Signals for call and putSorry for the Google Translate English
Indicator for signals of call and put, using Bollinger bands (period 20, standard deviation 2.5), market trend of (sma, períod 100) and stochastic (period 20, %D 3).
I was overthrown but in pine scrip, the function "stoch()" no way to smooth (3). If anyone knows how to smooth inside the script, help me! Please.
With smoothed stochastic the hit rate grows a lot.
Português (Pt-Br)
Indicador de sinais de compra e venda, usando bandas de Bollinger (período de 20, desvio de 2,5), tendencia de mercado com (sma período 100) e estocástico (período 20, %D de 3).
Eu travei porque no pine script, a função "stoch()" não tem como aplicar a suavização (3). Se alguem souber como suavizar dentro do script, me ajude! Por favor.
Cerca negli script per "20年美元汇率"
MG - Multiple Moving Averages & Candle Wick Alerts - 1.0Features:
- Each moving average has customizable length, type and source
- The ability to change the source of all moving averages with one input (changing an individual MA source will override the general for that MA)
- At a glance comparison of 20 SMA and 20 VWMA to gauge volume trend
- Wick alerts which can be toggled for each moving average.
- Bullish wick alerts are when the wick is the only part of the candle to drop below the moving average
- Bearish wick alerts are when the wick is the only part of the candle to reach above the moving average
- Simple candle closed alert if you want a notification, for example each hour.
Defaults: Four SMAs (20, 50, 100, 200) and a 20 VWMA .
Recommended Usage:
- Set the general source (sets the source of all moving averages) to 'low' when in an uptrend and 'high' in a downtrend to maximize Risk : Reward.
- Use Fibonacci levels, oscillators .etc for confluence
NOTE: The moving average component of this indicator is the same as the previous indicator ()
Indicator - Multiple Moving Averages 1.0Features:
- Each moving average has customizable length, type and source
- The ability to change the source of all moving averages with one input (changing an individual MA source will override the general for that MA)
- At a glance comparison of 20 SMA and 20 VWMA to gauge volume trend
Defaults: Four SMAs (20, 50, 100, 200) and a 20 VWMA.
Usage:
- Use Fibonacci levels, pivots .etc for confluence
- Personally, I like to set overall source to low in uptrends, to high in downtrends and then set alerts for when the price crosses any of the averages. Then pay particular attention to the candlesticks and other indicators.
TODO:
- Add alerts option so that it send alert on crossing up or down any alert lines.
XPloRR MA-Trailing-Stop StrategyXPloRR MA-Trailing-Stop Strategy
Long term MA-Trailing-Stop strategy with Adjustable Signal Strength to beat Buy&Hold strategy
None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy.
Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade.
My buy strategy is triggered by the fast buy EMA (blue) crossing over the slow buy SMA curve (orange) and the fast buy EMA has a certain up strength.
My sell strategy is triggered by either one of these conditions:
the EMA(6) of the close value is crossing under the trailing stop value (green) or
the fast sell EMA (navy) is crossing under the slow sell SMA curve (red) and the fast sell EMA has a certain down strength.
The trailing stop value (green) is set to a multiple of the ATR(15) value.
ATR(15) is the SMA(15) value of the difference between the high and low values.
The scripts shows a lot of graphical information:
The close value is shown in light-green. When the close value is lower then the buy value, the close value is shown in light-red. This way it is possible to evaluate the virtual losses during the trade.
the trailing stop value is shown in dark-green. When the sell value is lower then the buy value, the last color of the trade will be red (best viewed when zoomed)(in the example, there are 2 trades that end in gain and 2 in loss (red line at end))
the EMA and SMA values for both buy and sell signals are shown as a line
the buy and sell(close) signals are labeled in blue
How to use this strategy?
Every stock has it's own "DNA", so first thing to do is tune the right parameters to get the best strategy values voor EMA , SMA, Strength for both buy and sell and the Trailing Stop (#ATR).
Look in the strategy tester overview to optimize the values Percent Profitable and Net Profit (using the strategy settings icon, you can increase/decrease the parameters)
Then keep using these parameters for future buy/sell signals only for that particular stock.
Do the same for other stocks.
Important : optimizing these parameters is no guarantee for future winning trades!
Here are the parameters:
Fast EMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 10-20)
Slow SMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 30-100)
Minimum Buy Strength: minimum upward trend value of the Fast SMA Buy value (directional coefficient)(use values between 0-120)
Fast EMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 10-20)
Slow SMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 30-100)
Minimum Sell Strength: minimum downward trend value of the Fast SMA Sell value (directional coefficient)(use values between 0-120)
Trailing Stop (#ATR): the trailing stop value as a multiple of the ATR(15) value (use values between 2-20)
Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now) compared to the Buy&Hold Strategy(=do nothing):
BEKB(Bekaert): EMA-Buy=12, SMA-Buy=44, Strength-Buy=65, EMA-Sell=12, SMA-Sell=55, Strength-Sell=120, Stop#ATR=20
NetProfit: 996%, #Trades: 6, %Profitable: 83%, Buy&HoldProfit: 78%
BAR(Barco): EMA-Buy=16, SMA-Buy=80, Strength-Buy=44, EMA-Sell=12, SMA-Sell=45, Strength-Sell=82, Stop#ATR=9
NetProfit: 385%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 55%
AAPL(Apple): EMA-Buy=12, SMA-Buy=45, Strength-Buy=40, EMA-Sell=19, SMA-Sell=45, Strength-Sell=106, Stop#ATR=8
NetProfit: 6900%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 2938%
TNET(Telenet): EMA-Buy=12, SMA-Buy=45, Strength-Buy=27, EMA-Sell=19, SMA-Sell=45, Strength-Sell=70, Stop#ATR=14
NetProfit: 129%, #Trade
EMA Indicators with BUY sell SignalCombine 3 EMA indicators into 1. Buy and Sell signal is based on
- Buy signal based on 20 Days Highest High resistance
- Sell signal based on 10 Days Lowest Low support
Input :-
1 - Short EMA (20), Mid EMA (50) and Long EMA (200)
2 - Resistance (20) = 20 Days Highest High line
3 - Support (10) = 10 Days Lowest Low line
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.
Luxy trend & Momentum Indicators Suit V2Luxy Trend & Momentum Indicator Suite V2
The Luxy Trend & Momentum Suite V2 is a multi-purpose technical analysis tool designed to help traders quickly identify high-probability trend-following and momentum-based entries across timeframes.
This tool combines the most battle-tested market filters (EMAs, VWAP, MACD, ZLSMA, Supertrend, UT Bot, Volume/ADX/RSI filters) into a unified signal framework — backed by an optional Bias Table that displays alignment across methods and timeframes.
BACKGROUND — ABOUT THIS METHOD
This Indicators Suite is based on momentum-trend alignment , a trading methodology that:
* Confirms trend structure using moving averages (EMA crossovers & price vs EMA-200),
* Validates trend strength using MACD separation, volume pressure, and ADX confirmation,
* Confirms timing using momentum oscillators (RSI pullbacks), VWAP positioning, and trend filters,
* Optionally delays entries using the UT Bot trailing confirmation or Supertrend .
It's a multi-layered filtering helps reduce false signals, especially in choppy conditions.
USAGE
This indicator is best suited for:
Intraday trend trading (scalping or day trading),
Swing trading based on HTF confirmation (1D/1W),
Combining bias + technical signal + volume + price context for cleaner entries.
It is especially powerful on assets with well-defined structure (e.g., crypto, indices, high-volume stocks).
Signal Labels
The script plots `LONG` (green) or `SHORT` (red) labels when all your configured filters align.
✅ To use these labels effectively:
Only take LONG signals when the bias table shows green ("BULLISH"),
Only take SHORT when the bias table shows red ("BEARISH"),
Avoid signals on NEUTRAL bias (gray), or consider smaller positions.
Bias Table Panel
The indicator features a compact Bias summary table , showing the current directional bias from:
Timeframe trends (1H, 4H, 1D)
Indicator states (EMA cross, EMA200, VWAP, MACD, ZLSMA, UT Bot, Supertrend)
Each cell is color-coded:
🟢 Green = Bullish
🔴 Red = Bearish
⚪ Gray = Neutral
Trend Filters
These are the primary trend components:
EMA Short vs Long : Fast/Slow structure
EMA-200 : Long-term bias
ZLSMA : Zero-lag regression slope
Supertrend : Dynamic trendline with noise-filtering
UT Bot : ATR-based trailing signal with optional filters (swing, %change, delay)
Momentum & Entry Filters
The indicator offers several modular filters to refine entry signals:
✅ MACD Separation : Requires a minimum spread between MACD and Signal line (adjustable in ATR units).
✅ VWAP Filter : Confirms that price is above/below anchored VWAP.
✅ RSI Pullback Zone : Only triggers signals when RSI is between configured pullback ranges.
✅ Volume Strength : Only confirms signals when current volume is above SMA × factor (e.g. 1.2×).
✅ ADX/DI Filter : Enforces trend strength requirements based on ADX, DI+ and DI-.
RECOMMENDED WORKFLOWS
🔹 Intraday Trend Trading
Primary TF: "1H"
Confirmation: "4H"
Bias method: EMA(20/50) or ZLSMA
Lookback: 5 bars
VWAP: Session anchor
UT Bot: Enabled with 1.3 sensitivity, ATR=10
🔹 Swing Trading
Primary TF: "1D"
Confirmation: "1W"
Bias method: EMA(20/50) or MACD
Lookback: 10–20
VWAP: Weekly or Monthly
UT Bot: Disabled or conservative (1.7 key, ATR=14)
🔹 Position Trading
Primary: "1W"
Confirmation: "1M"
Bias method: EMA(50/200)
Filters: Strong MACD + Volume + ADX
UT: Disabled
SETTINGS
You can customize:
All EMA lengths (short, long, very long)
MACD periods and buffer thresholds
VWAP anchor and bands mode (Std Dev or %)
ZLSMA length and offset
UT Bot sensitivity, ATR, and filters
Supertrend ATR logic and neutral bars
Volume, ADX, RSI, and Donchian breakouts
Table text size, position, and visibility
Each input includes tooltips with suggested ranges and explanations.
🔶 LIMITATIONS
This is an **indicator**, not a strategy. It does **not place orders**.
UT Bot and Bias alignment work better on assets with structure and volume.
Repainting is avoided by using bar close logic where possible.
Corporate-event VWAPs (Earnings, Dividends) depend on data availability.
Always backtest , adjust filters per asset, and confirm entries with price action and context.
📧 Feedback & improvement requests:
Yelober - Market Internal direction+ Key levelsYelober – Market Internals + Key Levels is a focused intraday trading tool that helps you spot high-probability price direction by anchoring decisions to structure that matters: yesterday’s RTH High/Low, today’s pre-market High/Low, and a fast Value Area/POC from the prior session. Paired with a compact market internals dashboard (NYSE/NASDAQ UVOL vs. DVOL ratios, VOLD slopes, TICK/TICKQ momentum, and optional VIX trend), it gives you a real-time read on breadth so you can choose which direction to trade, when to enter (breaks, retests, or fades at PMH/PML/VAH/VAL/POC), and how to plan exits as internals confirm or deteriorate. On top of these intraday decision benefits, it also allows traders—in a very subtle but powerful way—to keep an eye on the VIX and immediately recognize significant spikes or sharp decreases that should be factored in before entering a trade, or used as a quick signal to modify an existing position. In short: clear levels for the chart, live internals for the context, and a smarter, rules-based path to execution.
# Yelober – Market Internals + Key Levels
*A TradingView indicator for session key levels + real‑time market internals (NYSE/NASDAQ TICK, UVOL/DVOL/VOLD, and VIX).*
**Script name in Pine:** `Yelober - Market Internal direction+ Key levels` (Pine v6)
---
## 1) What this indicator does
**Purpose:** Help intraday traders quickly find high‑probability reaction zones and read market internals momentum without switching charts. It overlays yesterday/today’s **automatic price levels** on your active chart and shows a **market breadth table** that summarizes NYSE/NASDAQ buying pressure and TICK direction, with an optional VIX trend read.
### Key features at a glance
* **Automatic Price Levels (overlay on chart)**
* Yesterday’s High/Low of Day (**yHoD**, **yLoD**)
* Extended Hours High/Low (**yEHH**, **yEHL**) across yesterday AH + today pre‑market
* Today’s Pre‑Market High/Low (**PMH**, **PML**)
* Yesterday’s **Value Area High/Low** (**VAH/VAL**) and **Point of Control (POC)** computed from a volume profile of yesterday’s **regular session**
* Smart de‑duplication:
* Shows **only the higher** of (yEHH vs PMH) and **only the lower** of (yEHL vs PML) to avoid redundant bands
* **Market Breadth Table (on‑chart table)**
* **NYSE ratio** = UVOL/DVOL (signed) with **VOLD slope** from session open
* **NASDAQ ratio** = UVOLQ/DVOLQ (signed) with **VOLDQ slope** from session open
* **TICK** and **TICKQ**: live cumulative ratio and short‑term slope
* **VIX** (optional): current value + slope over a configurable lookback/timeframe
* Color‑coded trends with sensible thresholds and optional normalization
---
## 2) How to use it (trader workflow)
1. **Mark your reaction zones**
* Watch **yHoD/yLoD**, **PMH/PML**, and **VAH/VAL/POC** for first touches, break/retest, and failure tests.
* Expect increased responsiveness when multiple levels cluster (e.g., PMH ≈ VAH ≈ daily pivot).
2. **Read the breadth panel for context**
* **NYSE/NASDAQ ratio** (>1 = more up‑volume than down‑volume; <−1 = down‑dominant). Strong green across both favors long setups; red favors short setups.
* **VOLD slopes** (NYSE & NASDAQ): positive and accelerating → broadening participation; negative → persistent pressure.
* **TICK/TICKQ**: cumulative ratio and **slope arrows** (↗ / ↘ / →). Use the slope to gauge **near‑term thrust or fade**.
* **VIX slope**: rising VIX (red) often coincides with risk‑off; falling VIX (green) with risk‑on.
3. **Confluence = higher confidence**
* Example: Price reclaims **PMH** while **NYSE/NASDAQ ratios** print green and **TICK slopes** point ↗ — consider break‑and‑go; if VIX slope is ↘, that adds risk‑on confidence.
* Example: Price rejects **VAH** while **VOLD slopes** roll negative and VIX ↗ — consider fade/reversal.
4. **Risk management**
* Place stops just beyond key levels tested; if breadth flips, tighten or exit.
> **Timeframes:** Works best on 1–15m charts for intraday. Value Area is computed from **yesterday’s RTH**; choose a smaller calculation timeframe (e.g., 5–15m) for stable profiles.
---
## 3) Inputs & settings (what each option controls)
### Global Style
* **Enable all automatic price levels**: master toggle for yHoD/yLoD, yEHH/yEHL, PMH/PML, VAH/VAL/POC.
* **Line style/width**: applies to all drawn levels.
* **Label size/style** and **label color linking**: use the same color as the line or override with a global label color.
* **Maximum bars lookback**: how far the script scans to build yesterday metrics (performance‑sensitive).
### Value Area / Volume Profile
* **Enable Value Area calculations** *(on by default)*: computes yesterday’s **POC**, **VAH**, **VAL** from a simplified intraday volume profile built from yesterday’s **regular session bars**.
* **Max Volume Profile Points** *(default 50)*: lower values = faster; higher = more precise.
* **Value Area Calculation Timeframe** *(default 15)*: the security timeframe used when collecting yesterday’s highs/lows/volumes.
### Individual Level Toggles & Colors
* **yHoD / yLoD** (yesterday high/low)
* **yEHH / yEHL** (yesterday AH + today pre‑market extremes)
* **PMH / PML** (today pre‑market extremes)
* **VAH / VAL / POC** (yesterday RTH value area + point of control)
### Market Breadth Panel
* **Show NYSE / NASDAQ / VIX**: choose which series to display in the table.
* **Table Position / Size / Background Color**: UI placement and legibility.
* **Slope Averaging Periods** *(default 5)*: number of recent TICK/TICKQ ratio points used in slope calculation.
* **Candles for Rate** *(default 10)* & **Normalize Rate**: VIX slope calculation as % change between `now` and `n` candles ago; normalize divides by `n`.
* **VIX Timeframe**: optionally compute VIX on a higher TF (e.g., 15, 30, 60) for a smoother regime read.
* **Volume Normalization** (NYSE & NASDAQ): display VOLD slopes scaled to `tens/thousands/millions/10th millions` for readable magnitudes; color thresholds adapt to your choice.
---
## 4) Data sources & definitions
* **UVOL/VOLD (NYSE)** and **UVOLQ/DVOLQ/VOLDQ (NASDAQ)** via `request.security()`
* **Ratio** = `UVOL/DVOL` (signed; negative when down‑volume dominates)
* **VOLD slope** ≈ `(VOLD_now − VOLD_open) / bars_since_open`, then normalized per your setting
* **TICK/TICKQ**: cumulative sum of prints this session with **positives vs negatives ratio**, plus a simple linear regression **slope** of the last `N` ratio values
* **VIX**: value and slope across a user‑selected timeframe and lookback
* **Sessions (EST/EDT)**
* **Regular:** 09:30–16:00
* **Pre‑Market:** 04:00–09:30
* **After Hours:** 16:00–20:00
* **Extended‑hours extremes** combine **yesterday AH** + **today PM**
> **Note:** All session checks are done with TradingView’s `time(…,"America/New_York")` context. If your broker’s RTH differs (e.g., futures), adjust expectations accordingly.
---
## 5) How the algorithms work (plain English)
### A) Key Levels
* **Yesterday’s RTH High/Low**: scans yesterday’s bars within 09:30–16:00 and records the extremes + bar indices.
* **Extended Hours**: scans yesterday AH and today PM to get **yEHH/yEHL**. Script shows **either yEHH or PMH** (whichever is **higher**) and **either yEHL or PML** (whichever is **lower**) to avoid duplicate bands stacked together.
* **Value Area & POC (RTH only)**
* Build a coarse volume profile with `Max Volume Profile Points` buckets across the price range formed by yesterday’s RTH bars.
* Distribute each bar’s volume uniformly across the buckets it spans (fast approximation to keep Pine within execution limits).
* **POC** = bucket with max volume. **VA** expands from POC outward until **70%** of cumulative volume is enclosed → yields **VAH/VAL**.
### B) Market Breadth Table
* **NYSE/NASDAQ Ratio**: signed UVOL/DVOL with basic coloring.
* **VOLD Slopes**: from session open to current, normalized to human‑readable units; colors flip green/red based on thresholds that map to your normalization setting (e.g., ±2M for NYSE, ±3.5×10M for NASDAQ).
* **TICK/TICKQ Slope**: linear regression over the last `N` ratio points → **↗ / → / ↘** with the rounded slope value.
* **VIX Slope**: % change between now and `n` candles ago (optionally divided by `n`). Red when rising beyond threshold; green when falling.
---
## 6) Recommended presets
* **Stocks (liquid, intraday)**
* Value Area **ON**, `Max Volume Points` = **40–60**, **Timeframe** = **5–15**
* Breadth: show **NYSE & NASDAQ & VIX**, `Slope periods` = **5–8**, `Candles for rate` = **10–20**, **Normalize VIX** = **ON**
* **Index futures / very high‑volume symbols**
* If you see Pine timeouts, set `Max Volume Points` = **20–40** or temporarily **disable Value Area**.
* Keep breadth panel **ON** (it’s light). Consider **VIX timeframe = 15/30** for regime clarity.
---
## 7) Tips, edge cases & performance
* **Performance:** The volume profile is capped (`maxBarsToProcess ≤ 500` and bucketed) to keep it responsive. If you experience slowdowns, reduce `Max Volume Points`, `Maximum bars lookback`, or disable Value Area.
* **Redundant lines:** The script **intentionally suppresses** PMH/PML when yEHH/yEHL are more extreme, and vice‑versa.
* **Label visibility:** Use `Label style = none` if you only want clean lines and read values from the right‑end labels.
* **Futures/RTH differences:** Value Area is from **yesterday’s RTH** only; for 24h instruments the RTH period may not reflect overnight structure.
* **Session transitions:** PMH/PML tracking stops as soon as RTH starts; values persist as static levels for the session.
---
## 8) Known limitations
* Uses public TradingView symbols: `UVOL`, `VOLD`, `UVOLQ`, `DVOLQ`, `VOLDQ`, `TICK`, `TICKQ`, `VIX`. If your data plan or region limits any symbol, the corresponding table rows may show `na`.
* The VA/POC approximation assumes uniform distribution of each bar’s volume across its high–low. That’s fast but not a tick‑level profile.
* Works best on US equities with standard NY session; alternative sessions may need code changes.
---
## 9) Troubleshooting
* **“Script is too slow / timed out”** → Lower `Max Volume Points`, lower `Maximum bars lookback`, or toggle **OFF** `Enable Value Area calculations` for that instrument.
* **Missing breadth values** → Ensure the symbols above load on your account; try reloading chart or switching timeframes once.
* **Overlapping labels** → Set `Label style = none` or reduce label size.
---
## 10) Version / license / contribution
* **Version:** Initial public release (Pine v6).
* **Author:** © yelober
* **License:** Free for community use and enhancement. Please keep author credit.
* **Contributing:** Open PRs/ideas: presets, alert conditions, multi‑day VA composites, optional mid‑value (`(VAH+VAL)/2`), session filter for futures, and alertable state machine for breadth regime transitions.
---
## 11) Quick start (TL;DR)
1. Add the indicator and **keep default settings**.
2. Trade **reactions** at yHoD/yLoD/PMH/PML/VAH/VAL/POC.
3. Use the **breadth table**: look for **green ratios + ↗ slopes** (risk‑on) or **red ratios + ↘ slopes** (risk‑off). Check **VIX** slope for confirmation.
4. Manage risk around levels; when breadth flips against you, tighten or exit.
---
### Changelog (public)
* **v1.0:** First community release with automatic RTH levels, VA/POC approximation, breadth dashboard (NYSE/NASDAQ/TICK/TICKQ/VIX) with normalization and adaptive color thresholds.
Pump/Dump Detector [Modular]//@version=5
indicator("Pump/Dump Detector ", overlay=true)
// ————— Inputs —————
risk_pct = input.float(1.0, "Risk %", minval=0.1)
capital = input.float(100000, "Capital")
stop_multiplier = input.float(1.5, "Stop Multiplier")
target_multiplier = input.float(2.0, "Target Multiplier")
volume_mult = input.float(2.0, "Volume Spike Multiplier")
rsi_low_thresh = input.int(15, "RSI Oversold Threshold")
rsi_high_thresh = input.int(85, "RSI Overbought Threshold")
rsi_len = input.int(2, "RSI Length")
bb_len = input.int(20, "BB Length")
bb_mult = input.float(2.0, "BB Multiplier")
atr_len = input.int(14, "ATR Length")
show_signals = input.bool(true, "Show Entry Signals")
use_orderflow = input.bool(true, "Use Order Flow Proxy")
use_ml_flag = input.bool(false, "Use ML Risk Flag")
use_session_filter = input.bool(true, "Use Volatility Sessions")
// ————— Symbol Filter (Optional) —————
symbol_nq = input.bool(true, "Enable NQ")
symbol_es = input.bool(true, "Enable ES")
symbol_gold = input.bool(true, "Enable Gold")
is_nq = str.contains(syminfo.ticker, "NQ")
is_es = str.contains(syminfo.ticker, "ES")
is_gold = str.contains(syminfo.ticker, "GC")
symbol_filter = (symbol_nq and is_nq) or (symbol_es and is_es) or (symbol_gold and is_gold)
// ————— Calculations —————
rsi = ta.rsi(close, rsi_len)
atr = ta.atr(atr_len)
basis = ta.sma(close, bb_len)
dev = bb_mult * ta.stdev(close, bb_len)
bb_upper = basis + dev
bb_lower = basis - dev
rolling_vol = ta.sma(volume, 20)
vol_spike = volume > volume_mult * rolling_vol
// ————— Session Filter (EST) —————
est_offset = -5
est_hour = (hour + est_offset + 24) % 24
session_filter = (est_hour >= 18 or est_hour < 6) or (est_hour >= 14 and est_hour < 17)
session_ok = not use_session_filter or session_filter
// ————— Order Flow Proxy —————
mfi = ta.mfi(close, 14)
buy_imbalance = ta.crossover(mfi, 50)
sell_imbalance = ta.crossunder(mfi, 50)
reversal_candle = close > open and close > ta.highest(close , 3)
// ————— ML Risk Flag (Placeholder) —————
ml_risk_flag = use_ml_flag and (ta.sma(close, 5) > ta.sma(close, 20))
// ————— Entry Conditions —————
long_cond = symbol_filter and session_ok and vol_spike and rsi < rsi_low_thresh and close < bb_lower and (not use_orderflow or (buy_imbalance and reversal_candle)) and (not use_ml_flag or ml_risk_flag)
short_cond = symbol_filter and session_ok and vol_spike and rsi > rsi_high_thresh and (not use_orderflow or sell_imbalance) and (not use_ml_flag or ml_risk_flag)
// ————— Position Sizing —————
risk_amt = capital * (risk_pct / 100)
position_size = risk_amt / atr
// ————— Plot Signals —————
plotshape(show_signals and long_cond, title="Long Signal", location=location.belowbar, color=color.green, style=shape.triangleup, size=size.small)
plotshape(show_signals and short_cond, title="Short Signal", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
// ————— Alerts —————
alertcondition(long_cond, title="Long Entry Alert", message="Pump fade detected: Long setup triggered")
alertcondition(short_cond, title="Short Entry Alert", message="Dump detected: Short setup triggered")
KAMA Trend Flip with Snap & Follow - SightLing Labs🔭 OVERVIEW
KAMA Snap Follow is a customized adaptation of the Kaufman Adaptive Moving Average (KAMA) that overlays a trend-tracking line on the chart. It computes an adaptive smoothing constant from the efficiency ratio, then incorporates conditional enhancements: a "snap" mechanism to boost responsiveness on significant counter-trend bars surpassing an ATR-based threshold, and a temporary "follow" mode after trend flips to intensify adaptation for a user-defined number of bars. This allows the line to hug price more closely during early reversal phases before returning to standard smoothing for noise filtration. The line colors green for upward trends (rising KAMA), red for downward (falling KAMA), and gray for neutral, with optional alerts on trend changes. If the structure invalidates (e.g., via excessive lag or unconfirmed flips), no automatic cleanup occurs—users manage via settings tweaks and backtesting.
🔭 CONCEPTS
* Adaptive smoothing core: Builds on KAMA's efficiency ratio to dynamically adjust between fast and slow constants, gliding over minor volatility while aiming to react to directional shifts.
* Snap trigger: Detects potential reversals via large bar changes opposing the prior trend, exceeding a multiplier of ATR; this temporarily amplifies the smoothing constant (capped at 1.0) to pull KAMA toward price.
* Follow mode activation: Post-flip, engages a boosted adaptation phase for a fixed bar count, forcing tighter shadowing in the new direction to reduce lag on true turns, then reverts to absorber mode.
* Trend detection: Simple comparison of current vs. prior KAMA values defines up/down/neutral, with no embedded signals—purely for visual trend context.
* Risk-aware design: No guarantees; focuses on lag reduction in simulations (e.g., 38-54% trough lag cuts on synthetic volatile series), but real-market performance varies—backtest thoroughly.
🔭 FEATURES
* Custom KAMA calculation with manual efficiency ratio and smoothing powers for baseline adaptation.
* ATR-integrated snap for reversal sensitivity, with adjustable multiplier and boost.
* Post-flip follow mode with configurable period and boost to enhance new-trend hugging.
* Trend coloring and flip alerts: Green/red/gray line with conditions for up/down/neutral; alerts on changes.
* User controls:
Source (e.g., close).
Efficiency Ratio Length (pivot-like sensitivity).
Fast/Slow Powers (adaptation speed).
ATR Length (volatility measure).
Snap Multiplier/Boost (reversal threshold/amplification).
Follow Period/Boost (post-flip duration/intensity).
* Efficient execution: Lightweight, no heavy buffers—suitable for intraday charts via backtested tweaks.
🔭 HOW TO USE
* Tune sensitivity: Shorten Efficiency Ratio Length on lower timeframes for quicker reactions; lengthen on higher for smoother trends. Test ATR Length against asset volatility.
* Monitor flips: Use green/red shifts as trend context—combine with your strategy (e.g., crossovers, support/resistance) for potential entries; alerts notify changes.
* Leverage modes: Snap helps catch sharp turns; follow mode tightens tracking post-reversal—observe on historical data to gauge lag reduction (e.g., 30-57% miss cuts on 0.20 moves in tests).
* Apply MTF: Spot broader trends on 5m; refine on 30s/1m near flips. Backtest configurations to avoid over-optimization.
* Integrate confluence: Pair with volume, RSI, or your filters; never rely solely—markets evolve, so validate via simulations and live observation.
🔭 CONCLUSION
KAMA Snap Follow evolves standard KAMA by adding snap and follow mechanics to combat reversal lag while filtering bumps, offering a visual tool for trend analysis in volatile intraday setups. Developed to address traditional adaptive averages' delays without introducing excessive whipsaw (e.g., zero added in noisy flats per tests), it provides adjustable parameters for customization. No performance promises—results hinge on backtesting and market fit; use as a framework for scenario evaluation, not automated trading.
Example Configurations (derived from synthetic tests on SOFI-like intraday volatility; backtest and adjust):
- For 30s charts (high noise, rapid shifts): Efficiency Ratio Length=20, Fast Power=1, Slow Power=15, ATR Length=10, Snap Multiplier=1.2, Snap Boost=2.0, Follow Period=5, Follow Boost=2.5—yields ~40% lag reduction on turns, filtering 85% of <0.01 fluctuations.
- For 1m charts (moderate volatility): Efficiency Ratio Length=30, Fast Power=2, Slow Power=20, ATR Length=14, Snap Multiplier=1.5, Snap Boost=2.5, Follow Period=8, Follow Boost=3.0—achieves ~30% lower reversal misses (e.g., 0.08 vs. 0.12 on 0.20 swings), stable in 50-bar chops.
- For 5m charts (trendier flows): Efficiency Ratio Length=50, Fast Power=3, Slow Power=40, ATR Length=20, Snap Multiplier=1.8, Snap Boost=3.0, Follow Period=12, Follow Boost=3.5—boosts post-flip hug by 25%, ignoring 90% of ±0.05 noise across 100 bars.
🏆 AI Gold Master IndicatorsAI Gold Master Indicators - Technical Overview
Core Purpose: Advanced Pine Script indicator that analyzes 20 technical indicators simultaneously for XAUUSD (Gold) trading, generating automated buy/sell signals through a sophisticated scoring system.
Key Features
📊 Multi-Indicator Analysis
Processes 20 indicators: RSI, MACD, Bollinger Bands, EMA crossovers, Stochastic, Williams %R, CCI, ATR, Volume, ADX, Parabolic SAR, Ichimoku, MFI, ROC, Fibonacci retracements, Support/Resistance, Candlestick patterns, MA Ribbon, VWAP, Market Structure, and Cloud MA
Each indicator generates BUY (🟢), SELL (🔴), or NEUTRAL (⚪) signals
⚖️ Dual Scoring Systems
Weighted System: Each indicator has configurable weights (10-200 points, total 1000), with higher weights for critical indicators like RSI (150) and MACD (150)
Simple Count System: Basic counting of BUY vs SELL signals across all indicators
🎯 Signal Generation
Configurable thresholds for both systems (weighted score threshold: 400-600 recommended)
Dynamic risk management with ATR-based TP/SL levels
Signal strength filtering to reduce false positives
📈 Advanced Configuration
Customizable thresholds for all 20 indicators (RSI levels, Stochastic bounds, Williams %R zones, etc.)
Dynamic weight bonuses that adapt to dominant market trends
Risk management with configurable TP1/TP2 multipliers and stop losses
🎛️ Visual Interface
Real-time master table displaying all indicators, their values, weights, and current signals
Visual trading signals (triangles) with detailed labels
Optional TP/SL lines and performance statistics
💡 Optimization Features
Gold-specific parameter tuning
Trend analysis with configurable lookback periods
Volume spike detection and volatility analysis
Multi-timeframe compatibility (15m, 1H, 4H recommended)
The system combines traditional technical analysis with modern weighting algorithms to provide comprehensive market analysis specifically optimized for gold trading.
Ragazzi è una meraviglia, pronto all uso, già configurato provatelo divertitevi e fate tanti soldoni poi magari una piccola donazione spontanea sarebbe molto gradita visto il tempo, risorse e gli insulti della moglie che mi diceva che perdevo tempo, fatemi sapere se vi piace.
nel codice troverete una descrizione del funzionamento se vi vengono in mente delle idee per migliorarlo contattatemi troverete i mie contatti in tabella un saluto.
Asistente de Barra de Estado ADX
// This is an all-in-one indicator designed to visually represent the market environment
// based on the G2 (trend-following) and SMOG (reversal/ranging) trading systems.
// It replaces the need for a separate ADX indicator.
//
// FEATURES:
//
// 1. Multi-Timeframe ADX:
// - 5-Minute ADX (Blue Line - The "Referee"): Determines the overall market environment (Trending or Ranging).
// - 1-Minute ADX (Yellow Line - The "Trigger"): Measures immediate momentum for trade entries.
//
// 2. Environment Background Coloring:
// The indicator's own background panel changes color to provide an instant signal:
// - Green: G2 Bullish Environment (5-min ADX > 25 & Price is Trending Up)
// - Red: G2 Bearish Environment (5-min ADX > 25 & Price is Trending Down)
// - Gray: Gray Zone (Indecisive/Risky Market, 5-min ADX between 20-25)
// - Blue: SMOG Environment (Weak/Ranging Market, 5-min ADX < 20)
//
// 3. Reference Lines:
// Includes horizontal lines at the key 20 and 25 levels for easy reference.
//
// HOW TO USE:
// Use this indicator as the primary tool to decide whether to look for a G2
// (trend-following) or a SMOG (reversal) setup.
//
EMA Range OscillatorEMA Range Oscillator (ERO) - User Guide
Overview
The EMA Range Oscillator (ERO) is a technical indicator that measures the distance between two Exponential Moving Averages (EMAs) and the distance between price and EMA. It normalizes these distances into a 0-100 range, helping traders identify trend strength, market momentum, and potential reversal points.
Components
Main Line
Green Line: EMA20 > EMA50 (Uptrend)
Red Line: EMA20 < EMA50 (Downtrend)
Histogram
White Histogram: Price distance from EMA20
Key Levels
Upper Level (80): High divergence zone
Middle Level (50): Neutral zone
Lower Level (20): Low divergence zone
Parameters
ParameterDefaultDescriptionFast EMA20Short-term EMA periodSlow EMA50Long-term EMA periodNormalization Period100Lookback period for scalingUpper80Upper threshold levelLower20Lower threshold level
How to Read the Indicator
High Values (Above 80)
Strong trend in progress
EMAs are widely separated
High momentum
Potential overbought/oversold conditions
Watch for possible trend exhaustion
Low Values (Below 20)
Consolidation phase
EMAs are close together
Low volatility
Potential breakout setup
Range-bound market conditions
Middle Zone (20-80)
Normal market conditions
Moderate trend strength
Balanced momentum
Look for directional clues from color changes
Trend Display Table (with Change Alerts)📌 Indicator: Trend Display Table (with Change Alerts)
This indicator helps identify trend direction based on a 15-minute 20 SMA compared against a 10 EMA applied to that SMA.
Trend Logic:
Bullish → 20 SMA crosses above 10 EMA (on SMA values)
Bearish → 20 SMA crosses below 10 EMA (on SMA values)
Neutral → No crossover (trend continues from previous state)
Display:
A compact trend table appears on the chart (top-right), showing the current trend with customizable colors, font size, and background.
Alerts:
Alerts are triggered only when the trend changes (from Bullish → Bearish or Bearish → Bullish).
This prevents repeated alerts on every bar.
✅ Useful for:
Confirming higher timeframe trend bias
Filtering trades in choppy markets
Getting notified instantly when the trend flips
DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard"
This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module.
________________________________________
1. Price and Daily Reference Points
The dashboard displays the current price, along with percentage change compared to the day’s opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range.
For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges.
________________________________________
2. VWAP (Volume Weighted Average Price)
VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it.
For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups.
________________________________________
3. Volume Analysis
The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage.
This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends.
________________________________________
4. RSI (Relative Strength Index)
RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars.
RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification.
________________________________________
5. MACD (Moving Average Convergence Divergence)
The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a “bullish cross” (MACD above signal line) or “bearish cross” (MACD below signal line) has occurred.
MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis.
________________________________________
6. Stochastic Oscillator
This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20).
Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic “flips” can align with volume surges or daily range endpoints.
________________________________________
7. Trend & Momentum Classification
The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (“bullish hold”, “bearish hold”, or neutral).
This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly.
________________________________________
8. Accumulation / Distribution Bias
Based on RSI levels, the script generates simplified tags such as “Accumulate Long”, “Accumulate Short”, or “Wait”.
This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing.
________________________________________
9. Overall Market Status and Score
Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal.
This scoring system isn’t a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align.
Extended Study Material with Formulas
________________________________________
1. Daily Reference Levels (High, Low, Open, Median, Range)
• Day High (H): Maximum price of the session.
DayHigh=max(Hightoday)DayHigh=max(Hightoday)
• Day Low (L): Minimum price of the session.
DayLow=min(Lowtoday)DayLow=min(Lowtoday)
• Day Open (O): Opening price of the session.
DayOpen=OpentodayDayOpen=Opentoday
• Day Range:
Range=DayHigh−DayLowRange=DayHigh−DayLow
• Median: Mid-point between high and low.
Median=DayHigh+DayLow2Median=2DayHigh+DayLow
These act as intraday guideposts for seeing how far the price has stretched from its key reference levels.
________________________________________
2. VWAP (Volume Weighted Average Price)
VWAP considers both price and volume for a weighted average:
VWAPt=∑i=1t(Pricei×Volumei)∑i=1tVolumeiVWAPt=∑i=1tVolumei∑i=1t(Pricei×Volumei)
Here, Price_i can be the average price (High + Low + Close) ÷ 3, also known as hlc3.
• Interpretation: Price above VWAP = bullish bias; Price below = bearish bias.
________________________________________
3. Volume Buy/Sell Analysis
The dashboard splits total volume into buy volume and sell volume based on candle type.
• Buy Volume:
BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0
• Sell Volume:
SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0
• Buy Ratio (%):
VolumeRatio=BuyVolBuyVol+SellVol×100VolumeRatio=BuyVol+SellVolBuyVol×100
This helps traders gauge who is in control during a session—buyers or sellers.
________________________________________
4. RSI (Relative Strength Index)
RSI measures strength of momentum by comparing gains vs. losses.
Step 1: Compute average gains (AG) and losses (AL).
AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods
Step 2: Calculate relative strength (RS).
RS=AGALRS=ALAG
Step 3: RSI formula.
RSI=100−1001+RSRSI=100−1+RS100
• Used to detect overbought (>70), oversold (<30), or neutral momentum zones.
________________________________________
5. MACD (Moving Average Convergence Divergence)
• Fast EMA:
EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast)
• Slow EMA:
EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow)
• MACD Line:
MACD=EMAfast−EMAslowMACD=EMAfast−EMAslow
• Signal Line:
Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal)
• Histogram:
Histogram=MACD−SignalHistogram=MACD−Signal
Crossovers between MACD and Signal are used in studying bullish/bearish phases.
________________________________________
6. Stochastic Oscillator
Stochastic compares the current close against a range of highs and lows.
%K=Close−LowestLowHighestHigh−LowestLow×100%K=HighestHigh−LowestLowClose−LowestLow×100
Where LowestLow and HighestHigh are the lowest and highest values over N periods.
The %D line is a smooth version of %K (using a moving average).
%D=SMA(%K,smooth)%D=SMA(%K,smooth)
• Values above 80 = overbought; below 20 = oversold.
________________________________________
7. Trend and Momentum Classification
This dashboard generates simplified trend/momentum logic using RSI.
• Trend:
• RSI < 40 → Downtrend
• RSI > 60 → Uptrend
• In Between → Neutral
• Momentum Bias:
• RSI > 70 → Bullish Hold
• RSI < 30 → Bearish Hold
• Otherwise Neutral
This is not predictive, only a classification framework for educational use.
________________________________________
8. Accumulation/Distribution Bias
Based on extreme RSI values:
• RSI < 25 → Accumulate Long Bias
• RSI > 80 → Accumulate Short Bias
• Else → Wait/No Action
This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking).
________________________________________
9. Overall Market Status and Score
The tool adds up 5 bullish conditions:
1. Price above VWAP
2. RSI > 50
3. MACD > Signal
4. Stochastic > 50
5. Price above Daily Median
BullishScore=ConditionsMet5×100BullishScore=5ConditionsMet×100
Then it categorizes the market:
• RSI > 70 or Stoch > 80 → Overbought
• RSI < 30 or Stoch < 20 → Oversold
• Else → Normal
This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals.
________________________________________
⚠️ Warning:
• Trading financial markets involves substantial risk.
• You can lose more money than you invest.
• Past performance of indicators does not guarantee future results.
• This script must not be copied, resold, or republished without authorization from aiTrendview.
By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice.
________________________________________
⚠️ Disclaimer and Warning (From aiTrendview)
This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the user’s own risk. Markets are inherently risky; losses can exceed initial investment.
The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels.
**The Solution:** This script implements an integrated approach that:
- Maps volume distribution across price levels using configurable row density
- Estimates delta (buying vs selling pressure) using three different methodologies
- Identifies Point of Control (highest volume price level) for key support/resistance
- Calculates Value Area boundaries where 70% of volume traded
- Provides real-time alerts for key level interactions and volume imbalances
**Unique Features:**
1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete
2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions
3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance
4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes
5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds
6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Volume Profile Methodology:
**1. Price Level Distribution:**
- Divides price range into user-defined rows (10-50 configurable)
- Calculates row height: `(Highest Price - Lowest Price) / Number of Rows`
- Distributes each bar's volume across price levels it touched proportionally
**2. Delta Volume Calculation Methods:**
**Price Action Method:**
```
Price Range = High - Low
Buy Pressure = (Close - Low) / Price Range
Sell Pressure = (High - Close) / Price Range
Buy Volume = Total Volume × Buy Pressure
Sell Volume = Total Volume × Sell Pressure
Delta = Buy Volume - Sell Volume
```
**Bid/Ask Estimation Method:**
```
Average Price = (High + Low + Close) / 3
Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4
Sell Volume = Total Volume - Buy Volume
```
**Cumulative Method:**
```
Buy Volume = Close > Open ? Volume : Volume × 0.3
Sell Volume = Close ≤ Open ? Volume : Volume × 0.3
```
**3. Point of Control (POC) Identification:**
- Scans all price levels to find maximum volume concentration
- POC represents the price level with highest trading activity
- Acts as significant support/resistance level
- **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation.
**4. Value Area Calculation:**
- Starts from POC and expands up/down to encompass 70% of total volume
- VAH (Value Area High): Upper boundary of value area
- VAL (Value Area Low): Lower boundary of value area
- Expansion algorithm prioritizes direction with higher volume
**5. Adaptive Range Selection:**
Based on profile type and timeframe optimization:
- **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars)
- **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days)
- **Session**: Current trading session or custom session times
### Performance Optimization Features:
- **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy
- **Memory Management**: Clears previous drawings to prevent performance degradation
- **Safety Constraints**: Prevents excessive memory usage with configurable limits
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Profile Configuration**: Select profile type based on trading style:
- N Bars Back: Precise control over data range
- Days Back: Intuitive calendar-based analysis
- Session: Real-time session development
2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance
3. **Delta Method**: Choose calculation method based on market type:
- Price Action: Best for trending markets
- Bid/Ask Estimate: Good for ranging markets
- Cumulative: Smoothed approach for volatile markets
4. **Visual Settings**: Configure colors, position (left/right), and display options
### Reading the Profile:
**Volume Bars:**
- **Length**: Represents relative volume at that price level
- **Color**: Green = net buying pressure, Red = net selling pressure
- **Intensity**: Darker colors indicate volume imbalances above threshold
**Key Levels:**
- **POC (Blue Line)**: Highest volume price - major support/resistance
- **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value
- **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value
- **Value Area Fill**: Shaded region showing main trading range
**Developing POC Trail:**
- **Blue Dotted Lines**: Show real-time POC evolution throughout the session
- **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution
- **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity
- **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment
### Trading Applications:
**Support/Resistance Analysis:**
- POC acts as magnetic price level - expect reactions
- VAH/VAL provide intermediate support/resistance levels
- Profile edges show areas of low volume acceptance
**Developing POC Analysis:**
- **Upward Migration**: POC moving higher = institutional accumulation, bullish bias
- **Downward Migration**: POC moving lower = institutional distribution, bearish bias
- **Stable POC**: Tight clustering = balanced market, range-bound conditions
- **Early Trend Detection**: POC direction change often precedes price breakouts
**Entry Strategies:**
- Buy at VAL with POC as target (in uptrends)
- Sell at VAH with POC as target (in downtrends)
- Breakout plays above/below profile extremes
**Volume Imbalance Trading:**
- Strong buying imbalance (>60% threshold) suggests continued upward pressure
- Strong selling imbalance suggests continued downward pressure
- Imbalances near key levels provide high-probability setups
**Multi-Timeframe Context:**
- Use higher timeframe profiles for major levels
- Lower timeframe profiles for precise entries
- Session profiles for intraday trading structure
## SCRIPT SETTINGS EXPLANATION
### Volume Profile Settings:
- **Profile Type**: Determines data range for calculation
- N Bars Back: Exact number of bars (20-500 range)
- Days Back: Calendar days with timeframe adaptation (1-365 days)
- Session: Trading session-based (intraday focus)
- **Number of Rows**: Profile resolution (10-50 range)
- **Profile Width**: Visual width as chart percentage (10-50%)
- **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard)
- **Auto-Adjust**: Automatically optimizes for different timeframes
### Delta Volume Settings:
- **Show Delta Volume**: Enable/disable delta calculations
- **Delta Calculation Method**: Choose methodology based on market conditions
- **Highlight Imbalances**: Visual emphasis for significant volume imbalances
- **Imbalance Threshold**: Percentage for imbalance detection (50-90%)
### Session Settings:
- **Session Type**: Daily, Weekly, Monthly, or Custom periods
- **Custom Session Time**: Define specific trading hours
- **Previous Sessions**: Number of historical sessions to display
### Days Back Settings:
- **Lookback Days**: Number of calendar days to analyze (1-365)
- **Automatic Calculation**: Script automatically converts days to bars based on timeframe:
- Intraday: Accounts for 6.5 trading hours per day
- Daily: 1 bar per day
- Weekly/Monthly: Proportional adjustment
### N Bars Back Settings:
- **Lookback Bars**: Exact number of bars to analyze (20-500)
- **Precise Control**: Best for systematic analysis and backtesting
### Visual Customization:
- **Colors**: Bullish (green), Bearish (red), and level colors
- **Profile Position**: Left or Right side of chart
- **Profile Offset**: Distance from current price action
- **Labels**: Show/hide level labels and values
- **Smooth Profile Bars**: Enhanced visual appearance
### Alert Configuration:
- **POC Touch**: Alerts when price interacts with Point of Control
- **VA Entry/Exit**: Alerts for Value Area boundary interactions
- **Major Imbalance**: Alerts for significant volume imbalances
## VISUAL FEATURES
### Profile Display:
- **Horizontal Bars**: Volume distribution across price levels
- **Color Coding**: Delta-based coloring for directional bias
- **Smooth Rendering**: Optional smoothing for cleaner appearance
- **Transparency**: Configurable opacity for chart readability
### Level Lines:
- **POC**: Solid blue line with optional label
- **VAH/VAL**: Dashed colored lines with value displays
- **Extension**: Lines extend across relevant time periods
- **Value Area Fill**: Optional shaded region between VAH/VAL
### Information Table:
- **Current Values**: Real-time POC, VAH, VAL prices
- **VA Range**: Value Area width calculation
- **Positioning**: Multiple table positions available
- **Text Sizing**: Adjustable for different screen sizes
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- Volume profile analysis provides structural context, not trading signals
- Delta calculations are estimations based on price action, not actual order flow
- Past volume distribution does not guarantee future price behavior
- Combine with other analysis methods for comprehensive market view
**Best Practices:**
- Use appropriate profile types for your trading style:
- Day Trading: Session or Days Back (1-5 days)
- Swing Trading: Days Back (10-30 days) or N Bars Back
- Position Trading: Days Back (60-180 days)
- Consider market context (trending vs ranging conditions)
- Verify key levels with additional technical analysis
- Monitor profile development for changing market structure
**Performance Considerations:**
- Higher row counts increase calculation complexity
- Large lookback periods may affect chart performance
- Auto-adjust feature optimizes for most use cases
- Consider using session profiles for intraday efficiency
**Limitations:**
- Delta calculations are estimations, not actual transaction data
- Profile accuracy depends on available price/volume history
- Effectiveness varies across different instruments and market conditions
- Requires understanding of volume profile concepts for optimal use
**Data Requirements:**
- Requires volume data for accurate calculations
- Works best on liquid instruments with consistent volume
- May be less effective on very low volume or exotic instruments
This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
Bottom Reversal Radar — Berk v1.4Bottom Reversal Radar — Berk v1.4
What it does:
Combines RSI recovery after oversold, MACD bull cross, close above EMA8, near-EMA200 proximity, volume expansion, and simple bullish divergence (pivot lows) into a single score.
Signal: Trigger when Score ≥ Threshold (default 3). Set alert via Create Alert → “Dipten Dönüş — Ana Sinyal” → Once per bar close.
How it works
RSI recovery: After touching oversold (30), RSI crosses up 35 within last X bars.
MACD bull cross: MACD Line crosses above Signal.
Close above EMA8 and BOS (close above recent swing high) confirm momentum.
Near EMA200: Price within −5%…+2% band adds a point.
Volume spike: Volume ≥ 1.5× SMA(20) adds a point.
Bullish divergence: Lower price low + higher RSI low (pivot 3/3) adds a point.
Inputs
RSI(14), rsiOS=30, rsiRecover=35, Volume SMA(20) with 1.5× multiplier, EMA200 proximity band −5%…+2%, lookbackBars=5, Score threshold default 3.
Usage tips
Best on Daily / 4H. If too many false positives: raise threshold to 4 and volume to 1.8–2.0×.
Pair with Screener filters: RSI≥35, MACD Line>Signal, Price above EMA8, Volume/Avg(20)≥1.5, and near EMA200 (%).
Disclaimer
For educational purposes only. Not financial advice.
Release notes (v1.4)
Fixed bullDiv typo; simplified visuals; Pine v5.
Tags: rsi, macd, ema, volume, divergence, reversal, trend, screener, bist, stocks, crypto
Seasonality Monte Carlo Forecaster [BackQuant]Seasonality Monte Carlo Forecaster
Plain-English overview
This tool projects a cone of plausible future prices by combining two ideas that traders already use intuitively: seasonality and uncertainty. It watches how your market typically behaves around this calendar date, turns that seasonal tendency into a small daily “drift,” then runs many randomized price paths forward to estimate where price could land tomorrow, next week, or a month from now. The result is a probability cone with a clear expected path, plus optional overlays that show how past years tended to move from this point on the calendar. It is a planning tool, not a crystal ball: the goal is to quantify ranges and odds so you can size, place stops, set targets, and time entries with more realism.
What Monte Carlo is and why quants rely on it
• Definition . Monte Carlo simulation is a way to answer “what might happen next?” when there is randomness in the system. Instead of producing a single forecast, it generates thousands of alternate futures by repeatedly sampling random shocks and adding them to a model of how prices evolve.
• Why it is used . Markets are noisy. A single point forecast hides risk. Monte Carlo gives a distribution of outcomes so you can reason in probabilities: the median path, the 68% band, the 95% band, tail risks, and the chance of hitting a specific level within a horizon.
• Core strengths in quant finance .
– Path-dependent questions : “What is the probability we touch a stop before a target?” “What is the expected drawdown on the way to my objective?”
– Pricing and risk : Useful for path-dependent options, Value-at-Risk (VaR), expected shortfall (CVaR), stress paths, and scenario analysis when closed-form formulas are unrealistic.
– Planning under uncertainty : Portfolio construction and rebalancing rules can be tested against a cloud of plausible futures rather than a single guess.
• Why it fits trading workflows . It turns gut feel like “seasonality is supportive here” into quantitative ranges: “median path suggests +X% with a 68% band of ±Y%; stop at Z has only ~16% odds of being tagged in N days.”
How this indicator builds its probability cone
1) Seasonal pattern discovery
The script builds two day-of-year maps as new data arrives:
• A return map where each calendar day stores an exponentially smoothed average of that day’s log return (yesterday→today). The smoothing (90% old, 10% new) behaves like an EWMA, letting older seasons matter while adapting to new information.
• A volatility map that tracks the typical absolute return for the same calendar day.
It calculates the day-of-year carefully (with leap-year adjustment) and indexes into a 365-slot seasonal array so “March 18” is compared with past March 18ths. This becomes the seasonal bias that gently nudges simulations up or down on each forecast day.
2) Choice of randomness engine
You can pick how the future shocks are generated:
• Daily mode uses a Gaussian draw with the seasonal bias as the mean and a volatility that comes from realized returns, scaled down to avoid over-fitting. It relies on the Box–Muller transform internally to turn two uniform random numbers into one normal shock.
• Weekly mode uses bootstrap sampling from the seasonal return history (resampling actual historical daily drifts and then blending in a fraction of the seasonal bias). Bootstrapping is robust when the empirical distribution has asymmetry or fatter tails than a normal distribution.
Both modes seed their random draws deterministically per path and day, which makes plots reproducible bar-to-bar and avoids flickering bands.
3) Volatility scaling to current conditions
Markets do not always live in average volatility. The engine computes a simple volatility factor from ATR(20)/price and scales the simulated shocks up or down within sensible bounds (clamped between 0.5× and 2.0×). When the current regime is quiet, the cone narrows; when ranges expand, the cone widens. This prevents the classic mistake of projecting calm markets into a storm or vice versa.
4) Many futures, summarized by percentiles
The model generates a matrix of price paths (capped at 100 runs for performance inside TradingView), each path stepping forward for your selected horizon. For each forecast day it sorts the simulated prices and pulls key percentiles:
• 5th and 95th → approximate 95% band (outer cone).
• 16th and 84th → approximate 68% band (inner cone).
• 50th → the median or “expected path.”
These are drawn as polylines so you can immediately see central tendency and dispersion.
5) A historical overlay (optional)
Turn on the overlay to sketch a dotted path of what a purely seasonal projection would look like for the next ~30 days using only the return map, no randomness. This is not a forecast; it is a visual reminder of the seasonal drift you are biasing toward.
Inputs you control and how to think about them
Monte Carlo Simulation
• Price Series for Calculation . The source series, typically close.
• Enable Probability Forecasts . Master switch for simulation and drawing.
• Simulation Iterations . Requested number of paths to run. Internally capped at 100 to protect performance, which is generally enough to estimate the percentiles for a trading chart. If you need ultra-smooth bands, shorten the horizon.
• Forecast Days Ahead . The length of the cone. Longer horizons dilute seasonal signal and widen uncertainty.
• Probability Bands . Draw all bands, just 95%, just 68%, or a custom level (display logic remains 68/95 internally; the custom number is for labeling and color choice).
• Pattern Resolution . Daily leans on day-of-year effects like “turn-of-month” or holiday patterns. Weekly biases toward day-of-week tendencies and bootstraps from history.
• Volatility Scaling . On by default so the cone respects today’s range context.
Plotting & UI
• Probability Cone . Plots the outer and inner percentile envelopes.
• Expected Path . Plots the median line through the cone.
• Historical Overlay . Dotted seasonal-only projection for context.
• Band Transparency/Colors . Customize primary (outer) and secondary (inner) band colors and the mean path color. Use higher transparency for cleaner charts.
What appears on your chart
• A cone starting at the most recent bar, fanning outward. The outer lines are the ~95% band; the inner lines are the ~68% band.
• A median path (default blue) running through the center of the cone.
• An info panel on the final historical bar that summarizes simulation count, forecast days, number of seasonal patterns learned, the current day-of-year, expected percentage return to the median, and the approximate 95% half-range in percent.
• Optional historical seasonal path drawn as dotted segments for the next 30 bars.
How to use it in trading
1) Position sizing and stop logic
The cone translates “volatility plus seasonality” into distances.
• Put stops outside the inner band if you want only ~16% odds of a stop-out due to noise before your thesis can play.
• Size positions so that a test of the inner band is survivable and a test of the outer band is rare but acceptable.
• If your target sits inside the 68% band at your horizon, the payoff is likely modest; outside the 68% but inside the 95% can justify “one-good-push” trades; beyond the 95% band is a low-probability flyer—consider scaling plans or optionality.
2) Entry timing with seasonal bias
When the median path slopes up from this calendar date and the cone is relatively narrow, a pullback toward the lower inner band can be a high-quality entry with a tight invalidation. If the median slopes down, fade rallies toward the upper band or step aside if it clashes with your system.
3) Target selection
Project your time horizon to N bars ahead, then pick targets around the median or the opposite inner band depending on your style. You can also anchor dynamic take-profits to the moving median as new bars arrive.
4) Scenario planning & “what-ifs”
Before events, glance at the cone: if the 95% band already spans a huge range, trade smaller, expect whips, and avoid placing stops at obvious band edges. If the cone is unusually tight, consider breakout tactics and be ready to add if volatility expands beyond the inner band with follow-through.
5) Options and vol tactics
• When the cone is tight : Prefer long gamma structures (debit spreads) only if you expect a regime shift; otherwise premium selling may dominate.
• When the cone is wide : Debit structures benefit from range; credit spreads need wider wings or smaller size. Align with your separate IV metrics.
Reading the probability cone like a pro
• Cone slope = seasonal drift. Upward slope means the calendar has historically favored positive drift from this date, downward slope the opposite.
• Cone width = regime volatility. A widening fan tells you that uncertainty grows fast; a narrow cone says the market typically stays contained.
• Mean vs. price gap . If spot trades well above the median path and the upper band, mean-reversion risk is high. If spot presses the lower inner band in an up-sloping cone, you are in the “buy fear” zone.
• Touches and pierces . Touching the inner band is common noise; piercing it with momentum signals potential regime change; the outer band should be rare and often brings snap-backs unless there is a structural catalyst.
Methodological notes (what the code actually does)
• Log returns are used for additivity and better statistical behavior: sim_ret is applied via exp(sim_ret) to evolve price.
• Seasonal arrays are updated online with EWMA (90/10) so the model keeps learning as each bar arrives.
• Leap years are handled; indexing still normalizes into a 365-slot map so the seasonal pattern remains stable.
• Gaussian engine (Daily mode) centers shocks on the seasonal bias with a conservative standard deviation.
• Bootstrap engine (Weekly mode) resamples from observed seasonal returns and adds a fraction of the bias, which captures skew and fat tails better.
• Volatility adjustment multiplies each daily shock by a factor derived from ATR(20)/price, clamped between 0.5 and 2.0 to avoid extreme cones.
• Performance guardrails : simulations are capped at 100 paths; the probability cone uses polylines (no heavy fills) and only draws on the last confirmed bar to keep charts responsive.
• Prerequisite data : at least ~30 seasonal entries are required before the model will draw a cone; otherwise it waits for more history.
Strengths and limitations
• Strengths :
– Probabilistic thinking replaces single-point guessing.
– Seasonality adds a small but meaningful directional bias that many markets exhibit.
– Volatility scaling adapts to the current regime so the cone stays realistic.
• Limitations :
– Seasonality can break around structural changes, policy shifts, or one-off events.
– The number of paths is performance-limited; percentile estimates are good for trading, not for academic precision.
– The model assumes tomorrow’s randomness resembles recent randomness; if regime shifts violently, the cone will lag until the EWMA adapts.
– Holidays and missing sessions can thin the seasonal sample for some assets; be cautious with very short histories.
Tuning guide
• Horizon : 10–20 bars for tactical trades; 30+ for swing planning when you care more about broad ranges than precise targets.
• Iterations : The default 100 is enough for stable 5/16/50/84/95 percentiles. If you crave smoother lines, shorten the horizon or run on higher timeframes.
• Daily vs. Weekly : Daily for equities and crypto where month-end and turn-of-month effects matter; Weekly for futures and FX where day-of-week behavior is strong.
• Volatility scaling : Keep it on. Turn off only when you intentionally want a “pure seasonality” cone unaffected by current turbulence.
Workflow examples
• Swing continuation : Cone slopes up, price pulls into the lower inner band, your system fires. Enter near the band, stop just outside the outer line for the next 3–5 bars, target near the median or the opposite inner band.
• Fade extremes : Cone is flat or down, price gaps to the upper outer band on news, then stalls. Favor mean-reversion toward the median, size small if volatility scaling is elevated.
• Event play : Before CPI or earnings on a proxy index, check cone width. If the inner band is already wide, cut size or prefer options structures that benefit from range.
Good habits
• Pair the cone with your entry engine (breakout, pullback, order flow). Let Monte Carlo do range math; let your system do signal quality.
• Do not anchor blindly to the median; recalc after each bar. When the cone’s slope flips or width jumps, the plan should adapt.
• Validate seasonality for your symbol and timeframe; not every market has strong calendar effects.
Summary
The Seasonality Monte Carlo Forecaster wraps institutional risk planning into a single overlay: a data-driven seasonal drift, realistic volatility scaling, and a probabilistic cone that answers “where could we be, with what odds?” within your trading horizon. Use it to place stops where randomness is less likely to take you out, to set targets aligned with realistic travel, and to size positions with confidence born from distributions rather than hunches. It will not predict the future, but it will keep your decisions anchored to probabilities—the language markets actually speak.
Correlation HeatMap Matrix Data [TradingFinder]🔵 Introduction
Correlation is a statistical measure that shows the degree and direction of a linear relationship between two assets.
Its value ranges from -1 to +1 : +1 means perfect positive correlation, 0 means no linear relationship, and -1 means perfect negative correlation.
In financial markets, correlation is used for portfolio diversification, risk management, pairs trading, intermarket analysis, and identifying divergences.
Correlation HeatMap Matrix Data TradingFinder is a Pine Script v6 library that calculates and returns raw correlation matrix data between up to 20 symbols. It only provides the data – it does not draw or render the heatmap – making it ideal for use in other scripts that handle visualization or further analysis. The library uses ta.correlation for fast and accurate calculations.
It also includes two helper functions for visual styling :
CorrelationColor(corr) : takes the correlation value as input and generates a smooth gradient color, ranging from strong negative to strong positive correlation.
CorrelationTextColor(corr) : takes the correlation value as input and returns a text color that ensures optimal contrast over the background color.
Library
"Correlation_HeatMap_Matrix_Data_TradingFinder"
CorrelationColor(corr)
Parameters:
corr (float)
CorrelationTextColor(corr)
Parameters:
corr (float)
Data_Matrix(Corr_Period, Sym_1, Sym_2, Sym_3, Sym_4, Sym_5, Sym_6, Sym_7, Sym_8, Sym_9, Sym_10, Sym_11, Sym_12, Sym_13, Sym_14, Sym_15, Sym_16, Sym_17, Sym_18, Sym_19, Sym_20)
Parameters:
Corr_Period (int)
Sym_1 (string)
Sym_2 (string)
Sym_3 (string)
Sym_4 (string)
Sym_5 (string)
Sym_6 (string)
Sym_7 (string)
Sym_8 (string)
Sym_9 (string)
Sym_10 (string)
Sym_11 (string)
Sym_12 (string)
Sym_13 (string)
Sym_14 (string)
Sym_15 (string)
Sym_16 (string)
Sym_17 (string)
Sym_18 (string)
Sym_19 (string)
Sym_20 (string)
🔵 How to use
Import the library into your Pine Script using the import keyword and its full namespace.
Decide how many symbols you want to include in your correlation matrix (up to 20). Each symbol must be provided as a string, for example FX:EURUSD .
Choose the correlation period (Corr\_Period) in bars. This is the lookback window used for the calculation, such as 20, 50, or 100 bars.
Call Data_Matrix(Corr_Period, Sym_1, ..., Sym_20) with your selected parameters. The function will return an array containing the correlation values for every symbol pair (upper triangle of the matrix plus diagonal).
For example :
var string Sym_1 = '' , var string Sym_2 = '' , var string Sym_3 = '' , var string Sym_4 = '' , var string Sym_5 = '' , var string Sym_6 = '' , var string Sym_7 = '' , var string Sym_8 = '' , var string Sym_9 = '' , var string Sym_10 = ''
var string Sym_11 = '', var string Sym_12 = '', var string Sym_13 = '', var string Sym_14 = '', var string Sym_15 = '', var string Sym_16 = '', var string Sym_17 = '', var string Sym_18 = '', var string Sym_19 = '', var string Sym_20 = ''
switch Market
'Forex' => Sym_1 := 'EURUSD' , Sym_2 := 'GBPUSD' , Sym_3 := 'USDJPY' , Sym_4 := 'USDCHF' , Sym_5 := 'USDCAD' , Sym_6 := 'AUDUSD' , Sym_7 := 'NZDUSD' , Sym_8 := 'EURJPY' , Sym_9 := 'EURGBP' , Sym_10 := 'GBPJPY'
,Sym_11 := 'AUDJPY', Sym_12 := 'EURCHF', Sym_13 := 'EURCAD', Sym_14 := 'GBPCAD', Sym_15 := 'CADJPY', Sym_16 := 'CHFJPY', Sym_17 := 'NZDJPY', Sym_18 := 'AUDNZD', Sym_19 := 'USDSEK' , Sym_20 := 'USDNOK'
'Stock' => Sym_1 := 'NVDA' , Sym_2 := 'AAPL' , Sym_3 := 'GOOGL' , Sym_4 := 'GOOG' , Sym_5 := 'META' , Sym_6 := 'MSFT' , Sym_7 := 'AMZN' , Sym_8 := 'AVGO' , Sym_9 := 'TSLA' , Sym_10 := 'BRK.B'
,Sym_11 := 'UNH' , Sym_12 := 'V' , Sym_13 := 'JPM' , Sym_14 := 'WMT' , Sym_15 := 'LLY' , Sym_16 := 'ORCL', Sym_17 := 'HD' , Sym_18 := 'JNJ' , Sym_19 := 'MA' , Sym_20 := 'COST'
'Crypto' => Sym_1 := 'BTCUSD' , Sym_2 := 'ETHUSD' , Sym_3 := 'BNBUSD' , Sym_4 := 'XRPUSD' , Sym_5 := 'SOLUSD' , Sym_6 := 'ADAUSD' , Sym_7 := 'DOGEUSD' , Sym_8 := 'AVAXUSD' , Sym_9 := 'DOTUSD' , Sym_10 := 'TRXUSD'
,Sym_11 := 'LTCUSD' , Sym_12 := 'LINKUSD', Sym_13 := 'UNIUSD', Sym_14 := 'ATOMUSD', Sym_15 := 'ICPUSD', Sym_16 := 'ARBUSD', Sym_17 := 'APTUSD', Sym_18 := 'FILUSD', Sym_19 := 'OPUSD' , Sym_20 := 'USDT.D'
'Custom' => Sym_1 := Sym_1_C , Sym_2 := Sym_2_C , Sym_3 := Sym_3_C , Sym_4 := Sym_4_C , Sym_5 := Sym_5_C , Sym_6 := Sym_6_C , Sym_7 := Sym_7_C , Sym_8 := Sym_8_C , Sym_9 := Sym_9_C , Sym_10 := Sym_10_C
,Sym_11 := Sym_11_C, Sym_12 := Sym_12_C, Sym_13 := Sym_13_C, Sym_14 := Sym_14_C, Sym_15 := Sym_15_C, Sym_16 := Sym_16_C, Sym_17 := Sym_17_C, Sym_18 := Sym_18_C, Sym_19 := Sym_19_C , Sym_20 := Sym_20_C
= Corr.Data_Matrix(Corr_period, Sym_1 ,Sym_2 ,Sym_3 ,Sym_4 ,Sym_5 ,Sym_6 ,Sym_7 ,Sym_8 ,Sym_9 ,Sym_10,Sym_11,Sym_12,Sym_13,Sym_14,Sym_15,Sym_16,Sym_17,Sym_18,Sym_19,Sym_20)
Loop through or index into this array to retrieve each correlation value for your custom layout or logic.
Pass each correlation value to CorrelationColor() to get the corresponding gradient background color, which reflects the correlation’s strength and direction (negative to positive).
For example :
Corr.CorrelationColor(SYM_3_10)
Pass the same correlation value to CorrelationTextColor() to get the correct text color for readability against that background.
For example :
Corr.CorrelationTextColor(SYM_1_1)
Use these colors in a table or label to render your own heatmap or any other visualization you need.
Scanner ADX & VolumenThis indicator is a market scanner specifically designed for scalping traders. Its function is to simultaneously monitor 30 cryptocurrency pairs from the BingX exchange to identify entry opportunities based on the start of a new, strengthening trend.
Strategy and Logic:
The scanner is based on the combination of two key conditions on a 15-minute timeframe:
Trend Strength (ADX): The primary signal is generated when the ADX (Average Directional Index) crosses above the 20 level. An ADX moving above this threshold suggests that the market is breaking out of a consolidation phase and that a new trend (either bullish or bearish) is beginning to gain strength.
Volume Confirmation: To validate the ADX signal, the indicator checks if the current candle's volume is higher than its simple moving average (defaulting to 20 periods). An increase in volume confirms market interest and participation, adding greater reliability to the emerging move.
How to Use It:
The indicator displays a table in the top-right corner of your chart with the following information:
Par: The name of the cryptocurrency pair.
ADX: The current ADX value. It turns green when it exceeds the 20 level.
Volume: Shows "OK" if the current volume is higher than its average.
Signal: This is the most important column. When both conditions (ADX crossover and high volume) are met, it will display the message "¡ENTRADA!" ("ENTRY!") with a highlighted background, alerting you to a potential trading opportunity.
In summary, this scanner saves you the effort of manually analyzing 30 charts, allowing you to focus solely on the assets that present the best conditions for a scalping trade.
Scanner ADX & Volumen This indicator is a market scanner specifically designed for scalping traders. Its function is to simultaneously monitor 30 cryptocurrency pairs from the BingX exchange to identify entry opportunities based on the start of a new, strengthening trend.
Strategy and Logic:
The scanner is based on the combination of two key conditions on a 15-minute timeframe:
Trend Strength (ADX): The primary signal is generated when the ADX (Average Directional Index) crosses above the 20 level. An ADX moving above this threshold suggests that the market is breaking out of a consolidation phase and that a new trend (either bullish or bearish) is beginning to gain strength.
Volume Confirmation: To validate the ADX signal, the indicator checks if the current candle's volume is higher than its simple moving average (defaulting to 20 periods). An increase in volume confirms market interest and participation, adding greater reliability to the emerging move.
How to Use It:
The indicator displays a table in the top-right corner of your chart with the following information:
Par: The name of the cryptocurrency pair.
ADX: The current ADX value. It turns green when it exceeds the 20 level.
Volume: Shows "OK" if the current volume is higher than its average.
Signal: This is the most important column. When both conditions (ADX crossover and high volume) are met, it will display the message "¡ENTRADA!" ("ENTRY!") with a highlighted background, alerting you to a potential trading opportunity.
In summary, this scanner saves you the effort of manually analyzing 30 charts, allowing you to focus solely on the assets that present the best conditions for a scalping trade.
Volume Rotor Clock [hapharmonic]🕰️ Volume Rotor Clock
The Volume Rotor Clock is an indicator that separates buy and sell volume, compiling these volumes over a recent number of bars or a specified past period, as defined by the user. This helps to reveal accumulation (buying) or distribution (selling) behavior, showing which side has superior volume. With its unique and beautiful display, the Volume Rotor Clock is more than just a timepiece; it's a dynamic dashboard that visualizes the buying and selling pressure of your favorite symbols, all wrapped in an elegant and fully customizable interface.
Instead of just tracking price, this indicator focuses on the engine behind the movement: volume. It helps you instantly identify which assets are under accumulation (buying) and which are under distribution (selling).
---
🎨 20 Pre-configured Templates
---
🧐 Interpreting the Clock Display
The interface is designed to give you multiple layers of information at a glance. Let's break down what each part represents.
1. The Main Clock Hands (Current Chart Symbol)
The clock hands—hour, minute, and second—are dedicated to the symbol on your current active chart .
Minute Hand: Displays the base currency of the current symbol (e.g., USDT, USD) at its tip.
Hour Hand: Displays the percentage of the winning volume side (buy vs. sell) at its tip.
Color Gauge: The color of the text characters at the tip of both the hour and minute hands acts as your primary volume gauge for the current symbol.
If buy volume is dominant , the text will be green .
If sell volume is dominant , the text will be red .
Tooltip: Hovering your mouse over the text at the tip of the hour or minute or other spherical elements hand will reveal a detailed tooltip with the precise Buy Volume, Sell Volume, Total Volume, Buy %, and Sell % for the current chart's symbol.
2. The Volume Scanner: Bulls & Bears (Symbols Inside the Clock) 🐂🐻
The circular symbols scattered inside the clock face are your multi-symbol volume scanner. They represent the assets you've selected in the indicator's settings.
Green Circles (Bulls - Upper Half): These represent symbols from your list where the total buy volume is greater than the total sell volume over the defined "Lookback" period. They are considered to be under bullish accumulation. The size of the circle and its text grows larger as the buy percentage becomes more dominant. The percentage shown within the circle represents the buy volume's share of the total volume, calculated over the 'Lookback (Bars)' you've set.
Red Circles (Bears - Lower Half): These represent symbols where the total sell volume is greater than the total buy volume. They are considered to be under bearish distribution or selling pressure. The size of the circle indicates the dominance of the sell-side volume. The percentage shown within the circle represents the sell volume's share of the total volume, calculated over the 'Lookback (Bars)' you've set.
3. The Bullish Watchlist (Symbols Above the Clock) ⭐
The symbols arranged neatly along the top edge of the clock are the "best of the bulls." They are symbols that are not only bullish but have also passed an additional, powerful strength filter.
What it Means: A symbol appears here when it shows signs of sustained, high-volume buying interest . It's a way to filter out noise and focus on assets with potentially significant accumulation phases.
The Filter Logic: For a bullish symbol (where total buy volume > total sell volume) to be promoted to the watchlist, its trading volume must meet specific criteria based on this formula:
ta.barssince(not(volume > ta.sma(volume, X))) >= Y
In plain English, this means: The indicator checks how many consecutive bars the `volume` has been greater than its `X`-bar Simple Moving Average (`ta.sma(volume, X)`). If this count is greater than or equal to `Y` bars, the condition is met.
(You can configure `X` (Volume MA Length) and `Y` (Consecutive Days Above MA) in the settings.)
Why it's Useful: This filter is powerful because it looks for consistency . A single spike in volume can be an anomaly. However, when an asset's volume remains consistently above its recent average for several consecutive days, it strongly suggests that larger players or a significant portion of the market are actively accumulating the asset. This sustained interest can often precede a significant upward price trend.
---
⚙️ Indicator Settings Explained
The Volume Rotor Clock is highly customizable. Here’s a detailed walkthrough of every setting available in the "Inputs" tab.
🎨 Color Scheme
This group allows you to control the entire aesthetic of the clock.
Template: Choose from a wide variety of professionally designed color themes.
Use Template: A simple checkbox to switch between using a pre-designed theme and creating your own.
`Checked`: You can select a theme from the dropdown menu, which offers 20 unique templates like "Cyberpunk Neon" or "Forest Green". All custom color settings below will be disabled (grayed out and unclickable).
`Unchecked`: The template dropdown is disabled, and you gain full control over every color element in the sections below.
🖌️ Custom Appearance & Colors
These settings are only active when "Use Template" is unchecked.
Flame Head / Tail: Sets the start and end colors for the dynamic flame effect that traces the clock's border, representing the second hand.
Numbers / Main Numbers: Customize the color of the regular hour numbers (1, 2, 4, 5...) and the main cardinal numbers (3, 6, 9, 12).
Sunburst Colors (1-6): Controls the six colors used in the gradient background for the "sunburst" effect inside the clock face.
Hands & Digital: Fine-tune the colors for the Hour/Minute Hand, Second Hand, central Pivot point, and the digital time display.
Chain Color / Width: Customize the appearance of the two chains holding the clock.
📡 Volume Scanner
Control the behavior of the multi-symbol scanner.
Show Scanner Labels: A master switch to show or hide all the bull/bear symbol circles inside the clock.
Lookback (Bars): A crucial setting that defines the calculation period for buy/sell volume for all scanned symbols. The calculation is a sum over the specified number of recent bars.
`0`: Calculates using the current bar only .
`7`: Calculates the sum of volume over the last 8 bars (the current bar + 7 historical bars).
Symbols List: Here you can enable/disable up to 20 slots and input the ticker for each symbol you want to scan (e.g., BINANCE:BTCUSDT , NASDAQ:AAPL ).
⭐ Bullish Watchlist Filter
Configure the criteria for the elite watchlist symbols displayed above the clock.
Enable Watchlist: A master switch to turn the entire watchlist feature on or off.
Volume MA Length: Sets the lookback period `(X)` for the Simple Moving Average of volume used in the filter.
Consecutive Days Above MA: Sets the minimum number of consecutive days `(Y)` that volume must close above its MA to qualify.
Symbols Per Row: Determines the maximum number of watchlist symbols that can fit in a single row before a new row is created above it.
Background / Text Color: When not using a template, you can set custom colors for the watchlist symbols' background and text.
📏 Position & Size
Adjust the clock's placement and dimensions on your chart.
Clock Timezone: Sets the timezone for the digital and analog time display. You can use standard formats like "America/New_York" or enter "Exchange" to sync with the chart's timezone.
Radius (Bars): Controls the overall size of the clock. The radius is measured in terms of the number of bars on the x-axis.
X Offset (Bars): Moves the entire clock horizontally. Positive values shift it to the right; negative values shift it to the left.
Y Offset (Price %): Moves the entire clock vertically as a percentage of your screen's price pane. Positive values move it up; negative values move it down.
Egg vs Tennis Ball — Drop/Rebound StrengthEgg vs Tennis Ball — Drop/Rebound Meter
What it does
Classifies selloffs as either:
Eggs — dead‑cat, no bounce
Tennis Balls — fast, decisive rebound
Core features
Detects swing drops from a Pivot High (PH) to a Pivot Low (PL)
Requires drops to be meaningful (volatility‑aware, ATR‑scaled)
Draws a bounce threshold line and a deadline
Decides outcome based on speed and extent of rebound
Tracks scores and win rates across multiple lookback windows
Includes a color‑coded meter and current streak display
Visuals at a glance
Gray diagonal — drop from PH to PL
Teal dotted horizontal — bounce threshold, from PH to the deadline
Solid green — Tennis Ball (bounce line broken before the deadline)
Solid red — Egg (deadline expired before the bounce)
Optional PH / PL labels for clarity
How the decision is made
1) Find pivots — symmetric pivots using Pivot Left / Right; PL confirms after Right bars.
2) Qualify the drop — Drop Size = PH − PL; must be ≥ (Drop Threshold × ATR at PL).
3) Define the bounce line — PL + (Bounce Multiple × Drop Size). 1.00× = full retrace to PH; up to 2.00× for overshoot.
4) Set the deadline — Drop Bars = PL index − PH index; Deadline = Drop Bars × Recovery Factor; timer starts from PH or PL.
5) Resolve — Tennis Ball if price hits the bounce line before the deadline; Egg if the deadline passes first.
Scoring system (−100 to +100)
+100 = perfect Tennis Ball (fastest possible + full overshoot)
−100 = perfect Egg (no recovery)
In between: scored by rebound speed and extent, shaped by your weight settings
Meter Table
Columns (toggle on/off)
All (off by default)
Last N1 (default 5)
Last N2 (default 10)
Last N3 (default 20)
Rows
Tennis / Eggs — counts
% Tennis — win rate
Avg Score — normalized quality from −100 to +100
Streak — overall (not windowed), e.g., +3 = 3 Tennis Balls in a row, −4 = 4 Eggs in a row
Alerts
Tennis Ball – Fast Rebound — triggers when the bounce line is broken in time
Egg – Window Expired — triggers when the deadline passes without a bounce
Inputs
① Drop Detection
Pivot Left / Right
ATR Length
Drop Threshold × ATR
② Bounce Requirement
Bounce Multiple × Drop Size (0.10–2.00×)
③ Timing
Timer Start — PH or PL
Recovery Factor × Drop Bars
Break Trigger — Close or High
④ Display
Show Pivot/Outcome Labels
Line Width
Table Position (corner)
⑤ Meter Columns
Show All (off by default)
Show N1 / N2 / N3 (5, 10, 20 by default)
⑥ Scoring Weights
Tennis — Base, Speed, Extent
Egg — Base, Strength
How to use it
Pick strictness — start with Drop Threshold = 2.0 ATR, Bounce Multiple = 1.0×, Recovery Factor = 3.0×; adjust to timeframe and volatility.
Watch the dotted line — it ends at the deadline; turns solid green (Tennis) if broken in time, solid red (Egg) if it expires.
Read the meter — short windows (5–10) show current behavior; Avg Score captures quality; Streak shows momentum.
Blend with your system — combine with trend filters, volume, or regime detection.
Tips
Close vs High trigger: Close is stricter; High is more responsive.
PH vs PL timer start: PH measures round‑trip; PL measures recovery only.
Increase pivot strength for fewer, more reliable signals.
Higher timeframes generally produce cleaner patterns.
Defaults
Pivot L/R: 5 / 5
ATR Length: 14
Drop Threshold: 2.0× ATR
Bounce Multiple: 1.00×
Recovery Factor: 3.0×
Break Trigger: Close
Windows: Last 5, 10, 20 (All off)
Interpreting results
Tennis‑y: Avg Score +30 to +70, %Tennis > 55%
Mixed: Avg Score near 0
Egg‑y: Avg Score −30 to −80, %Tennis < 45%