NFP RangesPlots the NFP daily ranges for NFP days. Includes extended hours ranges when the time frame is sub 1D, otherwise, only the daily range is taken.
NFP Dates are pre-populated through 2029 and historically through 2022. Will update script to include farther-out dates before they become necessary.
스크립트에서 "纳指ETF+加仓"에 대해 찾기
BuySell Volume Bar Chart• Separates estimated Buy and Sell volume per bar using price action logic
• Plots them in a dual-axis format: buy volume goes up, sell volume goes down
• Colors are dynamic — whichever side dominates gets the stronger color, the weaker side is shaded
• Includes a live difference metric (Δ Volume) as a third value in the indicator title
• Automatically filters out flat/no-move bars to avoid misleading spikes
The live difference metric ("Δ Volume") can be controlled.
This metric calculates the difference between the buying and selling volume live, where it takes the Buy Volume - Sell Volume.
This difference is then displayed in either green (BV > SV) or red (SV > BV). You can toggle it on/off by entering the indicator's settings or double tapping the indicator name on the TV chart.
Another pretty cool thing is the modular colors - you can customize your candle colors and shades to your liking within the code!
Monthly Seasonality Trend [DunesIsland]The Monthly Seasonality Trend is a indicator designed to analyze and visualize historical monthly seasonality patterns in financial markets. By calculating the average monthly return over a user-configurable lookback period (1 to 10 years), this indicator provides traders and investors with a clear projection of potential price movements for the current month, enabling data-driven decision-making.
How It Works
The indicator operates by retrieving monthly open and close prices for the specified lookback period (up to 10 years) and computing the average percentage return for the current month based on historical data. Key functionalities include:
Dynamic Trend Line: On the first trading day of each month, the indicator plots a line projecting the expected price trajectory, starting from the current close price and extending to the estimated end-of-month price based on the average historical return. The line is colored green for anticipated price increases or red for expected declines, offering an intuitive visual cue.
Average Return Label: A label is displayed at the start of each month, detailing the calculated average historical return for that month, expressed as a percentage, to provide context for the projected trend.
First Trading Day Marker: A small circle is plotted below the bar on the first trading day of each month, clearly marking the start of the projection period.
Adaptive Bar Counting: The indicator dynamically adjusts the length of the trend line based on the actual number of trading days in the previous month, ensuring accurate projections.
How to Interpret
Bullish Projection (Green Line): Indicates that historical data suggests an average price increase for the current month, potentially signaling buying opportunities.
Bearish Projection (Red Line): Suggests an average price decline based on historical trends, which may prompt caution or short-selling strategies.
Historical Context: The average return label provides a quantitative measure of past performance, helping traders assess the reliability of the projected trend.
Divergence Strategy [Trendoscope®]🎲 Overview
The Divergence Strategy is a sophisticated TradingView strategy that enhances the Divergence Screener by adding automated trade signal generation, risk management, and trade visualization. It leverages the screener’s robust divergence detection to identify bullish, bearish, regular, and hidden divergences, then executes trades with precise entry, stop-loss, and take-profit levels. Designed for traders seeking automated trading solutions, this strategy offers customizable trade parameters and visual feedback to optimize performance across various markets and timeframes.
For core divergence detection features, including oscillator options, trend detection methods, zigzag pivot analysis, and visualization, refer to the Divergence Screener documentation. This description focuses on the strategy-specific enhancements for automated trading and risk management.
🎲 Strategy Features
🎯Automated Trade Signal Generation
Trade Direction Control : Restrict trades to long-only or short-only to align with market bias or strategy goals, preventing conflicting orders.
Divergence Type Selection : Choose to trade regular divergences (bullish/bearish), hidden divergences, or both, targeting reversals or trend continuations.
Entry Type Options :
Cautious : Enters conservatively at pivot points and exits quickly to minimize risk exposure.
Confident : Enters aggressively at the latest price and holds longer to capture larger moves.
Mixed : Combines conservative entries with delayed exits for a balanced approach.
Market vs. Stop Orders: Opt for market orders for instant execution or stop orders for precise price entry.
🎯 Enhanced Risk Management
Risk/Reward Ratio : Define a risk-reward ratio (default: 2.0) to set profit targets relative to stop-loss levels, ensuring consistent trade sizing.
Bracket Orders : Trades include entry, stop-loss, and take-profit levels calculated from divergence pivot points, tailored to the entry type and risk-reward settings.
Stop-Loss Placement : Stops are strategically set (e.g., at recent pivot or last price point) based on entry type, balancing risk and trade validity.
Order Cancellation : Optionally cancel pending orders when a divergence is broken (e.g., price moves past the pivot in the wrong direction), reducing invalid trades. This feature is toggleable for flexibility.
🎯 Trade Visualization
Target and Stop Boxes : Displays take-profit (lime) and stop-loss (orange) levels as boxes on the price chart, extending 10 bars forward for clear visibility.
Dynamic Trade Updates : Trade visualizations are added, updated, or removed as trades are executed, canceled, or invalidated, ensuring accurate feedback.
Overlay Integration : Trade levels overlay the price chart, complementing the screener’s oscillator-based divergence lines and labels.
🎯 Strategy Default Configuration
Capital and Sizing : Set initial capital (default: $1,000,000) and position size (default: 20% of equity) for realistic backtesting.
Pyramiding : Allows up to 4 concurrent trades, enabling multiple divergence-based entries in trending markets.
Commission and Margin : Accounts for commission (default: 0.01%) and margin (100% for long/short) to reflect trading costs.
Performance Optimization : Processes up to 5,000 bars dynamically, balancing historical analysis and real-time execution.
🎲 Inputs and Configuration
🎯Trade Settings
Direction : Select Long or Short (default: Long).
Divergence : Trade Regular, Hidden, or Both divergence types (default: Both).
Entry/Exit Type : Choose Cautious, Confident, or Mixed (default: Cautious).
Risk/Reward : Set the risk-reward ratio for profit targets (default: 2.0).
Use Market Order : Enable market orders for immediate entry (default: false, uses limit orders).
Cancel On Break : Cancel pending orders when divergence is broken (default: true).
🎯Inherited Settings
The strategy inherits all inputs from the Divergence Screener, including:
Oscillator Settings : Oscillator type (e.g., RSI, CCI), length, and external oscillator option.
Trend Settings : Trend detection method (Zigzag, MA Difference, External), MA type, and length.
Zigzag Settings : Zigzag length (fixed repaint = true).
🎲 Entry/Exit Types for Divergence Scenarios
The Divergence Strategy offers three Entry/Exit Type options—Cautious, Confident, and Mixed—which determine how trades are entered and exited based on divergence pivot points. This section explains how these settings apply to different divergence scenarios, with placeholders for screenshots to illustrate each case.
The divergence pattern forms after 3 pivots. The stop and entry levels are formed on one of these levels based on Entry/Exit types.
🎯Bullish Divergence (Reversal)
A bullish divergence occurs when price forms a lower low, but the oscillator forms a higher low, signaling a potential upward reversal.
💎 Cautious:
Entry : At the pivot high point for a conservative entry.
Exit : Stop-loss at the last pivot point (previous low that is higher than the current pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Entry : At the last pivot low, (previous low which is higher than the current pivot low) for an aggressive entry.
Exit : Stop-loss at recent pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
💎Mixed:
Entry : At the pivot high point (conservative).
Exit : Stop-loss at the recent pivot point that has resulted in lower low (lazy exit). Canceled if price breaks below the pivot.
Behavior : Balances entry caution with extended holding for trend continuation.
🎯Bearish Divergence (Reversal)
A bearish divergence occurs when price forms a higher high, but the oscillator forms a lower high, indicating a potential downward reversal.
💎Cautious:
Entry : At the pivot low point (lower high) for a conservative short entry.
Exit : Stop-loss at the previous pivot high point (previous high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident:
Entry : At the last price point (previous high) for an aggressive short entry.
Exit : Stop-loss at the pivot point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Enters early to maximize trend continuation, holding longer.
💎Mixed:
Entry : At the previous piot high point (conservative).
Exit : Stop-loss at the last price point (delayed exit). Canceled if price breaks above the pivot.
Behavior : Combines conservative entry with extended holding for downtrend gains.
🎯Bullish Hidden Divergence (Continuation)
A bullish hidden divergence occurs when price forms a higher low, but the oscillator forms a lower low, suggesting uptrend continuation. In case of Hidden bullish divergence, b]Entry is always on the previous pivot high (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the recent pivot low point (higher than previous pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Exit : Stop-loss at previous pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
🎯Bearish Hidden Divergence (Continuation)
A bearish hidden divergence occurs when price forms a lower high, but the oscillator forms a higher high, suggesting downtrend continuation. In case of Hidden Bearish divergence, b]Entry is always on the previous pivot low (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the latest pivot high point (which is a lower high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident/Mixed:
Exit : Stop-loss at the previous pivot high point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Uses the late exit point to hold longer.
🎲 Usage Instructions
🎯Add to Chart:
Add the Divergence Strategy to your TradingView chart.
The oscillator and divergence signals appear in a separate pane, with trade levels (target/stop boxes) overlaid on the price chart.
🎯Configure Settings:
Adjust trade settings (direction, divergence type, entry type, risk-reward, market orders, cancel on break).
Modify inherited Divergence Screener settings (oscillator, trend method, zigzag length) as needed.
Enable/disable alerts for divergence notifications.
🎯Interpret Signals:
Long Trades: Triggered on bullish or bullish hidden divergences (if allowed), shown with green/lime lines and labels.
Short Trades: Triggered on bearish or bearish hidden divergences (if allowed), shown with red/orange lines and labels.
Monitor lime (target) and orange (stop) boxes for trade levels.
Review strategy performance metrics (e.g., profit/loss, win rate) in the strategy tester.
🎯Backtest and Optimize:
Use TradingView’s strategy tester to evaluate performance on historical data.
Fine-tune risk-reward, entry type, position sizing, and cancellation settings to suit your market and timeframe.
For questions, suggestions, or support, contact Trendoscope via TradingView or official support channels. Stay tuned for updates and enhancements to the Divergence Strategy!
Trading CalculatorTrading Calculator Indicator
VIBE CODED WITH GROK 3
The Trading Calculator is a Pine Script indicator designed to perform quick and useful trading-related calculations directly on your chart. It allows traders to execute basic arithmetic operations—such as addition, subtraction, multiplication, and division—as well as calculate percent change and average using either numerical values or trading variables (e.g., close, open, high, low, volume). The indicator displays its results in a table that resembles a calculator interface, making it both functional and visually intuitive. Unlike typical indicators, it does not overlay on the price chart but instead appears in a separate pane.
Inputs
Formula (new | old): First value or variable (e.g., 100, close, close ). Example: close uses the current closing price.
Operator: Mathematical operation (e.g., Plus, Minus, Multiply). Example: Plus adds the two inputs.
Second Input: Second value or variable (e.g., 50, open, close ). Example: open uses the current opening price.
Risk Distribution HistogramStatistical risk visualization and analysis tool for any ticker 📊
The Risk Distribution Histogram visualizes the statistical distribution of different risk metrics for any financial instrument. It converts risk data into histograms with quartile-based color coding, so that traders can understand their risk, tail-risks, exposure patterns and make data-driven decisions based on empirical evidence rather than assumptions.
The indicator supports multiple risk calculation methods, each designed for different aspects of market analysis, from general volatility assessment to tail risk analysis.
Risk Measurement Methods
Standard Deviation
Captures raw daily price volatility by measuring the dispersion of price movements. Ideal for understanding overall market conditions and timing volatility-based strategies.
Use case: Options trading and volatility analysis.
Average True Range (ATR)
Measures true range as a percentage of price, accounting for gaps and limit moves. Valuable for position sizing across different price levels.
Use case: Position sizing and stop-loss placement.
The chart above illustrates how ATR statistical distribution can be used by looking at the ATR % of price distribution. For example, 90% of the movements are below 5%.
Downside Deviation
Only considers negative price movements, making it ideal for checking downside risk and capital protection rather than capturing upside volatility.
Use case: Downside protection strategies and stop losses.
Drawdown Analysis
Tracks peak-to-trough declines, providing insight into maximum loss potential during different market conditions.
Use case: Risk management and capital preservation.
The chart above illustrates tale risk for the asset (TQQQ), showing that it is possible to have drawdowns higher than 20%.
Entropy-Based Risk (EVaR)
Uses information theory to quantify market uncertainty. Higher entropy values indicate more unpredictable price action, valuable for detecting regime changes.
Use case: Advanced risk modeling and tail-risk.
VIX Histogram
Incorporates the market's fear index directly into analysis, showing how current volatility expectations compare to historical patterns. The CAPITALCOM:VIX histogram is independent from the ticker on the chart.
Use case: Volatility trading and market timing.
Visual Features
The histogram uses quartile-based color coding that immediately shows where current risk levels stand relative to historical patterns:
Green (Q1): Low Risk (0-25th percentile)
Yellow (Q2): Medium-Low Risk (25-50th percentile)
Orange (Q3): Medium-High Risk (50-75th percentile)
Red (Q4): High Risk (75-100th percentile)
The data table provides detailed statistics, including:
Count Distribution: Historical observations in each bin
PMF: Percentage probability for each risk level
CDF: Cumulative probability up to each level
Current Risk Marker: Shows your current position in the distribution
Trading Applications
When current risk falls into upper quartiles (Q3 or Q4), it signals conditions are riskier than 50-75% of historical observations. This guides position sizing and portfolio adjustments.
Key applications:
Position sizing based on empirical risk distributions
Monitoring risk regime changes over time
Comparing risk patterns across timeframes
Risk distribution analysis improves trade timing by identifying when market conditions favor specific strategies.
Enter positions during low-risk periods (Q1)
Reduce exposure in high-risk periods (Q4)
Use percentile rankings for dynamic stop-loss placement
Time volatility strategies using distribution patterns
Detect regime shifts through distribution changes
Compare current conditions to historical benchmarks
Identify outlier events in tail regions
Validate quantitative models with empirical data
Configuration Options
Data Collection
Lookback Period: Control amount of historical data analyzed
Date Range Filtering: Focus on specific market periods
Sample Size Validation: Automatic reliability warnings
Histogram Customization
Bin Count: 10-50 bins for different detail levels
Auto/Manual Bin Width: Optimize for your data range
Visual Preferences: Custom colors and font sizes
Implementation Guide
Start with Standard Deviation on daily charts for the most intuitive introduction to distribution-based risk analysis.
Method Selection: Begin with Standard Deviation
Setup: Use daily charts with 20-30 bins
Interpretation: Focus on quartile transitions as signals
Monitoring: Track distribution changes for regime detection
The tool provides comprehensive statistics including mean, standard deviation, quartiles, and current position metrics like Z-score and percentile ranking.
Enjoy, and please let me know your feedback! 😊🥂
QEMO: Quantum Electromagnetic Oscillator (Safe Adjusted)This is a highly conceptual and oscillator and It attempts to model market dynamics by borrowing concepts from quantum physics and electromagnetism to create a unique oscillator. It does not represent any real physical phenomena but uses these concepts as metaphors for market forces.
Here is a breakdown of its core components:
1. Quantum Price Wavefunction (The Core Price Engine)
This is the most abstract part of the script. It tries to model price not as a single point, but as a "wavefunction" representing a distribution of probable future prices.
Volatility & Price Grid: It first calculates recent market volatility. Based on this volatility, it creates a dynamic grid of possible price levels (price_bins) around the current price.
Probability Density: It assigns a probability to each price level in the grid.
"Energy" Operators:
Kinetic Energy: Metaphorically represents the "momentum" or rate of change of the price probabilities.
Potential Energy: A force field that influences the probabilities, derived from a combination of volatility and trading volume.
Expected Price: After evolving these probabilities, it calculates a single "expected price" which is the weighted average of all prices in the grid, based on their final probabilities.
2. Electromagnetic Fields (Buying vs. Selling Pressure)
This section models the battle between buyers and sellers in a more familiar way:
E-Field (Electric/Buying): Represents buying pressure, calculated from upward price moves (close - open) multiplied by volume.
B-Field (Magnetic/Selling): Represents selling pressure, calculated from downward price moves (open - close) multiplied by volume.
Lorentz Force (F_net): This is the net force (E - B), representing the overall directional pressure in the market. A positive value means buyers are in control; a negative value means sellers are.
3. Entanglement Entropy (Systemic Risk/Stability)
This component aims to measure the market's stability or "systemic risk."
It calculates a form of auto-correlation on recent price returns.
A high degree of instability in this correlation results in a high "Entropy" (S) value.
Essentially, a high S suggests the market is chaotic and unpredictable (low stability), while a low S suggests it is more stable and trending.
4. Final QEMO Calculation & Plotting
All the components are combined to create the final oscillator value:
Final Value: The qemo value is a product of the expected_price, the amplified net force, and the market stability (1 - S).
Smoothing: This raw qemo value is then smoothed with an Adaptive Moving Average (AMA) to produce the final line that gets plotted on the chart.
Visualization:
The main oscillator line is plotted below the chart. Its color changes based on its value (e.g., blue for positive, red for negative).
The background color of the indicator pane changes based on the Entropy (S), providing an immediate visual cue of market stability (e.g., black for stable, white for chaotic).
The script also plots 99th and 1st percentile bands to help identify statistically extreme readings in the oscillator's value.
Fear and Greed Indicator [DunesIsland]The Fear and Greed Indicator is a TradingView indicator that measures market sentiment using five metrics. It displays:
Tiny green circles below candles when the market is in "Extreme Fear" (index ≤ 25), signalling potential buys.
Tiny red circles above candles when the market is in "Greed" (index > 75), indicating potential sells.
Purpose: Helps traders spot market extremes for contrarian trading opportunities.Components (each weighted 20%):
Market Momentum: S&P 500 (SPX) vs. its 125-day SMA, normalized over 252 days.
Stock Price Strength: Net NYSE 52-week highs (INDEX:HIGN) minus lows (INDEX:LOWN), normalized.
Put/Call Ratio: 5-day SMA of Put/Call Ratio (USI:PC).
Market Volatility: VIX (VIX), inverted and normalized.
Stochastic RSI: 14-period RSI on SPX with 3-period Stochastic SMA.
Alerts:
Buy: Index ≤ 25 ("Extreme Fear - Potential Buy").
Sell: Index > 75 ("Greed - Potential Sell").
Delta Volume BubblesDelta Volume Bubbles
Overview
The Delta Volume Bubbles indicator is an advanced order flow visualization tool that displays buying and selling pressure through dynamic bubble representations on your chart. Unlike traditional volume indicators that only show total volume, this indicator calculates the net delta volume (difference between buying and selling volume) and presents it as color-coded bubbles of varying sizes.
How It Works
Core Calculation Method
The indicator uses a sophisticated approach to estimate delta volume from standard OHLCV data:
1. Price Action Analysis: Analyzes the relationship between open, high, low, and close prices to determine market aggression
2. Body Ratio Calculation: body_ratio = |close - open| / (high - low)
3. Aggressive Factor: Applies multipliers based on price action:
- Strong moves (body_ratio > 0.7): 1.5x multiplier
- Moderate moves (body_ratio > 0.4): 1.2x multiplier
- Weak moves: 1.0x multiplier
4. Delta Volume Estimation:
- Buy Volume: price_change > 0 ? volume × aggressive_factor : 0
- Sell Volume: price_change < 0 ? volume × aggressive_factor : 0
- Net Delta: buy_volume - sell_volume
5. Delta Strength Normalization: delta_strength = |net_delta| / sma(volume, 20)
Percentile-Based Filtering
The indicator uses percentile filtering instead of fixed thresholds, making it adaptive to market conditions:
- Bubble Filter: Only shows bubbles when volume exceeds the specified percentile (default: 60%)
- Label Filter: Only displays numbers when volume exceeds a higher percentile (default: 90%)
- Dynamic Adaptation: Automatically adjusts to changing market volatility
Visual Elements
Bubble Sizes
- Tiny: Delta strength < 0.3
- Small: Delta strength 0.3 - 0.7
- Normal: Delta strength 0.7 - 1.2
- Large: Delta strength 1.2 - 2.0
- Huge: Delta strength > 2.0
Color Coding
- Aggressive Buy (Bright Green): Strong buying pressure with high body ratio
- Aggressive Sell (Bright Red): Strong selling pressure with high body ratio
- Passive Buy (Light Green): Moderate buying pressure
- Passive Sell (Light Red): Moderate selling pressure
Intensity Mode
Alternative coloring based on delta strength rather than flow direction:
- Gray: Low intensity (< 0.5)
- Blue: Medium intensity (0.5 - 1.0)
- Orange: High intensity (1.0 - 2.0)
- Red: Extreme intensity (> 2.0)
Parameters
Order Flow Settings
- Show Bubbles: Toggle bubble display on/off
- Bubble Volume %ile: Percentile threshold for bubble display (0-100%)
- Intensity Mode: Switch between flow-based and intensity-based coloring
Bubble Labels
- Show Numbers in Bubbles: Toggle numerical labels on/off
- Label Volume %ile: Higher percentile threshold for label display (0-100%)
Numbers are displayed in K-notation (e.g., 25000 → 25K, 1500000 → 1.5M) for better readability.
Ideal Usage Scenarios
Best Market Conditions
- High volume sessions: More accurate delta calculations
- Trending markets: Clear directional flow identification
- Breakout scenarios: Spot aggressive buying/selling at key levels
- Support/resistance testing: Identify accumulation vs distribution
Trading Applications
1. Entry Timing: Look for aggressive flow in your trade direction
2. Exit Signals: Watch for opposing aggressive flow
3. Trend Confirmation: Consistent flow direction confirms trends
4. Volume Climax: Huge bubbles may indicate exhaustion points
Optimization Tips
Parameter Adjustment
- Lower percentiles (40-60%): More bubbles, good for active markets
- Higher percentiles (70-90%): Fewer bubbles, focus on significant events
- Label percentile: Set 20-30% higher than bubble percentile for clarity
Visual Optimization
- Intensity mode: Better for identifying unusual volume spikes
- Flow mode: Better for directional bias analysis
- Label toggle: Turn off in crowded markets, on for key levels
Limitations
- Estimation-based: Uses approximation algorithms, not true order flow data
- Volume dependency: Requires accurate volume data to function properly
- Timeframe sensitivity: Works best on intraday timeframes with active volume
- Market hours: Most effective during high-volume trading sessions
Technical Notes
The indicator implements advanced Pine Script features including:
- Dynamic percentile calculations using ta.percentile_linear_interpolation()
- Conditional plotting with multiple size categories
- Custom number formatting functions
- Efficient label management to prevent display limits
This tool is designed for traders who want to understand the underlying buying and selling pressure beyond simple volume analysis, providing insights into market sentiment and potential turning points.
Multi SMA AnalyzerMulti SMA Analyzer with Custom SMA Table & Advanced Session Logic
A feature-rich SMA analysis suite for traders, offering up to 7 configurable SMAs, in-depth trend detection, real-time table, and true session-aware calculations.
Ideal for those who want to combine intraday, swing, and higher-timeframe trend analysis with maximum chart flexibility.
Key Features
📊 Multi-SMA Overlay
- 7 SMAs (default: 5, 20, 50, 100, 200, 21, 34)—individually configurable (period, source, color, line style)
- Show/hide each SMA, custom line style (solid, stepline, circles), and color logic
- Dynamic color: full opacity above SMA, reduced when below
⏰ Session-Aware SMAs
- Each SMA can be calculated using only user-defined session hours/days/timezone
- “Ignore extended hours” option for accurate intraday trend
📋 Smart Data Table
- Live SMA values, % distance from price, and directional arrows (↑/↓/→)
- Bull/Bear/Sideways trend classification
- Custom table position, size, colors, transparency
- Table can run on chart or custom (higher) timeframe for multi-TF analysis
🎯 Golden/Death Cross Detection
- Flexible crossover engine: select any two from (5, 10, 20, 50, 100, 200) for fast/slow SMA cross signals
- Plots icons (★ Golden, 💀 Death), optional crossover labels with custom size/colors
🏷️ SMA Labels
- Optional on-chart SMA period labels
- Custom placement (above/below/on line), size, color, offset
🚨 Signal & Trend Engine
- Bull/Bear/Sideways logic: price vs. multiple SMAs (not just one pair)
- Volume spike detection (2x 20-period SMA)
- Bullish engulfing candlestick detection
- All signals can use chart or custom table timeframe
🎨 Visual Customization
- Dynamic background color (Bull: green, Bear: red, Neutral: gray)
- Every visual aspect is customizable: label/table colors, transparency, size, position
🔔 Built-in Alerts
- Crossovers (SMA20/50, Golden/Death)
- Bull trend, volume spikes, engulfing pattern—all alert-ready
How It Works
- Session Filtering:
- SMAs can be set to count only bars from your chosen market session, for true intraday/trading-hour signals
Dynamic Table & Signals:
- Table and all signal logic run on your selected chart or custom timeframe
Flexible Crossover:
- Choose any pair (5, 10, 20, 50, 100, 200) for cross detection—SMA 10 is available for crossover even if not shown as an SMA line
Everything is modular:
- Toggle features, set visuals, and alerts to your workflow
🚨 How to Use Alerts
- All key signals (crossovers, trend shifts, volume spikes, engulfing patterns) are available as alert conditions.
To enable:
- Click the “Alerts” (clock) icon at the top of TradingView.
- Select your desired signal (e.g., “Golden Cross”) from the condition dropdown.
- Set your alert preferences and create the alert.
- Now, you’ll get notified automatically whenever a signal occurs!
Perfect For
- Multi-timeframe and swing traders seeking higher timeframe SMA confirmation
- Intraday traders who want to ignore pre/post-market data
- Anyone wanting a modern, powerful, fully customizable multi-SMA overlay
// P.S: Experiment with Golden Cross where Fast SMA is 5 and Slow SMA is 20.
// Set custom timeframe for 4 hr while monitoring your chart on 15 min time frame.
// Enable Background Color and Use Table Timeframe for Background.
// Uncheck Pine labels in Style tab.
Clean, open-source, and loaded with pro features—enjoy!
Like, share, and let me know if you'd like any new features added.
Dynamic Gap Probability ToolDynamic Gap Probability Tool measures the percentage gap between price and a chosen moving average, then analyzes your chart history to estimate the likelihood of the next candle moving up or down. It dynamically adjusts its sample size to ensure statistical robustness while focusing on the exact deviation level.
Originality and Value:
• Combines gap-based analysis with dynamic sample aggregation to balance precision and reliability.
• Automatically extends the sample when exact matches are scarce, avoiding misleading signals on rare extreme moves.
• Provides real “next-candle” probabilities based on historical occurrences rather than fixed thresholds or untested heuristics.
• Adds value by giving traders an evidence-based edge: you see how similar past deviations actually played out.
How It Works:
1. Calculate gap = (close – moving average) / moving average * 100.
2. Round the absolute gap to nearest percent (X%).
3. Count historical bars where gap ≥ X% above or ≤ –X% below.
4. If exact X% count is below the minimum occurrences threshold, include gaps at X+1%, X+2%, etc., until threshold is reached.
5. Compute “next-candle” green vs. red probabilities from the aggregated sample.
6. Display current gap, sample size, green probability, and red probability in a table.
Inputs:
• Moving Average Type (SMA, EMA, WMA, VWMA, HMA, SMMA, TMA)
• Moving Average Period (default 200)
• Minimum Occurrences Threshold (default 50)
• Table position and styling options
Examples:
• If price is 3% above the 200-period SMA and 120 occurrences ≥3% are found, with 84 green next candles (70%) and 36 red (30%), the script displays “3% | 120 | 70% green | 30% red.”
• If price is 8% below the SMA but only 20 exact matches exist, the script will include 9% and 10% gaps until it reaches 50 samples, then calculate probabilities from that broader set.
Why It’s Useful:
• Mean-reversion traders see green-probability signals at extreme overbought or oversold levels.
• Trend-followers identify continuation likelihood when red probability is high.
• Risk managers gauge reliability by inspecting sample size before acting on any signal.
Limitations:
• Historical probabilities do not guarantee future performance.
• Results depend on timeframe and symbol, backtest with your data before trading.
• Use realistic slippage and commission when overlaying on strategy scripts.
Fear and Greed Index [DunesIsland]The Fear and Greed Index is a sentiment indicator designed to measure the emotions driving the stock market, specifically investor fear and greed. Fear represents pessimism and caution, while greed reflects optimism and risk-taking. This indicator aggregates multiple market metrics to provide a comprehensive view of market sentiment, helping traders and investors gauge whether the market is overly fearful or excessively greedy.How It WorksThe Fear and Greed Index is calculated using four key market indicators, each capturing a different aspect of market sentiment:
Market Momentum (30% weight)
Measures how the S&P 500 (SPX) is performing relative to its 125-day simple moving average (SMA).
A higher value indicates that the market is trading well above its moving average, signaling greed.
Stock Price Strength (20% weight)
Calculates the net number of stocks hitting 52-week highs minus those hitting 52-week lows on the NYSE.
A greater number of net highs suggests strong market breadth and greed.
Put/Call Options (30% weight)
Uses the 5-day average of the put/call ratio.
A lower ratio (more call options being bought) indicates greed, as investors are betting on rising prices.
Market Volatility (20% weight)
Utilizes the VIX index, which measures market volatility.
Lower volatility is associated with greed, as investors are less fearful of large market swings.
Each component is normalized using a z-score over a 252-day lookback period (approximately one trading year) and scaled to a range of 0 to 100. The final Fear and Greed Index is a weighted average of these four components, with the weights specified above.Key FeaturesIndex Range: The index value ranges from 0 to 100:
0–25: Extreme Fear (red)
25–50: Fear (orange)
50–75: Neutral (yellow)
75–100: Greed (green)
Dynamic Plot Color: The plot line changes color based on the index value, visually indicating the current sentiment zone.
Reference Lines: Horizontal lines are plotted at 0, 25, 50, 75, and 100 to represent the different sentiment levels: Extreme Fear, Fear, Neutral, Greed, and Extreme Greed.
How to Interpret
Low Values (0–25): Indicate extreme fear, which may suggest that the market is oversold and could be due for a rebound.
High Values (75–100): Indicate greed, which may signal that the market is overbought and could be at risk of a correction.
Neutral Range (25–75): Suggests a balanced market sentiment, neither overly fearful nor greedy.
This indicator is a valuable tool for contrarian investors, as extreme readings often precede market reversals. However, it should be used in conjunction with other technical and fundamental analysis tools for a well-rounded view of the market.
Holy GrailThis is a long-only educational strategy that simulates what happens if you keep adding to a position during pullbacks and only exit when the asset hits a new All-Time High (ATH). It is intended for learning purposes only — not for live trading.
🧠 How it works:
The strategy identifies pullbacks using a simple moving average (MA).
When price dips below the MA, it begins monitoring for the first green candle (close > open).
That green candle signals a potential bottom, so it adds to the position.
If price goes lower, it waits for the next green candle and adds again.
The exit happens after ATH — it sells on each red candle (close < open) once a new ATH is reached.
You can adjust:
MA length (defines what’s considered a pullback)
Initial buy % (how much to pre-fill before signals start)
Buy % per signal (after pullback green candle)
Exit % per red candle after ATH
📊 Intended assets & timeframes:
This strategy is designed for broad market indices and long-term appreciating assets, such as:
SPY, NASDAQ, DAX, FTSE
Use it only on 1D or higher timeframes — it’s not meant for scalping or short-term trading.
⚠️ Important Limitations:
Long-only: The script does not short. It assumes the asset will eventually recover to a new ATH.
Not for all assets: It won't work on assets that may never recover (e.g., single stocks or speculative tokens).
Slow capital deployment: Entries happen gradually and may take a long time to close.
Not optimized for returns: Buy & hold can outperform this strategy.
No slippage, fees, or funding costs included.
This is not a performance strategy. It’s a teaching tool to show that:
High win rate ≠ high profitability
Patience can be deceiving
Many signals = long capital lock-in
🎓 Why it exists:
The purpose of this strategy is to demonstrate market psychology and risk overconfidence. Traders often chase strategies with high win rates without considering holding time, drawdowns, or opportunity cost.
This script helps visualize that phenomenon.
log.info() - 5 Exampleslog.info() is one of the most powerful tools in Pine Script that no one knows about. Whenever you code, you want to be able to debug, or find out why something isn’t working. The log.info() command will help you do that. Without it, creating more complex Pine Scripts becomes exponentially more difficult.
The first thing to note is that log.info() only displays strings. So, if you have a variable that is not a string, you must turn it into a string in order for log.info() to work. The way you do that is with the str.tostring() command. And remember, it's all lower case! You can throw in any numeric value (float, int, timestamp) into str.string() and it should work.
Next, in order to make your output intelligible, you may want to identify whatever value you are logging. For example, if an RSI value is 50, you don’t want a bunch of lines that just say “50”. You may want it to say “RSI = 50”.
To do that, you’ll have to use the concatenation operator. For example, if you have a variable called “rsi”, and its value is 50, then you would use the “+” concatenation symbol.
EXAMPLE 1
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
log.info(“RSI= ” + str.tostring(rsi))
Example Output =>
RSI= 50
Here, we use double quotes to create a string that contains the name of the variable, in this case “RSI = “, then we concatenate it with a stringified version of the variable, rsi.
Now that you know how to write a log, where do you view them? There isn’t a lot of documentation on it, and the link is not conveniently located.
Open up the “Pine Editor” tab at the bottom of any chart view, and you’ll see a “3 dot” button at the top right of the pane. Click that, and right above the “Help” menu item you’ll see “Pine logs”. Clicking that will open that to open a pane on the right of your browser - replacing whatever was in the right pane area before. This is where your log output will show up.
But, because you’re dealing with time series data, using the log.info() command without some type of condition will give you a fast moving stream of numbers that will be difficult to interpret. So, you may only want the output to show up once per bar, or only under specific conditions.
To have the output show up only after all computations have completed, you’ll need to use the barState.islast command. Remember, barState is camelCase, but islast is not!
EXAMPLE 2
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
if barState.islast
log.info("RSI=" + str.tostring(rsi))
plot(rsi)
However, this can be less than ideal, because you may want the value of the rsi variable on a particular bar, at a particular time, or under a specific chart condition. Let’s hit these one at a time.
In each of these cases, the built-in bar_index variable will come in handy. When debugging, I typically like to assign a variable “bix” to represent bar_index, and include it in the output.
So, if I want to see the rsi value when RSI crosses above 0.5, then I would have something like
EXAMPLE 3
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,0.5)
if rsiCrossedOver
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
Example Output =>
bix=19964 - RSI=51.8449459867
bix=19972 - RSI=50.0975830828
bix=19983 - RSI=53.3529808079
bix=19985 - RSI=53.1595745146
bix=19999 - RSI=66.6466337654
bix=20001 - RSI=52.2191767466
Here, we see that the output only appears when the condition is met.
A useful thing to know is that if you want to limit the number of decimal places, then you would use the command str.tostring(rsi,”#.##”), which tells the interpreter that the format of the number should only be 2 decimal places. Or you could round the rsi variable with a command like rsi2 = math.round(rsi*100)/100 . In either case you’re output would look like:
bix=19964 - RSI=51.84
bix=19972 - RSI=50.1
bix=19983 - RSI=53.35
bix=19985 - RSI=53.16
bix=19999 - RSI=66.65
bix=20001 - RSI=52.22
This would decrease the amount of memory that’s being used to display your variable’s values, which can become a limitation for the log.info() command. It only allows 4096 characters per line, so when you get to trying to output arrays (which is another cool feature), you’ll have to keep that in mind.
Another thing to note is that log output is always preceded by a timestamp, but for the sake of brevity, I’m not including those in the output examples.
If you wanted to only output a value after the chart was fully loaded, that’s when barState.islast command comes in. Under this condition, only one line of output is created per tick update — AFTER the chart has finished loading. For example, if you only want to see what the the current bar_index and rsi values are, without filling up your log window with everything that happens before, then you could use the following code:
EXAMPLE 4
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
bix = bar_index
if barstate.islast
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
Example Output =>
bix=20203 - RSI=53.1103309071
This value would keep updating after every new bar tick.
The log.info() command is a huge help in creating new scripts, however, it does have its limitations. As mentioned earlier, only 4096 characters are allowed per line. So, although you can use log.info() to output arrays, you have to be aware of how many characters that array will use.
The following code DOES NOT WORK! And, the only way you can find out why will be the red exclamation point next to the name of the indicator. That, and nothing will show up on the chart, or in the logs.
// CODE DOESN’T WORK
//@version=6
indicator("MW - log.info()")
var array rsi_arr = array.new()
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,50)
if rsiCrossedOver
array.push(rsi_arr, rsi)
if barstate.islast
log.info("rsi_arr:" + str.tostring(rsi_arr))
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
// No code errors, but will not compile because too much is being written to the logs.
However, after putting some time restrictions in with the i_startTime and i_endTime user input variables, and creating a dateFilter variable to use in the conditions, I can limit the size of the final array. So, the following code does work.
EXAMPLE 5
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
// CODE DOES WORK
//@version=6
indicator("MW - log.info()")
i_startTime = input.time(title="Start", defval=timestamp("01 Jan 2025 13:30 +0000"))
i_endTime = input.time(title="End", defval=timestamp("1 Jan 2099 19:30 +0000"))
var array rsi_arr = array.new()
dateFilter = time >= i_startTime and time <= i_endTime
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,50) and dateFilter // <== The dateFilter condition keeps the array from getting too big
if rsiCrossedOver
array.push(rsi_arr, rsi)
if barstate.islast
log.info("rsi_arr:" + str.tostring(rsi_arr))
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
Example Output =>
rsi_arr:
bix=20210 - RSI=56.9030578034
Of course, if you restrict the decimal places by using the rounding the rsi value with something like rsiRounded = math.round(rsi * 100) / 100 , then you can further reduce the size of your array. In this case the output may look something like:
Example Output =>
rsi_arr:
bix=20210 - RSI=55.6947486019
This will give your code a little breathing room.
In a nutshell, I was coding for over a year trying to debug by pushing output to labels, tables, and using libraries that cluttered up my code. Once I was able to debug with log.info() it was a game changer. I was able to start building much more advanced scripts. Hopefully, this will help you on your journey as well.
Intra-bar Close/Open Gap [YuL]Just checking one idea: look at gaps between close and open bars on lower timeframe to try to estimate how much slippage exists there that may be a result of buying or selling pressure.
Perhaps it only useful in real time to see if situation of the current bar is changing.
Open to ideas and suggestions.
All SMAs Bullish/Bearish Screener (Enhanced)All SMAs Bullish/Bearish Screener Enhanced: Uncover High-Conviction Trend Alignments with Confidence
Description:
Are you ready to elevate your trading from mere guesswork to precise, data-driven decisions? The "All SMAs Bullish/Bearish Screener Enhanced" is not just another indicator; it's a sophisticated, yet user-friendly, trend-following powerhouse designed to cut through market noise and pinpoint high-probability trading opportunities. Built on the foundational strength of comprehensive Moving Average confluence and fortified with critical confirmation signals from Momentum, Volume, and Relative Strength, this script empowers you to identify truly robust trends and manage your trades with unparalleled clarity.
The Power of Multi-Factor Confluence: Beyond Simple Averages
In the unpredictable world of financial markets, true strength or weakness is rarely an isolated event. It's the harmonious alignment of multiple technical factors that signals a high-conviction move. While our original "All SMAs Bullish/Bearish Screener" intelligently identified stocks where price was consistently above or below a full spectrum of Simple Moving Averages (5, 10, 20, 50, 100, 200), this Enhanced version takes it a crucial step further.
We've integrated a powerful three-pronged confirmation system to filter out weaker signals and highlight only the most compelling setups:
Momentum (Rate of Change - ROC): A strong trend isn't just about price direction; it's about the speed and intensity of that movement. Positive momentum confirms that buyers are still aggressively pushing price higher (for bullish signals), while negative momentum validates selling pressure (for bearish signals).
Volume: No trend is truly trustworthy without the backing of smart money. Above-average volume accompanying an "All SMAs" alignment signifies strong institutional participation and conviction behind the move. It separates genuine trend starts from speculative whims.
Relative Strength Index (RSI): This versatile oscillator ensures the trend isn't just "there," but that it's developing healthily. We use RSI to confirm a bullish bias (above 50) or a bearish bias (below 50), adding another layer of confidence to the direction.
When the price aligns above ALL six critical SMAs, and is simultaneously confirmed by robust positive momentum, healthy volume, and a bullish RSI bias, you have an exceptionally strong "STRONGLY BULLISH" signal. This confluence often precedes sustained upward moves, signaling prime accumulation phases. Conversely, a "STRONGLY BEARISH" signal, where price is below ALL SMAs with negative momentum, confirming volume, and a bearish RSI bias, indicates powerful distribution and potential for significant downside.
How to Use This Enhanced Screener:
Add to Chart: Go to TradingView's Pine Editor, paste the script, and click "Add to Chart."
Customize Parameters: Fine-tune the lengths of your SMAs, RSI, Momentum, and Volume averages via the indicator's settings. Experiment to find what best suits your trading style and the assets you trade.
Choose Your Timeframe Wisely:
Daily (1D) and 4-Hour (240 min) are highly recommended. These timeframes cut through intraday noise and provide more reliable, actionable signals for swing and position trading.
Shorter timeframes (e.g., 15min, 60min) can be used by advanced day traders for very short-term entries, but be aware of increased volatility and noise.
Visual Confirmation:
Green/Red Triangles: Appear on your chart, indicating confirmed bullish or bearish signals.
Background Color: The chart background will subtly turn lime green for "STRONGLY BULLISH" and red for "STRONGLY BEARISH" conditions.
On-Chart Status Table: A clear table displays the current signal status ("STRONGLY BULLISH/BEARISH," or "SMAs Mixed") for immediate feedback.
Set Up Alerts (Your Primary Screener Tool): This is the game-changer! Create custom alerts on TradingView based on the "Confirmed Bullish Trade" and "Confirmed Bearish Trade" conditions. Receive instant notifications (email, pop-up, mobile) for any stock in your watchlist that meets these stringent criteria. This allows you to scan the entire market effortlessly and act decisively.
Strategic Stop-Loss Placement: The Trader's Lifeline
Even the most robust signals can fail. Protecting your capital is paramount. For this trend-following strategy, your stop-loss should be placed where the underlying trend structure is broken.
For a "STRONGLY BULLISH" Trade: Place your stop-loss just below the most recent significant swing low (higher low). This is the last point where buyers stepped in to support the price. If price breaks below this, your bullish thesis is invalidated.
For a "STRONGLY BEARISH" Trade: Place your stop-loss just above the most recent significant swing high (lower high). If price breaks above this, your bearish thesis is invalidated.
Alternatively, consider placing your stop-loss just below the 20-period SMA (for bullish trades) or above the 20-period SMA (for bearish trades). A significant close beyond this intermediate-term average often indicates a critical shift in momentum. Always ensure your chosen stop-loss adheres to your pre-defined risk per trade (e.g., 1-2% of capital).
Disciplined Profit Booking: Maximizing Gains
Just as important as knowing when you're wrong is knowing when to take profits.
Trailing Stop-Loss: As your trade moves into profit, trail your stop-loss upwards (for longs) or downwards (for shorts). You can trail it using:
Previous Swing Lows/Highs: Move your stop to just below each new higher low (for longs) or just above each new lower high (for shorts).
A Moving Average (e.g., 10-period or 20-period SMA): If price closes below your chosen trailing SMA, exit. This allows you to ride the trend while protecting accumulated profits.
Target Levels: Identify potential resistance levels (for longs) or support levels (for shorts) using pivot points, previous highs/lows, or Fibonacci extensions. Consider taking partial profits at these levels and letting the rest run with a trailing stop.
Loss of Confluence: If the "STRONGLY BULLISH/BEARISH" condition ceases to be met (e.g., RSI crosses below 50, or volume drops significantly), this can be a signal to reduce or exit your position, even if your stop-loss hasn't been hit.
The "All SMAs Bullish/Bearish Screener Enhanced" is your comprehensive partner in navigating the markets. By combining robust trend identification with critical confirmation signals and disciplined risk management, you're equipped to make smarter, more confident trading decisions. Add it to your favorites and unlock a new level of precision in your trading journey!
#PineScript #TradingView #SMA #MovingAverage #TrendFollowing #StockScreener #TechnicalAnalysis #Bullish #Bearish #QQQ #Momentum #Volume #RSI #SPY #TradingStrategy #Enhanced #Signals #Analysis #DayTrading #SwingTrading
RSI-BBGun-v6.1RSI BB Gun – Operator's Guide
“Eyes on target. Wait for the right moment. Then strike.”
________________________________________
🎯 Mission Objective
RSI BB Gun identifies extreme market conditions using RSI and Bollinger Bands, then overlays trend and volatility intelligence so you know when the setup is real.
The ❌ is your target acquisition signal—price just moved from an extreme zone back into play. Now you’ve got a clean radar lock.
________________________________________
📡 How to Operate
🟣 Step 1: Watch for the ❌'s (Black X = RSI & Bollinger Band Extremes Encountered)
• The Purple X means price and RSI are both stretched—and just snapped back into range.
• The target is now in the cross hairs and potentially ready for engagement.
🟥 Step 2: Confirm the Trend
• The thick ribbon tells you if the trend is with you:
o 🟢 Green = Uptrend. Focus on long setups.
o 🔴 Red = Downtrend. Focus on puts or short plays.
• Align with trend. Only engage when the field favors your position.
🔺 Step 3: Evaluate Signal Context
• Green Triangles = price just crossed below lower Bollinger Band (oversold).
• Red Triangles = price crossed above upper Band (overbought).
• Horizontal Lines Disappeared = The bar after the green or red horizontal line disappears means its time. We patiently wait for this as it means the momentum may be changing.
• These are your early indicators—they scout the setup on the GO / NO GO DECISION.
• ❌ + triangle + trend = clean shot.
________________________________________
☁️ Avoid These Situations
• ❌ in a choppy/no-trend zone = false alarm. Don’t engage.
• Repeated black ❌s without a purple ❌confirmation = low conviction. Let it go.
________________________________________
________________________________________
🪖 Operator's Mindset
“You don’t chase trades. You stalk them. When the ❌ flashes, the system has found a target. What you do next is up to your discipline, your tools, and your plan.”
________________________________________
Note: This is a free version. Upcoming paid version includes multi-timeframes working together. Multiple strategies. Volatility meter. Make money and master the BB Gun so that you can elevate to the Snipers weapon.
🔒 Want More Firepower?
Upgraded version coming soon. Unlocks next-gen targeting tools:
• Multi-timeframe RSI intelligence in a live dashboard
• Precision-timed combo signals based on layered volatility + RSI logic
• Advanced trend filters, trade zone overlays, and sniper-level entry indicators
• Ideal for swing traders and options strategists who want clarity under pressure
💥 Budget-friendly. No subscription. Upgrade when you're ready to go Pro.
Tip: Make 4+ trades mastering this setup. Then use a small portion of the trades to gain more features. Always be in a position you cannot lose.
🆚 Why This Beats Standard RSI/BB Tools
Mission Feature Basic Indicators RSI Ribbon Lite
Trend Confirmation ❌ ✅ Ribbon Overlay
Multi-Timeframe Awareness ❌ ✅ 5-Timeframe RSI Grid
Volatility Confirmation ❌ ✅ Weighted ATR Scoring
Combo Signal Alerts ❌ ✅ ❌ Reentry Combo Alerts
TradingView Alerts ❌ ✅ Built-In Radar Ping
#rsi #bb #bollingerbands #hull ma #trend
Trend-Following Colored Bars w/ SignalsTheTechnicalTraders trendfollowing
Easy way to follow the trend.
TTM Squeeze Value OscillatorThis indicator is specifically designed for use with TradingView's Stock Screener, not for chart analysis. It provides numerical values and binary signals that allow traders to efficiently scan stocks for specific TTM Squeeze conditions, momentum patterns, and EMA alignments.
What It Does
The TTM Squeeze Value Oscillator converts the popular TTM Squeeze indicator into a screenable format by outputting specific numerical values and binary signals (1 or 0) that can be filtered in TradingView's screener tool.
Key Features
1. TTM Squeeze Compression Levels
Value 0: Low Compression (Black) - Bollinger Bands inside outer Keltner Channels
Value 1: Mid Compression (Red) - Bollinger Bands inside middle Keltner Channels
Value 2: High Compression (Orange) - Bollinger Bands inside inner Keltner Channels
Value 3: Squeeze Fired (Green) - Bollinger Bands outside Keltner Channels
2. Momentum Analysis
Four distinct momentum conditions based on TTM Squeeze methodology:
Buy Momentum Increasing - Positive momentum growing stronger
Buy Momentum Decreasing - Positive momentum weakening
Sell Momentum Increasing - Negative momentum growing stronger
Sell Momentum Decreasing - Negative momentum weakening
3. EMA Stacking Analysis
Three EMA alignment patterns using 8, 21, and 48 period EMAs:
EMA Stacked Bullish - 8 EMA > 21 EMA > 48 EMA (uptrend alignment)
EMA Stacked Bearish - 8 EMA < 21 EMA < 48 EMA (downtrend alignment)
EMA Mixed - EMAs not in clear bullish or bearish alignment
4. Consecutive Day Counters
Tracks how many consecutive days each squeeze condition has persisted:
Low Compression Days
Mid Compression Days
High Compression Days
Squeeze Fired Days
5. Combined Signal Analysis
Pre-calculated combinations of squeeze conditions with momentum:
All squeeze levels combined with all four momentum conditions
16 total combined signals for advanced screening
HMA Crossover + ATR + Curvature (Long & Short)📏 Hull Moving Averages (Trend Filters)
- fastHMA = ta.hma(close, fastLength)
- slowHMA = ta.hma(close, slowLength)
These two HMAs act as dynamic trend indicators:
- A bullish crossover of fast over slow HMA signals a potential long setup.
- A bearish crossunder triggers short interest.
⚡️ Curvature (Acceleration Filter)
- curv = ta.change(ta.change(fastHMA))
This calculates the second-order change (akin to the second derivative) of the fast HMA — effectively the acceleration of the trend. It serves as a filter:
- For long entries: curv > curvThresh (positive acceleration)
- For short entries: curv < -curvThresh (negative acceleration)
It helps eliminate weak or stagnating moves by requiring momentum behind the crossover.
📈 Volatility-Based Risk Management (ATR)
- atr = ta.atr(atrLength)
- stopLoss = atr * atrMult
- trailStop = atr * trailMult
These define your:
- Initial stop loss: scaled to recent volatility using ATR and atrMult.
- Trailing stop: also ATR-scaled, to lock in gains dynamically as price moves favorably.
💰 Position Sizing via Risk Percent
- capital = strategy.equity
- riskCapital = capital * (riskPercent / 100)
- qty = riskCapital / stopLoss
This dynamically calculates the position size (qty) such that if the stop loss is hit, the loss does not exceed the predefined percentage of account equity. It’s a volatility-adjusted position sizing method, keeping your risk consistent regardless of market conditions.
📌 Execution Logic
- Long Entry: on bullish HMA crossover with rising curvature.
- Short Entry: on bearish crossover with falling curvature.
- Exits: use ATR-based trailing stops.
- Position is closed when trend conditions reverse (e.g., bearish crossover exits the long).
This framework gives you:
- Trend-following logic (via HMAs)
- Momentum confirmation (via curvature)
- Volatility-aware execution and exits (via ATR)
- Risk-controlled dynamic sizing
Want to get surgical and test what happens if we use curvature on the difference between HMAs instead? That might give some cool insights into trend strength transitions.
VWAP Deviation Channels with Probability (Lite)VWAP Deviation Channels with Probability (Lite)
Version 1.2
Overview
This indicator is a powerful tool for intraday traders, designed to identify high-probability areas of support and resistance. It plots the Volume-Weighted Average Price (VWAP) as a central "value" line and then draws statistically-based deviation channels around it.
Its unique feature is a dynamic probability engine that analyzes thousands of historical price bars to calculate and display the real-time likelihood of the price touching each of these deviation levels. This provides a quantifiable edge for making trading decisions.
Core Concepts Explained
This indicator is built on three key concepts:
The VWAP (Volume-Weighted Average Price): The dotted midline of the channels is the session VWAP. Unlike a Simple Moving Average (SMA) which only considers price, the VWAP incorporates volume into its calculation. This makes it a much more significant benchmark, as it represents the true average price where the most business has been transacted during the day. It's heavily used by institutional traders, which is why price often reacts strongly to it.
Standard Deviation Channels: The channels above and below the VWAP are based on standard deviations. Standard deviation is a statistical measure of volatility.
- Wide Bands: When the channels are wide, it signifies high volatility.
- Narrow Bands: When the channels are tight and narrow, it signifies low volatility and
consolidation (a "squeeze").
The Conditional Probability Engine: This is the heart of the indicator. For every deviation level, the script displays a percentage. This percentage answers a very specific question:
"Based on thousands of previous bars, when the last candle had a certain momentum (bullish or bearish), what was the historical probability that the price would touch this specific level?"
The probabilities are calculated separately depending on whether the previous candle was green (bullish) or red (bearish). This provides a nuanced, momentum-based edge. The level with the highest probability is highlighted, acting as a "price magnet."
How to Use This Indicator
Recommended Timeframes:
This indicator is designed specifically for intraday trading. It works best on timeframes like the 1-minute, 5-minute, and 15-minute charts. It will not display correctly on daily or higher timeframes.
Recommended Trading Strategy: Mean Reversion
The primary strategy for this indicator is "Mean Reversion." The core idea is that as the price stretches to extreme levels far away from the VWAP (the "mean"), it is statistically more likely to "snap back" toward it.
Here is a step-by-step guide to trading this setup:
1. Identify the Extreme: Wait for the price to push into one of the outer deviation bands (e.g., the -2, -3, or -4 bands for a buy setup, or the +2, +3, or +4 bands for a sell setup).
2. Look for the High-Probability Zone: Pay close attention to the highlighted probability label. This is the level that has historically acted as the strongest magnet for price. A touch of this level represents a high-probability area for a potential reversal.
3. Wait for Confirmation: Do not enter a trade just because the price has touched a band. Wait for a confirmation candle that shows momentum is shifting.
- For a Buy: Look for a strong bullish candle (e.g., a green engulfing candle or a hammer/pin
bar) to form at the lower bands.
- For a Sell: Look for a strong bearish candle (e.g., a red engulfing candle or a shooting star)
to form at the upper bands.
Define Your Exit:
- Take Profit: A logical primary target for a mean reversion trade is the VWAP (midLine).
- Stop Loss: A logical place for a stop-loss is just outside the next deviation band. For
example, if you enter a long trade at the -3 band, your stop loss could be placed just
below the -4 band.
Disclaimer: This indicator is a tool for analysis and should not be considered a standalone trading system. Trading involves significant risk, and past performance is not indicative of future results. Always use this indicator in conjunction with other forms of analysis and sound risk management practices.
Morning Structure – Live 30 Min Range📝 Description:
This indicator captures the morning price structure by tracking the high and low during the first 30 minutes after market open (default: 9:30 AM to 10:00 AM, New York time).
🔧 How it works:
At market open, it begins tracking the highest high and lowest low
The high and low lines are dynamic and update in real-time during the first 30 minutes
Once the 30-minute range completes, the lines freeze at their final values
Lines extend horizontally across the rest of the session to mark the "Morning Range"
✅ Key Features:
Tracks live price action during the morning session
Freezes the structure after 30 minutes (or user-defined)
Automatically resets each new trading day
Built-in timezone setting (America/New_York) to align with standard U.S. market hours
Clean visual lines that scroll naturally with the chart
⚙️ Use Cases:
Identify morning breakout zones
Define support and resistance early in the session
Combine with breakout, fade, or range-trading strategies
⚠️ Note:
This version does not include alerts or labels, by design (clean and focused).
Those can be added easily for custom strategies.
Squeeze & Breakout Confirmation StrategyThis strategy focuses on identifying periods of low volatility (Bollinger Band Squeeze) and then confirming the direction of the subsequent breakout with momentum, volume, and candle strength.
Concepts Applied: Bollinger Bands (Squeeze), RSI (Momentum), Market Volume (Conviction), Candle Size (Strength)
Buy Signal:
Bollinger Band Squeeze: Look for a period where the Bollinger Bands contract significantly, indicating low volatility and consolidation. The bands should be very close to the price action.
RSI Breakout: After the squeeze, wait for the price to break decisively above the upper Bollinger Band. Simultaneously, the RSI should break above 60 (or even 70), indicating strong bullish momentum.
Volume Surge: The breakout candle should be accompanied by a significant increase in trading volume, ideally above its recent average, confirming strong buying interest.
Strong Bullish Candle: The breakout candle itself should be a large, bullish candle (e.g., a strong green candle with a small upper wick or a bullish engulfing pattern), demonstrating buyer conviction.
Sell Signal (Short):
Bollinger Band Squeeze: Look for a period where the Bollinger Bands contract significantly.
RSI Breakdown: After the squeeze, wait for the price to break decisively below the lower Bollinger Band. Simultaneously, the RSI should break below 40 (or even 30), indicating strong bearish momentum.
Volume Surge: The breakdown candle should be accompanied by a significant increase in trading volume, ideally above its recent average, confirming strong selling interest.
Strong Bearish Candle: The breakdown candle itself should be a large, bearish candle (e.g., a strong red candle with a small lower wick or a bearish engulfing pattern), demonstrating seller conviction.
