating the precision of the LSMA with the adaptability of the ATR. This dual approach allows traders to reduce noise in price data while responding to changes in volatility, leading to more accurate trend signals. The volatility-adjusted boundaries provide a dynamic range that helps traders avoid false signals and stay aligned with stronger trends. This makes the "Lsma ATR" an ideal tool for traders seeking to enhance their trend-following strategies while accounting for market volatility.
Alerts and Visual Cues
The script includes alert conditions that notify traders when the price crosses the ATR boundaries, signaling a potential trend change. The "Lsma ATR Long" alert is triggered when the price crosses above the upper boundary, indicating a potential upward trend, while the "Lsma ATR Short" alert signals a possible downward trend when the price crosses below the lower boundary. Visual cues, such as changes in the color of the LSMA line and shaded areas between the ATR boundaries, help traders quickly identify these trend shifts.
Summary and Usage Tips
The "Lsma ATR | viResearch" indicator combines the smoothing benefits of the LSMA with the volatility sensitivity of the ATR, providing traders with a robust tool for trend detection and volatility management. By incorporating this script into your trading strategy, you can improve your ability to detect trend reversals, confirm trend direction, and manage risk by adjusting to market volatility. The "Lsma ATR" offers a reliable and customizable solution for traders looking to enhance their technical analysis in both trending and volatile market environments.
Note: Backtests are based on past results and are not indicative of future performance.
Open interest buildup & Session Open high-lowThis indicator is to be used on srcipts in Futures Segment.
1. It visually displays in tabular format the change in open interest and the change in price compared to the previous day.
2. It also displays the scenario where open price of session is near high price of session or low price of session, indicating a emergence of strong sellers or strong buyers from start of session respectively.
3. A positive change in open interest and a positive change in price is denoted by a long buildup and open price near low price is an additional confirmation for a probable long scenario in the script.
4. A positive change in open interest and a negative change in price is denoted by a short buildup and open price near high price is and additional confirmation for a probable short scenario in the script.
Key features of the indicator include:
Override Symbol Input: Traders can override the default symbol and input their preferred symbol for analysis.
Open Interest Data: The indicator retrieves open interest data for the selected symbol and time frame, facilitating analysis based on changes in open interest.
Dashboard: The indicator features a customizable dashboard that displays key information such as build-up conditions, OI change, and price change.
Build-Up Conditions: The indicator identifies long build-up and short build-up scenarios based on user-defined thresholds for OI change and price change percentages.
Customization Options: Traders have the flexibility to customize various aspects of the indicator, including colors for long build-up, short build-up, positive OI change, negative OI change, positive price change, and negative price change.
Label Plots: Buy and sell labels are plotted on the chart to highlight potential trading opportunities. Traders can customize the colors and text colors of these labels based on their preferences.
Overall, the indicator offers traders a comprehensive tool for analyzing price movements and open interest changes, helping them make informed trading decisions in the futures segment.
RSI Missmatch(Divergence) OSC. by Neo_ with Missmatch Alert█ Definition
A divergence or missmatch occurs when an asset’s price is moving opposite to a specific technical indicator or is moving in a different direction from other relevant data. The divergence indicator warns traders and technical analysts of changes in a price trend, oftentimes that it is weakening or changing direction.
Divergence or missmatch can be either positive, signifying the possibility of a move that is higher in the asset’s price, or it can be negative, signifying the possibility of a move that is lower in the asset’s price.
█ Takeaways
Divergence or missmatch often works with other indicators and data. It is usually used by technical analysts and traders when the asset’s price is moving counter to the direction of another indicator.
As mentioned above, positive divergence or missmatch indicates that the price could start rising and usually occurs when the price is moving lower, but while another indicator counters this direction by moving higher. In other words, showing bullish signals.
Negative divergence or missmatch indicates that the price could start declining and usually occurs when the price is moving higher, while another indicator moves lower as well. In other words, showing bearish signals.
█ What to look for
Divergence or missmatch is most often used to track and analyze the momentum in an asset’s price and the odds of a price reversal within the current trend. While using divergence, traders and analysts can decide on whether or not they would like to exit the position or set a stop loss in the case the divergence is negative and prices begin to fall.
█ Limitations
It is best to use divergence or missmatch with the aid of other indicators and analysis tools in order to help identify and confirm trend reversals and major market patterns. Divergence should not be relied on by itself to tell you the pertinent information you need to know as an investor. Risk control is key in your analysis and the fact that divergence is not always present in price reversals should definitely be what pushes you to combine it with other tools and indicators.
Additionally, divergence or missmatch can reflect long-term or short-term changes. When making snap decisions, acting on divergence alone could prove detrimental to your trading. Make sure you have other risk factors applied to your charting and general market analysis.
█ What exactly is RSI Missmatches discrepancies using a lookback period in trading?
In trading, lookback period is the number of periods of historical data used for observation and calculation. It is how far into the past the system looks when trying to calculate the variable under consideration. The concept was based on the fact that history can provide information about the future, and my aim was to predict the periods when trend changes would begin within these periods with the RSI oscillator. But this is only true if you're locked back far enough, not locked any further or less!
We already use the idea of looking back in different aspects of our lives, and even in the world of financial trading it can be used in various ways. Of course you will want to learn more about the concept, so in this article we will cover the following topics:
█ What kind of hindsight is this?
The aim here is to check whether trends will change in certain cycles, so we chose the High + Low / 2 formula as the source. Because no matter how much the prices swing up or down, sometimes the rebound can go further. The aim here is to notice the points where the price leaves a needle at the levels where it oscillates and the slowdown in momentum.
█ What does look-back period mean in trade?
To understand what a lookback period means in trading, you need to ask yourself: What is a lookback period in trading? In financial trading, period refers to the duration of a particular trading session. For example, a one-week period means one full week of trading sessions or five trading days. In 5 trading days, the average time is 120 hours in FX markets and 40 hours in stock markets. Regardless of what happens in these cycles, I prefer to choose a time period of 55 periods. Because I noticed that in all the charts I examined, the cycles generally changed during this time period.
█ Let's talk about the meaning of catching Missmatches
As you know, technical indicators are all a mathematical calculation using historical market data (price, volume, or a combination of both). It shows the behavior of the price better and helps in the analysis of price movement. But the indicator can only serve your intended purpose if you get the lookback time right. What we mean here is the setting parameter that determines how much historical data it will use in its calculation. In other words, it is the retrospective review period.
For example, on the RSI indicator you can set this period to 13 periods (default setting) or even 2 periods. The period you choose can determine what the indicator tells you, which in turn determines the strategy you can create with the indicator. The 13- period RSI gives you information about price momentum, so you can effectively use it to create a momentum strategy. On the other hand, the 2-periods RSI can be used to create a mean reversion strategy. To catch any incompatibilities, I set this period to 55 periods. Nothing more, nothing less!
█ Summary
The missmatch indicator helps traders assess changes in the price trend and indicates when price will move with or against the direction of another indicator. It can be either positive or negative, but it is important to note its limitations and that it should be used with other indicators that can also monitor price trends.
We wish you to identify these incompatibilities in the market in the best way possible... Good luck.
█ Tanım
Bir varlığın fiyatı belirli bir teknik göstergenin tersi yönünde hareket ettiğinde veya diğer ilgili verilerden farklı bir yönde hareket ettiğinde bir sapma veya uyumsuzluk meydana gelir. Farklılık göstergesi, tüccarları ve teknik analistleri fiyat eğilimindeki değişiklikler konusunda uyarır; çoğu zaman zayıflıyor veya yön değiştiriyor.
Farklılık veya uyumsuzluk, varlığın fiyatında daha yüksek bir hareket olasılığını işaret ederek pozitif olabilir veya varlığın fiyatında daha düşük bir hareket olasılığını işaret ederek negatif olabilir.
█ Çıkarımlar
Farklılık veya uyumsuzluk çoğu zaman diğer göstergeler ve verilerle de çalışır. Genellikle teknik analistler ve yatırımcılar tarafından varlığın fiyatı başka bir göstergenin yönünün tersine hareket ettiğinde kullanılır.
Yukarıda bahsedildiği gibi pozitif sapma veya uyumsuzluk, fiyatın yükselmeye başlayabileceğini gösterir ve genellikle fiyat düşerken meydana gelir, ancak başka bir gösterge bu yöne yükselerek karşı koyar. Başka bir deyişle yükseliş sinyalleri veriyor.
Negatif sapma veya uyumsuzluk, fiyatın düşmeye başlayabileceğini gösterir ve genellikle fiyat yükselirken başka bir gösterge de düşerken meydana gelir. Başka bir deyişle düşüş sinyalleri veriyor.
█ Nelere bakılmalı
Farklılık veya uyumsuzluk çoğunlukla bir varlığın fiyatındaki momentumu ve mevcut trend içinde fiyatın tersine dönme olasılığını izlemek ve analiz etmek için kullanılır. Farklılaşmayı kullanırken tüccarlar ve analistler, sapmanın negatif olması ve fiyatların düşmeye başlaması durumunda pozisyondan çıkmak isteyip istemeyeceklerine veya zararı durdurma kararı verip veremeyeceklerine karar verebilirler.
█ Sınırlamalar
Trend dönüşlerini ve ana piyasa modellerini tanımlamaya ve doğrulamaya yardımcı olmak için diğer göstergeler ve analiz araçlarının yardımıyla sapmayı veya uyumsuzluğu kullanmak en iyisidir. Bir yatırımcı olarak bilmeniz gereken ilgili bilgileri size söylemesi için farklılığa tek başına güvenilmemelidir. Risk kontrolü analizinizin anahtarıdır ve fiyat dönüşlerinde farklılığın her zaman mevcut olmaması gerçeği kesinlikle sizi onu diğer araç ve göstergelerle birleştirmeye iten şey olmalıdır.
Ek olarak, farklılık veya uyumsuzluk uzun vadeli veya kısa vadeli değişiklikleri yansıtabilir. Ani kararlar verirken yalnızca farklılıklara göre hareket etmek ticaretinize zarar verebilir. Grafiğinize ve genel piyasa analizinize başka risk faktörlerinin uygulandığından emin olun.
█ Ticarette yeniden inceleme dönemi kullanan RSI Missmatches tutarsızlıkları tam olarak nedir?
Ticarette yeniden inceleme süresi, gözlem ve hesaplama için kullanılan geçmiş verilerin dönemlerinin sayısıdır. Söz konusu değişkeni hesaplamaya çalışırken sistemin ne kadar geçmişe baktığıdır. Konsept tarihin geleceğe dair bilgi verebileceği gerçeği üzerine kuruluydu ve amacım RSI osilatörü ile bu dönemler içerisinde trend değişimlerinin başlayacağı dönemleri tahmin etmekti. Ancak bu yalnızca yeterince geriye kilitlenmişseniz geçerlidir, daha fazla veya daha az kilitlenmemişseniz!
Geriye bakma fikrini hayatımızın farklı yönlerinde zaten kullanıyoruz ve hatta finansal ticaret dünyasında bile bu fikir çeşitli şekillerde kullanılabilir. Elbette konsept hakkında daha fazla bilgi edinmek isteyeceksiniz, bu nedenle bu yazıda aşağıdaki konuları ele alacağız:
█ Bu nasıl bir sonradan görmedir?
Burada amaç belli döngülerde trendlerin değişip değişmeyeceğini kontrol etmek olduğundan kaynak olarak Yüksek + Düşük / 2 formülünü seçtik. Çünkü fiyatlar ne kadar yukarı veya aşağı hareket ederse etsin bazen toparlanma daha da ileri gidebiliyor. Burada amaç fiyatın salınım yaptığı seviyelerde iğne bıraktığı noktaları ve momentumdaki yavaşlamayı fark etmektir.
█ Ticarette geriye bakma süresi ne anlama geliyor?
Ticarette yeniden inceleme süresinin ne anlama geldiğini anlamak için kendinize şu soruyu sormanız gerekir: Ticarette yeniden inceleme süresi nedir? Finansal ticarette dönem, belirli bir ticaret seansının süresini ifade eder. Örneğin, bir haftalık dönem, bir tam haftalık işlem seansı veya beş işlem günü anlamına gelir. 5 işlem gününde ortalama süre döviz piyasalarında 120 saat, borsalarda ise 40 saattir. Bu döngülerde ne olursa olsun 55 periyotluk bir zaman dilimini seçmeyi tercih ediyorum. Çünkü incelediğim tüm grafiklerde bu zaman diliminde döngülerin genel olarak değiştiğini fark ettim.
█ Kaçak Eşleşmeleri yakalamanın anlamı hakkında konuşalım
Bildiğiniz gibi teknik göstergeler, geçmiş piyasa verileri (fiyat, hacim veya her ikisinin birleşimi) kullanılarak yapılan matematiksel hesaplamalardır. Fiyatın davranışını daha iyi gösterir ve fiyat hareketinin analizine yardımcı olur. Ancak gösterge yalnızca yeniden inceleme süresini doğru yaparsanız amacınıza hizmet edebilir. Burada kast ettiğimiz, hesaplamasında ne kadar geçmiş veri kullanacağını belirleyen ayar parametresidir. Bir başka deyişle geriye dönük inceleme dönemidir.
Örneğin RSI göstergesinde bu süreyi 13 döneme (varsayılan ayar) ve hatta 2 döneme ayarlayabilirsiniz. Seçeceğiniz dönem, göstergenin size ne söyleyeceğini belirleyebilir ve bu da gösterge ile oluşturabileceğiniz stratejiyi belirler. 13 dönemlik RSI size fiyat momentumu hakkında bilgi verir, böylece onu bir momentum stratejisi oluşturmak için etkili bir şekilde kullanabilirsiniz. Öte yandan, ortalamaya dönüş stratejisi oluşturmak için 2 dönemlik RSI kullanılabilir. Herhangi bir uyumsuzluğu yakalamak için bu periyodu 55 periyoda ayarladım. Ne fazla ne eksik!
█ Özet
Uyumsuzluk göstergesi, yatırımcıların fiyat eğilimindeki değişiklikleri değerlendirmesine yardımcı olur ve fiyatın ne zaman başka bir göstergenin yönüne göre veya ona karşı hareket edeceğini gösterir. Olumlu ya da olumsuz olabilir, ancak sınırlamalarına dikkat etmek ve fiyat eğilimlerini de izleyebilecek diğer göstergelerle birlikte kullanılması gerektiğini unutmamak önemlidir.
Piyasadaki bu uyumsuzlukları en iyi şekilde tespit etmenizi dileriz... Bol Kazançlar.
Custom RSI with RMA SmoothingCustom RSI with RMA Smoothing is smoothing the classic Relative Strength Index to enhance the effectiveness of using the RSI for trend-following through noise reduction.
Principle:
1. RSI is smoothed by the Rolling Moving Average (RMA) and averaged Gains & Losses instead of the classic RSI calculation.
2. A RMA is plotted over the RSI where the crossovers can be entry and exit points.
How is RSI smoothed by the RMA:
1. Outside the common price sources a few new options like hhhlc or hlcc can be chosen where the emphasis is more on the high or the close of the chosen period.
2. Calculation of Price Change: After selecting the price source, the indicator calculates the price change by subtracting the previous period's price from the current price.
3. RMA Smoothing of Price Change: The key step in smoothing the RSI is the application of the Running Moving Average (RMA) to the price change. The length of this RMA is set by the user and determines the extent of smoothing. RMA is a type of moving average that gives more weight to recent data points, making it more responsive to new information while still smoothing out short-term fluctuations.
4. Determining Gains and Losses: The smoothed price change is then used to calculate the gains and losses for each period. Gains are considered when the smoothed price change is positive, and losses when it is negative.
5. Averaging Gains and Losses: These gains and losses are further smoothed by calculating their respective RMAs over the user-defined RSI length. This step is crucial as it dampens the impact of short-term price spikes and drops, giving a more stable and reliable measure of price momentum.
6. RSI Calculation: The standard RSI formula (100 - ) is then applied to these smoothed values. This results in the initial RSI value, which is already more stable than a typical RSI due to the previous smoothing steps.
7. Final RMA Smoothing of RSI: In a final layer of refinement, the RSI itself is smoothed using another RMA, over a length specified by the user. This additional smoothing further reduces the impact of short-term volatility and sharp price movements, providing a more coherent and interpretable RSI line.
SuperTrend with Chebyshev FilterModified Super Trend with Chebyshev Filter
The Modified Super Trend is an innovative take on the classic Super Trend indicator. This advanced version incorporates a Chebyshev filter, which significantly enhances its capabilities by reducing false signals and improving overall signal quality. In this post, we'll dive deep into the Modified Super Trend, exploring its history, the benefits of the Chebyshev filter, and how it effectively addresses the challenges associated with smoothing, delay, and noise.
History of the Super Trend
The Super Trend indicator, developed by Olivier Seban, has been a popular tool among traders since its inception. It helps traders identify market trends and potential entry and exit points. The Super Trend uses average true range (ATR) and a multiplier to create a volatility-based trailing stop, providing traders with a dynamic tool that adapts to changing market conditions. However, the original Super Trend has its limitations, such as the tendency to produce false signals during periods of low volatility or sideways trading.
The Chebyshev Filter
The Chebyshev filter is a powerful mathematical tool that makes an excellent addition to the Super Trend indicator. It effectively addresses the issues of smoothing, delay, and noise associated with traditional moving averages. Chebyshev filters are named after Pafnuty Chebyshev, a renowned Russian mathematician who made significant contributions to the field of approximation theory.
The Chebyshev filter is capable of producing smoother, more responsive moving averages without introducing additional lag. This is possible because the filter minimizes the worst-case error between the ideal and the actual frequency response. There are two types of Chebyshev filters: Type I and Type II. Type I Chebyshev filters are designed to have an equiripple response in the passband, while Type II Chebyshev filters have an equiripple response in the stopband. The Modified Super Trend allows users to choose between these two types based on their preferences.
Overcoming the Challenges
The Modified Super Trend addresses several challenges associated with the original Super Trend:
Smoothing: The Chebyshev filter produces a smoother moving average without introducing additional lag. This feature is particularly beneficial during periods of low volatility or sideways trading, as it reduces the number of false signals.
Delay: The Chebyshev filter helps minimize the delay between price action and the generated signal, allowing traders to make timely decisions based on more accurate information.
Noise Reduction: The Chebyshev filter's ability to minimize the worst-case error between the ideal and actual frequency response reduces the impact of noise on the generated signals. This feature is especially useful when using the true range as an offset for the price, as it helps generate more reliable signals within a reasonable time frame.
The Great Replacement
The Modified Super Trend with Chebyshev filter is an excellent replacement for the original Super Trend indicator. It offers significant improvements in terms of signal quality, responsiveness, and accuracy. By incorporating the Chebyshev filter, the Modified Super Trend effectively reduces the number of false signals during low volatility or sideways trading, making it a more reliable tool for identifying market trends and potential entry and exit points.
In-Depth Guide to the Modified Super Trend Settings
The Modified Super Trend with Chebyshev filter offers a wide range of settings that allow traders to fine-tune the indicator to suit their specific trading styles and objectives. In this section, we will discuss each setting in detail, explaining its purpose and how to use it effectively.
Source
The source setting determines the price data used for calculations. The default setting is hl2, which calculates the average of the high and low prices. You can choose other price data sources such as close, open, or ohlc4 (average of open, high, low, and close prices) based on your preference.
Up Color and Down Color
These settings control the color of the trend line when the market is in an uptrend (up_color) and a downtrend (down_color). You can customize these colors to your liking, making it easier to visually identify the current market trend.
Text Color
This setting controls the color of the text displayed on the chart when using labels to indicate trend changes. You can choose any color that contrasts well with your chart background for better readability.
Mean Length
The mean_length setting determines the length (number of bars) used for the Chebyshev moving average calculation. A shorter length will make the moving average more responsive to price changes, while a longer length will produce a smoother moving average. It is crucial to find the right balance between responsiveness and smoothness, as a too-short length may generate false signals, while a too-long length might produce lagging signals. The default value is 64, but you can experiment with different values to find the optimal setting for your trading strategy.
Mean Ripple
The mean_ripple setting influences the Chebyshev filter's ripple effect in the passband (Type I) or stopband (Type II). The ripple effect represents small oscillations in the frequency response, which can impact the moving average's smoothness. The default value is 0.01, but you can experiment with different values to find the best balance between smoothness and responsiveness.
Chebyshev Type: Type I or Type II
The style setting allows you to choose between Type I and Type II Chebyshev filters. Type I filters have an equiripple response in the passband, while Type II filters have an equiripple response in the stopband. Depending on your preference for smoothness and responsiveness, you can choose the type that best fits your trading style.
ATR Style
The atr_style setting determines the method used for calculating the Average True Range (ATR). By default (false), it uses the traditional high-low range. When set to true, it uses the absolute difference between the open and close prices. You can choose the method that works best for your trading strategy and the market you are trading.
ATR Length
The atr_length setting controls the length (number of bars) used for calculating the ATR. Similar to the mean_length, a shorter length will make the ATR more responsive to price changes, while a longer length will produce a smoother ATR. The default value is 64, but you can experiment with different values to find the optimal setting for your trading strategy.
ATR Ripple
The atr_ripple setting, like the mean_ripple, influences the ripple effect of the Chebyshev filter used in the ATR calculation. The default value is 0.05, but you can experiment with different values to find the best balance between smoothness and responsiveness.
Multiplier
The multiplier setting determines the factor by which the ATR is multiplied before being added
Super Trend Logic and Signal Optimization
The Modified Super Trend with Chebyshev filter is designed to minimize false signals and provide a clear indication of market trends. It does so by using a combination of moving averages, Average True Range (ATR), and a multiplier. In this section, we will discuss the Super Trend's logic, its ability to prevent false signals, and the early warning crosses added to the indicator.
Super Trend Logic
The Super Trend's logic is based on a combination of the Chebyshev moving average and ATR. The Chebyshev moving average is a smooth moving average that effectively filters out market noise, while the ATR is a measure of market volatility.
The Super Trend is calculated by adding or subtracting a multiple of the ATR from the Chebyshev moving average. The multiplier is a user-defined value that determines the distance between the trend line and the price action. A larger multiplier results in a wider channel, reducing the likelihood of false signals but potentially missing out on valid trend changes.
Preventing False Signals
The Super Trend is designed to minimize false signals by maintaining its trend direction until a significant change in the market occurs. In a downtrend, the trend line will only decrease in value, and in an uptrend, it will only increase. This helps prevent false signals caused by temporary price fluctuations or market noise.
When the price crosses the trend line, the Super Trend does not immediately change its direction. Instead, it employs a safety logic to ensure that the trend change is genuine. The safety logic checks if the new trend line (calculated using the updated moving average and ATR) is more extreme than the previous one. If it is, the trend line is updated; otherwise, the previous trend line is maintained. This mechanism further reduces the likelihood of false signals by ensuring that the trend line only changes when there is a significant shift in the market.
Early Warning Crosses
To provide traders with additional insight, the Modified Super Trend with Chebyshev filter includes early warning crosses. These crosses are plotted on the chart when the price crosses the trend line without the safety logic. Although these crosses do not necessarily indicate a trend change, they can serve as a valuable heads-up for traders to monitor the market closely and prepare for potential trend reversals.
In conclusion, the Modified Super Trend with Chebyshev filter offers a significant improvement over the original Super Trend indicator. By incorporating the Chebyshev filter, this modified version effectively addresses the challenges of smoothing, delay, and noise reduction while minimizing false signals. The wide range of customizable settings allows traders to tailor the indicator to their specific needs, while the inclusion of early warning crosses provides valuable insight into potential trend reversals.
Ultimately, the Modified Super Trend with Chebyshev filter is an excellent tool for traders looking to enhance their trend identification and decision-making abilities. With its advanced features, this indicator can help traders navigate volatile markets with confidence, making more informed decisions based on accurate, timely information.
ICT Concepts [LuxAlgo]The ICT Concepts indicator regroups core concepts highlighted by trader and educator "The Inner Circle Trader" (ICT) into an all-in-one toolkit. Features include Market Structure (MSS & BOS), Order Blocks, Imbalances, Buyside/Sellside Liquidity, Displacements, ICT Killzones, and New Week/Day Opening Gaps.
🔶 SETTINGS
🔹 Mode
When Present is selected, only data of the latest 500 bars are used/visualized, except for NWOG/NDOG
🔹 Market Structure
Enable/disable Market Structure.
Length: will set the lookback period/sensitivity.
In Present Mode only the latest Market Structure trend will be shown, while in Historical Mode, previous trends will be shown as well:
You can toggle MSS/BOS separately and change the colors:
🔹 Displacement
Enable/disable Displacement.
🔹 Volume Imbalance
Enable/disable Volume Imbalance.
# Visible VI's: sets the amount of visible Volume Imbalances (max 100), color setting is placed at the side.
🔹 Order Blocks
Enable/disable Order Blocks.
Swing Lookback: Lookback period used for the detection of the swing points used to create order blocks.
Show Last Bullish OB: Number of the most recent bullish order/breaker blocks to display on the chart.
Show Last Bearish OB: Number of the most recent bearish order/breaker blocks to display on the chart.
Color settings.
Show Historical Polarity Changes: Allows users to see labels indicating where a swing high/low previously occurred within a breaker block.
Use Candle Body: Allows users to use candle bodies as order block areas instead of the full candle range.
Change in Order Blocks style:
🔹 Liquidity
Enable/disable Liquidity.
Margin: sets the sensitivity, 2 points are fairly equal when:
'point 1' < 'point 2' + (10 bar Average True Range / (10 / margin)) and
'point 1' > 'point 2' - (10 bar Average True Range / (10 / margin))
# Visible Liq. boxes: sets the amount of visible Liquidity boxes (max 50), this amount is for Sellside and Buyside boxes separately.
Colour settings.
Change in Liquidity style:
🔹 Fair Value Gaps
Enable/disable FVG's.
Balance Price Range: this is the overlap of latest bullish and bearish Fair Value Gaps.
By disabling Balance Price Range only FVGs will be shown.
Options: Choose whether you wish to see FVG or Implied Fair Value Gaps (this will impact Balance Price Range as well)
# Visible FVG's: sets the amount of visible FVG's (max 20, in the same direction).
Color settings.
Change in FVG style:
🔹 NWOG/NDOG
Enable/disable NWOG; color settings; amount of NWOG shown (max 50).
Enable/disable NDOG ; color settings; amount of NDOG shown (max 50).
🔹 Fibonacci
This tool connects the 2 most recent bullish/bearish (if applicable) features of your choice, provided they are enabled.
3 examples (FVG, BPR, OB):
Extend lines -> Enabled (example OB):
🔹 Killzones
Enable/disable all or the ones you need.
Time settings are coded in the corresponding time zones.
🔶 USAGE
By default, the indicator displays each feature relevant to the most recent price variations in order to avoid clutter on the chart & to provide a very similar experience to how a user would contruct ICT Concepts by hand.
Users can use the historical mode in the settings to see historical market structure/imbalances. The ICT Concepts indicator has various use cases, below we outline many examples of how a trader could find usage of the features together.
In the above image we can see price took out Sellside liquidity, filled two bearish FVGs, a market structure shift, which then led to a clean retest of a bullish FVG as a clean setup to target the order block above.
Price then fills the OB which creates a breaker level as seen in yellow.
Broken OBs can be useful for a trader using the ICT Concepts indicator as it marks a level where orders have now been filled, indicating a solidified level that has proved itself as an area of liquidity. In the image above we can see a trade setup using a broken bearish OB as a potential entry level.
We can see the New Week Opening Gap (NWOG) above was an optimal level to target considering price may tend to fill / react off of these levels according to ICT.
In the next image above, we have another example of various use cases where the ICT Concepts indicator hypothetically allow traders to find key levels & find optimal entry points using market structure.
In the image above we can see a bearish Market Structure Shift (MSS) is confirmed, indicating a potential trade setup for targeting the Balanced Price Range imbalance (BPR) below with a stop loss above the buyside liquidity.
Although what we are demonstrating here is a hindsight example, it shows the potential usage this toolkit gives you for creating trading plans based on ICT Concepts.
Same chart but playing out the history further we can see directly after price came down to the Sellside liquidity & swept below it...
Then by enabling IFVGs in the settings, we can see the IFVG retests alongside the Sellside & Buyside liquidity acting in confluence.
Which allows us to see a great bullish structure in the market with various key levels for potential entries.
Here we can see a potential bullish setup as price has taken out a previous Sellside liquidity zone and is now retesting a NWOG + Volume Imbalance.
Users also have the option to display Fibonacci retracements based on market structure, order blocks, and imbalance areas, which can help place limit/stop orders more effectively as well as finding optimal points of interest beyond what the primary ICT Concepts features can generate for a trader.
In the above image we can see the Fibonacci extension was selected to be based on the NWOG giving us some upside levels above the buyside liquidity.
🔶 DETAILS
Each feature within the ICT Concepts indicator is described in the sub sections below.
🔹 Market Structure
Market structure labels are constructed from price breaking a prior swing point. This allows a user to determine the current market trend based on the price action.
There are two types of Market Structure labels included:
Market Structure Shift (MSS)
Break Of Structure (BOS)
A MSS occurs when price breaks a swing low in an uptrend or a swing high in a downtrend, highlighting a potential reversal. This is often labeled as "CHoCH", but ICT specifies it as MSS.
On the other hand, BOS labels occur when price breaks a swing high in an uptrend or a swing low in a downtrend. The occurrence of these particular swing points is caused by retracements (inducements) that highlights liquidity hunting in lower timeframes.
🔹 Order Blocks
More significant market participants (institutions) with the ability of placing large orders in the market will generally place a sequence of individual trades spread out in time. This is referred as executing what is called a "meta-order".
Order blocks highlight the area where potential meta-orders are executed. Bullish order blocks are located near local bottoms in an uptrend while bearish order blocks are located near local tops in a downtrend.
When price mitigates (breaks out) an order block, a breaker block is confirmed. We can eventually expect price to trade back to this breaker block offering a new trade opportunity.
🔹 Buyside & Sellside Liquidity
Buyside / Sellside liquidity levels highlight price levels where market participants might place limit/stop orders.
Buyside liquidity levels will regroup the stoploss orders of short traders as well as limit orders of long traders, while Sellside liquidity levels will regroup the stoploss orders of long traders as well as limit orders of short traders.
These levels can play different roles. More informed market participants might view these levels as source of liquidity, and once liquidity over a specific level is reduced it will be found in another area.
🔹 Imbalances
Imbalances highlight disparities between the bid/ask, these can also be defined as inefficiencies, which would suggest that not all available information is reflected by the price and would as such provide potential trading opportunities.
It is common for price to "rebalance" and seek to come back to a previous imbalance area.
ICT highlights multiple imbalance formations:
Fair Value Gaps: A three candle formation where the candle shadows adjacent to the central candle do not overlap, this highlights a gap area.
Implied Fair Value Gaps: Unlike the fair value gap the implied fair value gap has candle shadows adjacent to the central candle overlapping. The gap area is constructed from the average between the respective shadow and the nearest extremity of their candle body.
Balanced Price Range: Balanced price ranges occur when a fair value gap overlaps a previous fair value gap, with the overlapping area resulting in the imbalance area.
Volume Imbalance: Volume imbalances highlight gaps between the opening price and closing price with existing trading activity (the low/high overlap the previous high/low).
Opening Gap: Unlike volume imbalances opening gaps highlight areas with no trading activity. The low/high does not reach previous high/low, highlighting a "void" area.
🔹 Displacement
Displacements are scenarios where price forms successive candles of the same sentiment (bullish/bearish) with large bodies and short shadows.
These can more technically be identified by positive auto correlation (a close to open change is more likely to be followed by a change of the same sign) as well as volatility clustering (large changes are followed by large changes).
Displacements can be the cause for the formation of imbalances as well as market structure, these can be caused by the full execution of a meta order.
🔹 Kill Zones
Killzones represent different time intervals that aims at offering optimal trade entries. Killzones include:
- New York Killzone (7:9 ET)
- London Open Killzone (2:5 ET)
- London Close Killzone (10:12 ET)
- Asian Killzone (20:00 ET)
🔶 Conclusion & Supplementary Material
This script aims to emulate how a trader would draw each of the covered features on their chart in the most precise representation to how it's actually taught by ICT directly.
There are many parallels between ICT Concepts and Smart Money Concepts that we released in 2022 which has a more general & simpler usage:
ICT Concepts, however, is more specifically aligned toward the community's interpretation of how to analyze price 'based on ICT', rather than displaying features to have a more classic interpretation for a technical analyst.
[MT] Strategy Backtest Template| Initial Release | | EN |
An update of my old script, this script is designed so that it can be used as a template for all those traders who want to save time when programming their strategy and backtesting it, having functions already programmed that in normal development would take you more time to program, with this template you can simply add your favorite indicator and thus be able to take advantage of all the functions that this template has.
🔴Stop Loss and 🟢Take Profit:
No need to mention that it is a Stop Loss and a Take Profit, within these functions we find the options of: fixed percentage (%), fixed price ($), ATR, especially for Stop Loss we find the Pivot Points, in addition to this, the price range between the entry and the Stop Loss can be converted into a trailing stop loss, instead, especially for the Take Profit we have an option to choose a 1:X ratio that complements very well with the Pivot Points.
📈Heikin Ashi Based Entries:
Heikin Ashi entries are trades that are calculated based on Heikin Ashi candles but their price is executed to Japanese candles, thus avoiding false results that occur in Heikin candlestick charts, this making in certain cases better results in strategies that are executed with this option compared to Japanese candlesticks.
📊Dashboard:
A more visual and organized way to see the results and necessary data produced by our strategy, among them we can see the dates between which our operations are made regardless if you have activated some time filter, usual data such as Profit, Win Rate, Profit factor are also displayed in this panel, additionally data such as the total number of operations, how many were gains and how many losses, the average profit and loss for each operation and finally the maximum profits and losses followed, which are data that will be very useful to us when we elaborate our strategies.
Feel free to use this template to program your own strategies, if you find errors or want to request a new feature let me know in the comments or through my social networks found in my tradingview profile.
| Update 1.1 | | EN |
➕Additions: '
Time sessions filter and days of the week filter added to the time filter section.
Option to add leverage to the strategy.
5 Moving Averages, RSI, Stochastic RSI, ADX, and Parabolic Sar have been added as indicators for the strategy.
You can choose from the 6 available indicators the way to trade, entry alert or entry filter.
Added the option of ATR for Take Profit.
Ticker information and timeframe are now displayed on the dashboard.
Added display customization and color customization of indicator plots.
Added customization of display and color plots of trades displayed on chart.
📝Changes:
Now when activating the time filter it is optional to add a start or end date and time, being able to only add a start date or only an end date.
Operation plots have been changed from plot() to line creation with line.new().
Indicator plots can now be controlled from the "plots" section.
Acceptable and deniable range of profit, winrate and profit factor can now be chosen from the "plots" section to be displayed on the dashboard.
Aesthetic changes in the section separations within the settings section and within the code itself.
The function that made the indicators give inputs based on heikin ashi candles has been changed, see the code for more information.
⚙️Fixes:
Dashboard label now projects correctly on all timeframes including custom timeframes.
Removed unnecessary lines and variables to take up less code space.
All code in general has been optimized to avoid the use of variables, unnecessary lines and avoid unnecessary calculations, freeing up space to declare more variables and be able to use fewer lines of code.
| Lanzamiento Inicial | | ES |
Una actualización de mi antiguo script, este script está diseñado para que pueda ser usado como una plantilla para todos aquellos traders que quieran ahorrar tiempo al programar su estrategia y hacer un backtesting de ella, teniendo funciones ya programadas que en el desarrollo normal te tomaría más tiempo programar, con esta plantilla puedes simplemente agregar tu indicador favorito y así poder aprovechar todas las funciones que tiene esta plantilla.
🔴Stop Loss y 🟢Take Profit:
No hace falta mencionar que es un Stop Loss y un Take Profit, dentro de estas funciones encontramos las opciones de: porcentaje fijo (%), precio fijo ($), ATR, en especial para Stop Loss encontramos los Pivot Points, adicionalmente a esto, el rango de precio entre la entrada y el Stop Loss se puede convertir en un trailing stop loss, en cambio, especialmente para el Take Profit tenemos una opción para elegir un ratio 1:X que se complementa muy bien con los Pivot Points.
📈Entradas Basadas en Heikin Ashi:
Las entradas Heikin Ashi son operaciones que son calculados en base a las velas Heikin Ashi pero su precio esta ejecutado a velas japonesas, evitando así́ los falsos resultados que se producen en graficas de velas Heikin, esto haciendo que en ciertos casos se obtengan mejores resultados en las estrategias que son ejecutadas con esta opción en comparación con las velas japonesas.
📊Panel de Control:
Una manera más visual y organizada de ver los resultados y datos necesarios producidos por nuestra estrategia, entre ellos podemos ver las fechas entre las que se hacen nuestras operaciones independientemente si se tiene activado algún filtro de tiempo, datos usuales como el Profit, Win Rate, Profit factor también son mostrados en este panel, adicionalmente se agregaron datos como el número total de operaciones, cuantos fueron ganancias y cuantos perdidas, el promedio de ganancias y pérdidas por cada operación y por ultimo las máximas ganancias y pérdidas seguidas, que son datos que nos serán muy útiles al elaborar nuestras estrategias.
Siéntete libre de usar esta plantilla para programar tus propias estrategias, si encuentras errores o quieres solicitar una nueva función házmelo saber en los comentarios o a través de mis redes sociales que se encuentran en mi perfil de tradingview.
| Actualización 1.1 | | ES |
➕Añadidos:
Filtro de sesiones de tiempo y filtro de días de la semana agregados al apartado de filtro de tiempo.
Opción para agregar apalancamiento a la estrategia.
5 Moving Averages, RSI, Stochastic RSI, ADX, y Parabolic Sar se han agregado como indicadores para la estrategia.
Puedes escoger entre los 6 indicadores disponibles la forma de operar, alerta de entrada o filtro de entrada.
Añadido la opción de ATR para Take Profit.
La información del ticker y la temporalidad ahora se muestran en el dashboard.
Añadido personalización de visualización y color de los plots de indicadores.
Añadido personalización de visualización y color de los plots de operaciones mostradas en grafica.
📝Cambios:
Ahora al activar el filtro de tiempo es opcional añadir una fecha y hora de inicio o fin, pudiendo únicamente agregar una fecha de inicio o solamente una fecha de fin.
Los plots de operaciones han cambiados de plot() a creación de líneas con line.new().
Los plots de indicadores ahora se pueden controlar desde el apartado "plots".
Ahora se puede elegir el rango aceptable y negable de profit, winrate y profit factor desde el apartado "plots" para mostrarse en el dashboard.
Cambios estéticos en las separaciones de secciones dentro del apartado de configuraciones y dentro del propio código.
Se ha cambiado la función que hacía que los indicadores dieran entradas en base a velas heikin ashi, mire el código para más información.
⚙️Arreglos:
El dashboard label ahora se proyecta correctamente en todas las temporalidades incluyendo las temporalidades personalizadas.
Se han eliminado líneas y variables innecesarias para ocupar menos espacio en el código.
Se ha optimizado todo el código en general para evitar el uso de variables, líneas innecesarias y evitar los cálculos innecesarios, liberando espacio para declarar más variables y poder utilizar menos líneas de código.
Moving Average Filters Add-on w/ Expanded Source Types [Loxx]Moving Average Filters Add-on w/ Expanded Source Types is a conglomeration of specialized and traditional moving averages that will be used in most of indicators that I publish moving forward. There are 39 moving averages included in this indicator as well as expanded source types including traditional Heiken Ashi and Better Heiken Ashi candles. You can read about the expanded source types clicking here . About half of these moving averages are closed source on other trading platforms. This indicator serves as a reference point for future public/private, open/closed source indicators that I publish to TradingView. Information about these moving averages was gleaned from various forex and trading forums and platforms as well as TASC publications and other assorted research publications.
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Included moving averages
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA, it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA.
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average (DEMA) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA. It's also considered a leading indicator compared to the EMA, and is best utilized whenever smoothness and speed of reaction to market changes are required.
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA (Simple Moving Average). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA.
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Hull Moving Average - HMA
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points.
IE/2 - Early T3 by Tim Tilson
The IE/2 is a Moving Average that uses Linear Regression slope in its calculation to help with smoothing. It's a worthy Moving Average on it's own, even though it is the precursor and very early version of the famous "T3 Indicator".
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA (Simple Moving Average) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and it's smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA (Least Squares Moving Average)
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA. Although it's similar to the Simple Moving Average, the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track price better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average. The Linear Weighted Moving Average calculates the average by assigning different weight to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrows price.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA.
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average (SMA), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen a an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA (Smoothed Moving Average). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a a Two pole Butterworth filter combined with a 2-bar SMA (Simple Moving Average) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA. They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
The TMA and Sine Weighted Moving Average Filter are almost identical at times.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, it's signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers.
Volume Weighted EMA - VEMA
Utilizing tick volume in MT4 (or real volume in MT5), this EMA will use the Volume reading in its decision to plot its moves. The more Volume it detects on a move, the more authority (confirmation) it has. And this EMA uses those Volume readings to plot its movements.
Studies show that tick volume and real volume have a very strong correlation, so using this filter in MT4 or MT5 produces very similar results and readings.
Zero Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers, as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA, this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
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What are Heiken Ashi "better" candles?
The "better formula" was proposed in an article/memo by BNP-Paribas (In Warrants & Zertifikate, No. 8, August 2004 (a monthly German magazine published by BNP Paribas, Frankfurt), there is an article by Sebastian Schmidt about further development (smoothing) of Heikin-Ashi chart.)
They proposed to use the following:
(Open+Close)/2+(((Close-Open)/( High-Low ))*ABS((Close-Open)/2))
instead of using :
haClose = (O+H+L+C)/4
According to that document the HA representation using their proposed formula is better than the traditional formula.
What are traditional Heiken-Ashi candles?
The Heikin-Ashi technique averages price data to create a Japanese candlestick chart that filters out market noise.
Heikin-Ashi charts, developed by Munehisa Homma in the 1700s, share some characteristics with standard candlestick charts but differ based on the values used to create each candle. Instead of using the open, high, low, and close like standard candlestick charts, the Heikin-Ashi technique uses a modified formula based on two-period averages. This gives the chart a smoother appearance, making it easier to spots trends and reversals, but also obscures gaps and some price data.
Expanded generic source types:
Close = close
Open = open
High = high
Low = low
Median = hl2
Typical = hlc3
Weighted = hlcc4
Average = ohlc4
Average Median Body = (open+close)/2
Trend Biased = (see code, too complex to explain here)
Trend Biased (extreme) = (see code, too complex to explain here)
Included:
-Toggle bar color on/off
-Toggle signal line on/off
Adaptive Ehlers Deviation Scaled Moving Average (AEDSMA)AEDSMA INTRODUCTION
This indicator is a functional enhancement to “Ehlers Deviation Scaled Moving Average (EDSMA / DSMA)”. I’ve used Volume Breakout and Volatility for dynamic length adaption and further Slope too for trend evaluation.
EDSMA was originally developed by John F. Ehlers (Stocks & Commodities V. 36:8: The Deviation-Scaled Moving Average).
IDEA PLACEMENT
I’ve traded almost every kind of market with different volatility conditions using Moving Averages. It was too much of a hassle to select and use different MA length depending upon market trend. So, the journey started with adapting Moving Averages with another parameter and that’s how “MZ SAMA ” came into being where Slope was used to adapt Adaptive Moving Average with trend change. The problem was still pretty much the same as SAMA might not be effective on every market condition. Hence, I worked on Volume to adapt Moving Averages accordingly. I cane up with “MZ RVSI ” which I used in “MZ DVAMA ” to adapt dynamic length in Adaptive Moving Average and also used “MZ RVSI " alongside Slope as confirmation of trend changes.
Meanwhile, I started using DVAMA methodology on different types on Moving Averages that allow dynamic length for example Hull Moving Average, Linear Regression Curve, SMA, WMA, TMA and many more. All of my tested Mas showed too much flexibility because of volume based Adaptive length.
I came across a script of “Adaptive Hull Moving Average” which pretty much used the similar methodology as DVAMA but when I looked into its depth, its volume oscillator wasn’t working at all and only volatility based dynamic length was used. It was an interesting idea so, I decided to use Volume and Volatility alongside for better results but was nearly impossible to achieve what I wanted using only Hull Moving Average.
I had been using EDSMA in “MA MTF Cross Strategy” and “MZ SRSI Strategy V1.0” previously. It was the perfect choice when comparing to usage of slope on it. DSMA works perfectly as support and resistance as its Deviation Scaled. So, I tried using it to adapt dynamic length based on Volume and Volatility and I wasn’t disappointed. It worked like a charm when I adapted dynamic length between 50 and 255.
DYNAMIC LENGTH BENEFITS
Dynamic length adaption methodology works in a way of adapting Relatively Lower Length leading toward overfitting if trend is supported by Volume and Volatility . Similarly, adapting Relatively Higher Length leading toward underfitting if trend isn’t supported by Volume and Volatility .
Dynamic length adaption makes Moving Average to work better for both Bull and Bear-runs avoiding almost every fake break-in and breakouts. Hence, adaptive MA becomes more reliable for breakout trading.
MA would be more useful as it would adapt almost every chart based on its Volume and Volatility data.
DYNAMIC COLORS AND TREND CORRELATION
I’ve used dynamic coloring to identify trends with more detail which are as follows:
Lime Color: Strong Uptrend supported by Volume and Volatility or whatever you’ve chosen from both of them.
Fuchsia Color: Weak uptrend only supported by Slope or whatever you’ve selected.
Red Color: Strong Downtrend supported by Volume and Volatility or whatever you’ve chosen from both of them.
Grey Color: Weak Downtrend only supported by Slope or whatever you’ve selected.
Yellow Color: Possible reversal indication by Slope if enabled. Market is either sideways, consolidating or showing choppiness during that period.
SIGNALS
Green Circle: Market good for long with support of Volume and Volatility or whatever you’ve chosen from both of them.
Red Circle: Market good to short with support from Volume and Volatility or whatever you’ve chosen from both of them.
Yellow Cross: Market either touched top or bottom ATR band and can act as good TP or SL.
EDSMA EVELOPE/BANDS: I’ve included ATR based bands to the Adaptive EDSMA which act as good support/resistance despite from main Adaptive EDSMA Curve.
DEFAULT SETTINGS
I’ve set default Minimum length to 50 and Maximum length to 255 which I’ve found works best for almost all timeframes but you can change this delta to adapt your timeframe accordingly with more precision.
Dynamic length adoption is enabled based on both Volume and Volatility but only one or none of them can also be selected.
Trend signals are enabled based on Slope and Volume but Volatility can be enabled for more precise confirmations.
In “ RVSI ” settings TFS Volume Oscillator is set to default but others work good too especially Volume Zone Oscillator. For more details about Volume Breakout you can check “MZ RVSI Indicator".
ATR breakout is set to be positive if period 14 exceeds period 46 but can be changed if more adaption with volatility is required.
EDSMA super smoother filter length is set to 20 which can be increased to 50 or more for better smoothing but this will also change slope results accordingly.
EDSMA super smoother filter poles are set to 2 because found better results with 2 instead of 3.
FURTHER ENHANCEMENTS
So far, I’ve seen better results with Volume Breakout and Volatility but other parameters such as Linear Slope of Particular MA, MACD, “MZ SRSI ”, a Conditional Uptrend MA or simply KDJ can also be used for dynamic length adaption.
I haven't yet gotten used to pine script arrays so, defining and using conditional operators is pretty much lazy programming for me. Would be great redefining everything through truth matrix instead of using if-else conditions.
zigzagplusThis is same as existing zigzag library with respect to functionality. But, there is a small update with respect to how arrays are used internally. This also leads to issues with backward compatibility. Hence I decided to make this as new library instead of updating the older one.
Below are the major changes:
Earlier version uses array.unshift for adding new elements and array.pop for removing old elements. But, since array.unshift is considerably slower than alternative method array.push. Hence, this library makes use of array.push method to achieve performance.
While array.push increases the performance significantly, there is also an issue with removing as we no longer will be able to remove the element using pop which is again faster than shift (which need to shit all the elements by index). Hence, have removed the logic of removing elements for zigzag pivots after certain limit. Will think further about it once I find better alternative of handling it.
These implementation change also mean that zigzag pivots received by calling method will be ordered in reverse direction. Latest pivots will be stored with higher array index whereas older pivots are stored with lower array index. This is also the reason why backward compatibility is not achievable with this code change.
Library "zigzagplus"
Library dedicated to zigzags and related indicators
zigzag(length, useAlternativeSource, source, oscillatorSource, directionBias) zigzag: Calculates zigzag pivots and generates an array
Parameters:
length : : Zigzag Length
useAlternativeSource : : If set uses the source for genrating zigzag. Default is false
source : : Alternative source used only if useAlternativeSource is set to true. Default is close
oscillatorSource : : Oscillator source for calculating divergence
directionBias : : Direction bias for calculating divergence
Returns: zigzagpivots : Array containing zigzag pivots
zigzagpivotbars : Array containing zigzag pivot bars
zigzagpivotdirs : Array containing zigzag pivot directions (Lower High : 1, Higher High : 2, Lower Low : -2 and Higher Low : -1)
zigzagpivotratios : Array containing zigzag retracement ratios for each pivot
zigzagoscillators : Array of oscillator values at pivots. Will have valid values only if valid oscillatorSource is provided as per input.
zigzagoscillatordirs: Array of oscillator directions (HH, HL, LH, LL) at pivots. Will have valid values only if valid oscillatorSource is provided as per input.
zigzagtrendbias : Array of trend bias at pivots. Will have valid value only if directionBias series is sent in input parameters
zigzagdivergence : Array of divergence sentiment at each pivot. Will have valid values only if oscillatorSource and directionBias inputs are provided
newPivot : Returns true if new pivot created
doublePivot : Returns true if two new pivots are created on same bar (Happens in case of candles with long wicks and shorter zigzag lengths)
drawzigzag(length, , source, linecolor, linewidth, linestyle, oscillatorSource, directionBias, showHighLow, showRatios, showDivergence) drawzigzag: Calculates and draws zigzag pivots
Parameters:
length : : Zigzag Length
: useAlternativeSource: If set uses the source for genrating zigzag. Default is false
source : : Alternative source used only if useAlternativeSource is set to true. Default is close
linecolor : : zigzag line color
linewidth : : zigzag line width
linestyle : : zigzag line style
oscillatorSource : : Oscillator source for calculating divergence
directionBias : : Direction bias for calculating divergence
showHighLow : : show highlow label
showRatios : : show retracement ratios
showDivergence : : Show divergence on label (Only works if divergence data is available - that is if we pass valid oscillatorSource and directionBias input)
Returns: zigzagpivots : Array containing zigzag pivots
zigzagpivotbars : Array containing zigzag pivot bars
zigzagpivotdirs : Array containing zigzag pivot directions (Lower High : 1, Higher High : 2, Lower Low : -2 and Higher Low : -1)
zigzagpivotratios : Array containing zigzag retracement ratios for each pivot
zigzagoscillators : Array of oscillator values at pivots. Will have valid values only if valid oscillatorSource is provided as per input.
zigzagoscillatordirs: Array of oscillator directions (HH, HL, LH, LL) at pivots. Will have valid values only if valid oscillatorSource is provided as per input.
zigzagtrendbias : Array of trend bias at pivots. Will have valid value only if directionBias series is sent in input parameters
zigzagdivergence : Array of divergence sentiment at each pivot. Will have valid values only if oscillatorSource and directionBias inputs are provided
zigzaglines : Returns array of zigzag lines
zigzaglabels : Returns array of zigzag labels
Optimized Trend Tracker - Strategy VersionA brand new indicator from the developer of MOST (Moving Stop Loss) indicator Anıl Özekşi.
Optimized Trend Tracker OTT is an indicator that provides traders to find an existing trend or in another words to ser which side of the current trend we are on.
The original indicator was coded and published by Kıvanç Özbilgiç. You can access it from this link:
I transformed the indicator into a strategy and made some changes:
- You can run two different strategies. In the Settings section, you can test two different strategies, "Support Line Crossing Signals" and "Price / OTT Crossing Signals".
- Fixed the issue where BUY/SELL labels from the indicator script would hang in the air.
- I added a setting where you can hide BUY/SELL labels if you want.
- I painted the bars for BUY/SELL states, you can open and close in the settings section.
- As I do with every strategy script, I added a start and end date for the strategy test. You can specify the range you want to see working in the Settings section.
In addition, there were cases when the OTT line was reduced to zero in non-voluminous symbols; I changed this situation by making a small change in the code. I asked Kıvanç about the subject, I can update according to his answer.
Note : Strategy BUY / SELL tags and indicator BUY / SELL tags do not operate in the same bar because indicator tags are added when the next bar occurs. If you replay bars, you can observe label formations.
TÜRKÇE AÇIKLAMA
Orjinal indikatör Kıvanç Özbilgiç tarafından kodlanmış ve yayımlanmıştır. Bu linkten erişebilirsiniz:
İndikatörü strateji dönüştürdüm ve bazı değişiklikler yaptım:
- İki farklı strateji çalıştırabilirsiniz. Ayarlar kısmında Condition bölümünde "Support Line Crossing Signals" ve "Price/OTT Crossing Signals" olarak iki farklı stratejiyi test edebilirsiniz.
- İndikatör scriptinden gelen BUY/SELL etiketlerinin havada durması sorununu düzelttim.
- İsterseniz BUY/SELL etiketleri gizleyebileceğiniz bir ayar ekledim.
- BUY/SELL durumları için barları boyadım, ayarlar bölümünden açıp kapatabilirsiniz.
- Her strateji scriptinde yaptığım gibi, strateji testi için başlangıç ve bitiş tarihi ekledim. Ayarlar bölümünden çalışmasını görmek istediğiniz aralığı belirleyebilirsiniz.
- Ek olarak hacimsiz sembollerde OTT çizgisinin sıfıra indiği durumlar mevcuttu; kodda ufak bir değişiklik yaparak bu durumu değiştirdim. Kıvanç Bey'e konu ile ilgili soru sordum, cevabına göre güncelleme yapabilirim.
Not : Strateji BUY/SELL etiketleri ile indikatör BUY/SELL etiketleri aynı barda işlem yapmamaktadır çünkü indikatör etiketleri kendisinden sonraki bar oluşunca eklenmektedir. Barları replay yaptırırsanız oluşumlarını gözlemleyebilirsiniz.
Yale Confidence Index [nb]These are the Yale confidence indexes that show individual and institutional sentiment.
Options include:
showing two different indexes at once
labels for them
to filter through a moving average
highlighting when the first chosen index is greater than the second
shifting the series 6 months ahead
showing an average of both indexes
U.S. One-Year Confidence Index
The percent of the population expecting an increase in the Dow in the coming year.
The One-Year Confidence Index is the percentage of respondents giving a number strictly greater than zero for "in 1 year." Note that the question is worded to mention the possibility that the respondent could predict a downturn, and so this question will obtain more such responses than more optimistically worded questions used by some other surveys. However, the issue is how the answers change through time, and the wording of the question has not been changed through time (except to add the 1-month and the ten-year categories, which were not on the earliest questionnaires).
U.S. Buy-on-Dips Confidence Index
The percent of the population expecting a rebound the next day should the market ever drop 3% in one day.
The Buy-On-Dips Confidence Index is the number of respondents who choose 1 (increase) as a percent of those who chose 1, 2 or 3. This question was never changed.
U.S. Crash Confidence Index
The percent of the population who attach little probability to a stock market crash in the next six months.
The Crash Confidence Index is the percentage of respondents who think that the probability is strictly less than 10%. There were slight wording changes in this question, but inessential.
U.S. Valuation Confidence Index
The percent of the population who think that the market is not too high.
The Valuation Confidence Index is the number of respondents who choose 1 (Too Low) or 3 (About right) as a percentage of those who choose 1, 2, or 3. The wording of this question was never changed, and it was always the first question on the questionnaire.
Source:
som.yale.edu
Includes methodology and questions used.
Japanese indexes aren't updated so I did not include them.
