Custom Bollinger Band Squeeze Screener [Pineify]Custom Bollinger Band Squeeze Screener
Key Features
Multi-symbol scanning: Analyze up to 6 tickers simultaneously.
Multi-timeframe flexibility: Screen across four selectable timeframes for each symbol.
Bollinger Band Squeeze algorithm: Detect volatility contraction and imminent breakouts.
Advanced ATR integration: Measure expansion and squeeze states with custom multipliers.
Customizable indicator parameters: Fine-tune Bollinger and ATR settings for tailored detection.
Visual table interface: Rapidly compare squeeze and expansion signals across all instruments.
How It Works
At the core, this screener leverages a unique blend of Bollinger Bands and Average True Range (ATR) to quantify volatility states for multiple assets and timeframes at once. For each symbol and every selected timeframe, the indicator calculates Bollinger Band width and compares it against ATR levels, offering real-time squeeze (consolidation) and expansion (breakout) signals.
Bollinger Band width is computed using standard deviations around a SMA basis.
ATR is calculated to gauge market volatility independent of price direction.
Squeeze: Triggered when BB width contracts below a multiple of ATR, forecasting lower volatility and set-up for a move.
Expansion: Triggered when BB width expands above a higher ATR multiple, signaling a high-volatility breakout.
Display: Results shown in an intuitive table, marking each status per ticker and TF.
Trading Ideas and Insights
Spot assets poised for volatility-driven breakouts.
Compare squeeze presence across timeframes for optimal entry timing.
Integrate screener results with price action or volume for high-confidence setups.
Use squeeze signals to avoid choppy or non-trending conditions.
Expand and diversify watchlists with multi-symbol coverage.
How Multiple Indicators Work Together
This script seamlessly merges Bollinger Bands and ATR with customized multipliers:
Bollinger Bands identify price consolidation and volatility squeeze zones.
ATR tailors the definition of squeeze and expansion, making signals adaptive to volatility regime changes.
By layering these with multi-symbol/multi-timeframe data, traders access a high-precision view of market readiness for trend acceleration or reversal.
The real synergy is in the screener's ability to visualize volatility states for a diverse asset selection, transforming traditional single-chart analysis into a broad market view.
Unique Aspects
Original implementation: Not a simple trend or scalping indicator; utilizes advanced volatility logic.
Fully multi-symbol and multi-timeframe support uncommon in most screeners.
Custom ATR multipliers for both squeeze and expansion allow traders to match their risk profile and market dynamics.
Visual clarity: Table structure promotes actionable insights and reduces decision fatigue.
How to Use
Add the indicator to your TradingView chart (supports any asset class including crypto, forex, stocks).
Select up to six symbols (tickers) and set your preferred timeframes.
Adjust Bollinger Band Length/Deviation and ATR multipliers to refine squeeze/expansion criteria.
Review the screener table: Look for "SQZ" (squeeze) or "EXP" (expansion) cells for entry/exit ideas.
Combine screener information with other technical or fundamental signals for trade confirmation.
Customization
Symbols: Choose any tickers for scanning.
Timeframes: Select short- to long-term intervals to match your trading style.
Bollinger Band parameters: Modify length and deviation for sensitivity.
ATR multipliers: Set low or high values to adjust squeeze/expansion triggers.
Table size and layout: Adapt display for optimal workflow.
Conclusion
The Bollinger Band Squeeze Screener Pineify delivers an innovative, SEO-friendly multi-asset solution for volatility and trend detection. Harness its original algorithmic design to uncover powerful breakout opportunities and optimize your portfolio. Whether you trade crypto with dynamic volatility or scan stocks for momentum, this tool supercharges your TradingView workflow.
Indicators
Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
Copter 2.0💡 The indicator is designed for trading on any timeframe and includes a comprehensive system for determining entry and exit points based on technical analysis, price and volume.
📊 In the new version of Copter 2.0, the take profit and stop loss functions have been added
Let's analyze its key components:
✔️ Trend levels and extremes:
- The indicator determines local highs and lows for a certain period.
- the breakdown of these levels serves as a signal to open positions.
- the High-Low price dynamics analysis method is used to find key entry points.
✔️ Volumes:
-The indicator uses a configurable volume threshold to filter out candles with low volume and display only those with significant volume.
- the algorithm analyzes market data and sets an entry signal (opening a trade) and exit (profit taking/closing a position)
📍 Therefore, whether you are a beginner or an experienced trader, the indicator can help you stay ahead of the game and make more informed trading decisions.
📍 As a result, the trader can be sure that the signal is based on data analysis.
A long or short position can be stopped with either a profit or a small loss without prejudice to the potential profit.
✔️ Signal filtering:
- volume and volatile indicators are used to confirm the trend
- if a volume or volatility filter does not confirm the breakdown, the input signal is ignored
- analysis of moving averages of volumes and ATR is used
✔️ The use of the RSI in overbought and oversold analysis:
- the RSI indicator analyzes the strength of the current trend
- if the RSI exceeds 70, exit from a long position is possible
- if the RSI falls below 30, exit from a short position is possible
✔️ The use of EMA 20 and EMA 200
is additional moving average data that determines the current trend and the trend on higher timeframes.
- the main idea is that when they cross, we can see a change in trend movement and determine the general mood at the moment, based on which signals appear to open/close a deal.
- also, the indicator analyzes the past movement, thus determining the future direction
- based on the opening and closing of the past days, weeks, months.
✔️ Stop loss and risk management
- when entering a trade, a dynamic stop loss is set based on the percentage price change
- exit the position is carried out when a stop loss or a signal from the RSI is reached.
- it helps to minimize losses and protect profits
The market is unstable, and it is impossible to know what awaits it in the future.
The only way to manage risk is to limit the loss by setting a stop loss at 1% - 2% of the entry point.
It is recommended to set the profit in the ratio 1:1, 1:2,1:3, with partial fixation of 40%, 30%, 30% or wait for the indicator signal (TP)
We recommend fixing positions in parts. There will be a signal in the opposite direction when the volume is released.
To match the risk of the transaction, we recommend that you do not enter with high leverage.
Trade only with the amount that you are willing to lose.
With increased volatility in the market and flat, the indicator can give many signals.
After a strong fall or growth, we recommend not to open positions, because the probability of a flat is high.
✔️ Visualization of entry and exit points
- Entry points (long and short) are graphically displayed. green - long, orange - short
- stop loss levels are marked for clarity of risk management
✔️Recommendations for working with the indicator!
Entry/exit is performed on the next candle after the candle with the signal (buy/sell)
All timeframes and any trading pairs are used (when selecting settings for each one)
The indicator combines several methods of technical analysis:
- work with support and resistance levels
- filtering of signals based on volumes and volatility
- Overbought and oversold analysis using the RSI
- automatic risk management through stop loss
This approach makes the indicator a useful tool for short-term trading and active scalping.
❗️ NO REPAINT ! ❗️
Multi-Symbol and Multi-Timeframe Supertrend Screener [Pineify]Multi-Symbol and Multi-Timeframe Supertrend Screener
Advanced Supertrend screener for TradingView that monitors 6 symbols across 4 timeframes simultaneously. Features customizable ATR periods, visual alerts, and color-coded trend direction displays for efficient market scanning.
Key Features
The Supertrend Screener is a comprehensive multi-symbol market monitoring tool that displays Supertrend indicator signals across multiple assets and timeframes in a single, organized table view. This screener eliminates the need to manually check individual charts by providing real-time trend analysis for up to 6 symbols across 4 different timeframes simultaneously.
How It Works
The screener utilizes the proven Supertrend indicator methodology, which combines Average True Range (ATR) and price action to determine trend direction. The core calculation involves:
Computing the ATR using a customizable period (default: 10)
Applying a multiplication factor (default: 3.0) to create dynamic support/resistance levels
Determining trend direction based on price position relative to these levels
Displaying results through color-coded cells with customizable text labels
The indicator employs the request.security() function to fetch data from multiple symbols and timeframes, ensuring accurate cross-market analysis without chart switching.
Trading Ideas and Insights
This screener excels in several trading scenarios:
Market Overview: Quickly assess overall market sentiment across major cryptocurrencies or forex pairs
Trend Confirmation: Verify trend alignment across multiple timeframes before entering positions
Divergence Spotting: Identify when shorter timeframes diverge from longer-term trends
Opportunity Scanning: Locate assets showing consistent trend direction across all monitored timeframes
Risk Management: Monitor multiple positions simultaneously to spot potential trend reversals
The screener is particularly effective for swing traders and position traders who need to monitor multiple assets without constantly switching between charts.
How Multiple Indicators Work Together
While this screener focuses specifically on the Supertrend indicator, it incorporates several complementary technical analysis components:
ATR Foundation: Uses Average True Range to adapt to market volatility, making the indicator responsive to current market conditions
Multi-Timeframe Analysis: Combines signals from 1-minute, 5-minute, 10-minute, and 30-minute timeframes to provide comprehensive trend perspective
Price Action Integration: The Supertrend calculation inherently incorporates price action by using high, low, and close values
Volatility Adjustment: The ATR-based calculation ensures the indicator adapts to different volatility regimes across various assets
The synergy between these elements creates a robust screening system that accounts for both momentum and volatility , providing more reliable trend identification than single-timeframe analysis.
Unique Aspects
Several features distinguish this screener from standard Supertrend implementations:
Table-Based Display: Presents data in an organized, space-efficient format rather than overlay plots
Customizable Visual Elements: Full control over text labels, colors, and background styling
Multi-Asset Capability: Monitors 6 different symbols simultaneously without performance degradation
Efficient Resource Usage: Optimized code structure minimizes calculation overhead
Professional Presentation: Clean, institutional-grade visual design suitable for trading desks
How to Use
Symbol Configuration: Input your desired symbols in the Symbol section (default includes major crypto pairs)
Timeframe Setup: Configure four timeframes for analysis (default: 1m, 5m, 10m, 30m)
Supertrend Parameters: Adjust the Factor (sensitivity) and ATR Period according to your trading style
Visual Customization: Set custom text labels and colors for up/down trends
Market Analysis: Monitor the table for consistent signals across timeframes and symbols
Interpretation Guide:
- Green cells indicate uptrend (price above Supertrend line)
- Red cells indicate downtrend (price below Supertrend line)
- Look for alignment across multiple timeframes for stronger signal confidence
Customization
The screener offers extensive customization options:
Factor Setting: Adjust sensitivity (higher values = less sensitive, fewer signals)
ATR Period: Modify lookback period for volatility calculation
Text Labels: Customize up/down trend display text
Color Scheme: Full RGB color control for text and background elements
Symbol Selection: Monitor any TradingView-supported symbols
Timeframe Array: Choose any four timeframes for comprehensive analysis
Conclusion
The Supertrend Screener transforms traditional single-chart analysis into an efficient, multi-dimensional market monitoring system. By combining the reliability of the Supertrend indicator with multi-timeframe and multi-symbol capabilities, this tool empowers traders to make more informed decisions with greater market context.
Whether you're managing multiple positions, scanning for new opportunities, or confirming trend direction before entries, this screener provides the comprehensive overview needed for professional trading operations. The clean interface and customizable features make it suitable for traders of all experience levels while maintaining the analytical depth required for serious market analysis.
Perfect for day traders, swing traders, and anyone requiring efficient multi-market trend monitoring in a single view.
Supply & Demand Zones [QuantAlgo]🟢 Overview
The Supply & Demand (Support & Resistance) Zones indicator identifies price levels where significant buying and selling pressure historically emerged, using swing point analysis and pattern recognition to mark high-probability reversal and continuation areas. Unlike conventional support/resistance tools that draw arbitrary horizontal lines, this indicator can automatically detect structural zones, offering traders systematic entry and exit levels where institutional order flow likely congregates across any market or timeframe.
🟢 How to Use
# Zone Types:
Green/Demand Zones: Support areas where buying pressure historically emerged, representing potential long entry opportunities where price may bounce or consolidate before moving higher. These zones mark levels where buyers previously overcame sellers.
Red/Supply Zones: Resistance areas where selling pressure historically dominated, indicating potential short entry opportunities where price may reverse or stall before declining. These zones identify levels where sellers previously overwhelmed buyers.
# Zone Pattern Types:
Wick Rejection Zones: Zones created from candles with exceptionally long wicks showing violent price rejection. A demand rejection occurs when price drops sharply but closes well above the low, forming a long lower wick (relative to the total candle range) that demonstrates buyers aggressively defending that level. A supply rejection shows price spiking higher but closing well below the high, with the long upper wick proving sellers rejected that price aggressively. These zones often represent major institutional orders that absorbed significant market pressure. The rejection wick ratio setting controls how prominent the wick must be (higher ratios require more dramatic rejections and produce fewer but higher-quality zones).
Continuation Demand Zones: Areas where price rallied upward, paused in a brief consolidation base, then rallied again. This pattern confirms strong buying continuation (the consolidation represents profit-taking or minor pullbacks that failed to attract meaningful selling). When price returns to these zones, buyers who missed the initial rally often provide support, making them high-probability long entries within established uptrends. These zones follow the classic Rally-Base-Rally structure, demonstrating that buyers remain in control even during temporary pauses.
Reversal Demand Zones: Zones where price dropped, formed a consolidation base, then reversed into a rally. This structure marks potential trend reversals or major swing lows where buyers finally overwhelmed sellers after a decline. The base period represents accumulation by stronger hands, and these zones frequently appear at market bottoms or as significant pullback support within larger uptrends, signaling shifts in market control. These zones follow the Drop-Base-Rally pattern, showing the moment when selling pressure exhausted and buying interest emerged.
Continuation Supply Zones: Areas where price dropped, consolidated briefly, then dropped again. This pattern demonstrates strong selling continuation (the pause represents temporary buying attempts that failed to generate meaningful recovery). When price returns to these zones, sellers who missed the initial decline often provide resistance, creating short entry opportunities within established downtrends. These zones follow the Drop-Base-Drop structure, confirming that sellers maintain dominance even during temporary consolidations.
Reversal Supply Zones: Zones where price rallied upward, formed a consolidation base, then reversed into a decline. This formation identifies potential trend reversals or major swing highs where sellers overcame buyers after an advance. The base period often represents distribution by institutional participants, and these zones commonly appear at market tops or as key pullback resistance within larger downtrends, marking transfers of market control from buyers to sellers. These zones follow the Rally-Base-Drop pattern, capturing the transition point when buying exhaustion meets aggressive selling.
# Zone Mitigation Methods:
Wick Mitigation: Zones become invalidated immediately upon first contact by any wick. This assumes zones work only on their initial test, reflecting the belief that institutional orders concentrated at these levels get completely filled on first touch. Best for traders seeking only the highest-probability, untested zones and willing to accept that zones invalidate frequently in volatile markets. When price touches a zone boundary with even a single wick, that zone is considered "used up" and becomes mitigated.
Close Mitigation: Zones remain valid through wick penetration but become invalidated only when a candle closes through the zone boundary. This method allows price to briefly probe the zone with wicks while requiring actual commitment (a close) for invalidation. Suitable for traders who recognize that zones can withstand initial tests and prefer filtering out false breakouts caused by temporary volatility or liquidity hunts. A zone stays active as long as candles close within or outside it, regardless of wick penetration, until a close occurs beyond the boundary.
Full Body Mitigation: Zones stay valid until an entire candle body exists completely beyond the zone boundary, meaning both the open and close must be outside the zone. This approach maintains zone validity through partial penetrations, accommodating the reality that institutional zones can absorb considerable price action before exhausting. Ideal for volatile markets or traders who believe zones represent price ranges rather than precise levels, and who want zones to persist through aggressive but ultimately rejected breakout attempts. Only when both the open and close of a candle are beyond the zone does it become mitigated.
🟢 Pro Tips for Trading and Investing
→ Preset Selection: Choose presets matching your preferred timeframe - Scalping (M1-M30) for aggressive detection on minute charts, Intraday (H1-H12) for balanced filtering on hourly timeframes, or Swing Trading (1D+) for strict filtering on daily charts. Each preset automatically optimizes swing length, zone strength, and max zone counts for the selected timeframe.
→ Input Calibration: Adjust Swing Length based on market speed (lower values 3-7 for fast markets, higher values 12-20 for slower markets). Set Minimum Zone Strength according to asset volatility (0.05-0.15% for low-volatility assets, 0.25-0.5% for high-volatility assets). Tune Rejection Wick Ratio higher (0.6-0.8) for strict wick filtering or lower (0.3-0.5) to capture more subtle rejections.
→ Zone Pattern Toggle Strategy: Pattern types are mutually exclusive - enable Continuation OR Reversal patterns for each zone type, not both together. Recommended combinations: For trend trading, enable Rejection + Continuation (2-4 toggles total). For reversal trading, enable Rejection + Reversal (2-4 toggles). For scalping, enable only Rejection zones (1-2 toggles). Maximum 3-4 active toggles provides optimal chart clarity. A simple Wick Rejection toggle can also work on virtually any market and timeframe.
→ Mitigation Method Selection: Use Wick mitigation in clean trending markets for strict zone invalidation on first touch. Use Close mitigation in moderate volatility to filter out temporary spikes. Use Full Body mitigation in highly volatile markets to keep zones active through whipsaws and false breakouts.
→ Alert Configuration: Utilize built-in alerts for new zone creation, zone touches, and zone breaks. New zone alerts notify when fresh supply/demand areas form. Zone touch alerts signal potential entry opportunities as price reaches zones. Zone break alerts indicate when levels fail, signaling possible trend acceleration or structure changes.
Ichimoku Screener [Pineify]Advanced Multi-Timeframe Ichimoku Screener - Complete Market Analysis Tool
This sophisticated Ichimoku Screener represents a comprehensive approach to multi-timeframe market analysis, combining four distinct Ichimoku-based indicators into a unified screening system. Unlike traditional single-symbol indicators, this screener provides simultaneous analysis across multiple assets and timeframes, enabling traders to identify optimal trading opportunities with enhanced precision and efficiency.
Key Features
Multi-asset screening capability for up to 10 symbols simultaneously
Four customizable timeframes per symbol for comprehensive analysis
Four integrated Ichimoku-based indicators working in harmony
Real-time visual feedback with color-coded signals
Customizable Ichimoku parameters for personalized analysis
Clean, organized table display for easy interpretation
Automated signal strength assessment and timing
How It Works
The screener employs the traditional Ichimoku Kinko Hyo methodology, utilizing five core components: Conversion Line (Tenkan-sen), Base Line (Kijun-sen), Leading Span A (Senkou Span A), Leading Span B (Senkou Span B), and displacement calculations. Each component is mathematically calculated using specific period lengths:
Conversion Line = (Highest High + Lowest Low) / 2 over conversion period
Base Line = (Highest High + Lowest Low) / 2 over base period
Leading Span A = (Conversion Line + Base Line) / 2
Leading Span B = (Highest High + Lowest Low) / 2 over lagging span period
The screener processes these calculations across multiple securities simultaneously using TradingView's security() function, enabling real-time cross-asset analysis. The system tracks state changes using barssince() functions to provide precise timing information for each signal type.
Trading Ideas and Insights
This screener excels in identifying momentum convergence patterns where multiple Ichimoku components align across different timeframes. The most powerful signals occur when:
Cloud color aligns with price position relative to the cloud
Conversion Line crosses above/below Base Line in the same direction as cloud bias
Multiple timeframes show consistent directional bias
Entry signals appear with minimal bars since formation (indicating fresh momentum)
For trend following strategies , focus on symbols where the cloud maintains consistent color across higher timeframes while showing recent entry signals on lower timeframes. For reversal opportunities , identify assets where cloud color changes coincide with price re-entering the cloud after extended periods above or below.
The screener particularly excels in cryptocurrency and forex markets where momentum shifts can be dramatic and sustained. By monitoring multiple timeframes simultaneously, traders can identify when short-term signals align with longer-term trends, significantly improving trade success probability.
How Multiple Indicators Work Together
The four integrated indicators create a comprehensive analytical framework through synergistic interaction:
Ichimoku Cloud (IchiCld) establishes the primary trend bias by comparing Leading Span A with Leading Span B. When Span A > Span B, the cloud displays bullish characteristics; when Span A < Span B, bearish characteristics emerge. The indicator tracks duration since the last cloud color change, providing momentum persistence insight.
Ichimoku Lagging Cloud (IchiLagCld) determines price position relative to the displaced cloud formation. This indicator identifies whether current price action occurs above, below, or within the cloud structure, revealing support/resistance dynamics and trend confirmation signals.
Conversion vs Base (IchiC>Base) monitors the relationship between short-term (Conversion Line) and medium-term (Base Line) momentum. Crossovers in this relationship often precede significant price movements and provide early trend change warnings.
Ichimoku Entry (IchiEnt) synthesizes all components into actionable signals by requiring alignment between cloud bias, price position, and conversion/base relationship. This multi-factor confirmation approach significantly reduces false signals while maintaining sensitivity to genuine momentum shifts.
The mathematical foundation ensures that each indicator contributes unique information while maintaining logical consistency. The system's strength lies in requiring multiple confirmations before generating entry signals, following Ichimoku's original philosophy of comprehensive market analysis.
Unique Aspects
This implementation distinguishes itself through several innovative features:
Advanced State Tracking : Unlike standard Ichimoku indicators that show current values, this screener tracks duration since state changes , providing crucial timing information for signal freshness and momentum strength assessment.
Multi-Asset Efficiency : The screener eliminates the need to manually check multiple charts by presenting comparative analysis across assets and timeframes in a single view, dramatically improving analytical efficiency.
Customizable Visual Feedback : The color-coding system adapts to different signal types and strengths, with recent signals receiving enhanced visual prominence to draw attention to fresh opportunities.
Professional Table Architecture : The organized display accommodates up to 40 symbol-timeframe combinations (10 symbols × 4 timeframes), with intelligent pagination for optimal screen utilization.
Signal Correlation Analysis : By displaying multiple timeframes for each symbol, traders can quickly identify timeframe confluence and divergence patterns that would otherwise require extensive manual analysis.
How to Use
Symbol Configuration : Enter up to 10 symbols in the Symbol input group. Use full exchange:ticker format for optimal compatibility (e.g., "BINANCE:BTCUSDT").
Timeframe Selection : Configure four timeframes in ascending order for logical analysis progression. Recommended combinations include 1m/5m/15m/1h for intraday analysis or 1h/4h/1D/1W for swing trading.
Ichimoku Parameters : Adjust the four core parameters based on your trading style:
Conversion Line Length (default: 9) - Controls short-term momentum sensitivity
Base Line Length (default: 26) - Determines medium-term trend identification
Leading Span B Length (default: 52) - Sets long-term trend calculation period
Displacement (default: 26) - Controls forward projection of cloud structure
Signal Interpretation :
Green backgrounds indicate bullish conditions
Red backgrounds indicate bearish conditions
Numerical values show bars since last state change
"L:" prefix indicates long entry signals
"S:" prefix indicates short entry signals
"N/A" indicates neutral/transitional states
Trading Workflow : Scan for symbols showing consistent signals across multiple timeframes, prioritize fresh signals (low bar counts), and use individual charts for precise entry timing and risk management.
Customization
The screener accommodates various trading approaches through parameter adjustment:
Scalping Configuration : Use shorter periods (Conversion: 5, Base: 13, Span B: 26) with 1m/3m/5m/15m timeframes for high-frequency opportunities.
Swing Trading Setup : Employ standard parameters with 4h/1D/3D/1W timeframes for position trading across days or weeks.
Cryptocurrency Optimization : Given crypto's 24/7 nature, consider using 4h/8h/1D/3D combinations for optimal signal timing.
Symbol selection can focus on correlated assets (e.g., major cryptocurrencies) for sector analysis or diverse assets for portfolio opportunity identification. The flexible timeframe configuration allows adaptation to any market's characteristic volatility and trading patterns.
Conclusion
This Advanced Multi-Timeframe Ichimoku Screener transforms traditional single-chart analysis into a comprehensive market monitoring system. By integrating multiple Ichimoku components across various timeframes and assets, it provides traders with unprecedented analytical efficiency and signal reliability.
The mathematical rigor of traditional Ichimoku analysis combines with modern Pine Script capabilities to deliver a professional-grade screening tool. Whether used for identifying trend continuation opportunities, spotting potential reversals, or conducting broad market analysis, this screener offers the analytical depth and practical functionality required for serious trading applications.
The system's emphasis on signal confluence across multiple timeframes and indicators significantly improves trade selection quality while reducing analysis time. For traders seeking to leverage Ichimoku's proven methodology across multiple markets simultaneously, this screener represents an essential analytical upgrade to traditional single-symbol approaches.
Fisher Transform Trend Navigator [QuantAlgo]🟢 Overview
The Fisher Transform Trend Navigator applies a logarithmic transformation to normalize price data into a Gaussian distribution, then combines this with volatility-adaptive thresholds to create a trend detection system. This mathematical approach helps traders identify high-probability trend changes and reversal points while filtering market noise in the ever-changing volatility conditions.
🟢 How It Works
The indicator's foundation begins with price normalization, where recent price action is scaled to a bounded range between -1 and +1:
highestHigh = ta.highest(priceSource, fisherPeriod)
lowestLow = ta.lowest(priceSource, fisherPeriod)
value1 = highestHigh != lowestLow ? 2 * (priceSource - lowestLow) / (highestHigh - lowestLow) - 1 : 0
value1 := math.max(-0.999, math.min(0.999, value1))
This normalized value then passes through the Fisher Transform calculation, which applies a logarithmic function to convert the data into a Gaussian normal distribution that naturally amplifies price extremes and turning points:
fisherTransform = 0.5 * math.log((1 + value1) / (1 - value1))
smoothedFisher = ta.ema(fisherTransform, fisherSmoothing)
The smoothed Fisher signal is then integrated with an exponential moving average to create a hybrid trend line that balances statistical precision with price-following behavior:
baseTrend = ta.ema(close, basePeriod)
fisherAdjustment = smoothedFisher * fisherSensitivity * close
fisherTrend = baseTrend + fisherAdjustment
To filter out false signals and adapt to market conditions, the system calculates dynamic threshold bands using volatility measurements:
dynamicRange = ta.atr(volatilityPeriod)
threshold = dynamicRange * volatilityMultiplier
upperThreshold = fisherTrend + threshold
lowerThreshold = fisherTrend - threshold
When price momentum pushes through these thresholds, the trend line locks onto the new level and maintains direction until the opposite threshold is breached:
if upperThreshold < trendLine
trendLine := upperThreshold
if lowerThreshold > trendLine
trendLine := lowerThreshold
🟢 Signal Interpretation
Bullish Candles (Green): indicate normalized price distribution favoring bulls with sustained buying momentum = Long/Buy opportunities
Bearish Candles (Red): indicate normalized price distribution favoring bears with sustained selling pressure = Short/Sell opportunities
Upper Band Zone: Area above middle level indicating statistically elevated trend strength with potential overbought conditions approaching mean reversion zones
Lower Band Zone: Area below middle level indicating statistically depressed trend strength with potential oversold conditions approaching mean reversion zones
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant developments without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency and clarity
Configuration Presets: Three parameter sets available - Default (balanced settings), Scalping (faster response with higher sensitivity), and Swing Trading (slower response with enhanced smoothing)
Color Customization: Four color schemes including Classic, Aqua, Cosmic, and Custom options for personalized chart aesthetics
Ichimoku Cloud Indicator [TradingFinder] Kinko Hyo Cross Alerts🔵 Introduction
The Ichimoku Cloud (Ichimoku Kinko Hyo) is one of the most powerful and complete trading indicators in technical analysis. Originally developed by Japanese journalist Goichi Hosoda, the Ichimoku system combines multiple tools in one indicator, providing traders with instant insights into trend direction, support and resistance levels, and momentum. Unlike simple moving averages (SMA – Simple Moving Average), the Ichimoku Cloud (Kumo – Cloud) integrates dynamic elements that help traders forecast potential price action with greater clarity.
The Ichimoku Indicator (Ichimoku Signal System) is widely used across global markets, from Forex trading (FX – Foreign Exchange) to stocks, indices, and even cryptocurrencies. Its popularity comes from its ability to generate clear buy signals and sell signals based on the interaction of its components: Tenkan Sen (Conversion Line), Kijun Sen (Base Line), Senkou Span A, Senkou Span B, and Chikou Span (Lagging Line). When combined, these lines create the Ichimoku Cloud, which visually represents the balance between price action and market structure.
Ichimoku Cloud Lines Formulas :
Conversion Line (Tenkan Sen / Conversion Line) : Average of the highest high and lowest low over the past 9 periods => (9-PH + 9-PL) ÷ 2
Base Line (Kijun Sen / Base Line) : Average of the highest high and lowest low over the past 26 periods => (26-PH + 26-PL) ÷ 2
Leading Span A (Senkou Span A / Leading Span A) : Average of the Conversion Line and Base Line, plotted 26 periods ahead => (Tenkan Sen + Kijun Sen) ÷ 2
Leading Span B (Senkou Span B / Leading Span B) : Average of the highest high and lowest low over the past 52 periods, plotted 26 periods ahead => (52-PH + 52-PL) ÷ 2
Lagging Span (Chikou Span / Lagging Span) : Current closing price, plotted 26 periods behind.
One of the biggest advantages of the Ichimoku Trading Strategy (Ichimoku Cloud Trading System) is that it allows traders to identify the market condition at a glance. When the price is above the Kumo (Cloud), it indicates a bullish trend (uptrend). When the price is below the Kumo, the market is in a bearish trend (downtrend). And when the price is inside the cloud, the market is ranging (sideways trend). This simplicity and visual clarity make Ichimoku an essential indicator for both beginner traders and professional analysts.
The Ichimoku Cloud Indicator (Ichimoku Technical Analysis Tool) continues to be one of the most reliable charting methods. Traders often consider it superior to basic moving averages (MA – Moving Average) or exponential moving averages (EMA – Exponential Moving Average), because it not only shows trend direction but also highlights potential future support and resistance levels. With its unique combination of trend analysis, price forecasting, and trading signals, Ichimoku remains a core strategy in modern trading systems.
🔵 How to Use
The Ichimoku Cloud is more than just a set of lines; it’s a complete trading system that helps traders identify trends, momentum, and key support and resistance levels. By combining its five lines Conversion Line, Base Line, Leading Span A, Leading Span B, and Lagging Span traders can develop clear buy and sell strategies.
🟣 Identifying Trend Direction
Bullish Trend (Uptrend) : Price is above the cloud (Kumo), and the cloud is green. Leading Span A is above Leading Span B, signaling strong upward momentum.
Bearish Trend (Downtrend) : Price is below the cloud, and the cloud is red. Leading Span A is below Leading Span B, confirming a downward momentum.
Ranging / Sideways Market : Price is inside the cloud, indicating indecision and consolidation. Traders often avoid opening strong positions during these periods.
🟣 Buy Strategies
Conversion/Base Line Crossover : A buy signal occurs when the Conversion Line (Tenkan Sen) crosses above the Base Line (Kijun Sen). The signal is strongest when this crossover happens above the cloud.
Price Above Base Line : If the price moves above the Base Line while in an uptrend, it confirms bullish momentum and provides a favorable entry point.
Cloud Support Pullback : During a pullback in an uptrend, the price may touch or slightly enter the cloud. Traders can use the cloud as a dynamic support zone for buying opportunities.
Lagging Span Confirmation : Ensure the Lagging Span (Chikou Span) is above the price of 26 periods ago to confirm the strength of the bullish trend.
🟣 Sell Strategies
Conversion/Base Line Crossover : A sell signal is generated when the Conversion Line (Tenkan Sen) crosses below the Base Line (Kijun Sen). This signal is strongest when it occurs below the cloud.
Price Below Base Line : If the price falls below the Base Line in a downtrend, it confirms bearish momentum and strengthens the sell setup.
Cloud Resistance Pullback : During a bounce in a downtrend, the cloud acts as a resistance zone. Traders can enter sell positions when price approaches or touches the cloud from below.
Lagging Span Confirmation : The Lagging Span should be below the price of 26 periods ago, confirming downward momentum.
🟣 Cloud Breakout Signals
A strong buy occurs when the price breaks above the cloud from below, signaling a potential trend reversal.
A strong sell occurs when the price breaks below the cloud from above, indicating a shift toward a bearish trend.
🟣 Combining Signals for Stronger Entries
For higher probability trades, combine multiple signals : trend direction (cloud color and position), crossovers (Tenkan/Kijun), and Lagging Span position.
Avoid trading against the overall trend. For example, avoid buying when price is below a red cloud or selling when price is above a green cloud.
🔵 Setting
Tenkan Sen Period : Lookback period for Conversion Line (default: 9).
Kijun Sen Period : Lookback period for Base Line (default: 26).
Span B Period : Lookback period for Leading Span B, forms one Cloud boundary (default: 52).
Shift Lines : Periods forward for Cloud / backward for Lagging Span (default: 26).
Cross Tenkan/Kijun Alert : Alert on Conversion/Base Line crossover.
Cross Price/Tenkan Alert : Alert when price crosses Tenkan Sen.
Cross Price/Kijun Alert : Alert when price crosses Kijun Sen
🔵 Conclusion
The Ichimoku Cloud (Ichimoku Kinko Hyo) is much more than a simple indicator it is a complete trading system that combines trend detection, momentum analysis, and support/resistance identification in one view. By interpreting the position of price relative to the cloud, the interaction between Tenkan Sen (Conversion Line) and Kijun Sen (Base Line), the leading spans (Senkou Span A and B), and the Chikou Span (Lagging Line), traders can identify potential buy and sell opportunities with higher confidence.
The main advantage of the Ichimoku Cloud is its ability to provide a “one-look equilibrium” snapshot of the market. It highlights bullish trends when the price is above the cloud, bearish conditions when the price is below it, and indecision or transition when the price is inside the cloud. Crossovers, cloud breakouts, and confirmations by the Chikou Span strengthen the trading signals.
However, traders should keep in mind the limitations of the Ichimoku system. It is based on historical data and should not be used in isolation. Combining it with other tools such as RSI, volume analysis, or candlestick patterns can significantly improve accuracy and reduce false signals.
Laguerre Filter Trend Navigator [QuantAlgo]🟢 Overview
The Laguerre Filter Trend Navigator employs advanced polynomial filtering mathematics to smooth price data while minimizing lag, creating a responsive yet stable trend-following system. Unlike simple moving averages that apply equal weight to historical data, the Laguerre filter uses recursive calculations with exponentially weighted polynomials to extract meaningful directional signals from noisy market conditions. Combined with dynamic volatility-adjusted boundaries, this creates an adaptive framework for identifying high-probability trend reversals and continuations across all tradable instruments and timeframes.
🟢 How It Works
The indicator leverages Laguerre polynomial filtering, a mathematical technique originally developed for digital signal processing applications. The core mechanism processes price data through four cascaded filter stages (L0, L1, L2, L3), each applying the gamma coefficient to recursively smooth incoming information while preserving phase relationships. This multi-stage architecture eliminates random fluctuations more effectively than traditional moving averages while responding quickly to genuine directional shifts.
The gamma coefficient serves as the primary smoothing control, determining how aggressively the filter dampens noise versus tracking price movements. Lower gamma values reduce smoothing and increase filter responsiveness, while higher values prioritize stability over reaction speed. Each filter stage compounds this effect, creating progressively smoother output that converges toward true underlying trend direction.
Surrounding the filtered price line, the algorithm constructs adaptive boundaries using dynamic volatility regime measurements. These calculations quantify current market turbulence independently of direction, expanding during active trading periods and contracting during quiet phases. By multiplying this volatility assessment by a user-defined scaling factor, the system creates self-adjusting bands that automatically conform to changing market conditions without manual intervention.
The trend-following engine monitors price position relative to these volatility-adjusted boundaries. When the upper band falls below the current trend line, the system shifts downward to track bearish momentum. Conversely, when the lower band rises above the trend line, it elevates to follow bullish movement. These crossover events trigger color transitions between bullish (green) and bearish (red) states, providing clear visual confirmation of directional changes validated by volatility-normalized thresholds.
🟢 How to Use
Green/Bullish Trend Line: Laguerre filter positioned in upward trajectory, indicating momentum-confirmed conditions favorable for establishing or maintaining long positions (buy)
Red/Bearish Trend Line: Laguerre filter trending downward, signaling regime-validated environment suitable for initiating or holding short positions (sell)
Rising Green Line: Accelerating bullish filter with expanding separation from price lows, demonstrating strengthening upward momentum and increasing confidence in trend persistence with optimal long entry timing
Declining Red Line: Steepening bearish filter creating growing distance from price highs, revealing intensifying downside pressure and enhanced probability of continued decline with favorable short positioning opportunities
Flattening Trends: Horizontal or oscillating filter movement regardless of color suggests directional uncertainty where price action contradicts filter positioning, potentially indicating consolidation phases or impending volatility expansion requiring cautious trade management
🟢 Pro Tips for Trading and Investing
→ Preset Selection Framework: Match presets to your trading style - Scalping preset employs aggressive gamma (0.4) with tight volatility bands (1.0x) for rapid signal generation on sub-15-minute charts, Day Trading preset balances responsiveness and stability for hourly timeframes, while Swing Trading preset maximizes smoothing (0.8 gamma) with wide bands (2.5x) to filter intraday noise on daily and weekly charts.
→ Gamma Coefficient Calibration: Adjust gamma based on market personality - reduce values (0.3-0.5) for highly liquid, fast-moving assets like major currency pairs and tech stocks where quick filter adaptation prevents lag-induced losses, increase values (0.7-0.9) for slower instruments or trending markets where excessive sensitivity generates false reversals and whipsaw trades.
→ Volatility Period Optimization: Tailor the volatility measurement window to information cycles. Deploy shorter lookback periods (7-10) for instruments with rapid regime changes like individual equities during earnings seasons, standard periods (14-20) for balanced assessment across general market conditions, and extended periods (21-30) for commodities and indices exhibiting persistent volatility characteristics.
→ Band Width Multiplier Adaptation: Scale boundary distance to current market phase. Contract multipliers (1.0-1.5) during range-bound consolidations to capture early breakout signals as soon as genuine momentum emerges, expand multipliers (2.0-3.0) during trending markets or high-volatility events to avoid premature exits caused by normal retracement activity rather than authentic reversals.
→ Multi-Timeframe Filter Alignment: Implement the indicator across multiple timeframes, using higher intervals (4H/Daily) to identify primary trend direction via filter slope and lower intervals (15min/1H) for precision entry timing when filter colors align, ensuring trades flow with dominant momentum while optimizing execution at favorable price levels.
→ Alert-Driven Systematic Execution: Configure trend change alerts to capture every filter-validated directional shift from bullish to bearish conditions or vice versa, enabling consistent signal response without continuous chart monitoring and eliminating emotional decision-making during critical transition moments.
Bayesian Trend Navigator [QuantAlgo]🟢 Overview
The Bayesian Trend Navigator uses Bayesian statistics to continuously update trend probabilities by combining long-term expectations (prior beliefs) and short-term observations (likelihood evidence), rather than relying solely on recent price data like many conventional indicators. This mathematical framework produces robust directional signals that naturally balance responsiveness with stability, making it suitable for traders and investors seeking statistically-grounded trend identification across diverse market environments and asset types.
🟢 How It Works
The indicator operates on Bayesian inference principles, a statistical method for updating beliefs when new evidence emerges. The system begins by establishing a prior belief - a long-term trend expectation calculated from historical price behavior. This represents the "baseline hypothesis" about market direction before considering recent developments.
Simultaneously, the algorithm collects recent market evidence through short-term trend analysis, representing the likelihood component. This captures what current price action suggests about directional momentum independent of historical context.
The core Bayesian engine then combines these elements using conjugate normal distributions and precision weighting. It calculates prior precision (inverse variance) and likelihood precision, combining them to determine a posterior precision. The resulting posterior mean represents the mathematically optimal trend estimate given both historical patterns and current reality. This posterior calculation includes intervals derived from the posterior variance, providing probabilistic confidence bounds around the trend estimate.
Finally, volatility-based standard deviation bands create adaptive boundaries around the Bayesian estimate. The trend line adjusts within these constraints, generating color transitions between bullish (green) and bearish (red) states when the posterior calculation crosses these probabilistic thresholds.
🟢 How to Use
Green/Bullish Trend Line: Posterior probability favoring upward momentum, indicating statistically favorable conditions for long positions (buy)
Red/Bearish Trend Line: Posterior probability favoring downward momentum, signaling mathematically supported timing for short positions (sell)
Rising Green Line: Strengthening bullish posterior as new evidence reinforces upward beliefs, showing increasing probabilistic confidence in trend continuation with favorable long entry conditions
Declining Red Line: Intensifying bearish posterior with accumulating downside evidence, indicating growing statistical certainty in downtrend persistence and optimal short positioning opportunities
Flattening Trends: Diminishing posterior confidence regardless of color suggests equilibrium between prior beliefs and contradictory evidence, potentially signaling consolidation or insufficient statistical clarity for high-conviction trades
🟢 Pro Tips for Trading and Investing
→ Preset Configuration Strategy: Deploy presets based on your trading horizon - Scalping preset maximizes evidence weight (0.8) for rapid Bayesian updates on 1-15 minute charts, Default preset balances prior and likelihood for general applications, while Swing Trading preset equalizes weights (0.5/0.5) for stable inference on hourly and daily timeframes.
→ Prior Weight Adjustment: Calibrate prior weight according to market regime - increase values (0.5-0.7) in stable trending markets where historical patterns remain predictive, decrease values (0.2-0.3) during regime changes or news-driven volatility when recent evidence should dominate the posterior calculation.
→ Evidence Period Tuning: Modify the evidence period based on information flow velocity. Use shorter periods (5-8 bars) for assets with continuous price discovery like cryptocurrencies, medium periods (10-15) for liquid stocks, and longer periods (15-20) for slower-moving markets to ensure adequate likelihood sample size.
→ Likelihood Weight Optimization: Adjust likelihood weight inversely to market noise levels. Higher values (0.7-0.8) work well in clean trending conditions where recent data is reliable, while lower values (0.4-0.6) help during choppy periods by maintaining stronger reliance on established prior beliefs.
→ Multi-Timeframe Bayesian Confluence: Apply the indicator across multiple timeframes, using higher timeframes (Daily/Weekly) to establish prior belief direction and lower timeframes (Hourly/15-minute) for likelihood-driven entry timing, ensuring posterior probabilities align across temporal scales for maximum statistical confidence.
→ Standard Deviation Multiplier Management: Adapt the multiplier to match current uncertainty levels. Use tighter multipliers (1.0-1.5) during low-volatility consolidations to capture early trend emergence, and wider multipliers (2.0-2.5) during high-volatility events to avoid premature signals caused by statistical noise rather than genuine posterior shifts.
→ Variance-Based Position Sizing: Monitor the implicit posterior variance through trend line stability - smooth consistent movements indicate low uncertainty warranting larger positions, while erratic fluctuations suggest high statistical uncertainty calling for reduced exposure until clearer probabilistic convergence emerges.
→ Alert-Based Probabilistic Execution: Utilize trend change alerts to capture every statistically significant posterior shift from bullish to bearish states or vice versa without constantly monitoring the charts.
VWAP Daily/Weekly/Monthly - Automatic AnchoredExplanation:
This script plots Volume-Weighted Average Price (VWAP) lines that are automatically anchored to the beginning of key timeframes — daily, weekly, and monthly. VWAP is a widely used trading indicator that shows the average price of an asset weighted by trading volume, making it useful for identifying fair value and institutional trading levels.
The “automatic anchored” feature means that you don’t have to manually select starting points. Instead, the script automatically resets the VWAP at the start of each day, week, or month, depending on the chosen setting. This ensures the VWAP always reflects the true average price for that period, providing traders with a consistent reference for support, resistance, and trend direction across multiple timeframes.
Notice:
On the chart, you may notice visible “jumps” in the VWAP lines. These are intentional. Each jump marks the reset point at the start of a new day, week, or month, depending on the selected setting. This design keeps the VWAP history from the previous period intact, allowing you to clearly see how price interacted with VWAP in past sessions.
By keeping these historical resets, you can easily compare short-term (daily) VWAP behavior against longer-term levels like weekly and monthly VWAP. This provides valuable context, helping you spot when price respects or diverges from fair value across different timeframes.
In short:
Daily VWAP resets at the start of each trading day.
Weekly VWAP resets at the beginning of each trading week.
Monthly VWAP resets at the start of each month.
This makes it easy to analyze how price interacts with VWAP levels across different time horizons without manual adjustments.
Lakshmi - Vajra Energy Signal (VES)Vajra Energy Signal (VES) is an advanced volume analysis indicator that detects energy accumulated inside the market.
When assessing the strength of trading activity, conventional practice looks at the magnitude of volume; VES is designed with the understanding that the same volume can have different meanings depending on the price range.
VES analyzes the complex relationship between price movement and volume with a proprietary algorithm and can detect internal market activities that are invisible from surface‑level price action, visualizing the characteristic whereby the value rises before a breakout.
In other words, VES views the market as an “energy system.” In the energy accumulation phase, relatively high volume occurs relative to the price range, and in the energy release phase, the stored energy is emitted as high volatility in price, that is, a breakout—this is the core concept on which VES is established.
⚡️ Basic Demonstration
i.imgur.com
As you can see in the image above, VES simply displays the highs and lows of energy stored in the market as a thin line in a separate panel.
It is easy for traders to understand its intuitive patterns: it rises when hidden buying accumulation or selling activity continue and sink when a price breakout occurs. It can be applied across symbols and markets (stocks, commodities, cryptocurrencies, spot, and futures). While reducing clutter in price scale labels, it also supports dynamic autoscaling.
⚡️ Practical Usage
VES is expected to be used for the following purposes.
- Entry signal
When the VES value continues to rise—i.e., during energy accumulation—it can be considered on standby for a breakout. After a breakout, a trader can confirm the trend direction and enter.
- Exit signal
If the VES value rises during a trend, consider the possibility of a reversal and consider taking profits.
- Risk management
If the VES value remains elevated for a long period, regard it as increased market uncertainty and an approaching breakout; adopt a cautious trading strategy to prepare for higher volatility and adjust position size.
For example, in the BINANCE:SOLUSDT daily chart below, VES clearly shows how it functions in short‑term trading.
i.imgur.com
In September 2023, when the price was moving around 20 USDT, VES formed frequent small spikes. These early spikes suggest that market participants were still in a wait‑and‑see mode and that small‑scale accumulation was being conducted intermittently.
A decisive change came in early October 2023. While the price still stagnated in the 20–25 USDT range, VES suddenly formed a huge spike. The scale of this spike was far larger than those in September 2023, clearly suggesting that hidden substantial trading activities by large investors had begun.
In mid‑October 2023, the price began to rise. It climbed stepwise from 25 USDT to 40 USDT, then to 60 USDT and 75 USDT, and then surged to above 120 USDT within just a few weeks. This suggests that the energy built in the buy accumulation phase in early October 2023 was converted into price appreciation.
Therefore, after such a large VES signal is observed and the price breaks upward, entering a long position could have been profitable.
A large VES reaction is not only a quiet “buy signal” as in the example above; it can also be a “sell signal.” Such a case is explained below using an example on the BTC chart.
i.imgur.com
This BITSTAMP:BTCUSD 4‑hour chart is a valuable example showing how VES detects top formation on a short timeframe. In the first half of February 2024, the price moved in a relatively narrow 96,000–99,000 USD range. During this period, VES remained stable at low levels, and the market continued a calm uptrend.
The first sign appeared on February 16, 2024. While the price still held around 97,000 USD, VES formed a clearly identifiable small spike. This implied that some large investors had begun to take profits, or that new sellers had started to build short positions. However, at that point, the impact on price was limited, and many traders may have overlooked the signal.
The decisive turning point came on February 23, 2024. With the price moving around 98,000 USD, VES suddenly formed a huge spike. The scale of this spike was far larger than previous moves, clearly indicating that significant energy was accumulating.
Importantly, even at this moment the price still remained at the highs. On the surface, price barely moved and the bull trend appeared intact, but VES detected a major internal change underway.
On February 24, 2024, the price collapsed and began to fall. It dropped about 15% from 97,000 USD to 82,000 USD in a few days. The speed and magnitude of this decline corroborated the quiet “sell signal” indicated by the VES spikes.
The key lesson from this chart is that a VES spike does not necessarily mean buy accumulation. A large VES spike formed at high prices may instead indicate a distribution phase—that is, large investors exiting or building short positions. When the price is at elevated levels, a VES spike should be considered not only as a precursor to further upside but also as a warning of potential downside.
From a trading‑strategy perspective, the huge VES spike on February 23, 2024 was a clear signal to exit or to consider entering short positions. At that point, traders should have either closed long positions or to consider building a short position. The moment when price started to decline from its peak was exactly the entry timing for a short.
On the 4‑hour timeframe, changes in VES appear faster and more dramatically. While this allows more agile responses, the risk of false signals is also higher; therefore, confirmation on other timeframes and comprehensive judgment with price action are essential.
VES is a powerful tool for reading internal market activities, and this chart clearly shows that its interpretation requires flexibility that takes into account market conditions and price location.
⚡️ Parameter Settings
Strength 1: The lower the number, the more it emphasizes responses closer to the present timeframe; the higher the number, the more it emphasizes responses farther from the present timeframe. 5 is recommended.
Strength 2: The lower the number, the greater the volatility of the value; the higher the number, the smaller the volatility. 5 is recommended.
Scale: Adjusts the display scale. −30 is recommended.
⚡️ Conclusion
Vajra Energy Signal (VES) visualizes the cycle of energy accumulation in the market from the relative relationship between price range and volume, detecting hidden activities by market participants that conventional volume analysis cannot capture. VES serves as a powerful auxiliary tool for early detection of turning points, enabling deeper market understanding and more accurate timing decisions. As the examples show, there is a possibility of sensing major price movements in advance. When using VES, flexible interpretation according to market environment and price location is required, and it demonstrates its true value when combined with price action and other analysis methods such as support/resistance.
⚡️ Important Notes
- VES is a tool that infers internal market energy; it does not guarantee trades or suggest future results.
- We strongly recommend using it together with price action analysis and support/resistance.
- Confirmation across different timeframes improves reliability.
- Effectiveness may vary depending on market conditions and liquidity.
- Very illiquid instruments or newly listed assets may produce more noise.
⚡️ How to Get Access
This indicator is Public Invite‑Only. If you would like access, please apply by following the Author’s Instructions.
MACD Josh MACD Study — Visual Crossover Tags
Overview:
This script displays MACD signals in a clear, visual way by showing:
Histogram = EMA(Fast) − EMA(Slow)
Signal = EMA(Histogram, Signal Length)
It adds labels and arrows to help you see crossover events between the Histogram and the Signal line more easily.
⚠️ Disclaimer: This tool is for educational and research purposes only. It is not financial advice or an investment recommendation. Past performance does not guarantee future results. Users should make their own decisions and manage risk responsibly.
Features
Central Zero Line with Signal and Histogram plots
Optional labels/arrows to highlight Histogram–Signal crossovers
Alerts for crossover and crossunder events, integrated with TradingView’s alert system
Standard adjustable inputs: Fast EMA, Slow EMA, Signal EMA
How to Interpret (for study only)
When the Histogram crosses above the Signal, a visual label/arrow marks a positive MACD event
When the Histogram crosses below the Signal, a visual label/arrow marks a negative MACD event
The “BUY/SELL” labels are visual study tags only — they do not represent trade instructions or recommendations
Responsible Usage Tips
Test across multiple timeframes and different assets
Combine with higher-timeframe trend, support/resistance, or volume for confirmation
Use alerts with caution, and always test in a demo environment first
Technical Notes
The script does not use future data and does not repaint signals once bars are closed
Results depend on market conditions and may vary across assets and timeframes
License & Credits
Written in Pine Script® v5 for TradingView
The indicator name shown on chart is for labeling purposes only and carries no implication of advice or solicitation
Algorithmic Value Oscillator [CRYPTIK1]Algorithmic Value Oscillator
Introduction: What is the AVO? Welcome to the Algorithmic Value Oscillator (AVO), a powerful, modern momentum indicator that reframes the classic "overbought" and "oversold" concept. Instead of relying on a fixed lookback period like a standard RSI, the AVO measures the current price relative to a significant, higher-timeframe Value Zone .
This gives you a more contextual and structural understanding of price. The core question it answers is not just "Is the price moving up or down quickly?" but rather, " Where is the current price in relation to its recently established area of value? "
This allows traders to identify true "premium" (overbought) and "discount" (oversold) levels with greater accuracy, all presented with a clean, futuristic aesthetic designed for the modern trader.
The Core Concept: Price vs. Value The market is constantly trying to find equilibrium. The AVO is built on the principle that the high and low of a significant prior period (like the previous day or week) create a powerful area of perceived value.
The Value Zone: The range between the high and low of the selected higher timeframe.
Premium Territory (Distribution Zone): When the oscillator moves into the glowing pink/purple zone above +100, it is trading at a premium.
Discount Territory (Accumulation Zone): When the oscillator moves into the glowing teal/blue zone below -100, it is trading at a discount.
Key Features
1. Glowing Gradient Oscillator: The main oscillator line is a dynamic visual guide to momentum.
The line changes color smoothly from light blue to neon teal as bullish momentum increases.
It shifts from hot pink to bright purple as bearish momentum increases.
Multiple transparent layers create a professional "glow" effect, making the trend easy to see at a glance.
2. Dynamic Volatility Histogram: This histogram at the bottom of the indicator is a custom volatility meter. It has been engineered to be adaptive, ensuring that the visual differences between high and low volatility are always clear and dramatic, no matter your zoom level. It uses a multi-color gradient to visualize the intensity of market volatility.
3. Volatility Regime Dashboard: This simple on-screen table analyzes the histogram and provides a clear, one-word summary of the current market state: Compressing, Stable, or Expanding.
How to Use the AVO: Trading Strategies
1. Reversion Trading This is the most direct way to use the indicator.
Look for Buys: When the AVO line drops into the teal "Accumulation Zone" (below -100), the price is trading at a discount. Watch for the oscillator to form a bottom and start turning up as a signal that buying pressure is returning.
Look for Sells: When the AVO line moves into the pink "Distribution Zone" (above +100), the price is trading at a premium. Watch for the oscillator to form a peak and start turning down as a signal that selling pressure is increasing.
2. Best Practices & Settings
Timeframe Synergy: The AVO is most effective when your chart timeframe is lower than your selected "Value Zone Source." For example, if you trade on the 1-hour chart, set your Value Zone to "Previous Day."
Confirmation is Key: This indicator provides powerful context, but it should not be used in isolation. Always combine its readings with your primary analysis, such as market structure and support/resistance levels.
Trend Pro V2 [CRYPTIK1]Introduction: What is Trend Pro V2?
Welcome to Trend Pro V2! This analysis tool give you at-a-glance understanding of the market's direction. In a noisy market, the single most important factor is the dominant trend. Trend Pro V2 filters out this noise by focusing on one core principle: trading with the primary momentum.
Instead of cluttering your chart with confusing signals, this indicator provides a clean, visual representation of the trend, helping you make more confident and informed trading decisions.
The dashboard provides a simple, color-coded view of the trend across multiple timeframes.
The Core Concept: The Power of Confluence
The strength of any trading decision comes from confluence—when multiple factors align. Trend Pro V2 is built on this idea. It uses a long-term moving average (200-period EMA by default) to define the primary trend on your current chart and then pulls in data from three higher timeframes to confirm whether the broader market agrees.
When your current timeframe and the higher timeframes are all aligned, you have a state of "confluence," which represents a higher-probability environment for trend-following trades.
Key Features
1. The Dynamic Trend MA:
The main moving average on your chart acts as your primary guide. Its color dynamically changes to give you an instant read on the market.
Teal MA: The price is in a confirmed uptrend (trading above the MA).
Pink MA: The price is in a confirmed downtrend (trading below the MA).
The moving average changes color to instantly show you if the trend is bullish (teal) or bearish (pink).
2. The Multi-Timeframe (MTF) Trend Dashboard:
Located discreetly in the bottom-right corner, this dashboard is your window into the broader market sentiment. It shows you the trend status on three customizable higher timeframes.
Teal Box: The trend is UP on that timeframe.
Pink Box: The trend is DOWN on that timeframe.
Gray Box: The price is neutral or at the MA on that timeframe.
How to Use Trend Pro V2: A Simple Framework
Step 1: Identify the Primary Trend
Look at the color of the MA on your chart. This is your starting point. If it's teal, you should generally be looking for long opportunities. If it's pink, you should be looking for short opportunities.
Step 2: Check for Confluence
Glance at the MTF Trend Dashboard.
Strong Confluence (High-Probability): If your main chart shows an uptrend (Teal MA) and the dashboard shows all teal boxes, the market is in a strong, unified uptrend. This is a high-probability environment to be a buyer on dips.
Weak or No Confluence (Caution Zone): If your main chart shows an uptrend, but the dashboard shows pink or gray boxes, it signals disagreement among the timeframes. This is a sign of market indecision and a lower-probability environment. It's often best to wait for alignment.
Here, the daily trend is down, but the MTF dashboard shows the weekly trend is still up—a classic sign of weak confluence and a reason for caution.
Best Practices & Settings
Timeframe Synergy: For best results, use Trend Pro on a lower timeframe and set your dashboard to higher timeframes. For example, if you trade on the 1-hour chart, set your MTF dashboard to the 4-hour, 1-day, and 1-week.
Use as a Confirmation Tool: Trend Pro V2 is designed as a foundational layer for your analysis. First, confirm the trend, then use your preferred entry method (e.g., support/resistance, chart patterns) to time your trade.
This is a tool for the community, so feel free to explore the open-source code, adapt it, and build upon it. Happy trading!
For your consideration @TradingView
Bollinger Adaptive Trend Navigator [QuantAlgo]🟢 Overview
The Bollinger Adaptive Trend Navigator synthesizes volatility channel analysis with variable smoothing mechanics to generate trend identification signals. It uses price positioning within Bollinger Band structures to modify moving average responsiveness, while incorporating ATR calculations to establish trend line boundaries that constrain movement during volatile periods. The adaptive nature makes this indicator particularly valuable for traders and investors working across various asset classes including stocks, forex, commodities, and cryptocurrencies, with effectiveness spanning multiple timeframes from intraday scalping to longer-term position analysis.
🟢 How It Works
The core mechanism calculates price position within Bollinger Bands and uses this positioning to create an adaptive smoothing factor:
bbPosition = bbUpper != bbLower ? (source - bbLower) / (bbUpper - bbLower) : 0.5
adaptiveFactor = (bbPosition - 0.5) * 2 * adaptiveMultiplier * bandWidthRatio
alpha = math.max(0.01, math.min(0.5, 2.0 / (bbPeriod + 1) * (1 + math.abs(adaptiveFactor))))
This adaptive coefficient drives an exponential moving average that responds more aggressively when price approaches Bollinger Band extremes:
var float adaptiveTrend = source
adaptiveTrend := alpha * source + (1 - alpha) * nz(adaptiveTrend , source)
finalTrend = 0.7 * adaptiveTrend + 0.3 * smoothedCenter
ATR-based volatility boundaries constrain the final trend line to prevent excessive movement during volatile periods:
volatility = ta.atr(volatilityPeriod)
upperBound = bollingerTrendValue + (volatility * volatilityMultiplier)
lowerBound = bollingerTrendValue - (volatility * volatilityMultiplier)
The trend line direction determines bullish or bearish states through simple slope comparison, with the final output displaying color-coded signals based on the synthesis of Bollinger positioning, adaptive smoothing, and volatility constraints (green = long/buy, red = short/sell).
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward direction based on Bollinger positioning and adaptive smoothing = Potential long/buy opportunity
Falling Trend Line (Red): Indicates downward direction based on Bollinger positioning and adaptive smoothing = Potential short/sell opportunity
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant development without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency
Configuration Presets: Three parameter sets available - Default (standard settings), Scalping (faster response), and Swing Trading (slower response)
8 EMA/SMA + HMA + Pivot PointsMultiple customizeable Moing average indictors including Hall moving average, Exponential Moving average. Also includes Pivot Point indicator as an all-in-one indicator
Sine Weighted Trend Navigator [QuantAlgo]🟢 Overview
The Sine Weighted Trend Navigator utilizes trigonometric mathematics to create a trend-following system that adapts to various market volatility. Unlike traditional moving averages that apply uniform weights, this indicator employs sine wave calculations to distribute weights across historical price data, creating a more responsive yet smooth trend measurement. Combined with volatility-adjusted boundaries, it produces actionable directional signals for traders and investors across various market conditions and asset classes.
🟢 How It Works
At its core, the indicator applies sine wave mathematics to weight historical prices. The system generates angular values across the lookback period and transforms them through sine calculations, creating a weight distribution pattern that naturally emphasizes recent price action while preserving smoothness. The phase shift feature allows rotation of this weighting pattern, enabling adjustment of the indicator's responsiveness to different market conditions.
Surrounding this sine-weighted calculation, the system establishes volatility-responsive boundaries through market volatility analysis. These boundaries expand and contract based on current market conditions, creating a dynamic framework that helps distinguish meaningful trend movements from random price fluctuations.
The trend determination logic compares the sine-weighted value against these adaptive boundaries. When the weighted value exceeds the upper boundary, it signals upward momentum. When it drops below the lower boundary, it indicates downward pressure. This comparison drives the color transitions of the main trend line, shifting between bullish (green) and bearish (red) states to provide clear directional guidance on price charts.
🟢 How to Use
Green/Bullish Trend Line: Rising momentum indicating optimal conditions for long positions (buy)
Red/Bearish Trend Line: Declining momentum signaling favorable timing for short positions (sell)
Steepening Green Line: Accelerating bullish momentum with increasing sine-weighted values indicating strengthening upward pressure and high-probability trend continuation
Steepening Red Line: Intensifying bearish momentum with declining sine-weighted calculations suggesting persistent downward pressure and optimal shorting opportunities
Flattening Trend Lines: Gradual reduction in directional momentum regardless of color may indicate approaching consolidation or trend exhaustion requiring position management review
🟢 Pro Tips for Trading and Investing
→ Preset Strategy Selection: Utilize the built-in presets strategically - Scalping preset for ultra-responsive 1-15 minute charts, Default preset for balanced general trading, and Swing Trading preset for 1-4 hour charts and multi-day positions.
→ Phase Shift Optimization: Fine-tune the phase shift parameter based on market bias - use positive values (0.1-0.5) in trending bull markets to enhance uptrend sensitivity, negative values (-0.1 to -0.5) in bear markets for improved downtrend detection, and zero for balanced neutral market conditions.
→ Multiplier Calibration: Adjust the multiplier according to market volatility and trading style. Use lower values (0.5-1.0) for tight, responsive signals in stable markets, higher values (2.0-3.0) during earnings seasons or high-volatility periods to filter noise and reduce whipsaws.
→ Sine Period Adaptation: Customize the sine weighted period based on your trading timeframe and market conditions. Use 5-14 for day trading to capture short-term momentum shifts, 14-25 for swing trading to balance responsiveness with reliability, and 25-50 for position trading to maintain long-term trend clarity.
→ Multi-Timeframe Sine Validation: Apply the indicator across multiple timeframes simultaneously, using higher timeframes (4H/Daily) for overall trend bias and lower timeframes (15m/1H) for entry timing, ensuring sine-weighted calculations align across different time horizons.
→ Alert-Driven Systematic Execution: Leverage the built-in trend change alerts to eliminate emotional decision-making and capture every mathematically-confirmed trend transition, particularly valuable for traders managing multiple instruments or those unable to monitor charts continuously.
→ Risk Management: Increase position sizes during strong directional sine-weighted momentum while reducing exposure during frequent color changes that indicate mathematical uncertainty or ranging market conditions lacking clear directional bias.
inside forex vip📌 SuperTrend
Based on:
ATR Period (default 10).
Multiplier ATR (default 3).
Calculates the trend direction (upward/downward).
Generates buy/sell signals:
Buy: Positive crossover with EMA color matching (bullish).
Sell: Negative crossover with EMA color matching (bearish).
RSI Trend Navigator [QuantAlgo]🟢 Overview
The RSI Trend Navigator integrates RSI momentum calculations with adaptive exponential moving averages and ATR-based volatility bands to generate trend-following signals. The indicator applies variable smoothing coefficients based on RSI readings and incorporates normalized momentum adjustments to position a trend line that responds to both price action and underlying momentum conditions.
🟢 How It Works
The indicator begins by calculating and smoothing the RSI to reduce short-term fluctuations while preserving momentum information:
rsiValue = ta.rsi(source, rsiPeriod)
smoothedRSI = ta.ema(rsiValue, rsiSmoothing)
normalizedRSI = (smoothedRSI - 50) / 50
It then creates an adaptive smoothing coefficient that varies based on RSI positioning relative to the midpoint:
adaptiveAlpha = smoothedRSI > 50 ? 2.0 / (trendPeriod * 0.5 + 1) : 2.0 / (trendPeriod * 1.5 + 1)
This coefficient drives an adaptive trend calculation that responds more quickly when RSI indicates bullish momentum and more slowly during bearish conditions:
var float adaptiveTrend = source
adaptiveTrend := adaptiveAlpha * source + (1 - adaptiveAlpha) * nz(adaptiveTrend , source)
The normalized RSI values are converted into price-based adjustments using ATR for volatility scaling:
rsiAdjustment = normalizedRSI * ta.atr(14) * sensitivity
rsiTrendValue = adaptiveTrend + rsiAdjustment
ATR-based bands are constructed around this RSI-adjusted trend value to create dynamic boundaries that constrain trend line positioning:
atr = ta.atr(atrPeriod)
deviation = atr * atrMultiplier
upperBound = rsiTrendValue + deviation
lowerBound = rsiTrendValue - deviation
The trend line positioning uses these band constraints to determine its final value:
if upperBound < trendLine
trendLine := upperBound
if lowerBound > trendLine
trendLine := lowerBound
Signal generation occurs through directional comparison of the trend line against its previous value to establish bullish and bearish states:
trendUp = trendLine > trendLine
trendDown = trendLine < trendLine
if trendUp
isBullish := true
isBearish := false
else if trendDown
isBullish := false
isBearish := true
The final output colors the trend line green during bullish states and red during bearish states, creating visual buy/long and sell/short opportunity signals based on the combined RSI momentum and volatility-adjusted trend positioning.
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward momentum where RSI influence and adaptive smoothing favor continued price advancement = Potential buy/long positions
Declining Trend Line (Red): Indicates downward momentum where RSI influence and adaptive smoothing favor continued price decline = Potential sell/short positions
Flattening Trend Lines: Occur when momentum weakens and the trend line slope approaches neutral, suggesting potential consolidation before the next move
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, sending "RSI Trend Bullish Signal" or "RSI Trend Bearish Signal" messages for timely entry/exit
Color Bar Candles Option: Optional candle coloring feature that applies the same green/red trend colors to price bars, providing additional visual confirmation of the current trend direction
Linear Regression Trend Navigator [QuantAlgo]🟢 Overview
The Linear Regression Trend Navigator is a trend-following indicator that combines statistical regression analysis with adaptive volatility bands to identify and track dominant market trends. It employs linear regression mathematics to establish the underlying trend direction, while dynamically adjusting trend boundaries based on standard deviation calculations to filter market noise and maintain trend continuity. The result is a straightforward visual system where green indicates bullish conditions favoring buy/long positions, and red signals bearish conditions supporting sell/short trades.
🟢 How It Works
The indicator operates through a three-phase computational process that transforms raw price data into adaptive trend signals. In the first phase, it calculates a linear regression line over the specified period, establishing the mathematical best-fit line through recent price action to determine the underlying directional bias. This regression line serves as the foundation for trend analysis by smoothing out short-term price variations while preserving the essential directional characteristics.
The second phase constructs dynamic volatility boundaries by calculating the standard deviation of price movements over the defined period and applying a user-adjustable multiplier. These upper and lower bounds create a volatility-adjusted channel around the regression line, with wider bands during volatile periods and tighter bands during stable conditions. This adaptive boundary system operates entirely behind the scenes, ensuring the trend signal remains relevant across different market volatility regimes without cluttering the visual display.
In the final phase, the system generates a simple trend line that dynamically positions itself within the volatility boundaries. When price action pushes the regression line above the upper bound, the trend line adjusts to the upper boundary level. Conversely, when the regression line falls below the lower bound, the trend line moves to the lower boundary. The result is a single colored line that transitions between green (rising trend line = buy/long) and red (declining trend line = sell/short).
🟢 How to Use
Green Trend Line: Upward momentum indicating favorable conditions for long positions, buy signals, and bullish strategies
Red Trend Line: Downward momentum signaling optimal timing for short positions, sell signals, and bearish approaches
Rising Green Line: Accelerating bullish momentum with steepening angles indicating strengthening upward pressure and potential for trend continuation
Declining Red Line: Intensifying bearish momentum with increasing negative slopes suggesting persistent downward pressure and shorting opportunities
Flattening Trend Lines: Gradual reduction in slope regardless of color may indicate approaching consolidation or momentum exhaustion requiring position review
🟢 Pro Tips for Trading and Investing
→ Entry/Exit Timing: Trade exclusively on band color transitions rather than price patterns, as each color change represents a statistically-confirmed shift that has passed through volatility filtering, providing higher probability setups than traditional technical analysis.
→ Parameter Optimization for Asset Classes: Customize the linear regression period based on your trading style. For example, use 5-10 bars for day trading to capture short-term statistical shifts, 14-20 for swing trading to balance responsiveness with stability, and 25-50 for position trading to filter out medium-term noise.
→ Volatility Calibration Strategy: Adjust the standard deviation multiplier according to market volatility. For instance, increase to 2.0+ during high-volatility periods like earnings or news events to reduce false signals, decrease to 1.0-1.5 during stable market conditions to maintain sensitivity to genuine trends.
→ Cross-Timeframe Statistical Validation: Apply the indicator across multiple timeframes simultaneously, using higher timeframes for directional bias and lower timeframes for entry timing.
→ Alert-Based Systematic Trading: Use built-in alerts to eliminate discretionary decision-making and ensure you capture every statistically-significant trend change, particularly effective for traders who cannot monitor charts continuously.
→ Risk Allocation Based on Signal Strength: Increase position sizes during periods of strong directional movement while reducing exposure during frequent band color changes that indicate statistical uncertainty or ranging conditions.
Sequential Pattern Strength [QuantAlgo]🟢 Overview
The Sequential Pattern Strength indicator measures the power and sustainability of consecutive price movements by tracking unbroken sequences of up or down closes. It incorporates sequence quality assessment, price extension analysis, and automatic exhaustion detection to help traders identify when strong trends are losing momentum and approaching potential reversal or continuation points.
🟢 How It Works
The indicator's key insight lies in its sequential pattern tracking system, where pattern strength is measured by analyzing consecutive price movements and their sustainability:
if close > close
upSequence := upSequence + 1
downSequence := 0
else if close < close
downSequence := downSequence + 1
upSequence := 0
The system calculates sequence quality by measuring how "perfect" the consecutive moves are:
perfectMoves = math.max(upSequence, downSequence)
totalMoves = math.abs(bar_index - ta.valuewhen(upSequence == 1 or downSequence == 1, bar_index, 0))
sequenceQuality = totalMoves > 0 ? perfectMoves / totalMoves : 1.0
First, it tracks price extension from the sequence starting point:
priceExtension = (close - sequenceStartPrice) / sequenceStartPrice * 100
Then, pattern exhaustion is identified when sequences become overextended:
isExhausted = math.abs(currentSequence) >= maxSequence or
math.abs(priceExtension) > resetThreshold * math.abs(currentSequence)
Finally, the pattern strength combines sequence length, quality, and price movement with momentum enhancement:
patternStrength = currentSequence * sequenceQuality * (1 + math.abs(priceExtension) / 10)
enhancedSignal = patternStrength + momentum * 10
signal = ta.ema(enhancedSignal, smooth)
This creates a sequence-based momentum indicator that combines consecutive movement analysis with pattern sustainability assessment, providing traders with both directional signals and exhaustion insights for entry/exit timing.
🟢 Signal Interpretation
Positive Values (Above Zero): Sequential pattern strength indicating bullish momentum with consecutive upward price movements and sustained buying pressure = Long/Buy opportunities
Negative Values (Below Zero): Sequential pattern strength indicating bearish momentum with consecutive downward price movements and sustained selling pressure = Short/Sell opportunities
Zero Line Crosses: Pattern transitions between bullish and bearish regimes, indicating potential trend changes or momentum shifts when sequences break
Upper Threshold Zone: Area above maximum sequence threshold (2x maxSequence) indicating extremely strong bullish patterns approaching exhaustion levels
Lower Threshold Zone: Area below negative threshold (-2x maxSequence) indicating extremely strong bearish patterns approaching exhaustion levels
Mean Reversion Channel [QuantAlgo]🟢 Overview
The Mean Reversion Channel indicator is a range-bound trading system that combines dynamic price channels with momentum-weighted analysis to identify optimal mean reversion opportunities. It creates adaptive upper and lower reversion zones based on recent price action and volatility, while incorporating a momentum-biased equilibrium line that shifts based on volume-weighted price momentum. This creates a three-tier system where traders and investors can identify overbought and oversold conditions within established ranges, detect momentum exhaustion points, and anticipate channel breakouts or breakdowns. This indicator is particularly valuable for strategic dollar cost averaging (DCA) strategies, as it helps identify optimal accumulation zones during oversold conditions and provides tactical risk management levels for systematic investment approaches across different market conditions and asset classes.
🟢 How It Works
The indicator employs a four-stage calculation process that transforms raw price and volume data into actionable mean reversion signals. First, it establishes the base channel by calculating the highest high and lowest low over a user-defined lookback period, creating the foundational price range for mean reversion analysis. This channel adapts continuously as new price data becomes available, ensuring the system remains relevant to current market conditions.
In the second stage, the system calculates volume-weighted momentum by combining price momentum with volume activity. The momentum calculation takes the price change over a specified period and multiplies it by the volume ratio (current volume versus 20-period average volume, for instance) and a volume factor multiplier. This creates momentum readings that are more significant during high-volume periods and less influential during low-volume conditions.
The third stage creates the dynamic reversion zones using Average True Range (ATR) calculations. The upper reversion zone is positioned below the channel high by an ATR-based distance, while the lower reversion zone is positioned above the channel low. These zones contract when momentum is negative (upper zone) or positive (lower zone), creating asymmetric reversion bands that adapt to momentum conditions.
The final stage establishes the momentum-biased equilibrium line by calculating the midpoint between the reversion zones and adjusting it based on momentum bias. When momentum is positive, the equilibrium shifts upward; when negative, it shifts downward. This creates a dynamic reference level that helps identify when price action is moving against the prevailing momentum trend, signaling potential mean reversion opportunities.
🟢 How to Use
1. Mean Reversion Signal Identification
Lower Reversion Zone Signals: When price reaches or falls below the lower reversion zone with bearish momentum, the system generates potential long/buy entry signals indicating oversold conditions within the established range.
Upper Reversion Zone Signals: When price reaches or exceeds the upper reversion zone with bullish momentum, the system generates potential short/sell entry signals indicating overbought conditions.
2. Equilibrium Line Analysis and Momentum Exhaustion
Equilibrium Breaks: The dynamic equilibrium line serves as a momentum bias indicator within the channel. Price crossing above equilibrium suggests shifting to bullish bias, while breaks below indicate bearish bias development within the mean reversion framework.
Momentum Exhaustion Signals: The system identifies momentum exhaustion when price breaks through the equilibrium line opposite to the prevailing momentum direction. Bullish exhaustion occurs when price falls below equilibrium despite positive momentum, while bearish exhaustion happens when price rises above equilibrium during negative momentum periods.
3. Channel Expansion and Breakout Detection
Channel Boundary Breaks: When price breaks above the upper reversion zone or below the lower reversion zone, it signals potential channel expansion or false breakout conditions. These events often precede significant trend changes or range expansion phases.
Range Expansion Alerts: Breaks above the channel high or below the channel low indicate potential breakout from the mean reversion range, suggesting trend continuation or new directional movement beyond the established boundaries.
🟢 Pro Tips for Trading and Investing
→ Strategic DCA Optimization: Use the lower reversion zone as primary accumulation levels for dollar cost averaging strategies. When price reaches oversold conditions with bearish momentum exhaustion signals, it often represents optimal entry points for systematic investment programs, allowing investors to accumulate positions at statistically favorable price levels within the established range.
→ DCA Pause and Acceleration Signals : Monitor equilibrium line breaks to adjust DCA frequency and amounts. When price consistently trades below equilibrium with momentum exhaustion signals, consider accelerating DCA intervals or increasing investment amounts. Conversely, when price reaches upper reversion zones, consider pausing or reducing DCA activity until more favorable conditions return.
→ Momentum Divergence Detection: Watch for divergences between price action and momentum readings within the channel. When price makes new lows but momentum shows improvement, or price makes new highs with deteriorating momentum, these signal high-probability mean reversion setups ideal for contrarian investment approaches.
→ Alert-Based Systematic Investing/Trading: Utilize the comprehensive alert system for automated DCA triggers. Set up alerts for lower reversion zone touches combined with momentum exhaustion signals to create systematic entry points that remove emotional decision-making from long-term investment strategies, particularly effective for volatile assets where timing improvements can significantly impact overall returns.
