Quad Stochastic Div (Latching Quad)This script combines 4 stochastic lines, plotting only the %D lines.
(9,3)(14,3)(40,4)(60,10)
When all 4 are oversold or overbought, a buy or sell background is painted. When the slowest moving stochastic finally rotates back towards the center, the background will unlatch. This script also marks most divergences made between the chart and the 2 faster moving stochastic lines. White markers for the 9,3 and orange markers for the 14,4. Tradable signals are both orange and white divergence occurring on the same pivot, or either divergence leading out of a rotation. Generally more useful for scalping 1-5m charts.
I also built out some strength ratings to attempt to classify the divergences against one another, but this didn't seem to have much value in practice so by default the tags are turned off.
This indicator is helpful for anyone interested in daytradingrockstar on youtube's quad stochastic strategy.
Поиск скриптов по запросу "法国市值最大的10家公司"
Ultimate Pattern ScannerSmart Pattern Scanner Pro - Complete Study Guide
The Smart Pattern Scanner Pro is an advanced candlestick pattern recognition indicator that automatically detects over 30 traditional Japanese candlestick patterns across multiple timeframes simultaneously. It combines pattern recognition with volume analysis and trend confirmation to provide traders with comprehensive reversal and continuation signals.
Core Features:
• 30+ Candlestick Patterns: Complete library of traditional patterns
• Multi-Timeframe Scanning: Simultaneous analysis across up to 7 timeframes
• Volume Integration: Buy/sell volume analysis with pattern confirmation
• Trend Filtering: SMA-based trend confirmation for pattern validity
• Real-Time Dashboard: Professional interface with customizable display
• Alert System: Automated notifications when patterns are detected
________________________________________
Candlestick Pattern Categories
Reversal Patterns (Bullish)
Single Candle Patterns
1. Hammer
o Formation: Small body at top, long lower shadow (2x body size)
o Signal: Bullish reversal after downtrend
o Reliability: High when confirmed with volume
o Entry: Above hammer high with stop below low
2. Inverted Hammer
o Formation: Small body at bottom, long upper shadow
o Signal: Potential bullish reversal (needs confirmation)
o Reliability: Medium (requires next candle confirmation)
o Entry: Confirmed breakout above pattern
3. Dragonfly Doji
o Formation: Open = Close, long lower shadow, no upper shadow
o Signal: Strong bullish reversal signal
o Reliability: High in downtrends
o Entry: Above doji high with tight stop
4. Long Lower Shadow
o Formation: Lower shadow 2x body length
o Signal: Rejection of lower prices, bullish sentiment
o Reliability: Medium to high with volume
o Entry: Above candle high
Multi-Candle Patterns
1. Bullish Engulfing
o Formation: Large white candle completely engulfs previous black candle
o Signal: Strong bullish reversal
o Reliability: Very high with volume confirmation
o Entry: Above engulfing candle high
2. Morning Star
o Formation: 3-candle pattern (down, small, up)
o Signal: Major bullish reversal
o Reliability: Excellent (one of most reliable patterns)
o Entry: Above third candle high
3. Morning Doji Star
o Formation: Like Morning Star but middle candle is doji
o Signal: Strong bullish reversal
o Reliability: Very high
o Entry: Above third candle close
4. Piercing Pattern
o Formation: White candle opens below previous low, closes above midpoint
o Signal: Bullish reversal
o Reliability: High when closing >50% into previous candle
o Entry: Above piercing candle high
5. Bullish Harami
o Formation: Small white candle within previous large black candle
o Signal: Potential bullish reversal
o Reliability: Medium (needs confirmation)
o Entry: Above mother candle high
Reversal Patterns (Bearish)
Single Candle Patterns
1. Shooting Star
o Formation: Small body at bottom, long upper shadow
o Signal: Bearish reversal after uptrend
o Reliability: High with volume confirmation
o Entry: Below shooting star low
2. Hanging Man
o Formation: Like hammer but appears in uptrend
o Signal: Potential bearish reversal
o Reliability: Medium (needs confirmation)
o Entry: Below hanging man low
3. Gravestone Doji
o Formation: Open = Close, long upper shadow, no lower shadow
o Signal: Strong bearish reversal
o Reliability: High in uptrends
o Entry: Below doji low
4. Long Upper Shadow
o Formation: Upper shadow 2x body length
o Signal: Rejection of higher prices
o Reliability: Medium to high
o Entry: Below candle low
Multi-Candle Patterns
1. Bearish Engulfing
o Formation: Large black candle engulfs previous white candle
o Signal: Strong bearish reversal
o Reliability: Very high
o Entry: Below engulfing candle low
2. Evening Star
o Formation: 3-candle pattern (up, small, down)
o Signal: Major bearish reversal
o Reliability: Excellent
o Entry: Below third candle low
3. Dark Cloud Cover
o Formation: Black candle opens above previous high, closes below midpoint
o Signal: Bearish reversal
o Reliability: High when closing <50% into previous candle
o Entry: Below dark cloud low
Continuation Patterns
1. Rising Three Methods
o Formation: White candle, 3 small declining candles, white candle
o Signal: Bullish continuation
o Reliability: High in strong uptrends
2. Falling Three Methods
o Formation: Black candle, 3 small rising candles, black candle
o Signal: Bearish continuation
o Reliability: High in strong downtrends
Indecision Patterns
1. Doji
o Formation: Open = Close (or very close)
o Signal: Market indecision, potential reversal
o Reliability: Context-dependent
2. Spinning Tops
o Formation: Small body with upper and lower shadows
o Signal: Market indecision
o Reliability: Low without confirmation
________________________________________
Multi-Timeframe Analysis
Timeframe Hierarchy Strategy
Primary Analysis Flow:
1. Higher Timeframe (Daily/Weekly): Establish overall trend direction
2. Intermediate Timeframe (4H/1H): Identify key support/resistance levels
3. Lower Timeframe (15M/5M): Precise entry and exit timing
Configuration Guidelines:
• Scalping: 1M, 3M, 5M, 15M, 30M
• Day Trading: 5M, 15M, 30M, 1H, 4H
• Swing Trading: 1H, 4H, 1D, 1W
• Position Trading: 4H, 1D, 1W, 1M
Pattern Confluence Rules:
1. High Probability Setup: Same pattern type appears on 3+ timeframes
2. Trend Alignment: Reversal patterns should align with higher timeframe structure
3. Volume Confirmation: Strong volume on pattern timeframe and higher timeframes
________________________________________
Volume Analysis Integration
Volume Components:
1. Buy Volume: Volume when close > open (green candles)
2. Sell Volume: Volume when close ≤ open (red candles)
3. Volume Ratio: Current volume / 20-period moving average
4. Progress Indicator: Visual representation of volume strength
Volume Signal Interpretation:
• Ratio >1.5: Strong volume confirmation
• Ratio 1.0-1.5: Moderate volume support
• Ratio <1.0: Weak volume (pattern less reliable)
Volume Analysis Rules:
1. Bullish Patterns: Require strong buy volume for confirmation
2. Bearish Patterns: Require strong sell volume for confirmation
3. Volume Divergence: When pattern and volume disagree, favor volume
4. Volume Spikes: Ratios >2.0 indicate institutional interest
________________________________________
Live Market Application
Step 1: Dashboard Setup
1. Position Selection: Choose optimal table position for your layout
2. Timeframe Configuration: Set relevant timeframes for your strategy
3. Volume Analysis: Enable for confirmation signals
4. Progress Indicators: Enable for visual signal strength
Step 2: Pattern Identification Process
Real-Time Scanning:
1. Monitor Multiple Timeframes: Check all configured timeframes simultaneously
2. Pattern Priority: Focus on patterns appearing on higher timeframes first
3. Signal Confluence: Look for patterns appearing across multiple timeframes
4. Volume Confirmation: Verify adequate volume support
Pattern Validation:
1. Trend Context: Ensure pattern aligns with overall market structure
2. Support/Resistance: Check if pattern forms at key levels
3. Market Conditions: Consider overall market volatility and sentiment
4. Time of Day: Be aware of session characteristics (open, close, lunch)
Step 3: Entry Decision Matrix
High Probability Entries:
• Pattern on 3+ timeframes
• Strong volume confirmation (ratio >1.5)
• Trend alignment with higher timeframes
• Formation at key support/resistance
Medium Probability Entries:
• Pattern on 2 timeframes
• Moderate volume (ratio 1.0-1.5)
• Partial trend alignment
• Formation in trending market
Low Probability Entries:
• Single timeframe pattern
• Weak volume (ratio <1.0)
• Counter-trend formation
• Choppy/sideways market
________________________________________
Pattern Reliability Assessment
Tier 1 Patterns (Highest Reliability - 70-80% success rate):
• Morning Star / Evening Star
• Bullish/Bearish Engulfing
• Three White Soldiers / Three Black Crows
• Hammer (in strong downtrend)
• Shooting Star (in strong uptrend)
Tier 2 Patterns (High Reliability - 60-70% success rate):
• Piercing Pattern / Dark Cloud Cover
• Morning/Evening Doji Star
• Harami patterns
• Abandoned Baby
• Kicking patterns
Tier 3 Patterns (Moderate Reliability - 50-60% success rate):
• Doji patterns
• Tweezer Tops/Bottoms
• Window patterns
• Tasuki Gap patterns
• Marubozu patterns
Tier 4 Patterns (Lower Reliability - 40-50% success rate):
• Spinning Tops
• Long shadow patterns (single)
• Neutral doji formations
• Single candle continuation patterns
________________________________________
Trading Strategies
Strategy 1: Multi-Timeframe Reversal
Objective: Catch major trend reversals using high-reliability patterns
Rules:
1. Wait for Tier 1 patterns on Daily + 4H timeframes
2. Require volume ratio >1.5 on both timeframes
3. Enter on 1H confirmation candle
4. Stop loss below/above pattern extreme
5. Target 2:1 or 3:1 risk-reward ratio
Strategy 2: Intraday Scalping
Objective: Quick profits from short-term pattern formations
Rules:
1. Focus on 5M and 15M timeframes
2. Trade only Tier 1 and Tier 2 patterns
3. Require volume confirmation
4. Quick exits (10-30 pip targets)
5. Tight stops (5-15 pips)
Strategy 3: Swing Trading
Objective: Multi-day position holding based on pattern signals
Rules:
1. Use Daily and Weekly timeframes
2. Focus on major reversal patterns
3. Combine with fundamental analysis
4. Wider stops (2-5% of entry price)
5. Hold for 5-20 trading days
Strategy 4: Trend Continuation
Objective: Enter trending markets using continuation patterns
Rules:
1. Identify strong trends on higher timeframes
2. Wait for continuation patterns on lower timeframes
3. Enter in direction of main trend
4. Trail stops using pattern lows/highs
5. Pyramid positions on additional patterns
________________________________________
Risk Management
Position Sizing Rules:
1. Tier 1 Patterns: Risk up to 2% of account
2. Tier 2 Patterns: Risk up to 1.5% of account
3. Tier 3 Patterns: Risk up to 1% of account
4. Tier 4 Patterns: Risk up to 0.5% of account
Stop Loss Guidelines:
1. Reversal Patterns: Stop beyond pattern extreme + 1 ATR
2. Continuation Patterns: Stop at pattern invalidation level
3. Doji Patterns: Tight stops due to indecision nature
4. Multi-Candle Patterns: Use pattern range for stop placement
Take Profit Strategies:
1. Conservative: 1:1 risk-reward ratio
2. Moderate: 2:1 risk-reward ratio
3. Aggressive: 3:1 risk-reward ratio
4. Trailing: Move stops to breakeven after 1:1 achieved
________________________________________
Limitations and Considerations
Technical Limitations:
1. Pattern Subjectivity: Slight variations in pattern interpretation
2. Market Context Dependency: Patterns perform differently in various market conditions
3. False Signals: Not all patterns lead to expected price moves
4. Lagging Nature: Patterns are confirmed after formation is complete
Market Condition Considerations:
1. Trending Markets: Continuation patterns more reliable than reversals
2. Range-Bound Markets: Reversal patterns at extremes more effective
3. High Volatility: Patterns may not develop properly
4. News Events: Fundamental factors can override technical patterns
Optimal Usage Conditions:
1. Liquid Markets: Adequate volume and participation
2. Normal Volatility: Not during extreme market stress
3. Clear Market Structure: Defined support and resistance levels
4. Multiple Timeframe Alignment: Confluence across timeframes
When NOT to Trade Patterns:
1. Major News Releases: Economic announcements can invalidate patterns
2. Market Holidays: Reduced participation affects reliability
3. Extreme Volatility: VIX >30 or similar stress indicators
4. Gap Openings: Large gaps can negate pattern significance
________________________________________
Risk Disclaimer
CRITICAL WARNING FROM aiTrendview
TRADING FINANCIAL INSTRUMENTS INVOLVES SUBSTANTIAL RISK OF LOSS
This Smart Pattern Scanner Pro indicator ("the Indicator") is provided for educational and analytical purposes only. By using this indicator, you acknowledge and accept the following terms and conditions:
No Financial Advice
• NOT INVESTMENT ADVICE: This indicator does not constitute financial, investment, or trading advice
• NO RECOMMENDATIONS: Pattern signals are not recommendations to buy or sell any financial instrument
• EDUCATIONAL TOOL: Designed for learning technical analysis concepts and pattern recognition
• INDEPENDENT RESEARCH REQUIRED: Always conduct your own thorough analysis before making trading decisions
Substantial Trading Risks
• CAPITAL LOSS RISK: You may lose some or all of your trading capital
• LEVERAGE DANGERS: Margin trading can amplify losses beyond your initial investment
• MARKET VOLATILITY: Financial markets are inherently unpredictable and can move against any analysis
• PATTERN FAILURE: Candlestick patterns fail frequently and do not guarantee profitable outcomes
• FALSE SIGNALS: The indicator may generate incorrect or misleading signals
Technical Analysis Limitations
• NOT PREDICTIVE: Candlestick patterns analyze past price action, not future movements
• SUBJECTIVE INTERPRETATION: Pattern recognition can vary between traders and market conditions
• CONTEXT DEPENDENT: Patterns must be analyzed within broader market context
• NO GUARANTEE: No technical analysis method guarantees trading success
• STATISTICAL PROBABILITY: Even high-reliability patterns fail 20-30% of the time
User Responsibilities
• SOLE RESPONSIBILITY: You are entirely responsible for all trading decisions and outcomes
• RISK MANAGEMENT: Implement appropriate position sizing and stop-loss strategies
• PROFESSIONAL CONSULTATION: Seek advice from qualified financial professionals
• REGULATORY COMPLIANCE: Ensure compliance with local financial regulations
• CONTINUOUS EDUCATION: Maintain ongoing education in market analysis and risk management
Indicator Limitations
• SOFTWARE BUGS: Technical glitches or calculation errors may occur
• DATA DEPENDENCY: Relies on accurate price and volume data feeds
• PLATFORM LIMITATIONS: Subject to TradingView platform capabilities and restrictions
• VERSION UPDATES: Functionality may change with future updates
• COMPATIBILITY: May not work optimally with all chart configurations
Volume Analysis Limitations
• DATA ACCURACY: Volume data may be incomplete or delayed
• MARKET VARIATIONS: Volume patterns differ across markets and instruments
• INSTITUTIONAL ACTIVITY: Cannot guarantee detection of all institutional trading
• LIQUIDITY FACTORS: Low liquidity markets may produce unreliable volume signals
Multi-Timeframe Considerations
• CONFLICTING SIGNALS: Different timeframes may show contradictory patterns
• TIME SYNCHRONIZATION: Pattern timing may vary across timeframes
• COMPUTATIONAL LOAD: Multiple timeframe analysis may affect performance
• COMPLEXITY RISK: More data does not necessarily mean better decisions
Specific Trading Warnings
Pattern-Specific Risks:
1. Doji Patterns: Indicate indecision, not directional conviction
2. Single Candle Patterns: Generally less reliable than multi-candle formations
3. Continuation Patterns: May signal trend exhaustion rather than continuation
4. Gap Patterns: Subject to overnight and weekend gap risks
Market Condition Risks:
1. News Events: Fundamental factors can invalidate any technical pattern
2. Market Manipulation: Large players can create false pattern signals
3. Algorithmic Trading: High-frequency trading can distort traditional patterns
4. Market Crashes: Extreme events render technical analysis ineffective
Psychological Trading Risks:
1. Overconfidence: Successful patterns may lead to excessive risk-taking
2. Pattern Addiction: Over-reliance on patterns without broader analysis
3. Confirmation Bias: Seeing patterns that don't actually exist
4. Emotional Trading: Fear and greed can override pattern discipline
Legal and Regulatory Disclaimers
Intellectual Property:
• COPYRIGHT PROTECTION: This indicator is protected by copyright law
• AUTHORIZED USE ONLY: Use only as permitted by TradingView terms of service
• NO REDISTRIBUTION: Unauthorized copying or redistribution is prohibited
• MODIFICATION RESTRICTIONS: Code modifications may void any support or warranties
Regulatory Compliance:
• LOCAL LAWS: Ensure compliance with your jurisdiction's financial regulations
• LICENSING REQUIREMENTS: Some jurisdictions require licenses for trading or advisory activities
• TAX OBLIGATIONS: Trading profits/losses may have tax implications
• REPORTING REQUIREMENTS: Some jurisdictions require reporting of trading activities
Limitation of Liability:
• NO LIABILITY: aiTrendview accepts no liability for any losses, damages, or adverse outcomes
• INDIRECT DAMAGES: Not liable for consequential, incidental, or punitive damages
• MAXIMUM LIABILITY: Limited to amount paid for indicator access (if any)
• FORCE MAJEURE: Not responsible for events beyond reasonable control
Final Warnings and Recommendations
Before Using This Indicator:
1. DEMO TRADING: Practice extensively with paper trading before risking real money
2. EDUCATION: Thoroughly understand candlestick pattern theory and market dynamics
3. RISK ASSESSMENT: Honestly assess your risk tolerance and financial situation
4. PROFESSIONAL ADVICE: Consult with qualified financial advisors
5. START SMALL: Begin with minimal position sizes to test strategies
Red Flags - Do NOT Trade If:
• You cannot afford to lose the money you're risking
• You're experiencing financial stress or pressure
• You're trading emotionally or impulsively
• You don't understand the patterns or market mechanics
• You're using borrowed money or credit to trade
• You're treating trading as gambling rather than calculated risk-taking
Emergency Procedures:
• STOP TRADING immediately if experiencing significant losses
• SEEK HELP if trading is affecting your mental health or relationships
• REVIEW STRATEGY after any series of losses
• TAKE BREAKS from trading to maintain perspective
• PROFESSIONAL HELP: Contact financial counselors if needed
Acknowledgment Required
By using the Smart Pattern Scanner Pro indicator, you explicitly acknowledge that:
1. You have read and understood this entire disclaimer
2. You accept full responsibility for all trading decisions and outcomes
3. You understand the substantial risks involved in financial trading
4. You will not hold aiTrendview liable for any losses or damages
5. You will use this tool only for educational and personal analysis purposes
6. You will comply with all applicable laws and regulations
7. You will implement appropriate risk management practices
8. You understand that past performance does not predict future results
REMEMBER: The most important rule in trading is capital preservation. No pattern, indicator, or strategy is worth risking your financial well-being.
________________________________________
Disclaimer from aiTrendview.com
The content provided in this blog post is for educational and training purposes only. It is not intended to be, and should not be construed as, financial, investment, or trading advice. All charting and technical analysis examples are for illustrative purposes. Trading and investing in financial markets involve substantial risk of loss and are not suitable for every individual. Before making any financial decisions, you should consult with a qualified financial professional to assess your personal financial situation.
Volume Profile + Pivot Levels [ChartPrime]⯁ OVERVIEW
Volume Profile + Pivot Levels combines a rolling volume profile with price pivots to surface the most meaningful levels in your selected lookback window. It builds a left-side profile from traded volume, highlights the session’s Point of Control (PoC) , and then filters pivot highs/lows so only those aligned with significant profile volume are promoted to chart levels. Each promoted level extends forward until price retests it—so your chart stays focused on levels that actually matter.
⯁ KEY FEATURES
Rolling Volume Profile (Period & Resolution)
Calculates a profile over the last Period bars (default 200). The profile is discretized into Volume Profile Resolution bins (default 50) between the highest high and lowest low inside the window. Each bin accumulates traded volume and is drawn as a smooth left-side polyline for compact, lightweight rendering.
HL = array.new()
// collect highs/lows over 'start' bars to define profile range
for i = 0 to start - 1
HL.push(high ), HL.push(low )
H = HL.max(), L = HL.min()
bin_size = (H - L) / bins
// accumulate per-bin volume
for i = 0 to bins - 1
for j = 0 to start - 1
if close >= (L + bin_sizei) - bin_size and close < (L + bin_size*(i+1)) + bin_size
Bins += volume
Delta-Aware Coloring
The script tracks up-minus-down volume across all period to compute a net Delta . The profile, PoC line, and PoC label adopt a teal tone when net positive, and maroon when net negative—an immediate read on buyer/seller dominance inside the window.
Point of Control (PoC) + Volume Label
Automatically marks the highest-volume bin as the PoC . A horizontal PoC line extends to the last bar, and a label shows the absolute volume at the PoC. Toggle visibility via PoC input.
Pivot Detection with Volume Filter
Identifies raw pivots using Length (default 10) on both sides of the bar. Each candidate pivot is then validated against the profile: only pivots that land within their bin and meet or exceed the Filter % threshold (percentage of PoC volume) are promoted to chart levels. This removes weak, low-participation pivots.
// pivot promotion when volume% >= pivotFilter
if abs(mid - p.value) <= bin_size and volPercent >= pivotFilter
// draw labeled pivot level
line.new(p.index - pivotLength, p.value, p.index + pivotLength, p.value, width = 2)
Forward-Extending, Self-Stopping Levels
Promoted pivot levels extend forward as dotted rays. As soon as price intersects a level (high/low straddles it), that level stops extending—so your chart doesn’t clutter with stale zones.
Concise Level Labels (Volume + %)
Each promoted pivot prints a compact label at the pivot bar with its bin’s absolute volume and percentage of PoC volume (ordering flips for highs vs. lows for quick read).
Lightweight Visuals
The volume profile is rendered as a smooth polyline rather than dozens of boxes, keeping charts responsive even at higher resolutions.
⯁ SETTINGS
Volume Profile → Period : Lookback window used to compute the profile (max 500).
Volume Profile → Resolution : Number of bins; higher = finer structure.
Volume Profile → PoC : Toggle PoC line and volume label.
Pivots → Display : Show/hide volume-validated pivot levels.
Pivots → Length : Pivot detection left/right bars.
Pivots → Filter % 0–100 : Minimum bin strength (as % of PoC) required to promote a pivot level.
⯁ USAGE
Read PoC direction/color for a quick net-flow bias within your window.
Prioritize promoted pivot levels —they’re backed by meaningful participation.
Watch for first retests of promoted levels; the line will stop extending once tested.
Adjust Period / Resolution to match your timeframe (scalps → higher resolution, shorter period; swings → lower resolution, longer period).
Tighten or loosen Filter % to control how selective the level promotion is.
⯁ WHY IT’S UNIQUE
Instead of plotting every pivot or every profile bar, this tool cross-checks pivots against the profile’s internal volume weighting . You only see levels where price structure and liquidity overlap—clean, data-driven levels that self-retire after interaction, so you can focus on what the market actually defends.
Pivot Points mura visionWhat it is
A clean, single-set pivot overlay that lets you choose the pivot type (Traditional/Fibonacci), the anchor timeframe (Daily/Weekly/Monthly/Quarterly, or Auto), and fully customize colors, line width/style , and labels . The script never draws duplicate sets—exactly one pivot pack is displayed for the chosen (or auto-detected) anchor.
How it works
Pivots are computed with ta.pivot_point_levels() for the selected anchor timeframe .
The script supports the standard 7 levels: P, R1/S1, R2/S2, R3/S3 .
Lines span exactly one anchor period forward from the current bar time.
Label suffix shows the anchor source: D (Daily), W (Weekly), M (Monthly), Q (Quarterly).
Auto-anchor logic
Intraday ≤ 15 min → Daily pivots (D)
Intraday 20–120 min → Weekly pivots (W)
Intraday > 120 min (3–4 h) → Monthly pivots (M)
Daily and above → Quarterly pivots (Q)
This keeps the chart readable while matching the most common trader expectations across timeframes.
Inputs
Pivot Type — Traditional or Fibonacci.
Pivots Timeframe — Auto, Daily (1D), Weekly (1W), Monthly (1M), Quarterly (3M).
Line Width / Line Style — width 1–10; style Solid, Dashed, or Dotted.
Show Labels / Show Prices — toggle level tags and price values.
Colors — user-selectable colors for P, R*, S* .
How to use
Pick a symbol/timeframe.
Leave Pivots Timeframe = Auto to let the script choose; or set a fixed anchor if you prefer.
Toggle labels and prices to taste; adjust line style/width and colors for your theme.
Read the market like a map:
P often acts as a mean/rotation point.
R1/S1 are common first reaction zones; R2/S2 and R3/S3 mark stronger extensions.
Confluence with S/R, trendlines, session highs/lows, or volume nodes improves context.
Good practices
Use Daily pivots for intraday scalps (≤15m).
Use Weekly/Monthly for swing bias on 1–4 h.
Use Quarterly when analyzing on Daily and higher to frame larger cycles.
Combine with trend filters (e.g., EMA/KAMA 233) or volatility tools for entries and risk.
Notes & limitations
The script shows one pivot pack at a time by design (prevents clutter and duplicates).
Historical values follow TradingView’s standard pivot definitions; results can vary across assets/exchanges.
No alerts are included (levels are static within the anchor period).
PulseMA Oscillator Normalized v2█ OVERVIEW
PulseMA Oscillator Normalized v2 is a technical indicator designed for the TradingView platform, assisting traders in identifying potential trend reversal points based on price dynamics derived from moving averages. The indicator is normalized for easier interpretation across various market conditions, and its visual presentation with gradients and signals facilitates quick decision-making.
█ CONCEPTS
The core idea of the indicator is to analyze trend dynamics by calculating an oscillator based on a moving average (EMA), which is then normalized and smoothed. It provides insights into trend strength, overbought/oversold levels, and reversal signals, enhanced by gradient visualizations.
Why use it?
Identifying reversal points: The indicator detects overbought and oversold levels, generating buy/sell signals at their crossovers.
Price dynamics analysis: Based on moving averages, it measures how long the price stays above or below the EMA, incorporating trend slope.
Visual clarity: Gradients, fills, and colored lines enable quick chart analysis.
Flexibility: Configurable parameters, such as moving average lengths or normalization period, allow adaptation to various strategies and markets.
How it works?
Trend detection: Calculates a base exponential moving average (EMA with PulseMA Length) and measures how long the price stays above or below it, multiplied by the slope for the oscillator.
Normalization: The oscillator is normalized based on the minimum and maximum values over a lookback period (default 150 bars), scaling it to a range from -100 to 100: (oscillator - min) / (max - min) * 200 - 100. This ensures values are comparable across different instruments and timeframes.
Smoothing: The main line (PulseMA) is the normalized oscillator (oscillatorNorm). The PulseMA MA line is a smoothed version of PulseMA, calculated using an SMA with the PulseMA MA length. As PulseMA MA is smoothed, it reacts more slowly and can be used as a noise filter.
Signals: Generates buy signals when crossing the oversold level upward and sell signals when crossing the overbought level downward. Signals are stronger when PulseMA MA is in the overbought or oversold zone (exceeding the respective thresholds for PulseMA MA).
Visualization: Draws lines with gradients for PulseMA and PulseMA MA, levels with gradients, gradient fill to the zero line, and signals as triangles.
Alerts: Built-in alerts for buy and sell signals.
Settings and customization
PulseMA Length: Length of the base EMA (default 20).
PulseMA MA: Length of the SMA for smoothing PulseMA MA (default 20).
Normalization Lookback Period: Normalization period (default 150, minimum 10).
Overbought/Oversold Levels: Levels for the main line (default 100/-100) and thresholds for PulseMA MA, indicating zones where PulseMA MA exceeds set values (default 50/-50).
Colors and gradients: Customize colors for lines, gradients, and levels; options to enable/disable gradients and fills.
Visualizations: Show PulseMA MA, gradients for overbought/oversold/zero levels, and fills.
█ OTHER SECTIONS
Usage examples
Trend analysis: Observe PulseMA above 0 for an uptrend or below 0 for a downtrend. Use different values for PulseMA Length and PulseMA MA to gain a clearer trend picture. PulseMA MA, being smoothed, reacts more slowly and can serve as a noise filter to confirm trend direction.
Reversal signals: Look for buy triangles when PulseMA crosses the oversold level, especially when PulseMA MA is in the oversold zone. Similarly, look for sell triangles when crossing the overbought level with PulseMA MA in the overbought zone. Such confirmation increases signal reliability.
Customization: Test different values for PulseMA Length and PulseMA MA on a given instrument and timeframe to minimize false signals and tailor the indicator to market specifics.
Notes for users
Combine with other tools, such as support/resistance levels or other oscillators, for greater accuracy.
Test different settings for PulseMA Length and PulseMA MA on the chosen instrument and timeframe to find optimal values.
BBMA Enhanced Pro - Multi-Timeframe Band Breakout StrategyShort Title : BBMA Pro
Overview
The BBMA Enhanced Pro is a professional-grade trading indicator that builds on the Bollinger Bands Moving Average (BBMA) strategy, pioneered by Omar Ali , a Malaysian forex trader and educator. Combining Bollinger Bands with Weighted Moving Averages (WMA) , this indicator identifies high-probability breakout and reversal opportunities across multiple timeframes. With advanced features like multi-timeframe Extreme signal detection, eight professional visual themes, and a dual-mode dashboard, it’s designed for traders seeking precision in trending and consolidating markets. Optimized for dark chart backgrounds, it’s ideal for forex, stocks, and crypto trading.
History
The BBMA strategy was developed by Omar Ali (BBMA Oma Ally) in the early 2010s, gaining popularity in the forex trading community, particularly in Southeast Asia. Building on John Bollinger’s Bollinger Bands, Omar Ali integrated Weighted Moving Averages and a multi-timeframe approach to create a structured system for identifying reversals, breakouts, and extreme conditions. The BBMA Enhanced Pro refines this framework with modern features like real-time dashboards and customizable visualizations, making it accessible to both novice and experienced traders.
Key Features
Multi-Timeframe Extreme Signals : Detects Extreme signals (overbought/oversold conditions) on both current and higher timeframes simultaneously, a rare feature that enhances signal reliability through trend alignment.
Professional Visual Themes : Eight distinct themes (e.g., Neon Contrast, Fire Gradient) optimized for dark backgrounds.
Dual-Mode Dashboard : Choose between Full Professional (detailed metrics) or Simplified Trader (essential info with custom notes).
Bollinger Band Squeeze Detection : Identifies low volatility periods (narrow bands) signaling potential sideways markets or breakouts.
Confirmation Labels : Displays labels when current timeframe signals align with recent higher timeframe signals, highlighting potential consolidations or squeezes.
Timeframe Validation : Prevents selecting the same timeframe for current and higher timeframe analysis.
Customizable Visualization : Toggle signal dots, EMA 50, and confirmation labels for a clean chart experience.
How It Works
The BBMA Enhanced Pro combines Bollinger Bands (20-period SMA, ±2 standard deviations) with WMA (5 and 10 periods) to generate trade signals:
Buy Signal : WMA 5 Low crosses above the lower Bollinger Band, indicating a recovery from an oversold condition (Extreme buy).
Sell Signal : WMA 5 High crosses below the upper Bollinger Band, signaling a rejection from an overbought condition (Extreme sell).
Extreme Signals : Occur when prices or WMAs move significantly beyond the Bollinger Bands (±2σ), indicating statistically rare overextensions. These often coincide with Bollinger Band Squeezes (narrow bands, low standard deviation), signaling potential sideways markets or impending breakouts.
Multi-Timeframe Confirmation : The indicator’s unique strength is its ability to detect Extreme signals on both the current and higher timeframe (HTF) within the same chart. When the HTF generates an Extreme signal (e.g., buy), and the current timeframe follows with an identical signal, it suggests the lower timeframe is aligning with the HTF’s trend, increasing reliability. Labels appear only when this alignment occurs within a user-defined lookback period (default: 50 bars), highlighting periods of band contraction across timeframes.
Bollinger Band Squeeze : Narrow bands (low standard deviation) indicate reduced volatility, often preceding consolidation or breakouts. The indicator’s dashboard tracks band width, helping traders anticipate these phases.
Why Multi-Timeframe Extremes Matter
The BBMA Enhanced Pro’s multi-timeframe approach is rare and powerful. When the higher timeframe shows an Extreme signal followed by a similar signal on the current timeframe, it suggests the market is following the HTF’s trend or entering a consolidation phase. For example:
HTF Sideways First : If the HTF Bollinger Bands are shrinking (low volatility, low standard deviation), it signals a potential sideways market. Waiting for the current timeframe to show a similar Extreme signal confirms this consolidation, reducing the risk of false breakouts.
Risk Management : By requiring HTF confirmation, the indicator encourages traders to lower risk during uncertain periods, waiting for both timeframes to align in a low-volatility state before acting.
Usage Instructions
Select Display Mode :
Current TF Only : Shows Bollinger Bands and WMAs on the chart’s timeframe.
Higher TF Only : Displays HTF bands and WMAs.
Both Timeframes : Combines both for comprehensive analysis.
Choose Higher Timeframe : Select from 1min to 1D (e.g., 15min, 1hr). Ensure it differs from the current timeframe to avoid validation errors.
Enable Signal Dots : Visualize buy/sell Extreme signals as dots, sourced from current, HTF, or both timeframes.
Toggle Confirmation Labels : Display labels when current timeframe Extremes align with recent HTF Extremes, signaling potential squeezes or consolidations.
Customize Dashboard :
Full Professional Mode : View metrics like BB width, WMA trend, and last signal.
Simplified Trader Mode : Focus on essential info with custom trader notes.
Select Visual Theme : Choose from eight themes (e.g., Ice Crystal, Royal Purple) for optimal chart clarity.
Trading Example
Setup : 5min chart, HTF set to 1hr, signal dots and confirmation labels enabled.
Buy Scenario : On the 5min chart, WMA 5 Low crosses above the lower Bollinger Band (Extreme buy), confirmed by a recent 1hr Extreme buy signal within 50 bars. The dashboard shows narrow bands (squeeze), and a green label appears.
Action : Enter a long position, targeting the middle band, with a stop-loss below the recent low. The HTF confirmation suggests a strong trend or consolidation phase.
Sell Scenario : WMA 5 High crosses below the upper Bollinger Band on the 5min chart, confirmed by a recent 1hr Extreme sell signal. The dashboard indicates a squeeze, and a red label appears.
Action : Enter a short position, targeting the middle band, with a stop-loss above the recent high. The aligned signals suggest a potential reversal or sideways market.
Customization Options
BBMA Display Mode : Current TF Only, Higher TF Only, or Both Timeframes.
Higher Timeframe : 1min to 1D.
Visual Theme : Eight professional themes (e.g., Neon Contrast, Forest Glow).
Line Style : Smooth or Step Line for HTF plots.
Signal Dots : Enable/disable, select timeframe source (Current, Higher, or Both).
Confirmation Labels : Toggle and set lookback window (1-100 bars).
Dashboard : Enable/disable, choose mode (Full/Simplified), and set position (Top Right, Bottom Left, etc.).
Notes
Extreme Signals and Squeezes : Extreme signals often occur during Bollinger Band contraction (low standard deviation), signaling potential sideways markets or breakouts. Use HTF confirmation to filter false signals.
Risk Management : If the HTF shows a squeeze (narrow bands), wait for the current timeframe to confirm with an Extreme signal to reduce risk in choppy markets.
Limitations : Avoid trading Extremes in highly volatile markets without additional confirmation (e.g., volume, RSI).
Author Enhanced Professional Edition, inspired by Omar Ali’s BBMA strategy
Version : 6.0 Pro - Simplified
Last Updated : September 2025
License : Mozilla Public License 2.0
We’d love to hear your feedback! Share your thoughts or questions in the comments below.
HSM TOOLS//@version=5
indicator("HSM TOOLS", overlay=true, max_lines_count=500, max_labels_count=5, max_boxes_count=500)
// General Settings Inputs
TZI = input.string (defval="UTC -4", title="Timezone Selection", options= , tooltip="Select the Timezone. ( Shifts Chart Elements )", group="Global Settings")
Timezone = TZI == "UTC -10" ? "GMT-10:00" : TZI == "UTC -7" ? "GMT-07:00" : TZI == "UTC -6" ? "GMT-06:00" : TZI == "UTC -5" ? "GMT-05:00" : TZI == "UTC -4" ? "GMT-04:00" : TZI == "UTC -3" ? "GMT-03:00" : TZI == "UTC +0" ? "GMT+00:00" : TZI == "UTC +1" ? "GMT+01:00" : TZI == "UTC +2" ? "GMT+02:00" : TZI == "UTC +3" ? "GMT+03:00" : TZI == "UTC +3:30" ? "GMT+03:30" : TZI == "UTC +4" ? "GMT+04:00" : TZI == "UTC +5" ? "GMT+05:00" : TZI == "UTC +5:30" ? "GMT+05:30" : TZI == "UTC +6" ? "GMT+06:00" : TZI == "UTC +7" ? "GMT+07:00" : TZI == "UTC +8" ? "GMT+08:00" : TZI == "UTC +9" ? "GMT+09:00" : TZI == "UTC +9:30" ? "GMT+09:30" : TZI == "UTC +10" ? "GMT+10:00" : TZI == "UTC +10:30" ? "GMT+10:30" : TZI == "UTC +11" ? "GMT+11:00" : TZI == "UTC +13" ? "GMT+13:00" : "GMT+13:45"
inputMaxInterval = input.int (31, title="Hide Indicator Above Specified Minutes", tooltip="Above 30Min, Chart Will Become Messy & Unreadable", group="Global Settings")
// Session options
ShowTSO = input.bool (true, title="Show Today's Session Only", group="Session Options", tooltip="Hide Historical Sessions")
ShowTWO = input.bool (true, title="Show Current Week's Sessions Only", group="Session Options", tooltip="Show All Sessions from the current week")
SL4W = input.bool (true, title="Show Last 4 Week Sessions", group="Session Options", tooltip="Show All Sessions from Last Four Weeks \nShould Disable Current Week Session to Work")
ShowSFill = input.bool (false, title="Show Session Highlighting", group="Session Options", tooltip="Highlights Session from Top of the Chart to Bottom")
//----------------------------------------------
// Historical Lines
ShowMOPL = input.bool (title="Midnight Historical Price Lines", defval=false, group="Historical Lines", tooltip="Shows Historical Midnight Price Lines")
MOLHist = input.bool (title="Midnight Historical Vertical Lines", defval=true, group="Historical Lines", tooltip="Shows Historical Midnight Vertical Lines")
ShowPrev = input.bool (false, title="Misc. Historical Price Lines", group="Historical Lines", tooltip="Makes Chart Cluttered, Use For Backtesting Only")
//----------------------------------------------
// Session Bool
ShowLondon = input.bool (false, "", inline="LONDON", group="Sessions", tooltip="01:00 to 05:00")
ShowNY = input.bool (false, "", inline="NY", group="Sessions", tooltip="07:00 to 10:00")
ShowLC = input.bool (false, "", inline="LC", group="Sessions", tooltip="10:00 to 12:00")
ShowPM = input.bool (false, "",inline="PM", group="Sessions", tooltip="13:00 to 16:00")
ShowAsian = input.bool (false, "",inline="ASIA2", group="Sessions", tooltip="20:00 to 00:00")
ShowFreeSesh = input.bool (false, "",inline="FREE", group="Sessions", tooltip="Custom Session")
// Session Strings
txt2 = input.string ("LONDON", title="", inline="LONDON", group="Sessions")
txt3 = input.string ("NEW YORK", title="", inline="NY", group="Sessions")
txt4 = input.string ("LDN CLOSE", title="", inline="LC", group="Sessions")
txt5 = input.string ("AFTERNOON", title="", inline="PM", group="Sessions")
txt6 = input.string ("ASIA", title="", inline="ASIA2", group="Sessions")
txt9 = input.string ("FREE SESH", title="", inline="FREE", group="Sessions")
// CBDR = input.session ('1400-2000:1234567', "", inline="CBDR", group="Sessions")
// ASIA = input.session ('2000-0000:1234567', "", inline="ASIA", group="Sessions")
// Session Times
LDNsesh = input.session ('0200-0500:1234567', "", inline="LONDON", group="Sessions")
NYsesh = input.session ('0700-1000:1234567', "", inline="NY", group="Sessions")
LCsesh = input.session ('1000-1200:1234567', "", inline="LC", group="Sessions")
PMsesh = input.session ('1300-1600:1234567', "", inline="PM", group="Sessions")
ASIA2sesh = input.session ('2000-2359:1234567', "", inline="ASIA2", group="Sessions")
FreeSesh = input.session ('0000-0000:1234567', "", inline="FREE", group="Sessions")
// Session Color
LSFC = input.color (color.new(#787b86, 90), "", inline="LONDON", group="Sessions")
NYSFC = input.color (color.new(#787b86, 90), "",inline="NY", group="Sessions")
LCSFC = input.color (color.new(#787b86, 90), "",inline="LC", group="Sessions")
PMSFC = input.color (color.new(#787b86, 90), "",inline="PM", group="Sessions")
ASFC = input.color (color.new(#787b86, 90), "",inline="ASIA2", group="Sessions")
FSFC = input.color (color.new(#787b86, 90), "",inline="FREE", group="Sessions")
//----------------------------------------------
// Vertical Line Bool
ShowMOP = input.bool (title="", defval=true, inline="MOP", group="Vertical Lines", tooltip="00:00 AM")
txt12 = input.string ("MIDNIGHT", title="", inline="MOP", group="Vertical Lines")
ShowLOP = input.bool (title="", defval=false, inline="LOP", group="Vertical Lines", tooltip="03:00 AM")
txt14 = input.string ("LONDON", title="", inline="LOP", group="Vertical Lines")
ShowNYOP = input.bool (title="", defval=true, inline="NYOP", group="Vertical Lines", tooltip="08:30 AM")
txt15 = input.string ("NEW YORK", title="", inline="NYOP", group="Vertical Lines")
ShowEOP = input.bool (title="", defval=false, inline="EOP", group="Vertical Lines", tooltip="09:30 AM")
txt16 = input.string ("EQUITIES", title="", inline="EOP", group="Vertical Lines")
// Vertical Line Color
MOPColor = input.color (color.new(#787b86, 0), "", inline="MOP", group="Vertical Lines")
LOPColor = input.color (color.rgb(0,128,128,60), "", inline="LOP", group="Vertical Lines")
NYOPColor = input.color (color.rgb(0,128,128,60), "", inline="NYOP", group="Vertical Lines")
EOPColor = input.color (color.rgb(0,128,128,60), "", inline="EOP", group="Vertical Lines")
// Vertical LineStyle
Midnight_Open_LS = input.string ("Dotted", "", options= , inline="MOP", group="Vertical Lines")
london_Open_LS = input.string ("Solid", "", options= , inline="LOP", group="Vertical Lines")
NY_Open_LS = input.string ("Solid", "", options= , inline="NYOP", group="Vertical Lines")
Equities_Open_LS = input.string ("Solid", "", options= , inline="EOP", group="Vertical Lines")
// Vertical LineWidth
Midnight_Open_LW = input.string ("1px", "", options= , inline="MOP", group="Vertical Lines")
London_Open_LW = input.string ("1px", "", options= , inline="LOP", group="Vertical Lines")
NY_Open_LW = input.string ("1px", "", options= , inline="NYOP", group="Vertical Lines")
Equities_Open_LW = input.string ("1px", "", options= , inline="EOP", group="Vertical Lines")
//----------------------------------------------
// Opening Price Bool
ShowMOPP = input.bool (title="", defval=true, inline="MOPP", group="Opening Price Lines", tooltip="00:00 AM")
txt13 = input.string ("MIDNIGHT", title="", inline="MOPP", group="Opening Price Lines")
ShowNYOPP = input.bool (title="", defval=false, inline="NYOPP", group="Opening Price Lines", tooltip="08:30 AM")
txt17 = input.string ("NEW YORK", title="", inline="NYOPP", group="Opening Price Lines")
ShowEOPP = input.bool (title="", defval=false, inline="EOPP", group="Opening Price Lines", tooltip="09:30 AM")
txt18 = input.string ("EQUITIES", title="", inline="EOPP", group="Opening Price Lines")
ShowAFTPP = input.bool (title="", defval=false, inline="AFTOPP", group="Opening Price Lines", tooltip="01:30 PM")
txt1330 = input.string ("AFTERNOON", title="", inline="AFTOPP", group="Opening Price Lines")
// Opening Price Color
MOPColP = input.color (color.new(#787b86, 0), "", inline="MOPP", group="Opening Price Lines")
NYOPColP = input.color (color.new(#787b86, 0), "", inline="NYOPP", group="Opening Price Lines")
EOPColP = input.color (color.new(#787b86, 0), "", inline="EOPP", group="Opening Price Lines")
AFTOPColP = input.color (color.new(#787b86, 0), "", inline="AFTOPP", group="Opening Price Lines")
// Opening Price LineStyle
MOPLS = input.string ("Dotted", "", options= , inline="MOPP", group="Opening Price Lines")
NYOPLS = input.string ("Dotted", "", options= , inline="NYOPP", group="Opening Price Lines")
EOPLS = input.string ("Dotted", "", options= , inline="EOPP", group="Opening Price Lines")
AFTOPLS = input.string ("Dotted", "", options= , inline="AFTOPP", group="Opening Price Lines")
// Opening Price LineWidth
i_MOPLW = input.string ("1px", "", options= , inline="MOPP", group="Opening Price Lines")
i_NYOPLW = input.string ("1px", "", options= , inline="NYOPP", group="Opening Price Lines")
i_EOPLW = input.string ("1px", "", options= , inline="EOPP", group="Opening Price Lines")
i_AFTOPLW = input.string ("1px", "", options= , inline="AFTOPP", group="Opening Price Lines")
//----------------------------------------------
// W&M Bool
ShowWeekOpen = input.bool (defval=false, title="", tooltip="Draw Weekly Open Price Line", group="HTF Opening Price Lines", inline="WO")
showMonthOpen = input.bool (defval=false, title="", tooltip="Draw Monthly Open Price Line", group="HTF Opening Price Lines", inline="MO")
// W&M String
txt19 = input.string ("WEEKLY", title="", inline="WO", group="HTF Opening Price Lines")
txt20 = input.string ("MONTHLY", title="", inline="MO", group="HTF Opening Price Lines")
// W&M Color
i_WeekOpenCol = input.color (title="", defval=color.new(#787b86, 0), group="HTF Opening Price Lines", inline="WO")
i_MonthOpenCol = input.color (title="", tooltip="", defval=color.new(#787b86, 0), group="HTF Opening Price Lines", inline="MO")
// W&M LineStyle
WOLS = input.string ("Dotted", "", options= , inline="WO", group="HTF Opening Price Lines")
MOLS = input.string ("Dotted", "", options= , inline="MO", group="HTF Opening Price Lines")
// W&M LineWidth
i_WOPLW = input.string ("1px", "", options= , inline="WO", group="HTF Opening Price Lines")
i_MONPLW = input.string ("1px", "", options= , inline="MO", group="HTF Opening Price Lines")
//----------------------------------------------
// CBDR, ASIA & FLOUT
ShowCBDR = input.bool (true, "", inline='CBDR', group="CBDR, ASIA & FLOUT")
ShowASIA = input.bool (true, "", inline='ASIA', group="CBDR, ASIA & FLOUT")
ShowFLOUT = input.bool (false, "", inline='FLOUT', group="CBDR, ASIA & FLOUT")
// Strings
txt0 = input.string ("CBDR", title="", inline="CBDR", group="CBDR, ASIA & FLOUT", tooltip="16:00 to 20:00 \nSD Increments of 1")
txt1 = input.string ("ASIA", title="", inline="ASIA", group="CBDR, ASIA & FLOUT", tooltip="20:00 to 00:00 \nSD Increments of 1")
txt7 = input.string ("FLOUT", title="", inline="FLOUT", group="CBDR, ASIA & FLOUT", tooltip="16:00 to 00:00 \nSD Increments of 0.5")
// Color
CBDRBoxCol = input.color (color.new(#787b86, 0),"", inline='CBDR', group="CBDR, ASIA & FLOUT")
ASIABoxCol = input.color (color.new(#787b86, 0), "", inline='ASIA', group="CBDR, ASIA & FLOUT")
FLOUTBoxCol = input.color (color.new(#787b86, 0),"", inline='FLOUT', group="CBDR, ASIA & FLOUT")
// Extras
box_text_cbdr = input.bool (true, "Show Text", inline="CBDR", group="CBDR, ASIA & FLOUT")
box_text_cbdr_col = input.color (color.new(color.gray, 80), "", inline="CBDR", group="CBDR, ASIA & FLOUT")
bool_cbdr_dev = input.bool (true, "SD", inline="CBDR", group="CBDR, ASIA & FLOUT")
box_text_asia = input.bool (true, "Show Text", inline="ASIA", group="CBDR, ASIA & FLOUT")
box_text_asia_col = input.color (color.new(color.gray, 80), "", inline="ASIA", group="CBDR, ASIA & FLOUT")
bool_asia_dev = input.bool (true, "SD", inline="ASIA", group="CBDR, ASIA & FLOUT")
box_text_flout = input.bool (true, "Show Text", inline="FLOUT", group="CBDR, ASIA & FLOUT")
box_text_flout_col = input.color (color.new(color.gray, 80), "", inline="FLOUT", group="CBDR, ASIA & FLOUT")
bool_flout_dev = input.bool (true, "SD", inline="FLOUT", group="CBDR, ASIA & FLOUT")
// Table
// SD Lines
ShowDevLN = input.bool (title="", defval=true, inline="DEVLN", group="Standard Deviation", tooltip="Deviation Lines")
DEVLNTXT = input.string ("SD LINES", title="", inline="DEVLN", group="Standard Deviation")
DevLNCol = input.color (color.new(#787b86, 0), "", inline="DEVLN", group="Standard Deviation")
DEVLS = input.string ("Solid", "", options= , inline="DEVLN", group="Standard Deviation")
i_DEVLW = input.string ("1px", "", options= , inline="DEVLN", group="Standard Deviation")
DEVLSS = DEVLS=="Solid" ? line.style_solid : DEVLS == "Dotted" ? line.style_dotted : line.style_dashed
DEVLW = i_DEVLW=="1px" ? 1 : i_DEVLW == "2px" ? 2 : i_DEVLW == "3px" ? 3 : i_DEVLW == "4px" ? 4 : 5
ShowDev = input.bool (false, '', inline="DEV", group="Standard Deviation")
txt8 = input.string ("SD COUNT", title="", inline="DEV", group="Standard Deviation")
SDCountCol = input.color (color.new(#787b86, 0), "", inline="DEV", group="Standard Deviation")
DevInput = input.string ("2 SD", "", options= , inline="DEV", group="Standard Deviation")
DevDirection = input.string ("Both", "", options= , inline="DEV", group="Standard Deviation", tooltip="SD Count, NULL, SD Count, SD Direction")
DevCount = DevInput == "1 SD" ? 1 : DevInput == "2 SD" ? 2 : DevInput == "3 SD" ? 3 : 4
Auto_Select = input.bool (false, "", group="Standard Deviation", inline="AUTOSD", tooltip="Auto SD Selection | Charter Content, Range Table \nMight Bug Out On Mondays" )
txtSD = input.string ("AUTO SD", "", group="Standard Deviation", inline="AUTOSD")
Tab1txtCol = input.color (color.new(#808080, 0), "", inline='AUTOSD', group="Standard Deviation")
TabOptionShow = input.string ("Show Table", "", options= , inline="AUTOSD", group="Standard Deviation")
Stats = TabOptionShow == "Show Table" ? true : false
TabOption1 = input.string ("Top Right", "", options= , inline="AUTOSD", group="Standard Deviation")
tabinp1 = TabOption1 == "Top Left" ? position.top_left : TabOption1 == "Top Center" ? position.top_center : TabOption1 == "Top Right" ? position.top_right : TabOption1 == "Middle Left" ? position.middle_left : TabOption1 == "Middle Right" ? position.middle_right : TabOption1 == "Bottom Left" ? position.bottom_left : TabOption1 == "Bottom Center" ? position.bottom_center : position.bottom_right
L_Prof = true
CellBG = color.new(#131722, 100)
//----------------------------------------------
// Day Of Week & Labels
// Label Settings Inputs
ShowLabel = input.bool (true, title="", inline="Glabel", group="Day Of Week & Labels")
txt21 = input.string ("LABEL", title="", inline="Glabel", group="Day Of Week & Labels")
LabelColor = input.color (color.rgb(0,0,0,100), "", inline="Glabel", group="Day Of Week & Labels")
LabelSizeInput = input.string ("Normal", "", options= , inline="Glabel", group="Day Of Week & Labels")
Terminusinp = input.string ("Terminus @ Current Time +1hr", "", options = , inline="Glabel", group="Day Of Week & Labels", tooltip="Select Label Size & Color & Terminus \nHistorical Price Lines needs to be toggled off for using Terminus")
ShowLabelText = input.bool (true, title="", inline="label", group="Day Of Week & Labels")
txt22 = input.string ("LABEL TEXT", title="", inline="label", group="Day Of Week & Labels")
LabelTextColor = input.color (color.new(#787b86, 0), title="", inline="label", group="Day Of Week & Labels")
LabelTextOptioninput = input.string ("Time", "", options= , inline="label", group="Day Of Week & Labels", tooltip="Choose Between Descriptive Text as Label or Time \nShow/Hide Prices on Labels")
ShowPricesBool = input.string ("Hide Prices", title="", options= , group="Day Of Week & Labels", inline="label")
ShowPrices = ShowPricesBool == "Show Prices" ? true : false
showDOW = input.bool (true, title="", inline="DOW", group="Day Of Week & Labels")
txt24 = input.string ("DAY OF WEEK", title="", inline="DOW", group="Day Of Week & Labels")
i_DOWCol = input.color (color.new(#787b86, 0), title="", inline="DOW", group="Day Of Week & Labels")
DOWTime = input.int (defval = 12, title="", inline="DOW", group="Day Of Week & Labels")
DOWLoc_inpt = input.string ("Bottom", "", options = , inline="DOW", group="Day Of Week & Labels", tooltip="DOW Color, Time Alignment, Vertical Location")
DOWLoc = DOWLoc_inpt == "Bottom" ? location.bottom : location.top
//----------------------------------------------
BIAS_M_Bool = input.bool (false, "", group="BIAS & NOTES PRECONFIG", inline="stats")
txt100 = input.string ("BIAS", title="", inline="stats", group="BIAS & NOTES PRECONFIG")
TableBG2 = color.new(#131722, 100)
Tab2txtCol = input.color (color.new(#787b86, 0), "", inline='stats', group="BIAS & NOTES PRECONFIG")
TabOption2 = input.string ("Bottom Right", "", options= , inline="stats", group="BIAS & NOTES PRECONFIG")
tabinp2 = TabOption2 == "Top Left" ? position.top_left : TabOption2 == "Top Center" ? position.top_center : TabOption2 == "Top Right" ? position.top_right : TabOption2 == "Middle Left" ? position.middle_left : TabOption2 == "Middle Right" ? position.middle_right : TabOption2 == "Bottom Left" ? position.bottom_left : TabOption2 == "Bottom Center" ? position.bottom_center : position.bottom_right
notesbool = false
NOTES_M_Bool = input.bool (true, "", group="BIAS & NOTES PRECONFIG", inline="stats2")
txt101 = input.string ("NOTES", title="", inline="stats2", group="BIAS & NOTES PRECONFIG")
Tab3txtCol = input.color (color.new(#787b86, 0), "", inline='stats2', group="BIAS & NOTES PRECONFIG")
TabOption3 = input.string ("Top Center", "", options= , inline="stats2", group="BIAS & NOTES PRECONFIG")
tabinp3 = TabOption3 == "Top Left" ? position.top_left : TabOption3 == "Top Center" ? position.top_center : TabOption3 == "Top Right" ? position.top_right : TabOption3 == "Middle Left" ? position.middle_left : TabOption3 == "Middle Right" ? position.middle_right : TabOption3 == "Bottom Left" ? position.bottom_left : TabOption3 == "Bottom Center" ? position.bottom_center : position.bottom_right
BIASbool1 = input.bool (true, '', inline="BIAS1", group="BIAS & NOTES")
txt52 = input.string ("DXY ", title="", inline="BIAS1", group="BIAS & NOTES")
BIASOption1 = input.string ("Unclear", options= , title="", inline="BIAS1", group="BIAS & NOTES")
BIASbool2 = input.bool (true, '', inline="BIAS2", group="BIAS & NOTES")
txt53 = input.string ("SPX ", title="", inline="BIAS2", group="BIAS & NOTES")
BIASOption2 = input.string ("Unclear", options= , title="", inline="BIAS2", group="BIAS & NOTES")
BIASbool3 = input.bool (true, '', inline="BIAS3", group="BIAS & NOTES")
txt54 = input.string ("DOW ", title="", inline="BIAS3", group="BIAS & NOTES")
BIASOption3 = input.string ("Unclear", options= , title="", inline="BIAS3", group="BIAS & NOTES")
BIASbool4 = input.bool (true, '', inline="BIAS4", group="BIAS & NOTES")
txt55 = input.string ("NAS ", title="", inline="BIAS4", group="BIAS & NOTES")
BIASOption4 = input.string ("Unclear", options= , title="", inline="BIAS4", group="BIAS & NOTES")
notes = input.text_area ("@hiran.invest", "Notes", group = "BIAS & NOTES")
//--------------------END OF INPUTS--------------------//
// Pre-Def
DOM = (timeframe.multiplier <= inputMaxInterval) and (timeframe.isintraday)
newDay = ta.change(dayofweek)
newWeek = ta.change(weekofyear)
newMonth = ta.change(time("M"))
transparentcol = color.rgb(255,255,255,100)
LSVLC = color.rgb(255,255,255,100)
NYSVLC = color.rgb(255,255,255,100)
PMSVLC = color.rgb(255,255,255,100)
ASVLC = color.rgb(255,255,255,100)
LSVLS = "dotted"
NYSVLS = "dotted"
PMSVLS = "dotted"
ASVLS = "dotted"
// Functions
isToday = false
if year(timenow) == year(time) and month(timenow) == month(time) and dayofmonth(timenow) == dayofmonth(time)
isToday := true
// Current Week
thisweek = year(timenow) == year(time) and weekofyear(timenow) == weekofyear(time)
LastOneWeek = year(timenow) == year(time) and weekofyear(timenow-604800000) == weekofyear(time)
LastTwoWeek = year(timenow) == year(time) and weekofyear(timenow-1209600000) == weekofyear(time)
LastThreeWeek = year(timenow) == year(time) and weekofyear(timenow-1814400000) == weekofyear(time)
LastFourWeek = year(timenow) == year(time) and weekofyear(timenow-2419200000) == weekofyear(time)
Last4Weeks = false
if thisweek == true or LastOneWeek == true or LastTwoWeek == true or LastThreeWeek == true or LastFourWeek == true
Last4Weeks := true
// Function to draw Vertical Lines
vline(Start, Color, linestyle, LineWidth) =>
line.new(x1=Start, y1=low - ta.tr, x2=Start, y2=high + ta.tr, xloc=xloc.bar_time, extend=extend.both, color=Color, style=linestyle, width=LineWidth)
// Function to convert forex pips into whole numbers
atr = ta.atr(14)
toWhole(number) =>
if syminfo.type == "forex" // This method only works on forex pairs
_return = atr < 1.0 ? (number / syminfo.mintick) / 10 : number
_return := atr >= 1.0 and atr < 100.0 and syminfo.currency == "JPY" ? _return * 100 : _return
else
number
// Function for determining the Start of a Session (taken from the Pinescript manual: www.tradingview.com )
SessionBegins(sess) =>
t = time("", sess , Timezone)
DOM and (not barstate.isfirst) and na(t ) and not na(t)
// BarIn Session
BarInSession(sess) =>
time(timeframe.period, sess, Timezone) != 0
// Label Type Logic
var SFistrue = true
if LabelTextOptioninput == "Time"
SFistrue := true
else
SFistrue := false
// Session String to int
SeshStartHour(Session) =>
math.round(str.tonumber(str.substring(Session,0,2)))
SeshStartMins(Session) =>
math.round(str.tonumber(str.substring(Session,2,4)))
SeshEndHour(Session) =>
math.round(str.tonumber(str.substring(Session,5,7)))
SeshEndMins(Session) =>
math.round(str.tonumber(str.substring(Session,7,9)))
// Time periods
CBDR = "1600-2000:1234567"
ASIA = "2000-0000:1234567"
FLOUT = "1600-0000:1234567"
midsesh = "0000-1600:1234567"
cbdrOpenTime = timestamp (Timezone, year, month, dayofmonth, SeshStartHour(CBDR), SeshStartMins(CBDR), 00)
cbdrEndTime = timestamp (Timezone, year, month, dayofmonth, SeshEndHour(CBDR), SeshEndMins(CBDR), 00)
asiaOpenTime = timestamp (Timezone, year, month, dayofmonth, SeshStartHour(ASIA), SeshStartMins(ASIA), 00)
asiaEndTime = timestamp (Timezone, year, month, dayofmonth, SeshEndHour(ASIA), SeshEndMins(ASIA), 00)+86400000
floutOpenTime = timestamp (Timezone, year, month, dayofmonth, SeshStartHour(FLOUT), SeshStartMins(FLOUT), 00)
floutEndTime = timestamp (Timezone, year, month, dayofmonth, SeshEndHour(FLOUT), SeshEndMins(FLOUT), 00)+86400000
CBDRTime = time (timeframe.period, CBDR, Timezone)
ASIATime = time (timeframe.period, ASIA, Timezone)
FLOUTTime = time (timeframe.period, FLOUT, Timezone)
LabelOnlyToday = true
// Time Periods
LondonStartTime = timestamp(Timezone, year, month, dayofmonth, SeshStartHour(LDNsesh), SeshStartMins(LDNsesh), 00)
LondonEndTime = timestamp(Timezone, year, month, dayofmonth, SeshEndHour(LDNsesh), SeshEndMins(LDNsesh), 00)
NYStartTime = timestamp(Timezone, year, month, dayofmonth, SeshStartHour(NYsesh), SeshStartMins(NYsesh), 00)
NYEndTime = timestamp(Timezone, year, month, dayofmonth, SeshEndHour(NYsesh), SeshEndMins(NYsesh), 00)
LCStartTime = timestamp(Timezone, year, month, dayofmonth, SeshStartHour(LCsesh), SeshStartMins(LCsesh), 00)
LCEndTime = timestamp(Timezone, year, month, dayofmonth, SeshEndHour(LCsesh), SeshEndMins(LCsesh), 00)
PMStartTime = timestamp(Timezone, year, month, dayofmonth, SeshStartHour(PMsesh), SeshStartMins(PMsesh), 00)
PMEndTime = timestamp(Timezone, year, month, dayofmonth, SeshEndHour(PMsesh), SeshEndMins(PMsesh), 00)
AsianStartTime = timestamp(Timezone, year, month, dayofmonth, SeshStartHour(ASIA2sesh), SeshStartMins(ASIA2sesh), 00)
AsianEndTime = timestamp(Timezone, year, month, dayofmonth, SeshEndHour(ASIA2sesh), SeshEndMins(ASIA2sesh), 00)
FreeStartTime = timestamp(Timezone, year, month, dayofmonth, SeshStartHour(FreeSesh), SeshStartMins(FreeSesh), 00)
FreeEndTime = timestamp(Timezone, year, month, dayofmonth, SeshEndHour(FreeSesh), SeshEndMins(FreeSesh), 00)
MidnightOpenTime = timestamp(Timezone, year, month, dayofmonth, 0, 0, 00)
CLEANUPTIME = timestamp(Timezone, year, month, dayofmonth, 0, 0, 00) - 16200000
LondonOpenTime = timestamp(Timezone, year, month, dayofmonth, 3, 0, 00)
NYOpenTime = timestamp(Timezone, year, month, dayofmonth, 8, 30, 00)
EquitiesOpenTime = timestamp(Timezone, year, month, dayofmonth, 9, 30, 00)
AfternoonOpenTime = timestamp(Timezone, year, month, dayofmonth, 13, 30, 00)
tMidnight = time("1", "0000-0001:1234567", Timezone)
// Cleanup - Remove old drawing objects
Cleanup(days) =>
// Delete old drawing objects
// One day is 86400000 milliseconds
removal_timestamp = (CLEANUPTIME) - (days * 86400000) // Remove every drawing object older than the start of the Today's Midnight
a_allLines = line.all
a_allLabels = label.all
a_allboxes = box.all
// Remove old lines
if array.size(a_allLines) > 0
for i = 0 to array.size(a_allLines) - 1
line_x2 = line.get_x2(array.get(a_allLines, i))
if line_x2 < (removal_timestamp)
line.delete(array.get(a_allLines, i))
// Remove old labels
if array.size(a_allLabels) > 0
for i = 0 to array.size(a_allLabels) - 1
label_x = label.get_x(array.get(a_allLabels, i))
if label_x < removal_timestamp
label.delete(array.get(a_allLabels, i))
// Remove old boxes
if array.size(a_allboxes) > 0
for i = 0 to array.size(a_allboxes) - 1
box_x = box.get_right(array.get(a_allboxes, i))
if box_x < (removal_timestamp - 86400000)
box.delete(array.get(a_allboxes, i))
// End of Cleanup function
// Terminus Function
Terminus(Terminus_Inp)=>
if Terminus_Inp == "Terminus @ Current Time"
_return = timenow
else if Terminus_Inp == "Terminus @ Current Time +15min"
_return = timenow + 900000
else if Terminus_Inp == "Terminus @ Current Time +30min"
_return = timenow + 1800000
else if Terminus_Inp == "Terminus @ Current Time +45min"
_return = timenow + 2700000
else if Terminus_Inp == "Terminus @ Current Time +1hr"
_return = timenow + 3600000
else if Terminus_Inp == "Terminus @ Current Time +2hr"
_return = timenow + 7200000
else
_return = timenow + 10800000
// Linestyle Function
MNOPLS = Midnight_Open_LS=="Solid" ? line.style_solid : Midnight_Open_LS == "Dotted" ? line.style_dotted : line.style_dashed
LNOPLS = london_Open_LS=="Solid" ? line.style_solid : london_Open_LS == "Dotted" ? line.style_dotted : line.style_dashed
NWYOPLS = NY_Open_LS=="Solid" ? line.style_solid : NY_Open_LS == "Dotted" ? line.style_dotted : line.style_dashed
EQOPLS = Equities_Open_LS=="Solid" ? line.style_solid : Equities_Open_LS == "Dotted" ? line.style_dotted : line.style_dashed
MOPLSS = MOPLS=="Solid" ? line.style_solid : MOPLS == "Dotted" ? line.style_dotted : line.style_dashed
NYOPLSS = NYOPLS=="Solid" ? line.style_solid : NYOPLS == "Dotted" ? line.style_dotted : line.style_dashed
EOPLSS = EOPLS=="Solid" ? line.style_solid : EOPLS == "Dotted" ? line.style_dotted : line.style_dashed
AFTOPLSS = AFTOPLS=="Solid" ? line.style_solid : AFTOPLS == "Dotted" ? line.style_dotted : line.style_dashed
WeekOpenLS = WOLS=="Solid" ? line.style_solid : WOLS == "Dotted" ? line.style_dotted : line.style_dashed
MonthOpenLS = MOLS=="Solid" ? line.style_solid : MOLS == "Dotted" ? line.style_dotted : line.style_dashed
// Linewidth Function
MOPLW = Midnight_Open_LW=="1px" ? 1 : Midnight_Open_LW == "2px" ? 2 : Midnight_Open_LW == "3px" ? 3 : Midnight_Open_LW == "4px" ? 4 : 5
LOPLW = London_Open_LW=="1px" ? 1 : London_Open_LW == "2px" ? 2 : London_Open_LW == "3px" ? 3 : London_Open_LW == "4px" ? 4 : 5
NYOPLW = NY_Open_LW=="1px" ? 1 : NY_Open_LW == "2px" ? 2 : NY_Open_LW == "3px" ? 3 : NY_Open_LW == "4px" ? 4 : 5
EOPLW = Equities_Open_LW=="1px" ? 1 : Equities_Open_LW == "2px" ? 2 : Equities_Open_LW == "3px" ? 3 : Equities_Open_LW == "4px" ? 4 : 5
MOPPLW = i_MOPLW=="1px" ? 1 : i_MOPLW == "2px" ? 2 : i_MOPLW == "3px" ? 3 : i_MOPLW == "4px" ? 4 : 5
NYOPPLW = i_NYOPLW=="1px" ? 1 : i_NYOPLW == "2px" ? 2 : i_NYOPLW == "3px" ? 3 : i_NYOPLW == "4px" ? 4 : 5
EOPPLW = i_EOPLW=="1px" ? 1 : i_EOPLW == "2px" ? 2 : i_EOPLW == "3px" ? 3 : i_EOPLW == "4px" ? 4 : 5
AFTOPLW = i_AFTOPLW=="1px" ? 1 : i_AFTOPLW == "2px" ? 2 : i_AFTOPLW == "3px" ? 3 : i_AFTOPLW == "4px" ? 4 : 5
WEEKOPPLW = i_WOPLW=="1px" ? 1 : i_WOPLW == "2px" ? 2 : i_WOPLW == "3px" ? 3 : i_WOPLW == "4px" ? 4 : 5
MONTHOPPLW = i_MONPLW=="1px" ? 1 : i_MONPLW == "2px" ? 2 : i_MONPLW == "3px" ? 3 : i_MONPLW == "4px" ? 4 : 5
// Label Size Function
LabelSize =LabelSizeInput=="Auto" ? size.auto : LabelSizeInput=="Tiny" ? size.tiny : LabelSizeInput=="Small" ? size.small : LabelSizeInput=="Normal" ? size.normal : LabelSizeInput=="Large" ? size.large : size.huge
// Creating Variables
var London_Start_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=LSVLC, width=1)
var London_End_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=LSVLC, width=1)
var LondonFill = linefill.new(London_Start_Vline, London_End_Vline, LSFC)
var NY_Start_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=NYSVLC, width=1)
var NY_End_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=NYSVLC, width=1)
var NYFill = linefill.new(NY_Start_Vline, NY_End_Vline, NYSFC)
var LC_Start_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=NYSVLC, width=1)
var LC_End_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=NYSVLC, width=1)
var LCFill = linefill.new(LC_Start_Vline, LC_End_Vline, LCSFC)
var PM_Start_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=PMSVLC, width=1)
var PM_End_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=PMSVLC, width=1)
var PMFill = linefill.new(PM_Start_Vline, PM_End_Vline, PMSFC)
var Asian_Start_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=ASVLC, width=1)
var Asian_End_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=ASVLC, width=1)
var AsianFill = linefill.new(Asian_Start_Vline, Asian_End_Vline, ASFC)
var Free_Start_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=ASVLC, width=1)
var Free_End_Vline = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=ASVLC, width=1)
var FreeFill = linefill.new(Free_Start_Vline, Free_End_Vline, FSFC)
var Midnight_Open = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=MOPColor, width=1)
var London_Open = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=LOPColor, width=1)
var NY_Open = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=NYOPColor, width=1)
var Equities_Open = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=EOPColor, width=1)
// When a New Day Starts, Start Drawing all lines
if newDay and dayofweek != dayofweek.sunday
// London Session
if (ShowLondon and DOM)
if ShowTSO
line.delete(London_Start_Vline )
line.delete(London_End_Vline )
linefill.delete(LondonFill )
London_Start_Vline := vline(LondonStartTime,transparentcol, line.style_solid, 1)
London_End_Vline := vline(LondonEndTime, transparentcol, line.style_solid, 1)
if ShowSFill
LondonFill := linefill.new(London_Start_Vline, London_End_Vline, LSFC)
// New York Session
if (ShowNY and DOM)
if ShowTSO
line.delete(NY_Start_Vline )
line.delete(NY_End_Vline )
linefill.delete(NYFill )
NY_Start_Vline := vline(NYStartTime, transparentcol, line.style_solid, 1)
NY_End_Vline := vline(NYEndTime, transparentcol, line.style_solid, 1)
if ShowSFill
NYFill := linefill.new(NY_Start_Vline, NY_End_Vline, NYSFC)
// London Close
if (ShowLC and DOM)
if ShowTSO
line.delete(LC_End_Vline )
linefill.delete(LCFill )
LC_Start_Vline := vline(LCStartTime, transparentcol, line.style_solid, 1)
LC_End_Vline := vline(LCEndTime, transparentcol, line.style_solid, 1)
if ShowSFill
LCFill := linefill.new(LC_Start_Vline, LC_End_Vline, LCSFC)
// PM Session
if (ShowPM and DOM)
if ShowTSO
line.delete(PM_Start_Vline )
line.delete(PM_End_Vline )
linefill.delete(PMFill )
PM_Start_Vline := vline(PMStartTime, transparentcol, line.style_solid, 1)
PM_End_Vline := vline(PMEndTime, transparentcol, line.style_solid, 1)
if ShowSFill
PMFill := linefill.new(PM_Start_Vline, PM_End_Vline, PMSFC)
// Asian Session
if (ShowAsian and DOM)
if ShowTSO
line.delete(Asian_Start_Vline )
line.delete(Asian_End_Vline )
linefill.delete(AsianFill )
Asian_Start_Vline := vline(AsianStartTime, transparentcol, line.style_solid, 1)
Asian_End_Vline := vline(AsianEndTime, transparentcol, line.style_solid, 1)
// if dayofweek == dayofweek.friday
// // line.delete(Asian_Start_Vline)
// // line.delete(Asian_End_Vline)
// Asian_Start_Vline := vline(MidnightOpenTime+244800000, transparentcol, line.style_solid, 1)
// Asian_End_Vline := vline(MidnightOpenTime+259200000, transparentcol, line.style_solid, 1)
if ShowSFill
AsianFill := linefill.new(Asian_Start_Vline, Asian_End_Vline, ASFC)
// Free Session
if (ShowFreeSesh and DOM)
if ShowTSO
line.delete(Free_Start_Vline )
line.delete(Free_End_Vline )
linefill.delete(FreeFill )
Free_Start_Vline := vline(FreeStartTime, transparentcol, line.style_solid, 1)
Free_End_Vline := vline(FreeEndTime, transparentcol, line.style_solid, 1)
if ShowSFill
FreeFill := linefill.new(Free_Start_Vline, Free_End_Vline, FSFC)
// Midnight Opening Price
if (ShowMOP and DOM)
if MOLHist == false
line.delete(Midnight_Open )
Midnight_Open := vline(MidnightOpenTime, MOPColor, MNOPLS, MOPLW)
// London Opening Price
if (ShowLOP and DOM)
if ShowTSO
line.delete(London_Open )
London_Open := vline(LondonOpenTime, LOPColor, LNOPLS, LOPLW)
// New York Opening Price
if (ShowNYOP and DOM)
if ShowTSO
line.delete(NY_Open )
NY_Open := vline(NYOpenTime, NYOPColor, NWYOPLS, NYOPLW)
// Equities Opening Price
if (ShowEOP and DOM)
if ShowTSO
line.delete(Equities_Open )
Equities_Open := vline(EquitiesOpenTime, EOPColor, EQOPLS, EOPLW)
// Variables
var label MOPLB = na
var line MOPLN = na
var label NYOPLB = na
var line NYOPLN = na
var label EOPLB = na
var line EOPLN = na
var line AFTLN = na
var label AFTLB = na
// New York Midnight Open Price line
var openMidnight = 0.0
if tMidnight
if not tMidnight
openMidnight := open
else
openMidnight := math.max(open, openMidnight)
if (ShowMOPP and (openMidnight != openMidnight ) and DOM and barstate.isconfirmed)
label.delete(MOPLB )
if ShowMOPL == false
line.delete(MOPLN )
MOPLN := line.new(x1=tMidnight, y1=openMidnight, x2=tMidnight+86400000, xloc=xloc.bar_time, y2=openMidnight, color=MOPColP, style=MOPLSS, width=MOPPLW)
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
line.set_x2(MOPLN, tMidnight+259200000)
if ShowLabel
MOPLB := label.new(x=tMidnight+86400000, y=openMidnight, xloc=xloc.bar_time, color=LabelColor, textcolor=MOPColP, style=label.style_label_left, size=LabelSize, tooltip="Midnight Opening Price")
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
label.set_x(MOPLB, tMidnight+259200000)
if ShowLabelText
if SFistrue
if ShowPrices == true
label.set_text(MOPLB, " 00:00 | " + str.tostring(open))
else
label.set_text(MOPLB, " 00:00 ")
label.set_tooltip(MOPLB, "Midnight Opening Price")
else
if ShowPrices == true
label.set_text(MOPLB, " Midnight Opening Price | " + str.tostring(open))
else
label.set_text(MOPLB, " Midnight Opening Price ")
label.set_tooltip(MOPLB, "")
label.set_textcolor(MOPLB, LabelTextColor)
label.set_size(MOPLB,LabelSize)
if time > PMEndTime and time < (MidnightOpenTime + 86400000)
line.delete(MOPLN )
if Terminusinp != "Terminus @ Next Midnight" and ShowMOPL == false
line.set_x2(MOPLN, Terminus(Terminusinp))
label.set_x(MOPLB, Terminus(Terminusinp))
// New York Opening Price Line
if (ShowNYOPP and (time == NYOpenTime) and DOM)
label.delete(NYOPLB )
if ShowPrev == false
line.delete(NYOPLN )
NYOPLN := line.new(x1=NYOpenTime, y1=open, x2=NYOpenTime+55800000, xloc=xloc.bar_time, y2=open, color=NYOPColP, style=NYOPLSS, width=NYOPPLW)
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
line.set_x2(NYOPLN, NYOpenTime+228600000)
if ShowLabel
NYOPLB := label.new(x=NYOpenTime+55800000, y=open, xloc=xloc.bar_time, color=LabelColor, textcolor=NYOPColP, style=label.style_label_left, size=LabelSize, tooltip="New York Opening Price")
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
label.set_x(NYOPLB, NYOpenTime+228600000)
if ShowLabelText
if SFistrue
if ShowPrices == true
label.set_text(NYOPLB, " 08:30 | " + str.tostring(open))
else
label.set_text(NYOPLB, " 08:30 ")
label.set_tooltip(NYOPLB, "New York Opening Price")
else
if ShowPrices == true
label.set_text(NYOPLB, " New York Opening Price | " + str.tostring(open))
else
label.set_text(NYOPLB, " New York Opening Price ")
label.set_tooltip(NYOPLB, "")
label.set_textcolor(NYOPLB, LabelTextColor)
label.set_size(NYOPLB,LabelSize)
if Terminusinp != "Terminus @ Next Midnight" and ShowPrev == false
line.set_x2(NYOPLN, Terminus(Terminusinp))
label.set_x(NYOPLB, Terminus(Terminusinp))
// Equities Opening Price Line
if (ShowEOPP and (time == EquitiesOpenTime) and DOM)
label.delete(EOPLB )
if ShowPrev == false
line.delete(EOPLN )
EOPLN := line.new(x1=EquitiesOpenTime, y1=open, x2=EquitiesOpenTime+52200000, xloc=xloc.bar_time, y2=open, color=EOPColP, style=EOPLSS, width=EOPPLW)
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
line.set_x2(EOPLN, EquitiesOpenTime+225000000)
if ShowLabel
EOPLB := label.new(x=EquitiesOpenTime+52200000, y=open, xloc=xloc.bar_time, color=LabelColor, textcolor=EOPColP, style=label.style_label_left, size=LabelSize, tooltip="Equities Opening Price")
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
label.set_x(EOPLB, EquitiesOpenTime+225000000)
if ShowLabelText
if SFistrue
if ShowPrices == true
label.set_text(EOPLB, " 09:30 | " + str.tostring(open))
else
label.set_text(EOPLB, " 09:30 ")
label.set_tooltip(EOPLB, "Equities Opening Price")
else
if ShowPrices == true
label.set_text(EOPLB, " Equities Opening Price | " + str.tostring(open))
else
label.set_text(EOPLB, " Equities Opening Price ")
label.set_tooltip(EOPLB, "")
label.set_textcolor(EOPLB, LabelTextColor)
label.set_size(EOPLB,LabelSize)
if Terminusinp != "Terminus @ Next Midnight" and ShowPrev == false
line.set_x2(EOPLN, Terminus(Terminusinp))
label.set_x(EOPLB, Terminus(Terminusinp))
// Afternoon Opening Price Line
if (ShowAFTPP and (time == AfternoonOpenTime) and DOM)
label.delete(AFTLB )
if ShowPrev == false
line.delete(AFTLN )
AFTLN := line.new(x1=AfternoonOpenTime, y1=open, x2=EquitiesOpenTime+52200000, xloc=xloc.bar_time, y2=open, color=AFTOPColP, style=AFTOPLSS, width=AFTOPLW)
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
line.set_x2(AFTLN, EquitiesOpenTime+225000000)
if ShowLabel
AFTLB := label.new(x=EquitiesOpenTime+52200000, y=open, xloc=xloc.bar_time, color=LabelColor, textcolor=AFTOPColP, style=label.style_label_left, size=LabelSize, tooltip="Equities Opening Price")
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
label.set_x(AFTLB, EquitiesOpenTime+225000000)
if ShowLabelText
if SFistrue
if ShowPrices == true
label.set_text(AFTLB, " 01:30 | " + str.tostring(open))
else
label.set_text(AFTLB, " 01:30 ")
label.set_tooltip(AFTLB, " Afternoon Opening Price")
else
if ShowPrices == true
label.set_text(AFTLB, " Afternoon Opening Price | " + str.tostring(open))
else
label.set_text(AFTLB, " Afternoon Opening Price ")
label.set_tooltip(AFTLB, "")
label.set_textcolor(AFTLB, LabelTextColor)
label.set_size(AFTLB,LabelSize)
if Terminusinp != "Terminus @ Next Midnight" and ShowPrev == false
line.set_x2(AFTLN, Terminus(Terminusinp))
label.set_x(AFTLB, Terminus(Terminusinp))
// HTF Variables
var Weekly_open = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=i_WeekOpenCol, style=WeekOpenLS, width=1)
var Weekly_openlbl = label.new(x=na, y=na, xloc=xloc.bar_time, color=LabelColor, textcolor=LabelTextColor, style=label.style_label_left, size=LabelSize)
var WeeklyOpenTime = time
var Monthly_open = line.new(x1=na, y1=na, x2=na, xloc=xloc.bar_time, y2=close, color=i_MonthOpenCol, style=MonthOpenLS, width=1)
var Monthly_openlbl = label.new(x=na, y=na, xloc=xloc.bar_time, color=LabelColor, textcolor=LabelTextColor, style=label.style_label_left, size=LabelSize)
var MonthlyOpenTime = time
// Get HTF Price levels
WeeklyOpen = request.security(syminfo.tickerid, "W", open, lookahead = barmerge.lookahead_on)
MonthlyOpen = request.security(syminfo.tickerid, "M", open, lookahead = barmerge.lookahead_on)
// Weekly Open
if newWeek
WeeklyOpenTime := time
if ShowWeekOpen and newDay and Last4Weeks
label.delete(Weekly_openlbl )
line.delete(Weekly_open )
// if ShowPrev == false
// line.delete(Weekly_open )
Weekly_open:= line.new(x1=WeeklyOpenTime-25200000, y1=WeeklyOpen, x2=EquitiesOpenTime+52200000, xloc=xloc.bar_time, y2=WeeklyOpen, color=i_WeekOpenCol, style=WeekOpenLS, width=WEEKOPPLW)
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
line.set_x2(Weekly_open, EquitiesOpenTime+225000000)
if ShowLabel
Weekly_openlbl := label.new(x=EquitiesOpenTime+52200000, y=WeeklyOpen, xloc=xloc.bar_time, color=LabelColor, textcolor=LabelTextColor, style=label.style_label_left, size=LabelSize, tooltip="Weekly Open: " + str.tostring(WeeklyOpen))
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
label.set_x(Weekly_openlbl, EquitiesOpenTime+225000000)
if ShowLabelText
if SFistrue
if ShowPrices == true
label.set_text(Weekly_openlbl," W.O. | " + str.tostring(WeeklyOpen))
else
label.set_text(Weekly_openlbl," W.O. ")
label.set_tooltip(Weekly_openlbl, " Weekly Opening Price ")
else
if ShowPrices == true
label.set_text(Weekly_openlbl," Weekly Open | " + str.tostring(WeeklyOpen))
else
label.set_text(Weekly_openlbl," Weekly Open ")
label.set_tooltip(Weekly_openlbl, "")
label.set_textcolor(Weekly_openlbl, LabelTextColor)
label.set_size(Weekly_openlbl, LabelSize)
if timeframe.multiplier > 60
line.set_x2(Weekly_open, AsianEndTime + 232000000)
label.set_x(Weekly_openlbl, AsianEndTime + 232000000)
if timeframe.period == "D"
line.set_x2(Weekly_open, AsianEndTime + 832000000)
label.set_x(Weekly_openlbl, AsianEndTime + 832000000)
if timeframe.period == "M"
line.delete(Weekly_open)
label.delete(Weekly_openlbl)
if Terminusinp != "Terminus @ Next Midnight" and DOM
line.set_x2(Weekly_open, Terminus(Terminusinp))
label.set_x(Weekly_openlbl, Terminus(Terminusinp))
// Monthly Open
if newMonth
MonthlyOpenTime := time
if showMonthOpen and newDay
line.delete(Monthly_open )
label.delete(Monthly_openlbl )
Monthly_open:= line.new(x1=MonthlyOpenTime, y1=MonthlyOpen, x2=AsianEndTime, xloc=xloc.bar_time, y2=MonthlyOpen, color=i_MonthOpenCol, style=MonthOpenLS, width=MONTHOPPLW)
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
line.set_x2(Monthly_open, EquitiesOpenTime+225000000)
if ShowLabel
Monthly_openlbl := label.new(x=AsianEndTime, y=MonthlyOpen, xloc=xloc.bar_time, color=LabelColor, textcolor=LabelTextColor, style=label.style_label_left, size=LabelSize, tooltip="Monthly Open: " + str.tostring(MonthlyOpen))
if dayofweek == dayofweek.friday and syminfo.type != "crypto"
label.set_x(Monthly_openlbl, EquitiesOpenTime+225000000)
if ShowLabelText
if SFistrue
if ShowPrices == true
label.set_text(Monthly_openlbl," M.O. | " + str.tostring(MonthlyOpen))
else
label.set_text(Monthly_openlbl," M.O. ")
label.set_tooltip(Monthly_openlbl, " Monthly Opening Price ")
else
if ShowPrices == true
label.set_text(Monthly_openlbl, " Monthly Open | " + str.tostring(MonthlyOpen))
else
label.set_text(Monthly_openlbl, " Monthly Open ")
label.set_tooltip(Monthly_openlbl, "")
label.set_textcolor(Monthly_openlbl, LabelTextColor)
label.set_size(Monthly_openlbl, LabelSize)
if timeframe.multiplier > 60
line.set_x2(Monthly_open, AsianEndTime + 232000000)
label.set_x(Monthly_openlbl, AsianEndTime + 232000000)
if timeframe.period == "D"
line.set_x2(Monthly_open, AsianEndTime + 832000000)
label.set_x(Monthly_openlbl, AsianEndTime + 832000000)
if timeframe.period == "W"
line.set_x2(Monthly_open, AsianEndTime + 2592000000)
label.set_x(Monthly_openlbl, AsianEndTime + 2592000000)
if timeframe.period == "M"
line.delete(Monthly_open)
label.delete(Monthly_openlbl)
if Terminusinp != "Terminus @ Next Midnight" and DOM
line.set_x2(Monthly_open, Terminus(Terminusinp))
label.set_x(Monthly_openlbl, Terminus(Terminusinp))
// CBDR Stuff
var float cbdr_hi = na
var float cbdr_lo = na
var float cbdr_diff = na
var box cbdrbox = na
var line cbdr_hi_line = na
var line cbdr_lo_line = na
var line dev01negline = na
var line dev02negline = na
var line dev03negline = na
var line dev04negline = na
var line dev01posline = na
var line dev02posline = na
var line dev03posline = na
var line dev04posline = na
if SessionBegins(CBDR) and DOM
cbdr_hi := high
cbdr_lo := low
cbdr_diff := cbdr_hi - cbdr_lo
if ShowTSO
box.delete(cbdrbox )
line.delete(dev01posline )
line.delete(dev01negline )
line.delete(dev02posline )
line.delete(dev02negline )
line.delete(dev03posline )
line.delete(dev03negline )
line.delete(dev04posline )
line.delete(dev04negline )
if ShowCBDR
cbdrbox := box.new(cbdrOpenTime, cbdr_hi, cbdrEndTime, cbdr_lo, color.new(CBDRBoxCol,90), 1, line.style_solid, extend.none, xloc.bar_time, color.new(CBDRBoxCol,90), txt0, size.auto, color.new(box_text_cbdr_col,80), text_wrap=text.wrap_auto)
if dayofweek == dayofweek.friday
box.set_right(cbdrbox, cbdrOpenTime+187200000)
line.set_x2(cbdr_hi_line, cbdrOpenTime+187200000)
line.set_x2(cbdr_lo_line, cbdrOpenTime+187200000)
if box_text_cbdr == false
box.set_text(cbdrbox, "")
if ShowDev and ShowCBDR and bool_cbdr_dev
for i = 1 to DevCount by 1
if i == 1
dev01posline := line.new(cbdrOpenTime, cbdr_hi + cbdr_diff * i, cbdrEndTime, cbdr_hi + cbdr_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev01negline := line.new(cbdrOpenTime, cbdr_hi - cbdr_diff * i, cbdrEndTime, cbdr_lo - cbdr_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if dayofweek == dayofweek.friday
line.set_x2(dev01posline, cbdrOpenTime+187200000)
line.set_x2(dev01negline, cbdrOpenTime+187200000)
if i == 2
dev02posline := line.new(cbdrOpenTime, cbdr_hi + cbdr_diff * i, cbdrEndTime, cbdr_lo + cbdr_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev02negline := line.new(cbdrOpenTime, cbdr_hi - cbdr_diff * i, cbdrEndTime, cbdr_lo - cbdr_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if dayofweek == dayofweek.friday
line.set_x2(dev02posline, cbdrOpenTime+187200000)
line.set_x2(dev02negline, cbdrOpenTime+187200000)
if i == 3
dev03posline := line.new(cbdrOpenTime, cbdr_hi + cbdr_diff * i, cbdrEndTime, cbdr_lo + cbdr_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev03negline := line.new(cbdrOpenTime, cbdr_hi - cbdr_diff * i, cbdrEndTime, cbdr_lo - cbdr_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if dayofweek == dayofweek.friday
line.set_x2(dev03posline, cbdrOpenTime+187200000)
line.set_x2(dev03negline, cbdrOpenTime+187200000)
if i == 4
dev04posline := line.new(cbdrOpenTime, cbdr_hi + cbdr_diff * i, cbdrEndTime, cbdr_lo + cbdr_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev04negline := line.new(cbdrOpenTime, cbdr_hi - cbdr_diff * i, cbdrEndTime, cbdr_lo - cbdr_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if dayofweek == dayofweek.friday
line.set_x2(dev04posline, cbdrOpenTime+187200000)
line.set_x2(dev04negline, cbdrOpenTime+187200000)
else if CBDRTime
cbdr_hi := math.max(high, cbdr_hi)
cbdr_lo := math.min(low, cbdr_lo)
cbdr_diff := cbdr_hi - cbdr_lo
for i = 1 to DevCount by 1
if i == 1 and ShowDev
line.set_y1(dev01posline, cbdr_hi + cbdr_diff * i)
line.set_y2(dev01posline, cbdr_hi + cbdr_diff * i)
line.set_y1(dev01negline, cbdr_lo - cbdr_diff * i)
line.set_y2(dev01negline, cbdr_lo - cbdr_diff * i)
if i == 2 and ShowDev
line.set_y1(dev02posline, cbdr_hi + cbdr_diff * i)
line.set_y2(dev02posline, cbdr_hi + cbdr_diff * i)
line.set_y1(dev02negline, cbdr_lo - cbdr_diff * i)
line.set_y2(dev02negline, cbdr_lo - cbdr_diff * i)
if i == 3 and ShowDev
line.set_y1(dev03posline, cbdr_hi + cbdr_diff * i)
line.set_y2(dev03posline, cbdr_hi + cbdr_diff * i)
line.set_y1(dev03negline, cbdr_lo - cbdr_diff * i)
line.set_y2(dev03negline, cbdr_lo - cbdr_diff * i)
if i == 4 and ShowDev
line.set_y1(dev04posline, cbdr_hi + cbdr_diff * i)
line.set_y2(dev04posline, cbdr_hi + cbdr_diff * i)
line.set_y1(dev04negline, cbdr_lo - cbdr_diff * i)
line.set_y2(dev04negline, cbdr_lo - cbdr_diff * i)
if (cbdr_hi > cbdr_hi )
if ShowCBDR
box.set_top(cbdrbox, cbdr_hi)
if (cbdr_lo < cbdr_lo )
if ShowCBDR
box.set_bottom(cbdrbox, cbdr_lo)
if DevDirection == "Upside Only"
line.delete(dev01negline)
line.delete(dev02negline)
line.delete(dev03negline)
line.delete(dev04negline)
else if DevDirection == "Downside Only"
line.delete(dev01posline)
line.delete(dev02posline)
line.delete(dev03posline)
line.delete(dev04posline)
// ASIA Stuff
var float asia_hi = na
var float asia_lo = na
var float asia_diff = na
var box asia_box = na
var line asia_hi_line = na
var line asia_lo_line = na
var line dev01negline_asia = na
var line dev02negline_asia = na
var line dev03negline_asia = na
var line dev04negline_asia = na
var line dev01posline_asia = na
var line dev02posline_asia = na
var line dev03posline_asia = na
var line dev04posline_asia = na
if SessionBegins(ASIA) and DOM
asia_hi := high
asia_lo := low
asia_diff := asia_hi - asia_lo
if ShowTSO
box.delete(asia_box )
line.delete(dev01posline_asia )
line.delete(dev01negline_asia )
line.delete(dev02posline_asia )
line.delete(dev02negline_asia )
line.delete(dev03posline_asia )
line.delete(dev03negline_asia )
line.delete(dev04posline_asia )
line.delete(dev04negline_asia )
if ShowASIA
asia_box := box.new(asiaOpenTime, asia_hi, asiaEndTime, asia_lo, color.new(ASIABoxCol,90), 1, line.style_solid, extend.none, xloc.bar_time, color.new(ASIABoxCol,90), txt1, size.auto, color.new(box_text_asia_col,80), text_wrap=text.wrap_auto)
if box_text_asia == false
box.set_text(asia_box, "")
if ShowDev and ShowASIA and bool_asia_dev
for i = 1 to DevCount by 1
if i == 1
dev01posline_asia := line.new(asiaOpenTime, asia_hi + asia_diff * i, asiaEndTime, asia_hi + asia_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev01negline_asia := line.new(asiaOpenTime, asia_hi - asia_diff * i, asiaEndTime, asia_lo - asia_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if i == 2
dev02posline_asia := line.new(asiaOpenTime, asia_hi + asia_diff * i, asiaEndTime, asia_lo + asia_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev02negline_asia := line.new(asiaOpenTime, asia_hi - asia_diff * i, asiaEndTime, asia_lo - asia_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if i == 3
dev03posline_asia := line.new(asiaOpenTime, asia_hi + asia_diff * i, asiaEndTime, asia_lo + asia_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev03negline_asia := line.new(asiaOpenTime, asia_hi - asia_diff * i, asiaEndTime, asia_lo - asia_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if i == 4
dev04posline_asia := line.new(asiaOpenTime, asia_hi + asia_diff * i, asiaEndTime, asia_lo + asia_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev04negline_asia := line.new(asiaOpenTime, asia_hi - asia_diff * i, asiaEndTime, asia_lo - asia_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
else if ASIATime
asia_hi := math.max(high, asia_hi)
asia_lo := math.min(low, asia_lo)
asia_diff := asia_hi - asia_lo
for i = 1 to DevCount by 1
if i == 1 and ShowDev
line.set_y1(dev01posline_asia, asia_hi + asia_diff * i)
line.set_y2(dev01posline_asia, asia_hi + asia_diff * i)
line.set_y1(dev01negline_asia, asia_lo - asia_diff * i)
line.set_y2(dev01negline_asia, asia_lo - asia_diff * i)
if i == 2 and ShowDev
line.set_y1(dev02posline_asia, asia_hi + asia_diff * i)
line.set_y2(dev02posline_asia, asia_hi + asia_diff * i)
line.set_y1(dev02negline_asia, asia_lo - asia_diff * i)
line.set_y2(dev02negline_asia, asia_lo - asia_diff * i)
if i == 3 and ShowDev
line.set_y1(dev03posline_asia, asia_hi + asia_diff * i)
line.set_y2(dev03posline_asia, asia_hi + asia_diff * i)
line.set_y1(dev03negline_asia, asia_lo - asia_diff * i)
line.set_y2(dev03negline_asia, asia_lo - asia_diff * i)
if i == 4 and ShowDev
line.set_y1(dev04posline_asia, asia_hi + asia_diff * i)
line.set_y2(dev04posline_asia, asia_hi + asia_diff * i)
line.set_y1(dev04negline_asia, asia_lo - asia_diff * i)
line.set_y2(dev04negline_asia, asia_lo - asia_diff * i)
if (asia_hi > asia_hi )
box.set_top(asia_box, asia_hi)
if (asia_lo < asia_lo )
box.set_bottom(asia_box, asia_lo)
if DevDirection == "Upside Only"
line.delete(dev01negline_asia)
line.delete(dev02negline_asia)
line.delete(dev03negline_asia)
line.delete(dev04negline_asia)
else if DevDirection == "Downside Only"
line.delete(dev01posline_asia)
line.delete(dev02posline_asia)
line.delete(dev03posline_asia)
line.delete(dev04posline_asia)
// FLOUT Stuff
var float flout_hi = na
var float flout_lo = na
var float flout_diff = na
var box floutbox = na
var line flout_hi_line = na
var line flout_lo_line = na
var line dev01negline_flout = na
var line dev02negline_flout = na
var line dev03negline_flout = na
var line dev04negline_flout = na
var line dev01posline_flout = na
var line dev02posline_flout = na
var line dev03posline_flout = na
var line dev04posline_flout = na
if SessionBegins(FLOUT) and DOM
flout_hi := high
flout_lo := low
flout_diff := flout_hi - flout_lo
if ShowTSO
box.delete(floutbox )
line.delete(dev01posline_flout )
line.delete(dev01negline_flout )
line.delete(dev02posline_flout )
line.delete(dev02negline_flout )
line.delete(dev03posline_flout )
line.delete(dev03negline_flout )
line.delete(dev04posline_flout )
line.delete(dev04negline_flout )
if ShowFLOUT
floutbox := box.new(floutOpenTime, flout_hi, floutEndTime, flout_lo, color.new(FLOUTBoxCol,90), 1, line.style_solid, extend.none, xloc.bar_time, color.new(FLOUTBoxCol,90), txt7, size.auto, color.new(box_text_flout_col,80), text_wrap=text.wrap_auto)
if dayofweek == dayofweek.friday
box.set_right(floutbox, floutOpenTime+201600000)
line.set_x2(flout_hi_line, floutOpenTime+201600000)
line.set_x2(flout_lo_line, floutOpenTime+201600000)
if box_text_cbdr == false
box.set_text(floutbox, "")
if ShowDev and ShowFLOUT and bool_flout_dev
for i = 0.5 to DevCount by 0.5
if i == 0.5
dev01posline_flout := line.new(floutOpenTime, flout_hi + flout_diff * i, floutEndTime, flout_hi + flout_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev01negline_flout := line.new(floutOpenTime, flout_hi - flout_diff * i, floutEndTime, flout_lo - flout_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if dayofweek == dayofweek.friday
line.set_x2(dev01posline_flout, floutOpenTime+201600000)
line.set_x2(dev01negline_flout, floutOpenTime+201600000)
if i == 1
dev02posline_flout := line.new(floutOpenTime, flout_hi + flout_diff * i, floutEndTime, flout_lo + flout_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev02negline_flout := line.new(floutOpenTime, flout_hi - flout_diff * i, floutEndTime, flout_lo - flout_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if dayofweek == dayofweek.friday
line.set_x2(dev02posline_flout, floutOpenTime+201600000)
line.set_x2(dev02negline_flout, floutOpenTime+201600000)
if i == 1.5
dev03posline_flout := line.new(floutOpenTime, flout_hi + flout_diff * i, floutEndTime, flout_lo + flout_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev03negline_flout := line.new(floutOpenTime, flout_hi - flout_diff * i, floutEndTime, flout_lo - flout_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if dayofweek == dayofweek.friday
line.set_x2(dev03posline_flout, floutOpenTime+201600000)
line.set_x2(dev03negline_flout, floutOpenTime+201600000)
if i == 2
dev04posline_flout := line.new(floutOpenTime, flout_hi + flout_diff * i, floutEndTime, flout_lo + flout_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
dev04negline_flout := line.new(floutOpenTime, flout_hi - flout_diff * i, floutEndTime, flout_lo - flout_diff * i, xloc=xloc.bar_time, color=DevLNCol, style=DEVLSS, width=DEVLW)
if dayofweek == dayofweek.friday
line.set_x2(dev04posline_flout, floutOpenTime+201600000)
line.set_x2(dev04negline_flout, floutOpenTime+201600000)
else if FLOUTTime
flout_hi := math.max(high, flout_hi)
flout_lo := math.min(low, flout_lo)
flout_diff := flout_hi - flout_lo
for i = 0.5 to DevCount by 0.5
if i == 0.5 and ShowDev
line.set_y1(dev01posline_flout, flout_hi + flout_diff * i)
line.set_y2(dev01posline_flout, flout_hi + flout_diff * i)
line.set_y1(dev01negline_flout, flout_lo - flout_diff * i)
line.set_y2(dev01negline_flout, flout_lo - flout_diff * i)
if i == 1 and ShowDev
line.set_y1(dev02posline_flout, flout_hi + flout_diff * i)
line.set_y2(
Macros ICT KillZones [TradingFinder] Times & Price Trading Setup🔵 Introduction
ICT Macros, developed by Michael Huddleston, also known as ICT (Inner Circle Trader), is a powerful trading tool designed to help traders identify the best trading opportunities during key time intervals like the London and New York trading sessions.
For traders aiming to capitalize on market volatility, liquidity shifts, and Fair Value Gaps (FVG), understanding and using these critical time zones can significantly improve trading outcomes.
In today’s highly competitive financial markets, identifying the moments when the market is seeking buy-side or sell-side liquidity, or filling price imbalances, is essential for maximizing profitability.
The ICT Macros indicator is built on the renowned ICT time and price theory, which enables traders to track and leverage key market dynamics such as breaks of highs and lows, imbalances, and liquidity hunts.
This indicator automatically detects crucial market times and optimizes strategies for traders by highlighting the specific moments when price movements are most likely to occur. A standout feature of ICT Macros is its automatic adjustment for Daylight Saving Time (DST), ensuring that traders remain synced with the correct session times.
This means you can rely on accurate market timing without the need for manual updates, allowing you to focus on capturing profitable trades during critical timeframes.
🔵 How to Use
The ICT Macros indicator helps you capitalize on trading opportunities during key market moments, particularly when the market is breaking highs or lows, filling Fair Value Gaps (FVG), or addressing imbalances. This indicator is particularly beneficial for traders who seek to identify liquidity, market volatility, and price imbalances.
🟣 Sessions
London Sessions
London Macro 1 :
UTC Time : 06:33 to 07:00
New York Time : 02:33 to 03:00
London Macro 2 :
UTC Time : 08:03 to 08:30
New York Time : 04:03 to 04:30
New York Sessions
New York Macro AM 1 :
UTC Time : 12:50 to 13:10
New York Time : 08:50 to 09:10
New York Macro AM 2 :
UTC Time : 13:50 to 14:10
New York Time : 09:50 to 10:10
New York Macro AM 3 :
UTC Time : 14:50 to 15:10
New York Time : 10:50 to 11:10
New York Lunch Macro :
UTC Time : 15:50 to 16:10
New York Time : 11:50 to 12:10
New York PM Macro :
UTC Time : 17:10 to 17:40
New York Time : 13:10 to 13:40
New York Last Hour Macro :
UTC Time : 19:15 to 19:45
New York Time : 15:15 to 15:45
These time intervals adjust automatically based on Daylight Saving Time (DST), helping traders to enter or exit trades during key market moments when price volatility is high.
Below are the main applications of this tool and how to incorporate it into your trading strategies :
🟣 Combining ICT Macros with Trading Strategies
The ICT Macros indicator can easily be used in conjunction with various trading strategies. Two well-known strategies that can be combined with this indicator include:
ICT 2022 Trading Model : This model is designed based on identifying market liquidity, structural price changes, and Fair Value Gaps (FVG). By using ICT Macros, you can identify the key time intervals when the market is seeking liquidity, filling imbalances, or breaking through important highs and lows, allowing you to enter or exit trades at the right moment.
Silver Bullet Strategy : This strategy, which is built around liquidity hunting and rapid price movements, can work more accurately with the help of ICT Macros. The indicator pinpoints precise liquidity times, helping traders take advantage of market shifts caused by filling Fair Value Gaps or correcting imbalances.
🟣 Capitalizing on Price Volatility During Key Times
Large market algorithms often seek liquidity or fill Fair Value Gaps (FVG) during the intervals marked by ICT Macros. These periods are when price volatility increases, and traders can use these moments to enter or exit trades.
For example, if sell-side liquidity is drained and the market fills an imbalance, the price might move toward buy-side liquidity. By identifying these moments, which may also involve breaking a previous high or low, you can leverage rapid market fluctuations to your advantage.
🟣 Identifying Liquidity and Price Imbalances
One of the important uses of ICT Macros is identifying points where the market is seeking liquidity and correcting imbalances. You can determine high or low liquidity levels in the market before each ICT Macro, as well as Fair Value Gaps (FVG) and price imbalances that need to be filled, using them to adjust your trading strategy. This capability allows you to manage trades based on liquidity shifts or imbalance corrections without needing a bias toward a specific direction.
🔵 Settings
The ICT Macros indicator offers various customization options, allowing users to tailor it to their specific needs. Below are the main settings:
Time Zone Mode : You can select one of the following options to define how time is displayed:
UTC : For traders who need to work with Universal Time.
Session Local Time : The local time corresponding to the London or New York markets.
Your Time Zone : You can specify your own time zone (e.g., "UTC-4:00").
Your Time Zone : If you choose "Your Time Zone," you can set your specific time zone. By default, this is set to UTC-4:00.
Show Range Time : This option allows you to display the time range of each session on the chart. If enabled, the exact start and end times of each interval are shown.
Show or Hide Time Ranges : Toggle on/off for visual clarity depending on user preference.
Custom Colors : Set distinct colors for each session, allowing users to personalize their chart based on their trading style.These settings allow you to adjust the key time intervals of each trading session to your preference and customize the time format according to your own needs.
🔵 Conclusion
The ICT Macros indicator is a powerful tool for traders, helping them to identify key time intervals where the market seeks liquidity or fills Fair Value Gaps (FVG), corrects imbalances, and breaks highs or lows. This tool is especially valuable for traders using liquidity-based strategies such as ICT 2022 or Silver Bullet.
One of the key features of this indicator is its support for Daylight Saving Time (DST), ensuring you are always in sync with the correct trading session timings without manual adjustments. This is particularly beneficial for traders operating across different time zones.
With ICT Macros, you can capitalize on crucial market opportunities during sensitive times, take advantage of imbalances, and enhance your trading strategies based on market volatility, liquidity shifts, and Fair Value Gaps.
Adv EMA Cloud v6 (ADX, Alerts)Summary:
This indicator provides a multi-faceted view of market trends using Exponential Moving Averages (EMAs) arranged in visually intuitive clouds, enhanced with an optional ADX-based range filter and configurable alerts for key market conditions. It aims to help traders quickly gauge trend alignment across short, medium, and long timeframes while filtering signals during potentially choppy market conditions.
Key Features:
Multiple EMAs: Displays 10-period (Fast), 20-period (Mid), and 50-period (Slow) EMAs.
Long-Term Trend Filter: Includes a 200-period EMA to provide context for the overall dominant trend direction.
Dual EMA Clouds:
Fast/Mid Cloud (10/20 EMA): Fills the area between the 10 and 20 EMAs. Defaults to Green when 10 > 20 (bullish short-term momentum) and Red when 10 < 20 (bearish short-term momentum).
Mid/Slow Cloud (20/50 EMA): Fills the area between the 20 and 50 EMAs. Defaults to Aqua when 20 > 50 (bullish mid-term trend) and Fuchsia when 20 < 50 (bearish mid-term trend).
Optional ADX Range Filter: Uses the Average Directional Index (ADX) to identify potentially non-trending or choppy markets. When enabled and ADX falls below a user-defined threshold, the EMA clouds will turn grey, visually warning that trend-following signals may be less reliable.
Configurable Alerts: Provides several built-in alert conditions using Pine Script's alertcondition function:
Confluence Condition: Triggers when a 10/20 EMA crossover occurs while both EMA clouds show alignment (both bullish/green/aqua or both bearish/red/fuchsia) and price respects the 200 EMA filter and the ADX filter indicates a trend (if filters are enabled).
MA Filter Cross: Triggers when price crosses above or below the 200 EMA filter line.
Full Alignment Start: Triggers on the first bar where full bullish or bearish alignment occurs (both clouds aligned + MA filter respected + ADX trending, if filters are enabled).
How It Works:
EMA Calculation: Standard Exponential Moving Averages are calculated for the 10, 20, 50, and 200 periods based on the closing price.
Cloud Creation: The fill() function visually shades the area between the 10 & 20 EMAs and the 20 & 50 EMAs.
Cloud Coloring: The color of each cloud is determined by the relationship between the two EMAs that define it (e.g., if EMA 10 is above EMA 20, the first cloud is bullish-colored).
ADX Filter Logic: The script calculates the ADX value. If the "Use ADX Trend Filter?" input is checked and the calculated ADX is below the specified "ADX Trend Threshold", the script considers the market potentially ranging.
ADX Visual Effect: During detected ranging periods (if the ADX filter is active), the plotCloud12Color and plotCloud23Color variables are assigned a neutral grey color instead of their normal bullish/bearish colors before being passed to the fill() function.
Alert Logic: Boolean variables track the specific conditions (crossovers, cloud alignment, filter positions, ADX state). The alertcondition() function creates triggerable alerts based on these pre-defined conditions.
Potential Interpretation (Not Financial Advice):
Trend Alignment: When both clouds share the same directional color (e.g., both bullish - Green & Aqua) and price is on the corresponding side of the 200 EMA filter, it may suggest a stronger, more aligned trend. Conversely, conflicting cloud colors may indicate indecision or transition.
Dynamic Support/Resistance: The EMA lines themselves (especially the 20, 50, and 200) can sometimes act as dynamic levels where price might react.
Range Warning: Greyed-out clouds (when ADX filter is enabled) serve as a visual warning that trend-based strategies might face increased difficulty or whipsaws.
Confluence Alerts: The specific confluence alerts signal moments where multiple conditions align (crossover + cloud agreement + filters), which some traders might view as higher-probability setups.
Customization:
All EMA lengths (10, 20, 50, 200) are adjustable via the Inputs menu.
The ADX length and threshold are configurable.
The MA Trend Filter and ADX Trend Filter can be independently enabled or disabled.
Disclaimer:
This indicator is provided for informational and educational purposes only. Trading financial markets involves significant risk. Past performance is not indicative of future results. Always conduct your own thorough analysis and consider your risk tolerance before making any trading decisions. This indicator should be used in conjunction with other analysis methods and tools. Do not trade based solely on the signals or visuals provided by this indicator.
Pulse of Cycle Oscillator"Pulse of Cycle" Oscillator: Logic and Usage
What Is It and How Does It Work?
The "Pulse of Cycle" is an oscillator that measures the cycles of price rises and falls, helping you spot overbought and oversold conditions. Unlike classic indicators, it doesn’t focus on how much the price moves but tracks its direction (up or down) like a "pulse." Here’s the logic:
Price Movement:
If the price rises compared to the previous bar, it adds +1.
If the price falls, it subtracts -1.
If the price stays the same, it adds 0.
Decay Factor: Each step, the previous value is multiplied by a factor (e.g., 0.9) to shrink it slightly. This keeps the oscillator from growing too big and focuses it on recent price action.
Signals: The oscillator moves around zero. When it crosses certain levels (e.g., 5 and 10), it warns you about overbought or oversold zones:
Weak Signal: Above ±5, the market might be stretching a bit.
Strong Signal: Above ±10, a reversal is more likely.
In short, it tracks the "rhythm" of price streaks (consecutive ups or downs) and signals when things might be getting extreme.
How It Looks on the Chart
Line: The oscillator moves around a zero line.
Colors:
Blue: Normal zone (between -5 and +5).
Orange: Weak overbought (+5 and up) or oversold (-5 and down).
Red: Strong overbought (+10 and up).
Lime: Strong oversold (-10 and down).
Threshold Lines: You’ll see lines at 0, ±5, and ±10 on the chart to show where you are.
How to Use It?
Here’s how to trade with this oscillator:
Buy Opportunity (Long Position):
When?: The oscillator drops below -5 (weak) or -10 (strong), then starts moving back toward zero. This suggests the price has hit a bottom and might rise.
Example: It falls to -12 (lime), then rises to -8. You could buy, expecting a bounce.
Tip: Wait for a green candle to confirm if you want to be safer.
Sell Opportunity (Short Position):
When?: The oscillator rises above +5 (weak) or +10 (strong), then starts dropping back toward zero. This indicates the price might have peaked and could fall.
Example: It hits +11 (red), then drops to +7. You could sell, expecting a decline.
Tip: Look for a red candle to confirm the turn.
Neutral Zone: If it’s between -5 and +5, the market is balanced. You can wait for a clearer signal.
Practical Steps to Use
Add to TradingView:
Paste the code into Pine Editor and click “Add to Chart.”
Adjust Settings (Optional):
Decay (0.9): Lower to 0.7 for faster response, raise to 0.95 for smoother movement.
Thresholds (5 and 10): Change them (e.g., 4 and 8) based on your market.
Watch Signals:
Follow the color changes and threshold crossings.
Set Alerts:
Right-click the oscillator > “Add Alert” to get notified on overbought/oversold signals.
Things to Watch Out For
Confirmation: Pair it with support/resistance levels or candlestick patterns for stronger signals.
Market Type: Works best in range-bound (sideways) markets. In strong trends (all up or down), signals might mislead.
Risk: Always use a stop loss—below the last low for buys, above the last high for sells.
Summary
The "Pulse of Cycle" is a simple yet powerful tool that tracks price movement streaks. Use it to catch reversals at strong signals (-10/+10) or get early warnings at weak signals (±5). The colors and lines on the chart make it easy to see when to act.
Checklist By TradeINskiChecklist By TradeINski
First Things First
This indicator is a supporting tool for trading momentum burst that is 2 Lynch setup by stock bee aka Pradeep Bonde.
Disclaimer: This indicator will not give any buy or sell signal. This is just a supporting tool to improve efficiency in my trading.
Apply Indicators and then open indicator settings and read the following simultaneously to understand better.
Default color settings are best suited for light themes. Which is also my personal preference.
Users can change most of the default options in settings according to their personal preference in settings.
When we open settings we can see 3 tabs that are {Inputs tab} {Style tab} {Visibility tab} each tab have its own options, Understand and use it accordingly.
Indicator will be only visible in the Daily time frame as its primary TF is daily. In the lower time frame nothing is plotted.
An indicator is plotted on an existing plane and overlaid on the existing plane.
Contents
My Checklist Lynch
Table Header Settings
Position
Size
Text Color
Background Color
“ON/OFF” Header “Text Box” “Info”
Table Content
Text Color
Background Color
“ON/OFF” R (1 - 10) “Text Box” T (1 - 10) “Text Box”
My Checklist - 2Lynch
This is the checklist I use while placing the trade just to make use of not missing anything based on predefined rules of the setup I trade.
2 - The stock should not be Up more than 2 days in a row, Minor movement can be acceptable.
L - The stock price movement should be linear, validation of established momentum
Y - Young trend in preference 1 - 3rd breakout from base
N - Narrow Range or -ve day before breakout
C - Consolidation should be narrow, linear and low volume. No more than one 4% breakdown.
H - The candle should close near high or at least 20% within when entered.
Table Headers Settings
Position - “Drop Down” with 9 different options which are self explanatory. Users can change the position of the table as per their preference.
Size - “Drop Down” with 6 different options which are self explanatory. Users can change the size of all the text printed in the table as per their preference.
Text Color - “Default Color is White” This setting is specifically only for header text. And users can change the text color of the header as per their preference.
Background Color - “Default Color is Blue” This setting is specifically only for header
background color. Users can change the background color of the header as per their preference.
“ON/OFF” Header “Text Box” “Info”
“Check Mark” - To show or hide the header that is “ON/OFF”.
“Header” - Heading of the table.
“Text Box” - Users can input as per their preference.
“Info” - Info symbol that shows short form and important note that is (Max 50 characteristics for all text boxes) .
Table Content
Text Color - “Default Color is White” This setting is specifically for table texts. And users can change the text color of the all content table texts as per their preference.
Background Color - “Default Color is black” This setting is specifically for content table texts background color. Users can change the background color of the header as per their preference.
“ON/OFF” R (1 - 10) “Text Box” T (1 - 10) “Text Box”
“Check Mark” - To show or hide the complete Row. Users have options and can change as per their preferences.
R (1-10) - “R” stands for Row and (1-10) is Number of rows available for users to enter text. Users have 10 different options.
“Text Box” - Place to enter text that users want to print on column 1 of the table.
T (1-10) - “T” stands for table and (1-10) is Number of text boxes available for users to enter text. Users have 10 different options.
“Text Box” - Place to enter text that users want to print on column 2 of the table.
Realtime FootprintThe purpose of this script is to gain a better understanding of the order flow by the footprint. To that end, i have added unusual features in addition to the standard features.
I use "Real Time 5D Profile by LucF" main engine to create basic footprint(profile type) and added some popular features and my favorites.
This script can only be used in realtime, because tradingview doesn't provide historical Bid/Ask date.
Bid/Ask date used this script are up/down ticks.
This script can only be used by time based chart (1m, 5m , 60m and daily etc)
This script use many labels and these are limited max 500, so you can't display many bars.
If you want to display foot print bars longer, turn off the unused sub-display function.
Default setting is footprint is 25 labels, IB count is 1, COT high and Ratio high is 1, COT low and Ratio low is 1 and Delta Box Ratio Volume is 1 , total 29.
plus UA , IB stripes , ladder fading mark use several labels.
///////// General Setting ///////////
Resets on Volume / Range bar
: If you want to use simple time based Resets on, please set Total Volume is 0.
Your timeframe is always the first condition. So if you set Total Volume is 1000, both conditions(Volume >= 1000 and your timeframe start next bar) must be met. (that is, new footprint bar doesn't start at when total volume = exactly 1000).
Ticks per row and Maximum row of Bar
: 1 is minimum size(tick). "Maximum row of Bar" decide the number of rows used in one footprint. 1 row is created from 1 label, so you need to reduce this number to display many footprints (Max label is 500).
Volume Filter and For Calculation and Display
: "Volume Filter" decide minimum size of using volume for this script.
"For Calculation and Display" is used to convert volume to an integer.
This script only use integer to make profile look better (I contained Bid number and Ask number in one row( one label) to saving labels. This require to make no difference in width by the number of digits and this script corresponds integers from 0 to 3 digits).
ex) Symbol average volume size is from 0.0001 to 0.001. You decide only use Volume >= 0.0005 by "Volume Filter".
Next, you convert volume to integer, by setting "For Calculation and Display" is 1000 (0.0005 * 1000 = 5).
If 0.00052 → 5.2 → 5, 0.00058 → 5.8 → 6 (Decimal numbers are rounded off)
This integer is used to all calculation in this script.
//////// Main Display ///////
Footprint, Total, Row Delta, Diagonal Delta and Profile
: "Footprint" display Ask and Bid per row. "Total" display Ask + Bid per row.
"Row Delta" display Ask - Bid per row. "Diagonal Delta" display Ask(row N) - Bid(row N -1) per row.
Profile display Total Volume(Ask + Bid) per row by using Block. Profile Block coloring are decided by Row Delta value(default: positive Row Delta (Ask > Bid) is greenish colors and negative Row Delta (Ask < Bid) is reddish colors.)
Volume per Profile Block, Row Imbalance Ratio and Delta Bull/Bear/Neutral Colors
: "Volume per Profile Block" decide one block contain how many total volume.
ex) When you set 20, Total volume 70 display 3 block.
The maximum number of blocks that can be used per low is 20.
So if you set 20, Total volume 400 is 20 blocks. total volume 800 is 20 blocks too.
"Row Imbalance Ratio" decide block coloring. The row imbalance is that the difference between Ask and Bid (row delta) is large.
default is x3, x2 and x1. The larger the difference, the brighter the color.
ex) Ask 30 Bid 10 is light green. Ask 20 Bid 10 is green. Ask 11 Bid 10 is dark green.
Ask 0 Bid 1 is light red. Ask 1 Bid 2 is red. ask 30 Bid 59 is dark green.
Ask 10 Bid 10 is neutral color(gray)
profile coloring is reflected same row's other elements(Ask, Bid, Total and Delta) too.
It's because one label can only use one text color.
/////// Sub Display ///////
Delta, total and Commitment of Traders
: "Delta" is total Ask - total Bid in one footprint bar. Total is total Ask + total Bid in one footprint bar.
"Commitment of traders" is variation of "Delta". COT High is reset to 0 when current highest is touched. COT Low is opposite.
Basic concept of Delta is to compare price with Delta. Ordinary, when price move up, delta is positive. Price move down is negative delta.
This is because market orders move price and market orders are counted by Delta (although this description is not exactly correct).
But, sometimes prices do not move even though many market orders are putting pressure on price , or conversely, price move strongly without many market orders.
This is key point. Big player absorb market orders by iceberg order(Subdivide large orders and pretend to be small limit orders.
Small limit orders look weak in the order book, but they are added each time you fill, so they are more powerful than they look.), so price don't move.
On the other hand, when the price is moving easily, smart players may be aiming to attract and counterattack to a better price for them.
It's more of a sport than science, and there's always no right response. Pay attention to the relationship between price, volume and delta.
ex) If COT Low is large negative value, it means many sell market orders is coming, but iceberg order is absorbing their attack at limit order.
you should not do buy entry, only this clue. but this is one of the hints.
"Delta, Box Ratio and Total texts is contained same label and its color are "Delta" coloring. Positive Delta is Delta Bull color(green),Negative Delta is Delta Bear Color
and Delta = 0 is Neutral Color(gray). When Delta direction and price direction are opposite is Delta Divergence Color(yellow).
I didn't add the cumulative volume delta because I prefer to display the CVD line on the price chart rather than the number.
Box Ratio , Box Ratio Divisor and Heavy Box Ratio Ratio
: This is not ordinary footprint features, but I like this concept so I added.
Box Ratio by Richard W. Arms is simple but useful tool. calculation is "total volume (one bar) divided by Bar range (highest - lowest)."
When Bull and bear are fighting fiercely this number become large, and then important price move happen.
I made average BR from something like 5 SMA and if current BR exceeds average BR x (Heavy Box Ratio Ratio), BR box mark will be filled.
Box Ratio Divisor is used to good looking display(BR multiplied by Box Ratio Divisor is rounded off and displayed as an integer)
Diagonal Imbalance Count , D IB Mark and D IB Stripes
: Diagonal Imbalance is defined by "Diagonal Imbalance Ratio".
ex) You set 2. When Ask(row N) 30 Bid(row N -1)10, it's 30 > 10*2, so positive Diagonal Imbalance.
When Ask(row N) 4 Bid(row N -1)9, it's 4*2 < 9, so negative Diagonal Imbalance.
This calculation does not use equals to avoid Ask(row N) 0 Bid(row N -1)0 became Diagonal Imbalance.
Ask(row N) 0 Bid(row N -1)0, it's 0 = 0*2, not Diagonal Imbalance. Ask(row N) 10 Bid(row N -1)5, it's 10 = 5*2, not Diagonal Imbalance.
"D IB Mark" emphasize Ask or Bid number which is dominant side(Winner of Diagonal Imbalance calculation), by under line.
"Diagonal Imbalance Count" compare Ask side D IB Mark to Bid side D IB Mark in one footprint.
Coloring depend on which is more aggressive side (it has many IB Mark) and When Aggressive direction and price direction are opposite is Delta Divergence Color(yellow).
"D IB Stripes" is a function that further emphasizes with an arrow Mark, when a DIB mark is added on the same side for three consecutive row. Three consecutive arrow is added at third row.
Unfinished Auction, Ratio Bounds and Ladder fading Mark
: "Unfinished Auction" emphasize highest or lowest row which has both Ask and Bid, by Delta Divergence Color(yellow) XXXXXX mark.
Unfinished Auction sometimes has magnet effect, price may touch and breakout at UA side in the future.
This concept is famous as profit taking target than entry decision.
But, I'm interested in the case that Big player make fake breakout at UA side and trapped retail traders, and then do reversal with retail traders stop-loss hunt.
Anyway, it's not stand alone signal.
"Ratio Bounds" gauge decrease of pressure at extreme price. Ratio Bounds High is number which second highest ask is divided by highest ask.
Ratio Bounds Low is number which second lowest bid is divided by lowest bid. The larger the number, the less momentum the price has.
ex)first footprint bar has Ratio Bounds Low 2, second footprint bar has RBL 4, third footprint bar has RBL 20.
This indicates that the bear's power is gradually diminishing.
"Ladder fading mark" emphasizes the decrease of the value in 3 consecutive row at extreme price. I added two type Marks.
Ask/Bid type(triangle Mark) is Ask/Bid values are decreasing of three consecutive row at extreme price.
Row Imbalance type(Diamond Mark) are row Imbalance values are decreasing of three consecutive row at extreme price.
ex)Third lowest Bid 40, second lowest Bid 10 and lowest Bid 5 have triangle up Mark. That is bear's power is gradually diminishing.
(This Mark only check Bid value at lowest price and Ask value at highest price).
Third highest row delta + 60, second highest row delta + 5, highest delta - 20 have diamond Mark. That is Bull's power is gradually diminishing.
Sub display use Delta colors at bottom of Sub display section.
////// Candle & POC /////////
candle and POC
: Ordinary, "POC" Point of Control is row of largest total volume, but this script'POC is volume weighted average.
This is because the regular POC was visually displayed by the profile ,and I was influenced LucF's ideas.
POC coloring is decided in relation to the previous POC. When current POC is higher than previous POC, color is UP Bar Color(green).
In the opposite case, Down Bar color is used.
POC Divergence Color is used when Current POC is up but current bar close is lower than open (Down price Bar),or in the opposite case.
POC coloring has option also highlight background by Delta Divergence Color(yellow). but bg color is displayed at your time frame current price bar not current footprint bar.
The basic explanation is over.
I add some image to promote understanding basic ideas.
EAOBS by MIGVersion 1
1. Strategy Overview Objective: Capitalize on breakout movements in Ethereum (ETH) price after the Asian open pre-market session (7:00 PM–7:59 PM EST) by identifying high and low prices during the session and trading breakouts above the high or below the low.
Timeframe: Any (script is timeframe-agnostic, but align with session timing).
Session: Pre-market session (7:00 PM–7:59 PM EST, adjustable for other time zones, e.g., 12:00 AM–12:59 AM GMT).
Risk-Reward Ratios (R:R): Targets range from 1.2:1 to 5.2:1, with a fixed stop loss.
Instrument: Ethereum (ETH/USD or ETH-based pairs).
2. Market Setup Session Monitoring: Monitor ETH price action during the pre-market session (7:00 PM–7:59 PM EST), which aligns with the Asian market open (e.g., 9:00 AM–9:59 AM JST).
The script tracks the highest high and lowest low during this session.
Breakout Triggers: Buy Signal: Price breaks above the session’s high after the session ends (7:59 PM EST).
Sell Signal: Price breaks below the session’s low after the session ends.
Visualization: The session is highlighted on the chart with a white background.
Horizontal lines are drawn at the session’s high and low, extended for 30 bars, along with take-profit (TP) and stop-loss (SL) levels.
3. Entry Rules Long (Buy) Entry: Enter a long position when the price breaks above the session’s high price after 7:59 PM EST.
Entry price: Just above the session high (e.g., add a small buffer, like 0.1–0.5%, to avoid false breakouts, depending on volatility).
Short (Sell) Entry: Enter a short position when the price breaks below the session’s low price after 7:59 PM EST.
Entry price: Just below the session low (e.g., subtract a small buffer, like 0.1–0.5%).
Confirmation: Use a candlestick close above/below the breakout level to confirm the entry.
Optionally, add volume confirmation or a momentum indicator (e.g., RSI or MACD) to filter out weak breakouts.
Position Size: Calculate position size based on risk tolerance (e.g., 1–2% of account per trade).
Risk is determined by the stop-loss distance (10 points, as defined in the script).
4. Exit Rules Take-Profit Levels (in points, based on script inputs):TP1: 12 points (1.2:1 R:R).
TP2: 22 points (2.2:1 R:R).
TP3: 32 points (3.2:1 R:R).
TP4: 42 points (4.2:1 R:R).
TP5: 52 points (5.2:1 R:R).
Example for Long: If session high is 3000, TP levels are 3012, 3022, 3032, 3042, 3052.
Example for Short: If session low is 2950, TP levels are 2938, 2928, 2918, 2908, 2898.
Strategy: Scale out of the position (e.g., close 20% at TP1, 20% at TP2, etc.) or take full profit at a preferred TP level based on market conditions.
Stop-Loss: Fixed at 10 points from the entry.
Long SL: Session high - 10 points (e.g., entry at 3000, SL at 2990).
Short SL: Session low + 10 points (e.g., entry at 2950, SL at 2960).
Trailing Stop (Optional):After reaching TP2 or TP3, consider trailing the stop to lock in profits (e.g., trail by 10–15 points below the current price).
5. Risk Management per Trade: Limit risk to 1–2% of your trading account per trade.
Calculate position size: Account Size × Risk % ÷ (Stop-Loss Distance × ETH Price per Point).
Example: $10,000 account, 1% risk = $100. If SL = 10 points and 1 point = $1, position size = $100 ÷ 10 = 0.1 ETH.
Daily Risk Limit: Cap daily losses at 3–5% of the account to avoid overtrading.
Maximum Exposure: Avoid taking both long and short positions simultaneously unless using separate accounts or strategies.
Volatility Consideration: Adjust position size during high-volatility periods (e.g., major news events like Ethereum upgrades or macroeconomic announcements).
6. Trade Management Monitoring :Watch for breakouts after 7:59 PM EST.
Monitor price action near TP and SL levels using alerts or manual checks.
Trade Duration: Breakout lines extend for 30 bars (script parameter). Close trades if no TP or SL is hit within this period, or reassess based on market conditions.
Adjustments: If the market shows strong momentum, consider holding beyond TP5 with a trailing stop.
If the breakout fails (e.g., price reverses before TP1), exit early to minimize losses.
7. Additional Considerations Market Conditions: The 7:00 PM–7:59 PM EST session aligns with the Asian market open (e.g., Tokyo Stock Exchange open at 9:00 AM JST), which may introduce higher volatility due to Asian trading activity.
Avoid trading during low-liquidity periods or extreme volatility (e.g., major crypto news).
Check for upcoming events (e.g., Ethereum network upgrades, ETF decisions) that could impact price.
Backtesting: Test the strategy on historical ETH data using the session high/low breakouts for the 7:00 PM–7:59 PM EST window to validate performance.
Adjust TP/SL levels based on backtest results if needed.
Broker and Fees: Use a low-fee crypto exchange (e.g., Binance, Kraken, Coinbase Pro) to maximize R:R.
Account for trading fees and slippage in your position sizing.
Time zone Adjustment: Adjust session time input for your time zone (e.g., "0000-0059" for GMT).
Ensure your trading platform’s clock aligns with the script’s time zone (default: America/New_York).
8. Example Trade Scenario: Session (7:00 PM–7:59 PM EST) records a high of 3050 and a low of 3000.
Long Trade: Entry: Price breaks above 3050 (e.g., enter at 3051).
TP Levels: 3063 (TP1), 3073 (TP2), 3083 (TP3), 3093 (TP4), 3103 (TP5).
SL: 3040 (3050 - 10).
Position Size: For a $10,000 account, 1% risk = $100. SL = 11 points ($11). Size = $100 ÷ 11 = ~0.09 ETH.
Short Trade: Entry: Price breaks below 3000 (e.g., enter at 2999).
TP Levels: 2987 (TP1), 2977 (TP2), 2967 (TP3), 2957 (TP4), 2947 (TP5).
SL: 3010 (3000 + 10).
Position Size: Same as above, ~0.09 ETH.
Execution: Set alerts for breakouts, enter with limit orders, and monitor TPs/SL.
9. Tools and Setup Platform: Use TradingView to implement the Pine Script and visualize breakout levels.
Alerts: Set price alerts for breakouts above the session high or below the session low after 7:59 PM EST.
Set alerts for TP and SL levels.
Chart Settings: Use a 1-minute or 5-minute chart for precise session tracking.
Overlay the script to see high/low lines, TP levels, and SL levels.
Optional Indicators: Add RSI (e.g., avoid overbought/oversold breakouts) or volume to confirm breakouts.
10. Risk Warnings Crypto Volatility: ETH is highly volatile; unexpected news can cause rapid price swings.
False Breakouts: Breakouts may fail, especially in low-volume sessions. Use confirmation signals.
Leverage: Avoid high leverage (e.g., >5x) to prevent liquidation during volatile moves.
Session Accuracy: Ensure correct session timing for your time zone to avoid misaligned entries.
11. Performance Tracking Journaling :Record each trade’s entry, exit, R:R, and outcome.
Note market conditions (e.g., trending, ranging, news-driven).
Review: Weekly: Assess win rate, average R:R, and adherence to the plan.
Monthly: Adjust TP/SL or session timing based on performance.
Institutional Volume Profile# Institutional Volume Profile (IVP) - Advanced Volume Analysis Indicator
## Overview
The Institutional Volume Profile (IVP) is a sophisticated technical analysis tool that combines traditional volume profile analysis with institutional volume detection algorithms. This indicator helps traders identify key price levels where significant institutional activity has occurred, providing insights into market structure and potential support/resistance zones.
## Key Features
### 🎯 Volume Profile Analysis
- **Point of Control (POC)**: Identifies the price level with the highest volume activity
- **Value Area**: Highlights the price range containing a specified percentage (default 70%) of total volume
- **Multi-Row Distribution**: Displays volume distribution across 10-50 price levels for detailed analysis
- **Customizable Period**: Analyze volume profiles over 10-500 bars
### 🏛️ Institutional Volume Detection
- **Pocket Pivot Volume (PPV)**: Detects bullish institutional buying when up-volume exceeds recent down-volume peaks
- **Pivot Negative Volume (PNV)**: Identifies bearish institutional selling when down-volume exceeds recent up-volume peaks
- **Accumulation Detection**: Spots potential accumulation phases with high volume and narrow price ranges
- **Distribution Analysis**: Identifies distribution patterns with high volume but minimal price movement
### 🎨 Visual Customization Options
- **Multiple Color Schemes**: Heat Map, Institutional, Monochrome, and Rainbow themes
- **Bar Styles**: Solid, Gradient, Outlined, and 3D Effect rendering
- **Volume Intensity Display**: Visual intensity based on volume magnitude
- **Flexible Positioning**: Left or right side profile placement
- **Current Price Highlighting**: Real-time price level indication
### 📊 Advanced Visual Features
- **Volume Labels**: Display volume amounts at key price levels
- **Gradient Effects**: Multi-step gradient rendering for enhanced visibility
- **3D Styling**: Shadow effects for professional appearance
- **Opacity Control**: Adjustable transparency (10-100%)
- **Border Customization**: Configurable border width and styling
## How It Works
### Volume Distribution Algorithm
The indicator analyzes each bar within the specified period and distributes its volume proportionally across the price levels it touches. This creates an accurate representation of where trading activity has been concentrated.
### Institutional Detection Logic
- **PPV Trigger**: Current up-bar volume > highest down-volume in lookback period + above volume MA
- **PNV Trigger**: Current down-bar volume > highest up-volume in lookback period + above volume MA
- **Accumulation**: High volume + narrow range + bullish close
- **Distribution**: Very high volume + minimal price movement
### Value Area Calculation
Starting from the POC, the algorithm expands both upward and downward, adding volume until reaching the specified percentage of total volume (default 70%).
## Configuration Parameters
### Profile Settings
- **Profile Period**: 10-500 bars (default: 50)
- **Number of Rows**: 10-50 levels (default: 24)
- **Profile Width**: 10-100% of screen (default: 30%)
- **Value Area %**: 50-90% (default: 70%)
### Institutional Analysis
- **PPV Lookback Days**: 5-20 periods (default: 10)
- **Volume MA Length**: 10-200 periods (default: 50)
- **Institutional Threshold**: 1.0-2.0x multiplier (default: 1.2)
### Visual Controls
- **Bar Style**: Solid, Gradient, Outlined, 3D Effect
- **Color Scheme**: Heat Map, Institutional, Monochrome, Rainbow
- **Profile Position**: Left or Right side
- **Opacity**: 10-100%
- **Show Labels**: Volume amount display toggle
## Interpretation Guide
### Volume Profile Elements
- **Thick Horizontal Bars**: High volume nodes (strong support/resistance)
- **Thin Horizontal Bars**: Low volume nodes (weak levels)
- **White Line (POC)**: Strongest support/resistance level
- **Blue Highlighted Area**: Value Area (fair value zone)
### Institutional Signals
- **Blue Triangles (PPV)**: Bullish institutional buying detected
- **Orange Triangles (PNV)**: Bearish institutional selling detected
- **Color-Coded Bars**: Different colors indicate institutional activity types
### Color Scheme Meanings
- **Heat Map**: Red (high volume) → Orange → Yellow → Gray (low volume)
- **Institutional**: Blue (PPV), Orange (PNV), Aqua (Accumulation), Yellow (Distribution)
- **Monochrome**: Grayscale intensity based on volume
- **Rainbow**: Color-coded by price level position
## Trading Applications
### Support and Resistance
- POC acts as dynamic support/resistance
- High volume nodes indicate strong price levels
- Low volume areas suggest potential breakout zones
### Institutional Activity
- PPV above Value Area: Strong bullish signal
- PNV below Value Area: Strong bearish signal
- Accumulation patterns: Potential upward breakouts
- Distribution patterns: Potential downward pressure
### Market Structure Analysis
- Value Area defines fair value range
- Profile shape indicates market sentiment
- Volume gaps suggest potential price targets
## Alert Conditions
- PPV Detection at current price level
- PNV Detection at current price level
- PPV above Value Area (strong bullish)
- PNV below Value Area (strong bearish)
## Best Practices
1. Use multiple timeframes for confirmation
2. Combine with price action analysis
3. Pay attention to volume context (above/below average)
4. Monitor institutional signals near key levels
5. Consider overall market conditions
## Technical Notes
- Maximum 500 boxes and 100 labels for optimal performance
- Real-time calculations update on each bar close
- Historical analysis uses complete bar data
- Compatible with all TradingView chart types and timeframes
---
*This indicator is designed for educational and informational purposes. Always combine with other analysis methods and risk management strategies.*
ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
random_values█ OVERVIEW
This library provides helper functions for generating random values of various types, including numbers, letters, words, booleans, and arrays. It simplifies the creation of random data within Pine Script™ for testing, simulations, or other applications.
█ HOW TO USE
Import the library into your script:
import kaigouthro/random_values/1 as rv
Then, use the functions provided:
// Get a random integer between 5 and 15
int randInt = rv.intVal(5, 15)
// Generate a random word with 8 characters
string randWord = rv.word(8)
// Create a boolean array with 5 elements
array randBoolArray = rv.boolArray(5)
// And other options! See below for details.
█ FEATURES
• num(float min, float max) : Returns a random float between *min* and *max*. (Internal helper function, not exported).
• letter() : Returns a random lowercase letter (a-z).
• word(int size = 0) : Returns a random word. *size* specifies the length (default: random length between 3 and 10).
• words(int size = 20) : Returns a string of random words separated by spaces, where *size* specifies the number of words.
• boolVal() : Returns a random boolean (true or false).
• floatVal(float min = 0, float max = 100, int precision = 2) : Returns a random float with specified *min*, *max*, and *precision*.
• intVal(int min = 1, int max = 100) : Returns a random integer between *min* and *max*.
• stringArray(int size = 0) : Returns an array of random words. *size* specifies the array length (default: random between 3 and 10).
• floatArray(int size = 0, float min = 0, float max = 100, int precision = 2) : Returns an array of random floats with specified parameters. *size* determines the array length.
• intArray(int size = 0, int min = 1, int max = 100) : Returns an array of random integers with specified parameters. *size* determines the array length.
• boolArray(int size = 0) : Returns an array of random booleans. *size* specifies the array length (default: random between 3 and 10).
█ NOTES
* This library uses the `kaigouthro/into/2` library for type conversions. Make sure it's available.
* Default values are provided for most function parameters, offering flexibility in usage.
█ LICENSE
This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
```
**Changes and Rationale:**
* **OVERVIEW:** Clearly states the library's purpose.
* **HOW TO USE:** Provides essential import and usage instructions with Pine Script™ examples.
* **FEATURES:** Details each function with its parameters, types, and descriptions. Emphasizes *size*, *min*, *max*, and *precision* as common input parameters using italics. Uses custom bulleted lists.
* **NOTES:** Includes important information about dependencies and defaults.
* **LICENSE:** Directly links to the license URL using the proper ` ` tag.
* **Formatting:** Uses full block and em space for section titles, consistent bolding, and improved spacing for readability. Removes unnecessary blank lines.
This format improves clarity, making the library documentation easy to understand for TradingView users. Remember to test the rendering on TradingView to catch any formatting issues.
Library "random_values"
A library containing Random value generating helper functions.
letter()
Random letter generator.
Returns: (string) A random lowercase letter.
word(size)
Random word generator.
Parameters:
size (int) : (int) The desired length of the word. If 0 or not provided, a random length between 3 and 10 is used.
Returns: (string) A random word.
words(size)
Random words generator.
Parameters:
size (int) : (int) The number of words to generate. If 0 or not provided, a random number between 3 and 10 is used.
Returns: (string) A string of random words separated by spaces.
boolVal()
Random boolean generator.
Returns: (bool) A random boolean value (true or false).
floatVal(min, max, precision)
Random float number generator.
Parameters:
min (float) : (float) The minimum float value. Defaults to 0.
max (float) : (float) The maximum float value. Defaults to 100.
precision (int) : (int) The number of decimal places. Defaults to 2.
Returns: (float) A random float number.
intVal(min, max)
Random integer number generator.
Parameters:
min (int) : (int) The minimum integer value. Defaults to 1.
max (int) : (int) The maximum integer value. Defaults to 100.
Returns: (int) A random integer number.
stringArray(size)
Random string array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
Returns: (array) An array of random words.
floatArray(size, min, max, precision)
Random float array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
min (float) : (float) The minimum float value. Defaults to 0.
max (float) : (float) The maximum float value. Defaults to 100.
precision (int) : (int) The number of decimal places. Defaults to 2.
Returns: (array) An array of random float numbers.
intArray(size, min, max)
Random integer array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
min (int) : (int) The minimum integer value. Defaults to 1.
max (int) : (int) The maximum integer value. Defaults to 100.
Returns: (array) An array of random integer numbers.
boolArray(size)
Random boolean array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
Returns: (array) An array of random boolean values.
Financials Score All Description of the "Financials Score All" Script
This Pine Script calculates a financial score for a specific stock, based on various financial metrics. The purpose is to provide a comprehensive numerical score that reflects the financial health of the stock. The score is calculated using multiple financial indicators, including profitability, valuation, debt management, and liquidity. Here’s a breakdown of what each part of the script does:
period = input.string('FQ', 'Period', options= )
FQ refers to Quarterly financial data.
FY refers to Fiscal Year financial data.
Financial Metrics:
The script uses various financial metrics to calculate the score. These are obtained via request.financial, which retrieves financial data for the stock from TradingView's database. Below are the metrics used:
opmar (Operating Margin): Measures the company's profitability as a percentage of revenue.
eps (Earnings Per Share): Represents the portion of a company's profit allocated to each outstanding share.
eps_ttm (Earnings Per Share – Trailing Twelve Months): EPS over the most recent 12 months.
pe_ratio (Price-to-Earnings Ratio): A measure of the price investors are willing to pay for a stock relative to its earnings.
pb_ratio (Price-to-Book Ratio): A valuation ratio comparing a company’s market value to its book value.
de_ratio (Debt-to-Equity Ratio): A measure of the company’s financial leverage, showing how much debt it has compared to shareholders' equity.
roe_pb (Return on Equity Adjusted to Book): Measures the company's profitability relative to its book value.
fcf_per_share (Free Cash Flow per Share): Represents the free cash flow available for dividends, debt reduction, or reinvestment, per share.
pfcf_ratio (Price-to-Free-Cash-Flow Ratio): A measure comparing a company’s market value to its free cash flow.
current_ratio (Current Ratio): A liquidity ratio that measures a company's ability to pay short-term obligations with its current assets.
RSI Calculation:
The script calculates the Relative Strength Index (RSI) for the stock using an 8-period lookback:
rsi = ta.rsi(close, 8)
Score Calculation:
The script calculates a total score by adding points based on the values of the financial metrics. Each metric is checked against a condition, and if the condition is met, the score is incremented:
If the Operating Margin (opmar) is greater than 20, the score is incremented by 20 points.
If Earnings Per Share (EPS) is positive, 10 points are added.
If the P/E ratio is between 0 and 20, 10 points are added.
If the P/B ratio is less than 3, 10 points are added.
If the Debt-to-Equity ratio is less than 0.8, 10 points are added.
If the Return on Equity Adjusted to Book is greater than 10, 10 points are added.
If the P/FCF ratio is between 0 and 15, 10 points are added.
If the Current Ratio is greater than 1.61, 10 points are added.
If the RSI is less than 35, 10 points are added.
The score is accumulated based on these conditions and stored in the total_score variable.
Displaying the Total Score:
Finally, the total score is plotted on the chart:
Summary of How It Works:
This script calculates a financial score for a stock using a variety of financial indicators. Each metric has a threshold, and when the stock meets certain criteria (for example, a good operating margin, a healthy debt-to-equity ratio, or a low P/E ratio), points are added to the overall score. The result is a single numerical value that reflects the financial health of the stock.
This score can help traders or investors identify companies with strong financials, or serve as a comparison tool between different stocks based on their financial health.
Generally >60 is the best stocks for med and long term trades
ICT Macros [LuxAlgo]The ICT Macros indicator aims to highlight & classify ICT Macros, which are time intervals where algorithmic trading takes place to interact with existing liquidity or to create new liquidity.
🔶 SETTINGS
🔹 Macros
Macro Time options (such as '09:50 AM 10:10'): Enable specific macro display.
Top Line , Mid Line , Bottom Line and Extending Lines options: Controls the lines for the specific macro.
🔹 Macro Classification
Length : A length to detect Market Structure Brakes and classify macro type based on detection.
Swing Area : Swing or Liquidity Area selection, highest/lowest of the wick or the candle bodies.
Accumulation , Manipulation and Expansion color options for the classified macros.
🔹 Others
Macro Texts : Controls both the size and the visibility of the macro text.
Alert Macro Times in Advance (Minutes) : This option will plot a vertical line presenting the start of the next macro time. The line will not appear all the time, but it will be there based on remaining minutes specified in the option.
Daylight Saving Time (DST) : Adjust time appropriate to Daylight Saving Time of the specific region.
🔶 USAGE
A macro is a way to automate a task or procedure which you perform on a regular basis.
In the context of ICT's teachings, a macro is a small program or set of instructions that unfolds within an algorithm, which influences price movements in the market. These macros operate at specific times and can be related to price runs from one level to another or certain market behaviors during specific time intervals. They help traders anticipate market movements and potential setups during specific time intervals.
To trade these effectively, it is important to understand the time of day when certain macros come into play, and it is strongly advised to introduce the concept of liquidity in your analysis.
Macros can be classified into three categories where the Macro classification is calculated based on the Market Structure prior to macro and the Market Structure during the macro duration:
Manipulation Macro
Manipulation macros are characterized by liquidity being swept both on the buyside and sellside.
Expansion Macro
Expansion macros are characterized by liquidity being swept only on the buyside or sellside. Prices within these macros are highly correlated with the overall trend.
Accumulation Macro
Accumulation macros are characterized by an accumulation of liquidity. Prices within these macros tend to range.
The script returns the maximum/minimum price values reached during the macro interval alongside the average between the maximum/minimum and extends them until a new macro starts. These levels can act as supports and resistances.
🔶 DETAILS
All required data for the macro detection and classification is retrieved using 1 minute data sets, this includes candles as well as pivot/swing highs and lows. This approach guarantees the visually presented objects are same (same highs/lows) on higher timeframes as well as the macro classification remain same as it is in 1 min charts.
8 Macros can be displayed by the script (4 are enabled by default):
02:33 AM 03:00 London Macro
04:03 AM 04:30 London Macro
08:50 AM 09:10 New York Macro
09:50 AM 10:10 New York Macro
10:50 AM 11:10 New York Macro
11:50 AM 12:10 New York Launch Macro
13:10 PM 13:40 New York Macro
15:15 PM 15:45 New York Macro
🔶 ALERTS
When an alert is configured, the user will have the ability to be notified in advance of the next Macro time, where the value specified in 'Alert Macro Times in Advance (Minutes)' option indicates how early to be notified.
🔶 LIMITATIONS
The script is supported on 1 min, 3 mins and 5 mins charts.
🔶 RELATED SCRIPTS
ATR Table 2.0ATR Table 2.0
This script was created in order to display a table that "calculates" how far the price can go on the current day .
The script is a table with 3 lines that calculates:
First Line - Day TR: The True Range of the current day ( - , including an Opening GAP if it exists);
Second Line - 10 Day ATR: The Average True Range of the asset (including Opening GAPs) for the last 10 days;
Third LIne - Range Consumed: How much of the 10 Day ATR it was consumed on the current day.
Example of how to use the information on the table and the understanding of it's purpose:
1) Supose you are day trading an asset that, during the last 10 days, have moved around $1.00 a day - This is the 10 Day ATR.
2) On this day, after 2 hours of the opening market, the price have already moved $0.50 (supose that it has moved $0.30 up and $0.35 down from the close of the prior day and the price is now near the close of the prior day).
3) In this situation, knowing that the price often moves around $1.00 a day, and knowing that it already moved $0.65 ($0.30 up and $0.35 down based on the close of the prior day), you may pay attention when the price breaksthrough the max or the min of the day, cause it can still move $0.35 in that direction ($1.00 - $0.65).
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ATR Table 2.0
Esse script foi criado para disponibilizar uma tabela que "calcula" quanto o preço pode andar ainda no dia em questão .
O script é uma tabela com 3 linhas que calcula:
Primeira Linha - TR do Dia: O Range Verdadeira do dia em questão ( - , incluindo GAP de Abertura se for o caso);
Segunda Linha - ATR de 10 Dias: A média do Range Verdadeira do ativo (incluindo GAPs de abertura) dos últimos 10 dias;
Terceira Linha - Range Consumido: O quanto do ATR de 10dias já foi consumido no dia em questão.
Exemplo de como usar essa informação na tabela e o entendimento do seu propósito:
1) Suponha que você está realizando day trade de um ativo que, durante os últimos 10 dias, se move em torno de $1.00 por dia. Esse é o ATR de 10 dias.
2) Nesse dia, após 2 horas da abertura do pregão, o preço já se moveu $.050 (suponhamos que ele tenha se moveu $0.30 para cima e $0.35 para baixo a partir do fechamento do dia anterior e agora o preço está próximo do fechamento do dia anterior).
3) Nessa situação, sabendo que o preço se move por volta de $1.00 por dia, e sabendo que ele já se moveu $0.65 ($0.30 pra cima e $0.35 pra baixo a partir do fechamento do dia anterior), você deve se atentar para quando o preço romper a máxima ou a mínima do dia, pois ele pode se mover ainda $.035 na direção do rompimento ($1.00 - $0.65).
Liquid Pulse Liquid Pulse by Dskyz (DAFE) Trading Systems
Liquid Pulse is a trading algo built by Dskyz (DAFE) Trading Systems for futures markets like NQ1!, designed to snag high-probability trades with tight risk control. it fuses a confluence system—VWAP, MACD, ADX, volume, and liquidity sweeps—with a trade scoring setup, daily limits, and VIX pauses to dodge wild volatility. visuals include simple signals, VWAP bands, and a dashboard with stats.
Core Components for Liquid Pulse
Volume Sensitivity (volumeSensitivity) controls how much volume spikes matter for entries. options: 'Low', 'Medium', 'High' default: 'High' (catches small spikes, good for active markets) tweak it: 'Low' for calm markets, 'High' for chaos.
MACD Speed (macdSpeed) sets the MACD’s pace for momentum. options: 'Fast', 'Medium', 'Slow' default: 'Medium' (solid balance) tweak it: 'Fast' for scalping, 'Slow' for swings.
Daily Trade Limit (dailyTradeLimit) caps trades per day to keep risk in check. range: 1 to 30 default: 20 tweak it: 5-10 for safety, 20-30 for action.
Number of Contracts (numContracts) sets position size. range: 1 to 20 default: 4 tweak it: up for big accounts, down for small.
VIX Pause Level (vixPauseLevel) stops trading if VIX gets too hot. range: 10 to 80 default: 39.0 tweak it: 30 to avoid volatility, 50 to ride it.
Min Confluence Conditions (minConditions) sets how many signals must align. range: 1 to 5 default: 2 tweak it: 3-4 for strict, 1-2 for more trades.
Min Trade Score (Longs/Shorts) (minTradeScoreLongs/minTradeScoreShorts) filters trade quality. longs range: 0 to 100 default: 73 shorts range: 0 to 100 default: 75 tweak it: 80-90 for quality, 60-70 for volume.
Liquidity Sweep Strength (sweepStrength) gauges breakouts. range: 0.1 to 1.0 default: 0.5 tweak it: 0.7-1.0 for strong moves, 0.3-0.5 for small.
ADX Trend Threshold (adxTrendThreshold) confirms trends. range: 10 to 100 default: 41 tweak it: 40-50 for trends, 30-35 for weak ones.
ADX Chop Threshold (adxChopThreshold) avoids chop. range: 5 to 50 default: 20 tweak it: 15-20 to dodge chop, 25-30 to loosen.
VWAP Timeframe (vwapTimeframe) sets VWAP period. options: '15', '30', '60', '240', 'D' default: '60' (1-hour) tweak it: 60 for day, 240 for swing, D for long.
Take Profit Ticks (Longs/Shorts) (takeProfitTicksLongs/takeProfitTicksShorts) sets profit targets. longs range: 5 to 100 default: 25.0 shorts range: 5 to 100 default: 20.0 tweak it: 30-50 for trends, 10-20 for chop.
Max Profit Ticks (maxProfitTicks) caps max gain. range: 10 to 200 default: 60.0 tweak it: 80-100 for big moves, 40-60 for tight.
Min Profit Ticks to Trail (minProfitTicksTrail) triggers trailing. range: 1 to 50 default: 7.0 tweak it: 10-15 for big gains, 5-7 for quick locks.
Trailing Stop Ticks (trailTicks) sets trail distance. range: 1 to 50 default: 5.0 tweak it: 8-10 for room, 3-5 for fast locks.
Trailing Offset Ticks (trailOffsetTicks) sets trail offset. range: 1 to 20 default: 2.0 tweak it: 1-2 for tight, 5-10 for loose.
ATR Period (atrPeriod) measures volatility. range: 5 to 50 default: 9 tweak it: 14-20 for smooth, 5-9 for reactive.
Hardcoded Settings volLookback: 30 ('Low'), 20 ('Medium'), 11 ('High') volThreshold: 1.5 ('Low'), 1.8 ('Medium'), 2 ('High') swingLen: 5
Execution Logic Overview trades trigger when confluence conditions align, entering long or short with set position sizes. exits use dynamic take-profits, trailing stops after a profit threshold, hard stops via ATR, and a time stop after 100 bars.
Features Multi-Signal Confluence: needs VWAP, MACD, volume, sweeps, and ADX to line up.
Risk Control: ATR-based stops (capped 15 ticks), take-profits (scaled by volatility), and trails.
Market Filters: VIX pause, ADX trend/chop checks, volatility gates. Dashboard: shows scores, VIX, ADX, P/L, win %, streak.
Visuals Simple signals (green up triangles for longs, red down for shorts) and VWAP bands with glow. info table (bottom right) with MACD momentum. dashboard (top right) with stats.
Chart and Backtest:
NQ1! futures, 5-minute chart. works best in trending, volatile conditions. tweak inputs for other markets—test thoroughly.
Backtesting: NQ1! Frame: Jan 19, 2025, 09:00 — May 02, 2025, 16:00 Slippage: 3 Commission: $4.60
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Disclaimer this is for education only. past results don’t predict future wins. trading’s risky—only use money you can lose. backtest and validate before going live. (expect moderators to nitpick some random chart symbol rule—i’ll fix and repost if they pull it.)
About the Author Dskyz (DAFE) Trading Systems crafts killer trading algos. Liquid Pulse is pure research and grit, built for smart, bold trading. Use it with discipline. Use it with clarity. Trade smarter. I’ll keep dropping badass strategies ‘til i build a brand or someone signs me up.
2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
RSI Full Forecast [Titans_Invest]RSI Full Forecast
Get ready to experience the ultimate evolution of RSI-based indicators – the RSI Full Forecast, a boosted and even smarter version of the already powerful: RSI Forecast
Now featuring over 40 additional entry conditions (forecasts), this indicator redefines the way you view the market.
AI-Powered RSI Forecasting:
Using advanced linear regression with the least squares method – a solid foundation for machine learning - the RSI Full Forecast enables you to predict future RSI behavior with impressive accuracy.
But that’s not all: this new version also lets you monitor future crossovers between the RSI and the MA RSI, delivering early and strategic signals that go far beyond traditional analysis.
You’ll be able to monitor future crossovers up to 20 bars ahead, giving you an even broader and more precise view of market movements.
See the Future, Now:
• Track upcoming RSI & RSI MA crossovers in advance.
• Identify potential reversal zones before price reacts.
• Uncover statistical behavior patterns that would normally go unnoticed.
40+ Intelligent Conditions:
The new layer of conditions is designed to detect multiple high-probability scenarios based on historical patterns and predictive modeling. Each additional forecast is a window into the price's future, powered by robust mathematics and advanced algorithmic logic.
Full Customization:
All parameters can be tailored to fit your strategy – from smoothing periods to prediction sensitivity. You have complete control to turn raw data into smart decisions.
Innovative, Accurate, Unique:
This isn’t just an upgrade. It’s a quantum leap in technical analysis.
RSI Full Forecast is the first of its kind: an indicator that blends statistical analysis, machine learning, and visual design to create a true real-time predictive system.
⯁ SCIENTIFIC BASIS LINEAR REGRESSION
Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥.
The general formula for a simple linear regression is given by:
y = β₀ + β₁x + ε
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
y = is the predicted variable (e.g. future value of RSI)
x = is the explanatory variable (e.g. time or bar index)
β0 = is the intercept (value of 𝑦 when 𝑥 = 0)
𝛽1 = is the slope of the line (rate of change)
ε = is the random error term
The goal is to estimate the coefficients 𝛽0 and 𝛽1 so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares.
⯁ LEAST SQUARES ESTIMATION
To minimize the error between predicted and observed values, we use the following formulas:
β₁ = /
β₀ = ȳ - β₁x̄
Where:
∑ = sum
x̄ = mean of x
ȳ = mean of y
x_i, y_i = individual values of the variables.
Where:
x_i and y_i are the means of the independent and dependent variables, respectively.
i ranges from 1 to n, the number of observations.
These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity.
⯁ LINEAR REGRESSION IN MACHINE LEARNING
Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies.
By applying this model to the RSI, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis.
⯁ VISUAL INTERPRETATION
Imagine an RSI time series like this:
Time →
RSI →
The regression line will smooth these values and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted RSI, which can be crossed with the actual RSI to generate more intelligent signals.
⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED
Linear Regression Models the relationship between variables using a straight line.
Least Squares Minimizes the sum of squared errors between prediction and reality.
Time Series Forecasting Estimates future values based on historical data.
Supervised Learning Trains models to predict outputs from known inputs.
Statistical Smoothing Reduces noise and reveals underlying trends.
⯁ WHY THIS INDICATOR IS REVOLUTIONARY
Scientifically-based: Based on statistical theory and mathematical inference.
Unprecedented: First public RSI with least squares predictive modeling.
Intelligent: Built with machine learning logic.
Practical: Generates forward-thinking signals.
Customizable: Flexible for any trading strategy.
⯁ CONCLUSION
By combining RSI with linear regression, this indicator allows a trader to predict market momentum, not just follow it.
RSI Full Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology.
⯁ Example of simple linear regression, which has one independent variable:
⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ).
⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values using Matlab:
⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables.
⯁ The result of fitting a set of data points with a quadratic function:
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🔮 Linear Regression: PineScript Technical Parameters 🔮
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Forecast Types:
• Flat: Assumes prices will remain the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
ta.linreg (built-in function)
Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values calculated using the least squares method on the source series.
Syntax:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset: Offset.
• return: Linear regression curve.
This function has been cleverly applied to the RSI, making it capable of projecting future values based on past statistical trends.
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⯁ WHAT IS THE RSI❓
The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend.
⯁ HOW TO USE THE RSI❓
The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:
• Overbought: When the RSI is above 70, indicating that the asset may be overbought.
• Oversold: When the RSI is below 30, indicating that the asset may be oversold.
• Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions.
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⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📈 RSI Conditions:
🔹 RSI > Upper
🔹 RSI < Upper
🔹 RSI > Lower
🔹 RSI < Lower
🔹 RSI > Middle
🔹 RSI < Middle
🔹 RSI > MA
🔹 RSI < MA
📈 MA Conditions:
🔹 MA > Upper
🔹 MA < Upper
🔹 MA > Lower
🔹 MA < Lower
📈 Crossovers:
🔹 RSI (Crossover) Upper
🔹 RSI (Crossunder) Upper
🔹 RSI (Crossover) Lower
🔹 RSI (Crossunder) Lower
🔹 RSI (Crossover) Middle
🔹 RSI (Crossunder) Middle
🔹 RSI (Crossover) MA
🔹 RSI (Crossunder) MA
🔹 MA (Crossover) Upper
🔹 MA (Crossunder) Upper
🔹 MA (Crossover) Lower
🔹 MA (Crossunder) Lower
📈 RSI Divergences:
🔹 RSI Divergence Bull
🔹 RSI Divergence Bear
📈 RSI Forecast:
🔹 RSI (Crossover) MA Forecast
🔹 RSI (Crossunder) MA Forecast
🔹 RSI Forecast 1 > MA Forecast 1
🔹 RSI Forecast 1 < MA Forecast 1
🔹 RSI Forecast 2 > MA Forecast 2
🔹 RSI Forecast 2 < MA Forecast 2
🔹 RSI Forecast 3 > MA Forecast 3
🔹 RSI Forecast 3 < MA Forecast 3
🔹 RSI Forecast 4 > MA Forecast 4
🔹 RSI Forecast 4 < MA Forecast 4
🔹 RSI Forecast 5 > MA Forecast 5
🔹 RSI Forecast 5 < MA Forecast 5
🔹 RSI Forecast 6 > MA Forecast 6
🔹 RSI Forecast 6 < MA Forecast 6
🔹 RSI Forecast 7 > MA Forecast 7
🔹 RSI Forecast 7 < MA Forecast 7
🔹 RSI Forecast 8 > MA Forecast 8
🔹 RSI Forecast 8 < MA Forecast 8
🔹 RSI Forecast 9 > MA Forecast 9
🔹 RSI Forecast 9 < MA Forecast 9
🔹 RSI Forecast 10 > MA Forecast 10
🔹 RSI Forecast 10 < MA Forecast 10
🔹 RSI Forecast 11 > MA Forecast 11
🔹 RSI Forecast 11 < MA Forecast 11
🔹 RSI Forecast 12 > MA Forecast 12
🔹 RSI Forecast 12 < MA Forecast 12
🔹 RSI Forecast 13 > MA Forecast 13
🔹 RSI Forecast 13 < MA Forecast 13
🔹 RSI Forecast 14 > MA Forecast 14
🔹 RSI Forecast 14 < MA Forecast 14
🔹 RSI Forecast 15 > MA Forecast 15
🔹 RSI Forecast 15 < MA Forecast 15
🔹 RSI Forecast 16 > MA Forecast 16
🔹 RSI Forecast 16 < MA Forecast 16
🔹 RSI Forecast 17 > MA Forecast 17
🔹 RSI Forecast 17 < MA Forecast 17
🔹 RSI Forecast 18 > MA Forecast 18
🔹 RSI Forecast 18 < MA Forecast 18
🔹 RSI Forecast 19 > MA Forecast 19
🔹 RSI Forecast 19 < MA Forecast 19
🔹 RSI Forecast 20 > MA Forecast 20
🔹 RSI Forecast 20 < MA Forecast 20
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🔸 CONDITIONS TO SELL 📉
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📉 RSI Conditions:
🔸 RSI > Upper
🔸 RSI < Upper
🔸 RSI > Lower
🔸 RSI < Lower
🔸 RSI > Middle
🔸 RSI < Middle
🔸 RSI > MA
🔸 RSI < MA
📉 MA Conditions:
🔸 MA > Upper
🔸 MA < Upper
🔸 MA > Lower
🔸 MA < Lower
📉 Crossovers:
🔸 RSI (Crossover) Upper
🔸 RSI (Crossunder) Upper
🔸 RSI (Crossover) Lower
🔸 RSI (Crossunder) Lower
🔸 RSI (Crossover) Middle
🔸 RSI (Crossunder) Middle
🔸 RSI (Crossover) MA
🔸 RSI (Crossunder) MA
🔸 MA (Crossover) Upper
🔸 MA (Crossunder) Upper
🔸 MA (Crossover) Lower
🔸 MA (Crossunder) Lower
📉 RSI Divergences:
🔸 RSI Divergence Bull
🔸 RSI Divergence Bear
📉 RSI Forecast:
🔸 RSI (Crossover) MA Forecast
🔸 RSI (Crossunder) MA Forecast
🔸 RSI Forecast 1 > MA Forecast 1
🔸 RSI Forecast 1 < MA Forecast 1
🔸 RSI Forecast 2 > MA Forecast 2
🔸 RSI Forecast 2 < MA Forecast 2
🔸 RSI Forecast 3 > MA Forecast 3
🔸 RSI Forecast 3 < MA Forecast 3
🔸 RSI Forecast 4 > MA Forecast 4
🔸 RSI Forecast 4 < MA Forecast 4
🔸 RSI Forecast 5 > MA Forecast 5
🔸 RSI Forecast 5 < MA Forecast 5
🔸 RSI Forecast 6 > MA Forecast 6
🔸 RSI Forecast 6 < MA Forecast 6
🔸 RSI Forecast 7 > MA Forecast 7
🔸 RSI Forecast 7 < MA Forecast 7
🔸 RSI Forecast 8 > MA Forecast 8
🔸 RSI Forecast 8 < MA Forecast 8
🔸 RSI Forecast 9 > MA Forecast 9
🔸 RSI Forecast 9 < MA Forecast 9
🔸 RSI Forecast 10 > MA Forecast 10
🔸 RSI Forecast 10 < MA Forecast 10
🔸 RSI Forecast 11 > MA Forecast 11
🔸 RSI Forecast 11 < MA Forecast 11
🔸 RSI Forecast 12 > MA Forecast 12
🔸 RSI Forecast 12 < MA Forecast 12
🔸 RSI Forecast 13 > MA Forecast 13
🔸 RSI Forecast 13 < MA Forecast 13
🔸 RSI Forecast 14 > MA Forecast 14
🔸 RSI Forecast 14 < MA Forecast 14
🔸 RSI Forecast 15 > MA Forecast 15
🔸 RSI Forecast 15 < MA Forecast 15
🔸 RSI Forecast 16 > MA Forecast 16
🔸 RSI Forecast 16 < MA Forecast 16
🔸 RSI Forecast 17 > MA Forecast 17
🔸 RSI Forecast 17 < MA Forecast 17
🔸 RSI Forecast 18 > MA Forecast 18
🔸 RSI Forecast 18 < MA Forecast 18
🔸 RSI Forecast 19 > MA Forecast 19
🔸 RSI Forecast 19 < MA Forecast 19
🔸 RSI Forecast 20 > MA Forecast 20
🔸 RSI Forecast 20 < MA Forecast 20
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
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Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
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📜 SCRIPT : RSI Full Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
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o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal:
Yearly Quarters = 4 quarters of three months each.
Monthly Quarters = 4 quarters of one week each.
Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function.
Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day.
Sessions Quarters = 4 quarters of 90 minutes each.
90 Minute Quarters = 4 quarters of 22.5 minutes each.
Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each:
Q1 - January, February, March.
Q2 - April, May, June (True Open, April Open).
Q3 - July, August, September.
Q4 - October, November, December.
S&P 500 E-mini Futures (daily candles) — Monthly Cycle.
Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day):
Q1 - Week 1: first Monday of the month.
Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price).
Q3 - Week 3: third Monday of the month.
Q4 - Week 4: fourth Monday of the month.
S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle.
Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action:
Q1 - Monday.
Q2 - Tuesday (True Open, Daily Candle Open Price).
Q3 - Wednesday.
Q4 - Thursday.
S&P 500 E-mini Futures (1 hour candles) — Daily Cycle.
Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity:
Q1 - 18:00 - 00:00 Asia.
Q2 - 00:00 - 06:00 London (True Open).
Q3 - 06:00 - 12:00 NY AM.
Q4 - 12:00 - 18:00 NY PM.
S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle.
6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT):
Asian Session
Q1 - 18:00 - 19:30
Q2 - 19:30 - 21:00 (True Open)
Q3 - 21:00 - 22:30
Q4 - 22:30 - 00:00
London Session
Q1 - 00:00 - 01:30
Q2 - 01:30 - 03:00 (True Open)
Q3 - 03:00 - 04:30
Q4 - 04:30 - 06:00
NY AM Session
Q1 - 06:00 - 07:30
Q2 - 07:30 - 09:00 (True Open)
Q3 - 09:00 - 10:30
Q4 - 10:30 - 12:00
NY PM Session
Q1 - 12:00 - 13:30
Q2 - 13:30 - 15:00 (True Open)
Q3 - 15:00 - 16:30
Q4 - 16:30 - 18:00
S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle.
Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters:
Asian Session
Q1/1 18:00:00 - 18:22:30
Q2 18:22:30 - 18:45:00
Q3 18:45:00 - 19:07:30
Q4 19:07:30 - 19:30:00
Q2/1 19:30:00 - 19:52:30 (True Session Open)
Q2/2 19:52:30 - 20:15:00
Q2/3 20:15:00 - 20:37:30
Q2/4 20:37:30 - 21:00:00
Q3/1 21:00:00 - 21:23:30
etc. 21:23:30 - 21:45:00
London Session
00:00:00 - 00:22:30 (True Daily Open)
00:22:30 - 00:45:00
00:45:00 - 01:07:30
01:07:30 - 01:30:00
01:30:00 - 01:52:30 (True Session Open)
01:52:30 - 02:15:00
02:15:00 - 02:37:30
02:37:30 - 03:00:00
03:00:00 - 03:22:30
03:22:30 - 03:45:00
03:45:00 - 04:07:30
04:07:30 - 04:30:00
04:30:00 - 04:52:30
04:52:30 - 05:15:00
05:15:00 - 05:37:30
05:37:30 - 06:00:00
New York AM Session
06:00:00 - 06:22:30
06:22:30 - 06:45:00
06:45:00 - 07:07:30
07:07:30 - 07:30:00
07:30:00 - 07:52:30 (True Session Open)
07:52:30 - 08:15:00
08:15:00 - 08:37:30
08:37:30 - 09:00:00
09:00:00 - 09:22:30
09:22:30 - 09:45:00
09:45:00 - 10:07:30
10:07:30 - 10:30:00
10:30:00 - 10:52:30
10:52:30 - 11:15:00
11:15:00 - 11:37:30
11:37:30 - 12:00:00
New York PM Session
12:00:00 - 12:22:30
12:22:30 - 12:45:00
12:45:00 - 13:07:30
13:07:30 - 13:30:00
13:30:00 - 13:52:30 (True Session Open)
13:52:30 - 14:15:00
14:15:00 - 14:37:30
14:37:30 - 15:00:00
15:00:00 - 15:22:30
15:22:30 - 15:45:00
15:45:00 - 15:37:30
15:37:30 - 16:00:00
16:00:00 - 16:22:30
16:22:30 - 16:45:00
16:45:00 - 17:07:30
17:07:30 - 18:00:00
S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
Absolute Strength Index [ASI] (Zeiierman)█ Overview
The Absolute Strength Index (ASI) is a next-generation oscillator designed to measure the strength and direction of price movements by leveraging percentile-based normalization of historical returns. Developed by Zeiierman, this indicator offers a highly visual and intuitive approach to identifying market conditions, trend strength, and divergence opportunities.
By dynamically scaling price returns into a bounded oscillator (-10 to +10), the ASI helps traders spot overbought/oversold conditions, trend reversals, and momentum changes with enhanced precision. It also incorporates advanced features like divergence detection and adaptive signal smoothing for versatile trading applications.
█ How It Works
The ASI's core calculation methodology revolves around analyzing historical price returns, classifying them into top and bottom percentiles, and normalizing the current price movement within this framework. Here's a breakdown of its key components:
⚪ Returns Lookback
The ASI evaluates historical price returns over a user-defined period (Returns Lookback) to measure recent price behavior. This lookback window determines the sensitivity of the oscillator:
Shorter Lookback: Higher responsiveness to recent price movements, suitable for scalping or high-volatility assets.
Longer Lookback: Smoother oscillator behavior is ideal for identifying larger trends and avoiding false signals.
⚪ Percentile-Based Thresholds
The ASI categorizes returns into two groups:
Top Percentile (Winners): The upper X% of returns, representing the strongest upward price moves.
Bottom Percentile (Losers): The lower X% of returns, capturing the sharpest downward movements.
This percentile-based normalization ensures the ASI adapts to market conditions, filtering noise and emphasizing significant price changes.
⚪ Oscillator Normalization
The ASI normalizes current returns relative to the top and bottom thresholds:
Values range from -10 to +10, where:
+10 represents extreme bullish strength (above the top percentile threshold).
-10 indicates extreme bearish weakness (below the bottom percentile threshold).
⚪ Signal Line Smoothing
A signal line is optionally applied to the ASI using a variety of moving averages:
Options: SMA, EMA, WMA, RMA, or HMA.
Effect: Smooths the ASI to filter out noise, with shorter lengths offering higher responsiveness and longer lengths providing stability.
⚪ Divergence Detection
One of ASI's standout features is its ability to detect and highlight bullish and bearish divergences:
Bullish Divergence: The ASI forms higher lows while the price forms lower lows, signaling potential upward reversals.
Bearish Divergence: The ASI forms lower highs while the price forms higher highs, indicating potential downward reversals.
█ Key Differences from RSI
Dynamic Adaptability: ASI adjusts to market conditions through percentile-based scaling, while RSI uses static thresholds.
█ How to Use ASI
⚪ Trend Identification
Bullish Strength: ASI above zero suggests upward momentum, suitable for trend-following trades.
Bearish Weakness: ASI below zero signals downward momentum, ideal for short trades or exits from long positions.
⚪ Overbought/Oversold Levels
Overbought Zone: ASI in the +8 to +10 range indicates potential exhaustion of bullish momentum.
Oversold Zone: ASI in the -8 to -10 range points to potential reversal opportunities.
⚪ Divergence Signals
Look for bullish or bearish divergence labels to anticipate trend reversals before they occur.
⚪ Signal Line Crossovers
A crossover between the ASI and its signal line (e.g., EMA or SMA) can indicate a shift in momentum:
Bullish Crossover: ASI crosses above the signal line, signaling potential upside.
Bearish Crossover: ASI crosses below the signal line, suggesting downside momentum.
█ Settings Explained
⚪ Absolute Strength Index
Returns Lookback: Sets the sensitivity of the oscillator. Shorter periods detect short-term changes, while longer periods focus on broader trends.
Top/Bottom Percentiles: Adjust thresholds for defining winners and losers. Narrower percentiles increase sensitivity to outliers.
Signal Line Type: Choose from SMA, EMA, WMA, RMA, or HMA for smoothing.
Signal Line Length: Fine-tune the responsiveness of the signal line.
⚪ Divergence
Divergence Lookback: Adjusts the period for detecting divergence. Use longer lookbacks to reduce noise.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
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