Level Founder indicatorQuesto strumento, ideato per l'individuazione dei livelli orizzontali sensibili si prepone l'obiettivo di semplificare la lettura tecnica dei grafici. Alla base di questo indicatore c'è il concetto di volatilità, inteso come scontro tra domanda ed offerta, come escursione delle forze nel campo di battaglia fino alla determinazione del prezzo finale di ogni candela. Di fatto, andando a cogliere quella che è la volatilità candela per candela, l'indicatore la calcola in termini assoluti rendendola un numericamente comparabile, in un range tra 0 e 100. Quando questo valore tocca i 100 si genera un picco di volatilità, il quale va ad identificare un punto di attenzione sul grafico di uno strumento. In corrispondenza di questi picchi si osserva dove la battaglia tra compratori e venditori si è conclusa, ovvero dove domanda ed offerta si sono incontrati per definire un prezzo: la chiusura di candela. In corrispondenza di tale prezzo si ha, quindi, un accordo certo tra domanda ed offerta dopo un periodo di contrattazione volatile, andando a certificare quello che è un livello di prezzo "sudato" per un determinato sottostante. Tale soglia si traduce in un livello orizzontale sensibile, che in futuro (avendo il mercato memoria degli scontri passati) potrà comportarsi da supporto o da resistenza, a seconda della situazione. In breve quindi, si traccia una linea orizzontale in corrispondenza delle chiusure di candela che condividono un picco sull'indicatore "Level Founder Indicator". Funziona su ogni time-frame e sottostante.
N.B. A ridosso di questi livelli si possono cercare pattern per l'operatività oppure cercare delle rotture di questi livelli per delle conferme/inversioni, spaziando dal trading intraday all'investimento di lungo periodo.
ENGLISH VERSION:
This tool, designed to identify sensitive horizontal levels, aims to simplify the technical reading of charts. This indicator is based on the concept of volatility, understood as the clash between supply and demand, the oscillation of forces on the battlefield until the final price of each candlestick is determined. By capturing the volatility candlestick by candlestick, the indicator calculates it in absolute terms, making it numerically comparable, within a range between 0 and 100. When this value reaches 100, a volatility spike is generated, which identifies a point of focus on an instrument's chart. At these peaks, we observe where the battle between buyers and sellers has concluded, that is, where supply and demand have met to define a price: the candlestick's close. At this price, therefore, a definite agreement between supply and demand occurs after a period of volatile trading, certifying what is a "hard-earned" price level for a given underlying asset. This threshold translates into a sensitive horizontal level, which in the future (given the market's memory of past clashes) could act as support or resistance, depending on the situation. In short, a horizontal line is drawn at the candlestick closes that share a peak on the "Level Founder Indicator." It works on any timeframe and underlying asset.
N.B.: Near these levels, you can look for trading patterns or look for breakouts of these levels for confirmations/reversals, ranging from intraday trading to long-term investing.
חפש סקריפטים עבור "technical"
Quarter Strength Table (3M) [CHE] Quarter Strength Table (3M) — quarterly seasonality overview for the current symbol
Is there seasonality in certain assets? Some YouTubers claim there is—can you test it yourself?
Summary
This indicator builds a compact table that summarizes quarterly seasonality from three-month bars. It aggregates the simple return of each historical quarter, counts observations, computes the average return and the win rate for each quarter, and flags the historically strongest quarter. The output is a five-column table rendered on the chart, designed for quick comparison rather than signal generation. Because it processes only confirmed higher-timeframe bars, results are stable once a quarter has closed.
Motivation: Why this design?
Seasonality tools often mix intraperiod estimates with live bars, which can lead to misleading flips and inconsistent statistics. The core idea here is to restrict aggregation to completed three-month bars only and to deduplicate events by timestamp. This avoids partial information and double counting, so the table reflects a consistent, closed-bar history.
What’s different vs. standard approaches?
Baseline: Typical seasonality studies that compute monthly or quarterly stats directly on the chart timeframe or update on live higher-timeframe bars.
Architecture differences:
Uses explicit higher-timeframe requests for open, close, time, and calendar month from three-month bars.
Confirms the higher-timeframe bar before recording a sample; deduplicates by the higher-timeframe timestamp.
Keeps fixed arrays of length four for the four quarters; renders a fixed five-by-five table with zebra rows.
Practical effect: Once a quarter closes, counts and averages are stable. The “Best” column marks the highest average quarter so you can quickly identify the historically strongest period.
How it works (technical)
On every chart bar, the script requests three-month open, close, time, and the calendar month derived from that bar’s time. When the three-month bar is confirmed, it computes the simple return for that bar and maps the month to a quarter index between zero and three. A guard stores the last seen three-month timestamp to avoid duplicate writes. Per quarter, it accumulates the sum of returns, the number of samples, and the number of positive samples. From these, it derives average return and win rate. The table header is created once on the first bar; content updates only on the last visible chart bar for efficiency. No forward references are used, and lookahead is disabled in all higher-timeframe requests to avoid peeking.
Parameter Guide
Percent — Formats values as percentages. Default: true. Trade-off: Easier visual comparison; disable if you prefer raw unit returns.
Decimals — Number of digits shown. Default: two. Bounds: zero to six. Trade-off: More digits improve precision but reduce readability.
Show table — Toggles table rendering. Default: true. Trade-off: Disable when space is limited or for batch testing.
Reading & Interpretation
The table shows rows for Q1 through Q4 and columns for Count, Avg Ret, P(win), and Best.
Count: Number of completed three-month bars observed for that quarter.
Avg Ret: Average simple return across all samples in that quarter.
P(win): Share of samples with a positive return.
Best: An asterisk marks the quarter with the highest average return among those with at least one sample.
Use the combination of average and win rate to judge both magnitude and consistency. Low counts signal limited evidence.
Practical Workflows & Combinations
Trend following filter: Favor setups when the upcoming or active quarter historically shows a positive average and a stable win rate. Combine with structure analysis such as higher highs and higher lows to avoid fighting dominant trends.
Exits and risk: When entering during a historically weak quarter, consider tighter risk controls and quicker profit taking.
Multi-asset and multi-timeframe: The default settings work across most liquid symbols. For assets with sparse history, treat results as low confidence due to small sample sizes.
Behavior, Constraints & Performance
Repaint and confirmation: Aggregation occurs only when the three-month bar is confirmed; values do not change afterward for that bar. During an open quarter, no new sample is added.
Higher-timeframe usage: All higher-timeframe requests disable lookahead and rely on confirmation to mitigate repaint.
Resources: Declared `max_bars_back` is two thousand. Arrays are fixed at length four. The script updates the table only on the last visible bar to reduce work.
Known limits: Averages can be affected by outliers and structural market changes. Limited history reduces reliability. Corporate actions and contract rolls may influence returns depending on the symbol’s data source. This is a visualization and not a trading system.
Sensible Defaults & Quick Tuning
Starting values: Percent true; Decimals two; Show table true.
If numbers feel noisy: Decrease decimals to one to reduce visual clutter.
If you need raw values: Turn off Percent to display unit returns.
If the table overlaps price: Toggle Show table off when annotating, or reposition via your chart’s table controls.
What this indicator is—and isn’t
This is a historical summary of quarterly behavior. It visualizes evidence and helps frame expectations. It is not predictive, does not generate trade signals, and does not manage positions or risk. Always combine with market structure, liquidity considerations, and independent risk controls.
Inputs with defaults
Percent: true, boolean.
Decimals: two, integer between zero and six.
Show table: true, boolean.
Pine version: v6
Overlay: true
Primary outputs: Table with five columns and five rows.
Metrics/functions used: Higher-timeframe data requests, table rendering, arrays, bar state checks, month mapping.
Special techniques: Closed-bar aggregation, deduplication by higher-timeframe timestamp, zebra row styling.
Performance/constraints: Two thousand bars back, small fixed loops, higher-timeframe requests without lookahead.
Compatibility/assets/timeframes: Works on time-based charts across most assets with sufficient history.
Limitations/risks: Sample size sensitivity, regime shifts, data differences across venues.
Debug/diagnostics: (Unknown/Optional)
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
ATR Volatility and Trend AnalysisATR Volatility and Trend Analysis
Unlock the power of the Average True Range (ATR) with the ATR Volatility and Trend Analysis indicator. This comprehensive tool is designed to provide traders with a multi-faceted view of market dynamics, combining volatility analysis, dynamic support and resistance levels, and trend detection into a single, easy-to-use indicator.
How It Works
The ATR Volatility and Trend Analysis indicator is built upon the core concept of the ATR, a classic measure of market volatility. It expands on this by providing several key features:
Dynamic ATR Bands: The indicator plots three sets of upper and lower bands around the price. These bands are calculated by multiplying the current ATR value by user-defined multipliers. They act as dynamic support and resistance levels, widening during volatile periods and contracting during calm markets.
Volatility Breakout Signals: Identify potential breakouts with precision. The indicator generates a signal when the current ATR value surges above its own moving average by a specified threshold, indicating a significant increase in volatility that could lead to a strong price move.
Trend Detection: The indicator determines the market trend by analyzing both price action and ATR behavior. A bullish trend is signaled when the price is above its moving average and volatility is increasing. Conversely, a bearish trend is signaled when the price is below its moving average and volatility is increasing.
How to Use the ATR Multi-Band Indicator
Identify Support and Resistance: Use the ATR bands as key levels. Price approaching the outer bands may indicate overbought or oversold conditions, while a break of the bands can signal a strong continuation.
Confirm Breakouts: Look for a volatility breakout signal to confirm the strength behind a price move. A breakout from a consolidation range accompanied by a volatility signal is a strong indicator of a new trend.
Trade with the Trend: Use the background coloring and trend signals to align your trades with the dominant market direction. Enter long positions during confirmed bullish trends and short positions during bearish trends.
Set Up Alerts: The indicator includes alerts for band crosses, trend changes, and volatility breakouts, ensuring you never miss a potential trading opportunity.
What makes it different?
While many indicators use ATR, the ATR Volatility and Trend Analysis tool is unique in its integration of multiple ATR-based concepts into a single, cohesive system. It doesn't just show volatility; it interprets it in the context of price action to deliver actionable trend and breakout signals, making it a complete solution for ATR-based analysis.
Disclaimer
This indicator is designed as a technical analysis tool and should be used in conjunction with other forms of analysis and proper risk management.
Past performance does not guarantee future results, and traders should thoroughly test any strategy before implementing it with real capital.
Seasonal Pattern DecoderSeasonal Pattern Decoder
The Seasonal Pattern Decoder is a powerful tool designed for traders and analysts who want to uncover and leverage seasonal tendencies in financial markets. Instead of cluttering your chart with complex visuals, this indicator presents a clean, intuitive table that summarizes historical monthly performance, allowing you to spot recurring patterns at a glance.
How It Works
The indicator fetches historical monthly data for any symbol and calculates the percentage return for each month over a specified number of years. It then organizes this data into a comprehensive table, providing a clear, year-by-year and month-by-month breakdown of performance.
Key Features
Historical Performance Table: Displays monthly returns for up to a user-defined number of years, making it easy to compare performance across different periods.
Color-Coded Heatmap: Each cell is colored based on the performance of the month. Strong positive returns are shaded in green, while strong negative returns are shaded in red, allowing for immediate visual analysis of monthly strength or weakness.
Annual Summary: A "Σ" column shows the total percentage return for each full calendar year.
AVG Row: Calculates and displays the average return for each month across all the years shown in the table.
WR Row: Shows the "Win Rate" for each month, which is the percentage of time that month had a positive return. This is crucial for identifying high-probability seasonal trends.
How to Use
Add the "Seasonal Pattern Decoder" indicator to your chart. Note that it works best on Daily, Weekly, or Monthly timeframes. A warning message will be displayed on intraday charts.
In the indicator settings, adjust the "Lookback Period" to control how many years of historical data you want to analyze.
Use the "Show Years Descending" option to sort the table from the most recent year to the oldest.
The "Heat Range" setting allows you to adjust the sensitivity of the color-coding to fit the volatility of the asset you are analyzing.
This tool is ideal for confirming trading biases, developing seasonal strategies, or simply gaining a deeper understanding of an asset's typical behavior throughout the year.
## Disclaimer
This indicator is designed as a technical analysis tool and should be used in conjunction with other forms of analysis and proper risk management.
Past performance does not guarantee future results, and traders should thoroughly test any strategy before implementing it with real capital.
2MA Cross with Glow Effects 2MA Cross with Glow Effects
Overview
This indicator enhances the classic moving average crossover strategy with a dynamic and visually appealing "glow" effect. It plots two customisable moving averages on the chart and illuminates the area around them when a crossover occurs, providing a clear and intuitive signal for potential trend changes.
Features
Dual Moving Averages: Configure two independent moving averages to suit your trading style.
Multiple MA Types: Choose from a wide range of moving average types for each line, including:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume-Weighted Moving Average)
RMA (Relative Moving Average)
HMA (Hull Moving Average)
ALMA (Arnaud Legoux Moving Average)
LSMA (Least Squares Moving Average)
Customisable Appearance: Adjust the length, line width, and color for each moving average.
Unique Glow Effect: A configurable glow appears around the moving averages during a crossover, providing an unmistakable visual cue. You can control the intensity and width of this effect.
How It Works
The core of the indicator is the calculation of two moving averages based on the user's selected type and length. The script continuously monitors the relationship between these two MAs.
The "glow" is a sophisticated visual effect achieved by using Pine Script's `fill()` function to create a smooth, colored gradient around the MA lines. The glow is conditionally rendered:
When the first moving average (MA1) crosses above the second (MA2), MA1 will glow above its line.
When MA1 crosses below MA2, it will glow below its line.
The same logic is applied to MA2, creating a dual-glow effect that clearly shows which MA is dominant.
To ensure a consistent visual appearance across different chart timeframes, the indicator incorporates a `tfMultiplier` that automatically adjusts the glow's width.
How to Use
This indicator can be used in the same way as a standard moving average crossover strategy
Bullish Signal: Look for the shorter-period moving average to cross above the longer-period moving average. The glow effect will make this event highly visible.
Bearish Signal: Look for the shorter-period moving average to cross below the longer-period moving average.
Traders can use this for trend identification, entry/exit signals, and as a component of a more comprehensive trading system. For example, a common setup is using a 20-period EMA and a 50-period EMA to capture medium-term trends.
Disclaimer
This indicator is designed as a technical analysis tool and should be used in conjunction with other forms of analysis and proper risk management.
Past performance does not guarantee future results, and traders should thoroughly test any strategy before implementing it with real capital.
Adaptive Machine Learning Trading System [PhenLabs]📊Adaptive ML Trading System
Version: PineScript™v6
📌Description
The Adaptive ML Trading System is a sophisticated machine learning indicator that combines ensemble modeling with advanced technical analysis. This system uses XGBoost, Random Forest, and Neural Network algorithms to generate high-confidence trading signals while incorporating robust risk management features. Traders benefit from objective, data-driven decision-making that adapts to changing market conditions.
🚀Points of Innovation
• Machine Learning Ensemble - Three integrated models (XGBoost, Random Forest, Neural Network)
• Confidence-Based Trading - Only executes trades when ML confidence exceeds threshold
• Dynamic Risk Management - ATR-based stop loss and max drawdown protection
• Adaptive Position Sizing - Volatility-adjusted position sizing with confidence weighting
• Real-Time Performance Metrics - Live tracking of win rate, Sharpe ratio, and performance
• Multi-Timeframe Feature Analysis - Adaptive lookback periods for different market regimes
🔧Core Components
• ML Ensemble Engine - Weighted combination of XGBoost, Random Forest, and Neural Network outputs
• Feature Normalization System - Advanced preprocessing with custom tanh/sigmoid activation
• Risk Management Module - Dynamic position sizing and drawdown protection
• Performance Dashboard - Real-time metrics and risk status monitoring
• Alert System - Comprehensive alert conditions for entries, exits, and risk events
🔥Key Features
• High-confidence ML signals with customizable confidence thresholds
• Multiple trading modes (Conservative, Balanced, Aggressive) for different risk profiles
• Integrated stop loss and risk management with ATR-based calculations
• Real-time performance metrics including win rate and Sharpe ratio
• Comprehensive alert system with entry, exit, and risk management notifications
• Visual confidence bands and threshold indicators for easy signal interpretation
🎨Visualization
• ML Signal Line - Primary signal output ranging from -1 to +1
• Confidence Bands - Visual representation of model confidence levels
• Threshold Lines - Customizable buy/sell threshold levels
• Position Histogram - Current market position visualization
• Performance Tables - Real-time metrics display in customizable positions
📖Usage Guidelines
Model Configuration
• Confidence Threshold: Default 0.55, Range 0.5-0.95 - Minimum confidence for signals
• Model Sensitivity: Default 0.9, Range 0.1-2.0 - Adjusts signal sensitivity
• Ensemble Mode: Conservative/Balanced/Aggressive - Trading style preference
• Signal Threshold: Default 0.55, Range 0.3-0.9 - ML signal threshold for entries
Risk Management
• Position Size %: Default 10%, Range 1-50% - Portfolio percentage per trade
• Max Drawdown %: Default 15%, Range 5-30% - Maximum allowed drawdown
• Stop Loss ATR: Default 2.0, Range 0.5-5.0 - Stop loss in ATR multiples
• Dynamic Sizing: Default true - Volatility-based position adjustment
Display Settings
• Show Signals: Default true - Display entry/exit signals
• Show Threshold Signals: Default true - Display ±0.6 threshold crosses
• Show Confidence Bands: Default true - Display ML confidence levels
• Performance Dashboard: Default true - Show metrics table
✅Best Use Cases
• Swing trading with 1-5 day holding periods
• Trend-following strategies in established trends
• Volatility breakout trading during high-confidence periods
• Risk-adjusted position sizing for portfolio management
• Multi-timeframe confirmation for existing strategies
⚠️Limitations
• Requires sufficient historical data for accurate ML predictions
• May experience low confidence periods in choppy markets
• Performance varies across different asset classes and timeframes
• Not suitable for very short-term scalping strategies
• Requires understanding of basic risk management principles
💡What Makes This Unique
• True machine learning ensemble with multiple model types
• Confidence-based trading rather than simple signal generation
• Integrated risk management with dynamic position sizing
• Real-time performance tracking and metrics
• Adaptive parameters that adjust to market conditions
🔬How It Works
Feature Calculation: Computes 20+ technical features from price/volume data
Feature Normalization: Applies custom normalization for ML compatibility
Ensemble Prediction: Combines XGBoost, Random Forest, and Neural Network outputs
Signal Generation: Produces confidence-weighted trading signals
Risk Management: Applies position sizing and stop loss rules
Execution: Generates alerts and visual signals based on thresholds
💡Note:
This indicator works best on daily and 4-hour timeframes for most assets. Ensure you understand the risk management settings before live trading. The system includes automatic risk-off modes that halt trading during excessive drawdown periods.
Market Sentiment Trend Gauge [LevelUp]Market Sentiment Trend Gauge simplifies technical analysis by mathematically combining momentum, trend direction, volatility position, and comparison against a market benchmark, into a single trend score from -100 to +100. Displayed in a separate pane below your chart, it resolves conflicting signals from RSI, moving averages, Bollinger Bands, and market correlations, providing clear insights into trend direction, strength, and relative performance.
THE PROBLEM MARKET SENTIMENT TREND GAUGE (MSTG) SOLVES
Traditional indicators often produce conflicting signals, such as RSI showing overbought while prices rise or moving averages indicating an uptrend despite market underperformance. MSTG creates a weighted composite score to answer: "What's the overall bias for this asset?"
KEY COMPONENTS AND WEIGHTINGS
The trend score combines
▪ Momentum (25%): Normalized 14-period RSI, capped at ±100.
▪ Trend Direction (35%): 10/21-period EMA relationships,
▪ Volatility Position (20%): Price position, 20-period Bollinger Bands, capped at ±100.
▪ Market Comparison (20%): Daily performance vs. SPY benchmark, capped at ±100.
Final score = Weighted sum, smoothed with 5-period EMA.
INTERPRETING THE MSTG CHART
Trend Score Ranges and Colors
▪ Bright Green (>+30): Strong bullish; ideal for long entries.
▪ Light Green (+10 to +30): Weak bullish; cautiously favorable.
▪ Gray (-10 to +10): Neutral; avoid directional trades.
▪ Light Red (-10 to -30): Weak bearish; exercise caution.
▪ Bright Red (<-30): Strong bearish; high-risk for longs, consider shorts.
Reference Lines
▪ Zero Line (Gray): Separates bullish/bearish; crossovers signal trend changes.
▪ ±30 Lines (Dotted, Green/Red): Thresholds for strong trends.
▪ ±60 Lines (Dashed, Green/Red): Extreme strength zones (not overbought/oversold); manage risk (tighten stops, partial profits) but trends may persist.
Background Colors
▪ Green Tint (>+20): Bullish environment; favorable for longs.
▪ Red Tint (<-20): Bearish environment; caution for longs.
▪ Light Gray Tint (-20 to +20): Neutral/range-bound; wait for signals.
Extreme Readings vs. Traditional Signals
MSTG ±60 indicates maximum alignment of all factors, not reversals (unlike RSI >70/<30). Use for risk management, not automatic exits. Strong trends can sustain extremes; breakdowns occur below +30 or above -30.
INFORMATION TABLE INTERPRETATION
Trend Score Symbols
▲▲ >+30 strong bullish
▲ +10 to +30
● -10 to +10 neutral
▼ -30 to -10
▼▼ <-30 strong bearish
Colors: Green (positive), White (neutral), Red (negative).
Momentum Score
+40 to +100 strong bullish
0 to +40 moderate bullish
-40 to 0 moderate bearish
-100 to -40 strong bearish
Market vs. Stock
▪ Green: Stock outperforming market
▪ Red: Stock underperforming market
Example Interpretations:
-0.45% / +1.23% (Green): Market down, stock up = Strong relative strength
+2.10% / +1.50% (Red): Both rising, but stock lagging = Relative weakness
-1.20% / -0.80% (Green): Both falling, but stock declining less = Defensive strength
UNDERSTANDING EXTREME READINGS VS TRADITIONAL OVERBOUGHT/OVERSOLD
⚠️ Critical distinctions
Traditional Overbought/Oversold Signals:
▪ Single indicator (like RSI >70 or <30) showing momentum excess
▪ Often suggests immediate reversal or pullback expected
▪ Based on "price moved too far, too fast" concept
MSTG Extreme Readings (±60):
▪ Composite alignment of 4 different factors (momentum, trend, volatility, relative strength)
▪ Indicates maximum strength in current direction
▪ NOT a reversal signal - means "all systems extremely bullish/bearish"
Key Differences:
▪ RSI >70: "Price got ahead of itself, expect pullback"
▪ MSTG >+60: "Everything is extremely bullish right now"
▪ Strong trends can maintain extreme MSTG readings during major moves
▪ Breakdowns happen when MSTG falls below +30, not at +60
Proper Usage of Extreme Readings:
▪ Risk Management: Tighten stops, take partial profits
▪ Position Sizing: Reduce new position sizes at extremes
▪ Trend Continuation: Watch for sustained extreme readings in strong markets
▪ Exit Signals: Look for breakdown below +30, not reversal from +60
TRADING WITH MSTG
Quick Assessment
1. Check trend symbol for direction.
2. Confirm momentum strength.
3. Note relative performance color.
Examples:
▲▲ 55.2 (Green), Momentum +28.4, Outperforming: Strong buy setup.
▼ -18.6 (Red), Momentum -43.2, Underperforming: Defensive positioning.
Entry Conditions
▪ Long: stock outperforming market
- Score >+30 (bright green)
- Sustained green background
- ▲▲ symbol,
▪ Short: stock underperforming market
- Score <-30 (bright red)
- Sustained red background
- ▼▼ symbol
Avoid Trading When:
▪ Gray zone (-10 to +10).
▪ Rapid color changes or frequent zero-line crosses (choppy market).
▪ Gray background (range-bound).
Risk Management:
▪ Stop Loss: Exit on zero-line crossover against position.
▪ Take Profit: Partial at ±60 for risk control.
▪ Position Sizing: Larger when signals align; smaller in extremes or mixed conditions.
KEY ADVANTAGES
▪ Unified View: Weighted composite reduces noise and conflicts.
▪ Visual Clarity: 5-color system with gradients for rapid recognition.
▪ Market Context: Relative strength vs. SPY identifies leaders/laggards.
▪ Flexibility: Works across timeframes (1-min to weekly); customizable table.
▪ Noise Reduction: EMA smoothing minimizes false signals.
EXAMPLES
Strong Bull: Trend Score 71.9, Momentum Score 76.9
Neutral: Trend Score 0.1, Momentum Score -9.2
Strong Bear: Trend Score -51.7, Momentum Score -51.5
PERFORMANCE AND LIMITATIONS
Strengths: Trend identification, noise reduction, relative performance versus market.
Limitations: Lags at turning points, less effective in extreme volatility or non-trending markets.
Recommendations: View on multiple timeframes, combine with price action and fundamentals.
Swing Dashboard - Pro Trader Metrics with MTF & Enhanced VolumeDESCRIPTION:
A comprehensive real-time dashboard designed for swing traders and active investors trading US equities. Displays all critical metrics in one customizable panel overlay - no need to clutter your chart with multiple indicators.
KEY FEATURES:
📊 Relative Strength Analysis:
Stock vs Market (SPY/QQQ/IWM/DIA)
Stock vs Sector (automatic sector ETF detection)
Sector vs Market comparison
Customizable lookback period (5-60 days)
📈 Price & Range Metrics:
Daily range, change, and gap percentages
Distance from SMA20, SMA50, VWAP
52-week position percentage
ATR% and ADR% for volatility assessment
Range/ADR ratio for breakout detection
💪 Advanced Volume Analysis:
RVOL (full day volume vs 20-day average)
Volume Strength (bar-by-bar analysis)
Volume Trend (5-day vs 20-day momentum)
Customizable RVOL alert thresholds
Non-repainting volume calculations
⚙️ Multi-Timeframe (MTF) Mode:
View daily charts with 5-min or 15-min metric updates
Perfect for monitoring positions without switching timeframes
All calculations remain accurate across timeframes
🎨 Fully Customizable:
Choose which metrics to display
9 position options for the dashboard
Adjustable text size and colors
Toggle individual metrics on/off
Sector-specific ETF mapping for accurate RS calculations
TECHNICAL SPECIFICATIONS:
✅ Non-repainting - all calculations use confirmed bar data
✅ No lookahead bias or future data
✅ Optimized for US stocks with proper sector mapping
✅ Works on any timeframe (best on 5m-Daily)
✅ Pine Script v6 with best practices
✅ Handles edge cases and missing data gracefully
IDEAL FOR:
Swing traders monitoring multiple positions
Day traders needing quick metric overview
Investors tracking relative strength and momentum
Anyone who wants institutional-grade metrics in one place
SECTOR ETF MAPPING:
Automatically maps to correct sector ETFs: XLK, XLF, XLV, XLY, XLP, XLE, XLB, XLI, XLRE, XLC, XLU
HOW TO USE:
Green = Positive/Strong | Red = Negative/Weak | White = Neutral
RS > 0 = Outperforming benchmark/sector
RVOL > 1.5x = High volume day
VWAP% negative = Price below VWAP (mean reversion opportunity)
R/ADR > 100% = Extended range (potential exhaustion)
Perfect for traders who need professional-grade analysis without chart clutter.
TAGS:
dashboard, swing, relativestrengrh, sectoranalysis, volume, rvol, multitimeframe, mtf, tradingdashboard, metrics, daytrading, swingtrading, momentum, vwap, atr, volatility, volumeanalysis
RVol+ Enhanced Relative Volume Indicator📊 RVol+ Enhanced Relative Volume Indicator
Overview
RVol+ (Relative Volume Plus) is an advanced time-based relative volume indicator designed specifically for swing traders and breakout detection. Unlike simple volume comparisons, RVol+ analyzes volume at the same time of day across multiple sessions, providing statistically significant insights into institutional activity and breakout potential.
🎯 Key Features
Core Volume Analysis
Time-Based RVol Calculation - Compares current cumulative volume to the average volume at this exact time over the past N days
Statistical Z-Score - Measures volume in standard deviations from the mean for true anomaly detection
Volume Percentile - Shows where current volume ranks historically (0-100%)
Sustained Volume Filter - 3-bar moving average prevents false signals from single-bar spikes
Breakout Detection
🚀 Confirmed Breakouts - Identifies price breakouts validated by high volume (RVol > 1.5x)
⚠️ False Breakout Warnings - Alerts when price breaks key levels on low volume (high failure risk)
Multi-Timeframe Context - Weekly volume overlay prevents chasing daily noise
Advanced Metrics
OBV Divergence Detection - Spots bullish/bearish accumulation/distribution patterns
Volume Profile Integration - Identifies institutional positioning
Money Flow Analysis - Tracks smart money vs retail activity
Extreme Volume Alerts - 🔥 Labels mark unusual spikes beyond the display cap
Visual Intelligence
Smart Color Coding:
🟢 Bright Teal = High activity (RVol ≥ 1.5x)
🟡 Medium Teal = Caution zone (RVol ≥ 1.2x)
⚪ Light Teal = Normal activity
🟠 Orange = Breakout confirmed
🔴 Red = False breakout risk
Comprehensive Stats Table:
Current Volume (formatted as M/K/B)
RVol ratio
Z-Score with significance
Volume percentile
Historical average and standard deviation
Sustained volume confirmation
📈 How to Use
For Swing Trading (1D - 3W Holds)
Perfect Setup:
✓ RVol > 1.5x (bright teal)
✓ Z-Score > 2.0 (⚡ alert)
✓ Percentile > 90%
✓ Sustained = ✓
✓ 🚀 Breakout label appears
Avoid:
✗ Red "Low Vol" warning during breakouts
✗ RVol < 1.0 at key levels
✗ Sustained volume not confirmed
Signal Interpretation
⚡ Z>2 Labels - Statistically significant volume (95th+ percentile) - highest probability moves
↗️ OBV+ Labels - Bullish accumulation (OBV rising while price consolidates)
↘️ OBV- Labels - Bearish distribution (OBV falling while price rises)
🔵 Blue Background - Weekly volume elevated (confirms daily strength)
⚙️ Customization
Basic Settings
N Day Average - Number of historical days for comparison (default: 5)
RVol Thresholds - Customize highlight levels (default: 1.2x, 1.5x)
Visual Display Cap - Prevent extreme spikes from compressing view (default: 4.0x)
Advanced Metrics (Toggle On/Off)
Z-Score analysis
Weekly RVol context
OBV divergence detection
Volume percentile ranking
Breakout signal generation
Table Customization
Position - 9 placement options to avoid chart overlap
Size - Tiny to Huge
Colors - Full customization of positive/negative/neutral values
Transparency - Adjustable background
Debug Mode
Enable Pine Logs for calculation transparency
Adjustable log frequency
Real-time calculation breakdown
🔬 Technical Details
Algorithm:
Binary search for historical lookups (O(log n) performance)
Time-zone aware session detection
DST-safe timestamp calculations
Exponentially weighted standard deviation
Anti-repainting architecture
Performance:
Optimized for max_bars_back = 5000
Efficient array management
Built-in function optimization
Memory-conscious data structures
📊 What Makes RVol+ Different?
vs. Standard Volume:
Context-aware (time-of-day matters)
Statistical significance testing
False breakout filtering
vs. Basic RVol:
Z-Score normalization (2-3 sigma detection)
Multi-timeframe confirmation
OBV divergence integration
Sustained volume filtering
Smart visual scaling
vs. Professional Tools:
Free and open-source
Fully customizable
No black-box algorithms
Educational debug logs
💡 Best Practices
Wait for Confirmation - Don't enter on first bar; wait for sustained volume ✓
Combine with Price Action - RVol validates, price structure determines entry
Weekly Context Matters - Blue background = institutional interest
Z-Score is King - Focus on ⚡ alerts for highest probability
Avoid Low Volume Breakouts - Red ⚠️ labels = high failure risk
🎓 Trading Psychology
Volume precedes price. When RVol+ shows:
High RVol + Rising OBV = Accumulation before breakout
High RVol at Resistance = Test of conviction
Low RVol on Breakout = Retail-driven (fade candidate)
Z-Score > 3 = Potential "whale" positioning
📝 Credits
Based on the time-based RVol concept from /u/HurlTeaInTheSea, enhanced with:
Statistical analysis (z-scores, percentiles)
Multi-timeframe integration
OBV divergence detection
Professional-grade visualization
Swing trading optimization
🔧 Version History
v2.0 - Enhanced Edition
Added Z-Score analysis
Multi-timeframe volume context
OBV divergence detection
Breakout confirmation system
Smart color coding
Customizable stats table
Debug logging mode
Performance optimizations
📚 Learn More
For optimal use with swing trading:
Combine with support/resistance levels
Watch for volume clusters in consolidation
Use weekly timeframe for trend confirmation
Monitor OBV divergence for early warnings
⚠️ Disclaimer
This indicator is for educational purposes. Volume analysis is one component of trading decisions. Always use proper risk management, consider multiple timeframes, and validate signals with price structure. Past performance does not guarantee future results.
🚀 Getting Started
Add indicator to chart
Adjust "N Day Average" to your preference (5-10 days typical)
Position stats table to avoid overlap
Enable features you want to monitor
Watch for 🚀 breakout confirmations!
Happy Trading! 📈
Relative Performance Indicator - TrendSpider StyleRelative Performance Indicator - TrendSpider Style
📈 Overview
This Relative Performance (RP) indicator measures how your stock is performing compared to a benchmark index, displayed as a percentile ranking from 0-100. Based on TrendSpider's methodology, it answers the critical question: "Is this stock a leader or a laggard?"
Unlike simple ratio charts, this indicator uses percentile ranking to normalize relative performance, making it easy to identify when a stock is showing exceptional strength (>80) or concerning weakness (<20) compared to its historical relationship with the benchmark.
✨ Key Features
Three Calculation Modes:
Quarterly: 3-month relative performance for swing trading
Yearly: Weighted 4-quarter performance for position trading
TechRank: Composite of 6 technical indicators for multi-factor analysis
Clean Visual Design:
Green fills above 80 (strong outperformance)
Red fills below 20 (significant underperformance)
Dotted median line at 50 for quick reference
Current value label for instant reading
Flexible Benchmarks:
Compare against major indices (SPY, QQQ, IWM)
Sector ETFs for within-sector analysis
Custom symbols for specialized comparisons
Built-in Alerts:
Strong performance zone entry (>80)
Weak performance zone entry (<20)
Median crossovers (50 level)
📊 How To Use
Buy Signals:
RP crosses above 80: Stock entering leadership status
RP holding above 60: Maintaining relative strength
RP rising while price consolidating: Accumulation phase
Sell/Avoid Signals:
RP drops below 50: Losing relative strength
RP below 20: Significant underperformance
RP falling while price rising: Bearish divergence
Sector Rotation:
Compare multiple assets to find strongest sectors
Rotate into high RP assets (>70)
Exit low RP positions (<30)
🎯 Reading The Values
80-100: Exceptional outperformance - Strong buy/hold
60-80: Moderate outperformance - Hold positions
40-60: Market perform - No edge
20-40: Underperformance - Caution/reduce
0-20: Severe underperformance - Avoid/exit
⚙️ Calculation Method
Calculates percentage performance of both your stock and the benchmark
Finds the performance differential
Ranks this differential against historical values using percentile analysis
Normalizes to 0-100 scale for easy interpretation
This percentile approach adapts to different market conditions and volatility regimes, providing consistent signals whether in trending or choppy markets.
💡 Pro Tips
For Growth Stocks: Use quarterly mode with QQQ as benchmark
For Value Stocks: Use yearly mode with SPY as benchmark
For Small Caps: Compare against IWM, not SPY
For Sector Analysis: Use sector ETFs (XLK, XLF, XLE, etc.)
Combine with Price Action: High RP + price breakout = powerful signal
⚠️ Important Notes
RP is relative, not absolute - stocks can fall with high RP if the market falls harder
Choose appropriate benchmarks for meaningful comparisons
Best used in conjunction with price action and volume analysis
Historical lookback period affects sensitivity (adjustable in settings)
🔧 Customization
Fully customizable visual settings, thresholds, calculation periods, and smoothing options. Adjust the normalization lookback period (default 252 days) to fine-tune sensitivity to your trading timeframe.
📌 Credit
Inspired by TrendSpider's Relative Performance implementation, adapted for TradingView with enhanced customization options and Pine Script v6 optimization.
Tags to include: relativeperformance, relativestrength, percentile, ranking, sectorrotation, benchmark, outperformance, trendspider, marketbreadth, strengthindicator
Category: Momentum Indicators / Trend Analysis
Feel free to modify this description to match your style or add any specific points you want to emphasize!
CCI PKTELUGUTRADERThe Commodity Channel Index (CCI) is a momentum oscillator that helps traders identify potential buy and sell opportunities by measuring how far the price of a security deviates from its average price over a specific period. It’s widely used for spotting new trends, overbought and oversold conditions, and possible price reversals in various financial markets.
Description of CCI
The CCI calculates the difference between the current price and its historical average price, normalized by mean deviation. Unlike indicators such as RSI, the CCI is an unbounded oscillator, meaning its values can go above +100 or below -100, providing broader insights into momentum shifts in prices.
The formula for CCI is:
CCI
=
Typical Price
−
SMA of Typical Price
0.015
×
Mean Deviation
CCI=
0.015×Mean Deviation
Typical Price−SMA of Typical Price
where:
Typical Price = (High + Low + Close) / 3
SMA is the Simple Moving Average of the Typical Price over the chosen period
Mean Deviation is the average deviation from the SMA.
Buy and Sell Signals
A buy signal is typically generated when the CCI moves above +100, indicating the start of a strong uptrend.
A sell signal occurs when the CCI drops below -100, signaling a strong downtrend.
Many traders close their buy positions when the CCI falls back below +100 and close their sell positions when it rises above -100, or use price action confirmation to validate signals.
Values above +100 suggest overbought conditions, while below -100 indicate oversold; extreme values (like +200 or -200) suggest even stronger momentum.
CCI divergences (price moves not confirmed by the indicator) may indicate potential reversals.
Summary Table: CCI Signals
CCI Level Market Condition Potential Action
Above +100 Overbought/Uptrend Consider Buying
Below -100 Oversold/Downtrend Consider Selling
Back between -100 and +100 Neutral/Indecision Exit or Wait
The CCI is best used alongside other technical indicators for confirmation, as it can generate false signals during sideways markets.
References:
Guide to Commodity Channel Index
What Is CCI?
CCI Trading Strategies
CCI: Technical Indicator
Commodity channel index
Historical VolatilityHistorical Volatility Indicator with Custom Trading Sessions
Overview
This indicator calculates **annualized Historical Volatility (HV)** using logarithmic returns and standard deviation. Unlike standard HV indicators, this version allows you to **customize trading sessions and holidays** for different markets, ensuring accurate volatility calculations for options pricing and risk management.
Key Features
✅ Custom Trading Sessions - Define multiple trading sessions per day with precise start/end times
✅ Multiple Markets Support - Pre-configured for US, Russian, European, and crypto markets
✅ Clearing Periods Handling - Account for intraday clearing breaks
✅ Flexible Calendar - Set trading days per year for different countries
✅ All Timeframes - Works correctly on intraday, daily, weekly, and monthly charts
✅ Info Table - Optional display showing calculation parameters
How It Works
The indicator uses the classical volatility formula:
σ_annual = σ_period × √(periods per year)
Where:
- σ_period = Standard deviation of logarithmic returns over the specified period
- Periods per year = Calculated based on actual trading time (not calendar time)
Calculation Method
1. Computes log returns: ln(close / close )
2. Calculates standard deviation over the lookback period
3. Annualizes using the square root rule with accurate period count
4. Displays as percentage
Settings
Calculation
- Period (default: 10) - Lookback period for volatility calculation
Trading Schedule
- Trading Days Per Year (default: 252) - Number of actual trading days
- USA: 252
- Russia: 247-250
- Europe: 250-253
- Crypto (24/7): 365
- Trading Sessions - Define trading hours in format: `hh:mm:ss-hh:mm:ss, hh:mm:ss-hh:mm:ss`
Display
- Show Info Table - Shows calculation parameters in real-time
Market Presets
United States (NYSE/NASDAQ)
Trading Sessions: 09:30:00-16:00:00
Trading Days Per Year: 252
Trading Minutes Per Day: 390
Russia (MOEX)
Trading Sessions: 10:00:00-14:00:00, 14:05:00-18:40:00
Trading Days Per Year: 248
Trading Minutes Per Day: 515
Europe (LSE)
Trading Sessions: 08:00:00-16:30:00
Trading Days Per Year: 252
Trading Minutes Per Day: 510
Germany (XETRA)
Trading Sessions: 09:00:00-17:30:00
Trading Days Per Year: 252
Trading Minutes Per Day: 510
Cryptocurrency (24/7)
Trading Sessions: 00:00:00-23:59:59
Trading Days Per Year: 365
Trading Minutes Per Day: 1440
Use Cases
Options Trading
- Compare HV vs IV - Historical volatility compared to implied volatility helps identify mispriced options
- Volatility mean reversion - Identify when volatility is unusually high or low
- Straddle/strangle selection - Choose optimal strikes based on historical movement
Risk Management
- Position sizing - Adjust position size based on current volatility
- Stop-loss placement - Set stops based on expected price movement
- Portfolio volatility - Monitor individual asset volatility contribution
Market Analysis
- Regime identification - Detect transitions between low and high volatility environments
- Cross-market comparison - Compare volatility across different assets and markets
Why Accurate Trading Hours Matter
Standard HV indicators assume 24-hour trading or use simplified day counts, leading to significant errors in annualized volatility:
- 5-minute chart error : Can be off by 50%+ if using wrong period count
- Options pricing impact : Even 2-3% HV error affects option values substantially
- Intraday vs overnight : Correctly excludes non-trading periods
This indicator ensures your HV calculations match the methodology used in professional options pricing models.
Technical Notes
- Uses actual trading minutes, not calendar days
- Handles multiple clearing periods within a single trading day
- Properly scales volatility across all timeframes
- Logarithmic returns for more accurate volatility measurement
- Compatible with Pine Script v6
Author Notes: This indicator was designed specifically for options traders who need precise volatility measurements across different global markets. The customizable trading sessions ensure your HV calculations align with actual market hours and industry-standard options pricing models.
Z-Score Regression Bands [BOSWaves]Z-Score Regression Bands – Adaptive Trend and Volatility Insight
Overview
The Z-Score Regression Bands is a trend and volatility analysis framework designed to give traders a clear, structured view of price behavior. It combines Least Squares Moving Average (LSMA) regression, a statistical method to detect underlying trends, with Z-Score standardization, which measures how far price deviates from its recent average.
Traditional moving average bands, like Bollinger Bands, often lag behind trends or generate false signals in noisy markets. Z-Score Regression Bands addresses these limitations by:
Tracking trends accurately using LSMA regression
Normalizing deviations with Z-Scores to identify statistically significant price extremes
Visualizing multiple bands for normal, strong, and extreme moves
Highlighting trend shifts using diamond markers based on Z-Score crossings
This multi-layered approach allows traders to understand trend strength, detect overextensions, and identify periods of low or high volatility — all from a single, clear chart overlay. It is designed for traders of all levels and can be applied across scalping, day trading, swing trading, and longer-term strategies.
Theoretical Foundation
The Z-Score Regression Bands are grounded in statistical and trend analysis principles. Here’s the idea in plain terms:
Least Squares Moving Average (LSMA) – Unlike standard moving averages, LSMA fits a straight line to recent price data using regression. This “best-fit” line shows the underlying trend more precisely and reduces lag, helping traders see trend changes earlier.
Z-Score Standardization – A Z-Score expresses how far the LSMA is from its recent mean in standard deviation units. This shows whether price is unusually high or low, which can indicate potential reversals, pullbacks, or acceleration of a trend.
Multi-Band Structure – The three bands represent: Band #1: Normal range of price fluctuations; Band #2: Significant deviation from the trend; Band #3: Extreme price levels that are statistically rare. The distance between bands dynamically adapts to market volatility, allowing traders to visualize expansions (higher volatility) and contractions (lower volatility).
Trend Signals – When Z-Score crosses zero, diamonds appear on the chart. These markers signal potential trend initiation, continuation, or reversal, offering a simple alert for shifts in market momentum.
How It Works
The indicator calculates and plots several layers of information:
LSMA Regression (Trend Detection)
Computes a line that best fits recent price points.
The LSMA line smooths out minor fluctuations while reflecting the general direction of the market.
Z-Score Calculation (Deviation Measurement)
Standardizes the LSMA relative to its recent average.
Positive Z-Score → LSMA above average, negative → LSMA below average.
Helps identify overbought or oversold conditions relative to the trend.
Multi-Band Construction (Volatility Envelope)
Upper and lower bands are placed at configurable multiples of standard deviation.
Band #1 captures typical price movement, Band #2 signals stronger deviation, Band #3 highlights extreme moves.
Bands expand and contract with volatility, giving an intuitive visual guide to market conditions.
Trend Signals (Diamonds)
Appear when Z-Score crosses zero.
Indicates moments when momentum may shift, helping traders time entries or exits.
Visual Interpretation
Band width = volatility: wide bands indicate strong movement; narrow bands indicate calm periods.
LSMA shows underlying trend direction, while bands show how far price has strayed from that trend.
Interpretation
The Z-Score Regression Bands provide a multi-dimensional view of market behavior:
Trend Analysis – LSMA line slope shows general market direction.
Momentum & Volatility – Z-Score indicates whether the trend is accelerating or losing strength; band width indicates volatility levels.
Price Extremes – Price touching Band #2 or #3 may suggest overextension and potential reversals.
Trend Shifts – Diamonds signal statistically significant changes in momentum.
Cycle Awareness – Standard deviation bands help distinguish normal market fluctuations from extreme events.
By combining these insights, traders can avoid false signals and react to meaningful structural shifts in the market.
Strategy Integration
Trend Following
Enter trades when diamonds indicate momentum aligns with LSMA direction.
Use Band #1 and #2 for stop placement and partial exits.
Breakout Trading
Watch for narrow bands (low volatility) followed by price pushing outside Band #1 or #2.
Confirm with Z-Score movement in the breakout direction.
Mean Reversion/Pullback
If price reaches Band #2 or #3 without continuation, expect a pullback toward LSMA.
Exhaustion & Reversals
Flattening Z-Score near zero while price remains at extreme bands signals trend weakening.
Tighten stops or scale out before a potential reversal.
Multi-Timeframe Confirmation
High timeframe LSMA confirms the main trend.
Lower timeframe bands provide refined entry and exit points.
Technical Implementation
LSMA Regression : Best-fit line minimizes lag and captures trend slope.
Z-Score Standardization : Normalizes deviation to allow consistent interpretation across markets.
Multi-Band Envelope : Three layers for normal, strong, and extreme deviations.
Trend Signals : Automatic diamonds for Z-Score zero-crossings.
Band Fill Options : Optional shading to visualize volatility expansions and contractions.
Optimal Application
Asset Classes:
Forex : Capture breakouts, overextensions, and trend shifts.
Crypto : High-volatility adaptation with adjustable band multipliers.
Stocks/ETFs : Identify trending sectors, reversals, and pullbacks.
Indices/Futures : Track cycles and structural trends.
Timeframes:
Scalping (1–5 min) : Focus on Band #1 and trend signals for fast entries.
Intraday (15m–1h) : Use Bands #1–2 for continuation and breakout trades.
Swing (4h–Daily) : Bands #2–3 capture trend momentum and exhaustion.
Position (Daily–Weekly) : LSMA trend dominates; Bands #3 highlight regime extremes.
Performance Characteristics
Strong Performance:
Trending markets with moderate-to-high volatility
Assets with steady liquidity and identifiable cycles
Weak Performance:
Flat or highly choppy markets
Very short timeframes (<1 min) dominated by noise
Integration Tips
Combine with support/resistance, volume, or order flow analysis for confirmation.
Use bands for stops, targets, or scaling positions.
Apply multi-timeframe analysis: higher timeframe LSMA confirms main trend, lower timeframe bands refine entries.
Disclaimer
The Z-Score Regression Bands is a trading analysis tool, not a guaranteed profit system. Its effectiveness depends on market conditions, parameter selection, and disciplined risk management. Use it as part of a broader trading strategy, not in isolation.
RXTrend█ OVERVIEW
The "RXTrend" indicator is a technical analysis tool based on a unique approach to trend identification using RSI values from overbought and oversold zones. Designed for traders seeking a precise tool to identify key market levels and trend direction, the indicator offers flexible settings, dynamic trend lines, candlestick coloring, and buy/sell signals, supported by alerts for key events.
█ CONCEPTS
"RXTrend" leverages the Relative Strength Index (RSI) to identify overbought and oversold zones, which are often significant areas on the chart due to potentially higher volume, increased volatility, or acting as pivot points. To address this, I created an indicator that uses RSI values from these zones, mapping them to price levels to determine the trend. Additionally, for a clearer market picture, boxes are added to highlight overbought and oversold zones on the chart, and candlestick coloring is based on the direction of the RSI moving average. This provides further confirmation of the trend direction and identifies potential correction or reversal points. The indicator is universal and works across all markets (stocks, forex, cryptocurrencies) and timeframes.
█ FEATURES
- RSI Calculation: Calculates RSI based on the closing price over a specified period, with a default length of 14.
- Trend Line: A smoothed trend line based on mapping RSI values from overbought (for downtrends) or oversold (for uptrends) zones to price levels. RSI values are transformed into prices using the price range from a selected period (default: 50 bars) and then smoothed to form the trend line. The line changes color based on the trend direction (blue for uptrend, orange for downtrend).
- Candlestick Coloring: Option to color candles based on the direction of the RSI moving average (RSI MA). Candle colors align with the trend and box colors (blue for uptrend, orange for downtrend, gray for neutral).
- Overbought and Oversold Zones: Identifies overbought (RSI > OB) and oversold (RSI < OS) levels, drawing dynamic boxes on the price chart to reflect these zones. Boxes update in real-time, adjusting to new highs and lows.
- Buy and Sell Signals: Generates buy signals (blue "Buy" labels) when the price crosses above the smoothed oversold line and sell signals (orange "Sell" labels) when the price crosses below the smoothed overbought line.
- Shadow Fill: Option to fill the space between the trend line and price (HL2) with adjustable transparency, aiding visual trend assessment.
Alerts: Built-in alerts for:
- Buy and sell signals.
- Appearance of new overbought/oversold boxes.
- RSI MA direction change (candle color change to uptrend or downtrend).
Customization: Allows adjustment of RSI length, overbought/oversold levels, smoothing period, colors, box and label transparency, and the option to keep boxes after RSI returns to normal.
█ HOW TO USE
Add to Chart: Apply the indicator to your TradingView chart via the Pine Editor or Indicators menu.
Configure Settings:
RSI Settings:
- RSI Length: Sets the RSI calculation period (default: 14).
- Overbought Level (OB): Sets the overbought threshold (default: 70).
- Oversold Level (OS): Sets the oversold threshold (default: 30).
Price Settings:
- Price Range Lookback: Defines the period for calculating the price range (default: 50).
Candle Coloring:
- Color Candles: Enables/disables candle coloring based on RSI MA direction.
- RSI MA Length: Sets the RSI moving average period (default: 21).
Smoothing Settings:
- Smoothing Length: Degree of trend line smoothing (default: 5).
Colors:
- Trend Colors: Customize colors for uptrend (default: blue), downtrend (default: orange), and shadow fill.
Box Settings:
- Box Transparency: Adjusts box transparency (0-100).
- Box Colors: Sets colors for overbought (orange) and oversold (blue) zones.
- Keep Boxes: Determines if boxes remain after RSI returns to normal.
Signals:
- Show Buy/Sell Signals: Enables/disables signal label display.
- Label Transparency: Adjusts signal label transparency.
Interpreting Signals:
- Trend Line: Shows market direction (blue for uptrend, orange for downtrend).
- Buy Signals: Blue "Buy" label appears when the price crosses above the smoothed oversold line, signaling a potential uptrend.
- Sell Signals: Orange "Sell" label appears when the price crosses below the smoothed overbought line, signaling a potential downtrend.
- Overbought/Oversold Boxes: Orange boxes indicate overbought zones (RSI > OB), blue boxes indicate oversold zones (RSI < OS). Boxes expand dynamically in real-time.
- Candlestick Coloring: Candle colors align with the trend and box colors, reflecting RSI MA direction.
- Alerts: Set up alerts in TradingView for buy/sell signals, new overbought/oversold boxes, or RSI MA direction changes.
- Combining with Other Tools: Use the indicator alongside support/resistance levels, Fair Value Gaps (FVG), or other indicators to confirm signals.
█ APPLICATIONS
The "RXTrend" indicator is designed to identify key market zones and trend direction, making it useful for trend-following and reversal strategies. It enables:
- Trend Confirmation: Candlestick coloring and the trend line help assess the dominant market direction, supporting entry or exit decisions. The trend line can act as a significant support/resistance level, and a price bounce from it may provide a good entry point, especially when confirmed by Fibonacci levels. Additionally, the appearance of overbought/oversold boxes combined with a change in candle color (RSI MA direction) may indicate an impending correction. This allows analysis of potential market overextension and correction endings, enabling multiple entries within a trend.
- Overbought and Oversold Zone Identification: Boxes highlight potential reversal or correction points, especially when combined with support/resistance levels or FVG.
- Signal-Based Strategies: Buy and sell signals can be used as entry points in a trend or as warnings of potential reversals.
█ NOTES
- The indicator is universal and works across all markets and timeframes due to its RSI-based and price-mapping logic.
- Adjust settings (e.g., RSI length, OB/OS levels, smoothing) to suit your trading style and timeframe.
- Use in conjunction with other technical analysis tools to enhance signal accuracy.
Intraday Rising & Reversal ScannerPine Script Description: Intraday Rising & Reversal ScannerThis Pine Script is a TradingView indicator designed to identify stocks with intraday (1-hour timeframe) potential for bullish (rising) or bearish (reversal) movements. It scans for stocks based on user-defined technical criteria, including price change, relative volume, RSI, EMA, ATR, and VWAP. The script plots signals on the chart, displays a summary table, and triggers alerts when conditions are met.FeaturesBullish Signal (Rising Stocks):1H Price Change: > 1% (configurable, e.g., >2% for volatile markets).
Relative Volume: > 2.0 (volume is at least twice the 20-period average).
RSI (14): Between 50 and 70 (strong but not overbought momentum).
Price vs EMA 13: Price above the 13-period EMA (confirms short-term uptrend).
ATR (14): Current ATR above its 20-period average (indicates volatility).
VWAP: Price above VWAP (optional, shown on chart for manual confirmation).
Bearish Signal (Reversal Stocks):1H Price Change: < -1% (configurable, e.g., <-2% for stronger reversals).
Relative Volume: > 2.0 (high volume confirms selling pressure).
RSI (14): > 70 (overbought, increasing reversal likelihood).
Price vs EMA 13: Price below the 13-period EMA (confirms short-term downtrend).
ATR (14): Current ATR above its 20-period average (indicates volatility).
VWAP: Price below VWAP (optional, shown on chart for manual confirmation).
Visualization:Bullish Signal: Green triangle below the bar.
Bearish Signal: Red triangle above the bar.
VWAP: Plotted as a blue line for manual verification.
Table: Displays real-time metrics (Change %, Relative Volume, RSI, Price vs EMA, ATR, VWAP) in the top-right corner, color-coded (green for bullish, red for bearish).
Alerts:Separate alerts for bullish ("Intraday Bullish Signal") and bearish ("Intraday Bearish Signal") conditions.
Customizable alert messages include parameter values for easy tracking.
How It WorksThe script runs on the 1-hour (1H) timeframe, ensuring all calculations are based on hourly data.
Indicators are computed:Change %: Percentage price change over the last hour.
Relative Volume: Current volume divided by the 20-period SMA of volume.
RSI: 14-period Relative Strength Index.
EMA 13: 13-period Exponential Moving Average.
ATR: 14-period Average True Range, compared to its 20-period SMA.
VWAP: Volume Weighted Average Price, plotted for visual confirmation.
Signals are generated when all conditions for either bullish or bearish criteria are met.
A table summarizes key metrics, and alerts can be set up for real-time notifications.
Usage InstructionsApply the Script:Open TradingView’s Pine Editor.
Copy and paste the script.
Click "Add to Chart" and set the chart to the 1-hour (1H) timeframe.
Set Up Alerts:Right-click on the chart > "Add Alert".
Select "Intraday Bullish Signal" or "Intraday Bearish Signal" as the condition.
Configure notifications (e.g., SMS, email, or TradingView alerts).
Manual VWAP Check:VWAP is plotted as a blue line. Verify that the price is above VWAP for bullish signals or below for bearish signals using the table or chart.
To make VWAP a mandatory filter, uncomment the VWAP conditions in the bull_signal and bear_signal definitions.
LA - Opening Price based Previous day Range PivotThis "LA - Opening Price based Previous day Range Pivot" indicator is a custom technical analysis tool designed for Trading View charts. It plots support and resistance levels (often referred to as pivots or ranges) based on the current opening price combined with the previous period's trading range. The "previous period" can be daily, weekly, or monthly, making it a multi-timeframe tool. These levels are projected using Fibonacci-inspired multipliers to create potential breakout or reversal zones.
The core idea is inspired by concepts like the Opening Range Breakout (ORB) strategy or Fibonacci pivots, but it's customized here to use a dynamic range calculation (the maximum of several absolute price differences) rather than a simple high-low range. This makes it more robust for volatile markets. Levels are symmetric above (resistance) and below (support) the opening price, helping traders identify potential entry/exit points, stop-losses, or targets. This will be useful when there is a gap-up/down as in Nifty/Sensex .
Purpose of the Indicator:
To visualize potential support/resistance zones for the current trading session based on the opening price and historical range data. This helps traders anticipate price movements, such as breakouts above resistance or bounces off support
Use Cases:
Intraday Trading: On lower timeframes (e.g., 5-min or 15-min charts), it shows daily levels for short-term trades.
Swing Trading: On higher timeframes (e.g., hourly or daily), it displays weekly/monthly levels for longer holds.
Range Identification: The filled bands highlight "zones" where price might consolidate or reverse.
Conditional Display: Levels only appear on appropriate timeframes (e.g., daily levels on intraday charts <60min), preventing clutter.
Theoretical Basis: It builds on pivot point theory, where the opening price acts as a central pivot. Multipliers (e.g., 0.618 for Fibonacci golden ratio) project levels, assuming price often respects these ratios due to market psychology.
How Calculations Work
Let's dive into the math with examples. Assume a stock with:
Current daily open (cdo) = $100
Previous daily high (pdh) = $105, low (pdl) = $95, close (pdc) = $102, close 2 days ago (pdc2) = $98
Step 1: Dynamic Range Calculation (var_d2):
This is the max of:
|pdh - pdc2| = |105 - 98| = 7
|pdl - pdc2| = |95 - 98| = 3
|pdh - pdl| = |105 - 95| = 10 (previous day range)
|pdh - cdo| = |105 - 100| = 5
|pdl - cdo| = |95 - 100| = 5
|pdc - cdo| = |102 - 100| = 2
|pdc2 - cdo| = |98 - 100| = 2
Max = 10 (so range = 10). This ensures the range accounts for gaps and extended moves, not just high-low.
Step 2: Level Projections:
Resistance (above open): Open + (Range * Multiplier)
dre6 = 100 + (10 * 1.5) = 115
dre5 = 100 + (10 * 1.27) ≈ 112.7
... down to dre0 = 100 + (10 * 0.1) = 101
dre50 = 100 + (10 * 0.5) = 105 (midpoint)
Support (below open): Open - (Range * Multiplier)
dsu0 = 100 - (10 * 0.1) = 99
... up to dsu6 = 100 - (10 * 1.5) = 85
Without Indicator
With Indicator
Pros and Cons
Pros:
Multi-Timeframe Flexibility: Seamlessly integrates daily, weekly, and monthly levels, useful for aligning short-term trades with longer trends (e.g., intraday breakout confirmed by weekly support).
Dynamic Range Calculation: Unlike standard pivots (just (H+L+C)/3), it uses max of multiple diffs, capturing gaps/volatility better—great for stocks with overnight moves.
Customizable via Inputs: Users can toggle levels, adjust multipliers, or change timeframes without editing code. Inline inputs keep the UI clean.
Visual Aids: Filled bands make zones obvious; conditional colors highlight "tight" vs. "wide" ranges (e.g., for volatility assessment).
Fibonacci Integration: Levels based on proven ratios, appealing to technical traders. Symmetric supports/resistances simplify strategy building (e.g., buy at support, sell at resistance).
No Repainting: Uses historical data with lookahead, so levels are fixed once calculated—reliable for back-testing.
Cons:
Chart Clutter: With all toggles on, 50+ plots/fills can overwhelm the chart, especially on mobile or small screens. Requires manual disabling.
Complexity for Beginners: Many inputs and calculations; without understanding fib ratios or range logic, it might confuse new users.
Performance Overhead: On low timeframes (e.g., 1-min), fetching higher TF data multiple times could lag, especially with many symbols or back-tests.
Assumes Volatility Persistence: Relies on previous range projecting future moves; in low-vol markets (e.g., sideways trends), levels may be irrelevant or too wide/narrow.
No Alerts or Signals: Purely visual; no built-in buy/sell alerts or crossover conditions—users must add separately.
Hardcoded Styles/Colors: Limited customization without code edits (e.g., can't change line styles via inputs).
Also, not optimized for non-stock assets (e.g., forex with 24/7 trading).
In summary, this is a versatile pivot tool for range-based trading based on Opening price, excelling in volatile markets but requiring some setup. If you're using it, start with defaults on a daily chart and toggle off unnecessary levels.
