IU Engulfing Candlestick PatternDISCRIPTION
📈 The IU Engulfing Candlestick Pattern indicator spotlights both bullish and bearish engulfing formations in real‑time. It shades each pattern with a transparent box and drops a concise label so you can catch potential reversals at a glance—no clutter, no noise, just the candles that matter.
USER INPUTS :
1. Pattern Recognition Based on = “Both” | “Wicks” | “Body” ( Default Both )
• Both → only highlights candles that satisfy **both** wick‑and‑body engulfing rules
• Wicks → checks full candle range (high‑to‑low)
• Body → checks only the real bodies (open‑to‑close)
2. Show Labels ( Default true )
If ticked then it will show the text as "Bullish Engulfing" or "Bearish Engulfing".
3. Show The Box ( Default true)
if ticked then it will show the green or red boxes.
INDICATOR LOGIC:
🔹 Bullish Engulfing (green box)
– Current bar closes higher than it opens and fully “wraps” the prior bar per your chosen rule.
🔹 Bearish Engulfing (red box)
– Current bar closes lower than it opens and fully “wraps” the prior bar per your chosen rule.
🔸 When a pattern confirms:
1. The script records the local high/low range.
2. Draws a semi‑transparent box spanning the engulfing pair.
3. Prints a compact up/down label exactly at the reaction point.
4. Fires a once‑per‑bar alert (“Bullish Engulfing” / “Bearish Engulfing”) you can route to webhooks or notifications.
WHY IT IS UNIQUE:
✨ Combines classic body‑only engulfing with an optional wick filter, letting traders demand stricter confirmation when markets are noisy.
✨ Box overlays visually segment the engulfed range—clearer than single‑bar markers.
✨ Lightweight: one input, zero repaint, and capped at 500 boxes to keep charts responsive.
✨ Ready‑to‑use alerts—no extra code needed for automation.
HOW USER CAN BENIFIT FROM IT :
- Spot early reversal zones or continuation thrusts without scanning candle by candle.
- Pair the alerts with trading bots, TradingView strategy testers, or mobile push notifications.
- Adapt the strictness (Body vs. Wicks vs. Both) to suit different assets, timeframes, or volatility regimes.
- Use the colored range boxes as dynamic support/resistance references for entries, targets, and stop‑loss placement.
📌 Tip: Test on multiple instruments and timeframes to find the sweet spot that matches your risk profile. This script is for educational purposes—always combine with sound risk management and confirm signals with broader market context.
Disclaimer :
This Video is not financial advice, it's for educational purposes only highlighting the power of coding( pine script) in TradingView, I am not a SEBI-registered advisor. Trading and investing involve risk, and you should consult with a qualified financial advisor before making any trading decisions. I do not guarantee profits or take responsibility for any losses you may incur.
Search in scripts for "标普500指数+成分股"
H turnoverTrading Value refers to the total monetary amount of all transactions for a particular stock or the entire market over a specific period. It is calculated by multiplying the trading volume (the number of shares traded) by the price at which they were traded. For example, if 10,000 shares of a stock are traded in a day at an average price of 50,000 KRW, the trading value for that day would be 500,000,000 KRW.
Key points about trading value:
Market Activity and Liquidity: A high trading value indicates an active and liquid market.
Flow of Investment Funds: Increasing trading value suggests more money is flowing into the market or a particular stock.
Relationship with Price Movements: When both trading value and price rise together, it often signals strong buying interest. Conversely, significant price changes with low trading value may be less reliable.
Market Sentiment Indicator: Changes in trading value can reflect shifts in investor interest and sentiment.
In summary, trading value is the total amount of money exchanged in trades and serves as an important indicator of market activity, liquidity, and investor sentiment.
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.
Divergence Screener [Trendoscope®]🎲Overview
The Divergence Screener is a powerful TradingView indicator designed to detect and visualize bullish and bearish divergences, including hidden divergences, between price action and a user-selected oscillator. Built with flexibility in mind, it allows traders to customize the oscillator type, trend detection method, and other parameters to suit various trading strategies. The indicator is non-overlay, displaying divergence signals directly on the oscillator plot, with visual cues such as lines and labels on the chart for easy identification.
This indicator is ideal for traders seeking to identify potential reversal or continuation signals based on price-oscillator divergences. It supports multiple oscillators, trend detection methods, and alert configurations, making it versatile for different markets and timeframes.
🎲Features
🎯Customizable Oscillator Selection
Built-in Oscillators : Choose from a variety of oscillators including RSI, CCI, CMO, COG, MFI, ROC, Stochastic, and WPR.
External Oscillator Support : Users can input an external oscillator source, allowing integration with custom or third-party indicators.
Configurable Length : Adjust the oscillator’s period (e.g., 14 for RSI) to fine-tune sensitivity.
🎯Divergence Detection
The screener identifies four types of divergences:
Bullish Divergence : Price forms a lower low, but the oscillator forms a higher low, signaling potential upward reversal.
Bearish Divergence : Price forms a higher high, but the oscillator forms a lower high, indicating potential downward reversal.
Bullish Hidden Divergence : Price forms a higher low, but the oscillator forms a lower low, suggesting trend continuation in an uptrend.
Bearish Hidden Divergence : Price forms a lower high, but the oscillator forms a higher high, suggesting trend continuation in a downtrend.
🎯Flexible Trend Detection
The indicator offers three methods to determine the trend context for divergence detection:
Zigzag : Uses zigzag pivots to identify trends based on higher highs (HH), higher lows (HL), lower highs (LH), and lower lows (LL).
MA Difference : Calculates the trend based on the difference in a moving average (e.g., SMA, EMA) between divergence pivots.
External Trend Signal : Allows users to input an external trend signal (positive for uptrend, negative for downtrend) for custom trend analysis.
🎯Zigzag-Based Pivot Analysis
Customizable Zigzag Length : Adjust the zigzag length (default: 13) to control the sensitivity of pivot detection.
Repaint Option : Choose whether divergence lines repaint based on the latest data or wait for confirmed pivots, balancing responsiveness and reliability.
🎯Visual and Alert Features
Divergence Visualization : Divergence lines are drawn between price pivots and oscillator pivots, color-coded for easy identification:
Bullish Divergence : Green
Bearish Divergence : Red
Bullish Hidden Divergence : Lime
Bearish Hidden Divergence : Orange
Labels and Tooltips : Labels (e.g., “D” for divergence, “H” for hidden) appear on price and oscillator pivots, with tooltips providing detailed information such as price/oscillator values, ratios, and pivot directions.
Alerts : Configurable alerts for each divergence type (bullish, bearish, bullish hidden, bearish hidden) trigger on bar close, ensuring timely notifications.
🎲 How It Works
🎯Oscillator Calculation
The indicator calculates the selected oscillator (or uses an external source) and plots it on the chart.
Oscillator values are stored in a map for reference during divergence calculations.
🎯Pivot Detection
A zigzag algorithm identifies pivots in the oscillator data, with configurable length and repainting options.
Price and oscillator pivots are compared to detect divergences based on their direction and ratio.
🎯Divergence Identification
The indicator compares price and oscillator pivot directions (HH, HL, LH, LL) to identify divergences.
Trend context is determined using the selected method (Zigzag, MA Difference, or External).
Divergences are classified as bullish, bearish, bullish hidden, or bearish hidden based on price-oscillator relationships and trend direction.
🎯Visualization and Alerts
Valid divergences are drawn as lines connecting price and oscillator pivots, with corresponding labels.
Alerts are triggered for allowed divergence types, providing detailed information via tooltips.
🎯Validation
Divergence lines are validated to ensure no intermediate bars violate the divergence condition, enhancing signal reliability.
🎲 Usage Instructions as Indicator
🎯Add to Chart:
Add the “Divergence Screener ” to your TradingView chart.
The indicator appears in a separate pane below the price chart, plotting the oscillator and divergence signals.
🎯Configure Settings:
Adjust the oscillator type and length to match your trading style.
Select a trend detection method and configure related parameters (e.g., MA type/length or external signal).
Set the zigzag length and repainting preference.
Enable/disable alerts for specific divergence types.
I🎯nterpret Signals:
Bullish Divergence (Green) : Look for potential buy opportunities in a downtrend.
Bearish Divergence (Red) : Consider sell opportunities in an uptrend.
Bullish Hidden Divergence (Lime) : Confirm continuation in an uptrend.
Bearish Hidden Divergence (Orange): Confirm continuation in a downtrend.
Use tooltips on labels to review detailed pivot and divergence information.
🎯Set Alerts:
Create alerts for each divergence type to receive notifications via TradingView’s alert system.
Alerts include detailed text with price, oscillator, and divergence information.
🎲 Example Scenarios as Indicator
🎯 With External Oscillator (Use MACD Histogram as Oscillator)
In order to use MACD as an oscillator for divergence signal instead of the built in options, follow these steps.
Load MACD Indicator from Indicator library
From Indicator settings of Divergence Screener, set Use External Oscillator and select MACD Histograme from the dropdown
You can now see that the oscillator pane shows the data of selected MACD histogram and divergence signals are generated based on the external MACD histogram data.
🎯 With External Trend Signal (Supertrend Ladder ATR)
Now let's demonstrate how to use external direction signals using Supertrend Ladder ATR indicator. Please note that in order to use the indicator as trend source, the indicator should return positive integer for uptrend and negative integer for downtrend. Steps are as follows:
Load the desired trend indicator. In this example, we are using Supertrend Ladder ATR
From the settings of Divergence Screener, select "External" as Trend Detection Method
Select the trend detection plot Direction from the dropdown. You can now see that the divergence signals will rely on the new trend settings rather than the built in options.
🎲 Using the Script with Pine Screener
The primary purpose of the Divergence Screener is to enable traders to scan multiple instruments (e.g., stocks, ETFs, forex pairs) for divergence signals using TradingView’s Pine Screener, facilitating efficient comparison and identification of trading opportunities.
To use the Divergence Screener as a screener, follow these steps:
Add to Favorites : Add the Divergence Screener to your TradingView favorites to make it available in the Pine Screener.
Create a Watchlist : Build a watchlist containing the instruments (e.g., stocks, ETFs, or forex pairs) you want to scan for divergences.
Access Pine Screener : Navigate to the Pine Screener via TradingView’s main menu: Products -> Screeners -> Pine, or directly visit tradingview.com/pine-screener/.
Select Watchlist : Choose the watchlist you created from the Watchlist dropdown in the Pine Screener interface.
Choose Indicator : Select Divergence Screener from the Choose Indicator dropdown.
Configure Settings : Set the desired timeframe (e.g., 1 hour, 1 day) and adjust indicator settings such as oscillator type, zigzag length, or trend detection method as needed.
Select Filter Criteria : Select the condition on which the watchlist items needs to be filtered. Filtering can only be done on the plots defined in the script.
Run Scan : Press the Scan button to display divergence signals across the selected instruments. The screener will show which instruments exhibit bullish, bearish, bullish hidden, or bearish hidden divergences based on the configured settings.
🎲 Limitations and Possible Future Enhancements
Limitations are
Custom input for oscillator and trend detection cannot be used in pine screener.
Pine screener has max 500 bars available.
Repaint option is by default enabled. When in repaint mode expect the early signal but the signals are prone to repaint.
Possible future enhancements
Add more built-in options for oscillators and trend detection methods so that dependency on external indicators is limited
Multi level zigzag support
Micro Futures Contract Calculator Micro Futures Contract Calculator
Synopsis: The Micro Futures Contract Calculator is a sleek, minimalist indicator that calculates the number of Micro E-mini Nasdaq-100 (MNQ) or S&P 500 (MES) contracts you can trade based on a fixed dollar risk and stop-loss (in ticks). Displayed in a compact, professional table in the top-right corner, it shows your risk, stop-loss, contract type, and calculated contracts, helping traders maintain consistent risk management.
How to Use:
Add the indicator to your chart (search “Micro Futures Contract Calculator”).
In settings, input:
Maximum Risk ($): Your total risk per trade (e.g., $100).
Stop-Loss (Ticks): Stop-loss size in ticks (e.g., 20 ticks = 5 points).
Contract Type: Select MNQ or MES.
Check the top-right table for:
Risk, stop-loss, contract type, and number of contracts (e.g., “10” for MNQ, “4” for MES).
Use the contract number to size trades, ensuring risk stays fixed.
Why Standardized Risk is Important:
Consistency: Fixed risk per trade (e.g., $100) prevents oversized losses, stabilizing long-term performance.
Discipline: Removes emotional guesswork, enforcing a systematic approach across MNQ/MES trades.
Capital Protection: Limits exposure, preserving your account during losing streaks and volatile markets.
Scalability: Aligns position sizing with your risk tolerance, enabling confident scaling as your account grows.
This indicator simplifies risk management, making it essential for disciplined futures trading.
Normalized Open InterestNormalized Open Interest (nOI) — Indicator Overview
What it does
Normalized Open Interest (nOI) transforms raw futures open-interest data into a 0-to-100 oscillator, so you can see at a glance whether participation is unusually high or low—similar in spirit to an RSI but applied to open interest. The script positions today’s OI inside a rolling high–low range and paints it with contextual colours.
Core logic
Data source – Loads the built-in “_OI” symbol that TradingView provides for the current market.
Rolling range – Looks back a user-defined number of bars (default 500) to find the highest and lowest OI in that window.
Normalization – Calculates
nOI = (OI – lowest) / (highest – lowest) × 100
so 0 equals the minimum of the window and 100 equals the maximum.
Visual cues – Plots the oscillator plus fixed horizontal levels at 70 % and 30 % (or your own numbers). The line turns teal above the upper level, red below the lower, and neutral grey in between.
User inputs
Window Length (bars) – How many candles the indicator scans for the high–low range; larger numbers smooth the curve, smaller numbers make it more reactive.
Upper Threshold (%) – Default 70. Anything above this marks potentially crowded or overheated interest.
Lower Threshold (%) – Default 30. Anything below this marks low or capitulating interest.
Practical uses
Spot extremes – Values above the upper line can warn that the long side is crowded; values below the lower line suggest disinterest or short-side crowding.
Confirm breakouts – A price breakout backed by a sharp rise in nOI signals genuine engagement.
Look for divergences – If price makes a new high but nOI does not, participation might be fading.
Combine with volume or RSI – Layer nOI with other studies to filter false signals.
Tips
On intraday charts for non-crypto symbols the script automatically fetches daily OI data to avoid gaps.
Adjust the thresholds to 80/20 or 60/40 to fit your market and risk preferences.
Alerts, shading, or additional signal logic can be added easily because the oscillator is already normalised.
Mongoose Conflict Risk Radar v1.1 (Separate Panel) description
The Mongoose Capital: Risk Rotation Index is a macro market sentiment tool designed to detect elevated risk conditions by aggregating signals across key asset classes.
This script evaluates trend strength across 8 ETFs representing major risk-on and risk-off flows:
GLD – Gold
VIXY – Volatility
TLT – Long-Term Bonds
SPY – S&P 500
UUP – U.S. Dollar Index
EEM – Emerging Markets
SLV – Silver
FXI – China Large-Cap
Each asset is assigned a binary signal based on price position vs. its 21-period SMA (or a crossover for bonds). The signals are then totaled into a composite Risk Rotation Score, plotted as a bar graph.
How to Use
0–2 = Low risk-on behavior
3–4 = Caution / Mixed regime
5–8 = Elevated conflict or macro stress
Use this as a macro confirmation layer for trend entries, risk reduction, or allocation shifts.
Alerts
Set alerts when the index exceeds 5 to track major rotations into defensive assets.
LVN/HVN Auto Detection [PhenLabs]📊 PhenLabs - LVN/HVN Auto Detection
Version: PineScript™ v6
📌 Description
The PhenLabs LVN/HVN Auto Detection indicator is an advanced volume profile analysis tool that automatically identifies Low Volume Nodes (LVN) and High Volume Nodes (HVN) across multiple trading sessions. This sophisticated indicator analyzes volume distribution patterns to pinpoint critical support and resistance levels where price is likely to react, providing traders with high-probability zones for entries, exits, and risk management.
Unlike traditional volume indicators that only show current activity, this tool builds comprehensive volume profiles from historical sessions and intelligently filters the most significant levels. It combines real-time volume analysis with dynamic level detection, offering both visual bubbles for immediate volume activity and persistent horizontal lines that act as ongoing support/resistance references.
🚀 Points of Innovation
Multi-Session Volume Profile Analysis - Automatically calculates and analyzes volume profiles across the last 5 trading sessions
Intelligent Level Separation Logic - Prevents overlapping signals by maintaining minimum separation between LVN and HVN levels
Dynamic Timeframe Adaptation - Automatically adjusts session lengths based on chart timeframe for optimal level detection
Real-Time Activity Bubbles - Shows volume activity strength through different bubble sizes at key levels
Persistent Line Management - Creates horizontal lines that extend until price crosses them, providing ongoing reference points
Dual Threshold System - Independent percentage-based thresholds for both LVN and HVN identification
🔧 Core Components
Volume Profile Engine : Builds 20-row volume profiles for each analyzed session, distributing volume across price levels
Level Identification Algorithm : Uses percentage-based thresholds to classify volume distribution patterns
Separation Logic : Ensures minimum distance between conflicting levels, prioritizing HVN when overlap occurs
Line Management System : Tracks active support/resistance lines and removes them when price crosses through
Volume Activity Monitor : Compares current volume to 13-period moving average for activity classification
🔥 Key Features
Customizable Thresholds : LVN threshold (5-35%, default 20%) and HVN threshold (65-95%, default 80%) for precise level filtering
Volume Activity Multiplier : Adjustable volume threshold (0.5+, default 1.5) for bubble and line creation sensitivity
Flexible Display Modes : Choose between Lines only, Bubbles only, or Both for optimal chart clarity
Smart Level Separation : Minimum separation percentage (0.1-2%, default 0.5%) prevents conflicting signals
Color Customization : Independent color controls for LVN (red) and HVN (blue) elements
Performance Optimization : Processes every 15 bars with maximum 500 active lines for smooth operation
🎨 Visualization
Colored Bubbles : Three sizes (large, medium, small) indicate volume activity strength at key levels
Horizontal Lines : Persistent support/resistance lines with width corresponding to volume activity
Dual Color System : Semi-transparent red for LVN areas, semi-transparent blue for HVN zones
Information Tooltip : Optional table showing usage guidelines and optimization tips
📖 Usage Guidelines
Volume Thresholds
LVN Threshold
○ Default: 20.0%
○ Range: 5.0-35.0%
○ Description: Price levels with volume below this percentage are marked as LVNs. Lower values create fewer, more significant levels. Typical range 15-25% works for most instruments.
HVN Threshold
○ Default: 80.0%
○ Range: 65.0-95.0%
○ Description: Price levels with volume above this percentage are marked as HVNs. Higher values create fewer, stronger levels. Range 75-85% is optimal for most trading.
Display Controls
Volume Threshold
○ Default: 1.5
○ Range: 0.5+
○ Description: Multiplier for volume significance (High=2+threshold, Medium=1+threshold, Low=0+threshold). Higher values require more volume for signals.
✅ Best Use Cases
Swing Trading : Identify key levels for position entries and exits over multiple days
Scalping : Use bubbles for immediate volume activity confirmation at critical levels
Risk Management : Place stops beyond LVN levels where price moves quickly
Breakout Trading : Monitor HVN levels for potential breakout or rejection scenarios
Multi-Timeframe Analysis : Combine with higher timeframe levels for confluence
⚠️ Limitations
Timeframe Sensitivity : Lower timeframes may produce too many levels; higher timeframes recommended for cleaner signals
Volume Data Dependency : Accuracy depends on reliable volume data from your data provider
Historical Analysis : Uses past volume data which may not predict future price behavior
Performance Impact : High number of active lines may affect chart performance on slower devices
💡 What Makes This Unique
Automated Session Analysis : No manual drawing required - automatically analyzes multiple sessions
Intelligent Filtering : Advanced separation logic prevents overlapping and conflicting signals
Adaptive Processing : Adjusts to different timeframes automatically for optimal level detection
Dual Visualization System : Combines persistent lines with real-time activity indicators
🔬 How It Works
1. Volume Profile Construction :
Analyzes the last 5 trading sessions with dynamic session length based on timeframe
Divides each session’s price range into 20 equal levels for volume distribution analysis
2. Level Classification :
Calculates volume percentage at each price level relative to session maximum
Identifies LVN levels below threshold and HVN levels above threshold
3. Signal Generation :
Creates bubbles when volume activity exceeds thresholds at identified levels
Draws horizontal lines that persist until price crosses through them
💡 Note : For optimal results, increase your chart timeframe if you see too many levels. The indicator performs best on 15-minute and higher timeframes where volume patterns are more meaningful and less noisy.
Share SizePurpose: The "Share Size" indicator is a powerful risk management tool designed to help traders quickly determine appropriate share/contract sizes based on their predefined risk per trade and the current market's volatility (measured by ATR). It calculates potential dollar differences from recent highs/lows and translates them into a recommended share/contract size, accounting for a user-defined ATR-based offset. This helps you maintain consistent risk exposure across different instruments and market conditions.
How It Works: At its core, the indicator aims to answer the question: "How many shares/contracts can I trade to keep my dollar risk within limits if my stop loss is placed at a recent high or low, plus an ATR-based buffer?"
Price Difference Calculation: It first calculates the dollar difference between the current close price and the high and low of the current bar (Now) and the previous 5 bars (1 to 5).
Tick Size & Value Conversion: These price differences are then converted into dollar values using the instrument's specific tickSize and tickValue. You can select common futures contracts (MNQ, MES, MGC, MCL), a generic "Stock" setting, or define custom values.
ATR Offset: An Average True Range (ATR) based offset is added to these dollar differences. This offset acts as a buffer, simulating a stop loss placed beyond the immediate high/low, accounting for market noise or volatility.
Risk-Based Share Size: Finally, using your Default Risk ($) input, the indicator calculates how many shares/contracts you can take for each of the 6 high/low scenarios (current bar, 5 previous bars) to ensure your dollar risk per trade remains constant.
Dynamic Table: All these calculations are presented in a clear, real-time table at the bottom-left of your chart. The table dynamically adjusts its "Label" to show the selected symbol preset, making it easy to see which instrument's settings are currently being used. The "Shares" rows indicate the maximum shares/contracts you can trade for a given risk and stop placement. The cells corresponding to the largest dollar difference (and thus smallest share size) for both high and low scenarios are highlighted, drawing your attention to the most conservative entry points.
Key Benefits:
Consistent Risk: Helps maintain a consistent dollar risk per trade, regardless of the instrument or its current price/volatility.
Dynamic Sizing: Automatically adjusts share/contract size based on market volatility and your chosen stop placement.
Quick Reference: Provides a real-time, easy-to-read table directly on your chart, eliminating manual calculations.
Informed Decision Making: Assists in quickly assessing trade opportunities and potential position sizes.
Setup Parameters (Inputs)
When you add the "Share Size" indicator to your chart, you'll see a settings dialog with the following parameters:
1. Symbol Preset:
Purpose: This is the primary setting to define the tick size and value for your chosen trading instrument.
Options:
MNQ (Micro Nasdaq 100 Futures)
MES (Micro E-mini S&P 500 Futures)
MGC (Micro Gold Futures)
MCL (Micro Crude Oil Futures)
Stock (Generic stock setting, with tick size/value of 0.01)
Custom (Allows you to manually input tick size and value)
Default: MNQ
Importance: Crucial for accurate dollar calculations. Ensure this matches the instrument you are trading.
2. Tick Size (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the smallest price increment for your instrument.
Type: Float
Default: 0.25
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. You might need to change display=display.none to display=display.inline in the code if you want to see and adjust it directly in the settings for "Custom" mode.
3. Tick Value (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the dollar value of one tickSize increment.
Type: Float
Default: 0.50
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. Similar to Tick Size, you might need to adjust its display property if you want it visible.
4. Default Risk ($):
Purpose: This is your maximum desired dollar risk per trade. All share size calculations will be based on this value.
Type: Float
Default: 50.0
Hidden: This input is hidden (display=display.none). It's a critical setting, so consider making it visible by changing display=display.none to display=display.inline in the code if you want users to easily adjust their risk.
ATR Offset Settings (Group): This group of settings allows you to fine-tune the ATR-based buffer added to your potential stop loss.
5. ATR Offset Length:
Purpose: Defines the lookback period for the Average True Range (ATR) calculation used for the offset.
Type: Integer
Default: 7
Hidden: This input is hidden (display=display.none).
6. ATR Offset Timeframe:
Purpose: Specifies the timeframe on which the ATR for the offset will be calculated. This allows you to use ATR from a higher timeframe for your stop buffer, even if your chart is on a lower timeframe.
Type: Timeframe string (e.g., "1" for 1 minute, "60" for 1 hour, "D" for Daily)
Default: "1" (1 Minute)
Hidden: This input is hidden (display=display.none).
7. ATR Offset Multiplier (x ATR):
Purpose: Multiplies the calculated ATR value to determine the final dollar offset added to your high/low price difference. A value of 1.0 means one full ATR is added. A value of 0.5 means half an ATR is added.
Type: Float
Minimum Value: 0 (no offset)
Default: 1.0
Hidden: This input is hidden (display=display.none).
Simple Pips GridOverview
This is a clean, simple, and highly practical indicator that draws horizontal grid lines at user-defined pip intervals.
Unlike other complex grid indicators, this script is designed to be lightweight and error-free. It eliminates automatic symbol detection and instead gives you full manual control, ensuring it works perfectly with any symbol you trade—FX, CFDs, Crypto, Stocks, Indices, and more.
Key Features
Universal Compatibility: Works with any trading pair by letting you manually define the pip value.
Fully Customizable: Easily set the pip interval for your grid (e.g., 10 pips, 50 pips, 100 pips).
Lightweight & Fast: Simple code ensures smooth performance without lagging your chart.
Visual Customization: Change the color, width, and style (solid, dashed, dotted) of the grid lines.
How to Use
It's incredibly simple to set up. You only need to configure two main settings:
Step 1: Set the "Pip Value"
This is the most important setting. You need to tell the indicator what "1 pip" means for the symbol you are currently viewing.
Go to the indicator settings and find the "Pip Value" input. Here are some common examples:
Symbol Pip Value (Input this number)
USD/JPY 0.01
EUR/USD 0.0001
GBP/USD 0.0001
XAU/USD (Gold) 0.1
JP225 (Nikkei 225) 10
US500 (S&P 500) 1
BTC/USD 0.1 or 1.0 (depending on your preference)
Step 2: Set the "Pip Interval"
Next, in the "Pip Interval" input, simply type how many pips you want between each line.
For a 10-pip grid, enter 10.
For a 50-pip grid, enter 50.
That's it! The grid will now be perfectly aligned to your specifications.
Additional Settings
Line Color, Width, Style: Customize the appearance of the lines to match your chart theme.
Number of Lines: Adjust how many lines are drawn above and below the current price to optimize performance and visibility.
This script was created with the assistance of Gemini (Google's AI) to be a simple and reliable tool for all traders. Feel free to use and modify it. Happy trading!
Mark4ex vWapMark4ex VWAP is a precision session-anchored Volume Weighted Average Price (VWAP) indicator crafted for intraday traders who want clean, reliable VWAP levels that reset daily to match a specific market session.
Unlike the built-in continuous VWAP, this version anchors each day to your chosen session start and end time, most commonly aligned with the New York Stock Exchange Open (9:30 AM EST) through the market close (4:00 PM EST). This ensures your VWAP reflects only intraday price action within your active trading window — filtering out irrelevant overnight moves and providing clearer mean-reversion signals.
Key Features:
Fully configurable session start & end times — adapt it for NY session or any other market.
Anchored VWAP resets daily for true session-based levels.
Built for the New York Open Range Breakout strategy: see how price interacts with VWAP during the volatile first 30–60 minutes of the US market.
Plots a clean, dynamic line that updates tick-by-tick during the session and disappears outside trading hours.
Designed to help you spot real-time support/resistance, intraday fair value zones, and liquidity magnets used by institutional traders.
How to Use — NY Open Range Breakout:
During the first hour of the New York session, institutional traders often define an “Opening Range” — the high and low formed shortly after the bell. The VWAP in this zone acts as a dynamic pivot point:
When price is above the session VWAP, bulls are in control — the level acts as a support floor for pullbacks.
When price is below the session VWAP, bears dominate — the level acts as resistance against bounces.
Breakouts from the opening range often test the VWAP for confirmation or rejection.
Traders use this to time entries for breakouts, retests, or mean-reversion scalps with greater confidence.
⚙️ Recommended Settings:
Default: 9:30 AM to 4:00 PM New York time — standard US equities session.
Adjust hours/minutes to match your target market’s open and close.
👤 Who is it for?
Scalpers, day traders, prop traders, and anyone trading the NY Open, indices like the S&P 500, or highly liquid stocks during US cash hours.
🚀 Why use Mark4ex VWAP?
Because a properly anchored VWAP is a trader’s real-time institutional fair value, giving you better context than static moving averages. It adapts live to volume shifts and helps you follow smart money footprints.
This indicator will reconfigure every day, anchored to the New York Open, it will also leave historical NY Open VWAP for study purpose.
Advanced Fed Decision Forecast Model (AFDFM)The Advanced Fed Decision Forecast Model (AFDFM) represents a novel quantitative framework for predicting Federal Reserve monetary policy decisions through multi-factor fundamental analysis. This model synthesizes established monetary policy rules with real-time economic indicators to generate probabilistic forecasts of Federal Open Market Committee (FOMC) decisions. Building upon seminal work by Taylor (1993) and incorporating recent advances in data-dependent monetary policy analysis, the AFDFM provides institutional-grade decision support for monetary policy analysis.
## 1. Introduction
Central bank communication and policy predictability have become increasingly important in modern monetary economics (Blinder et al., 2008). The Federal Reserve's dual mandate of price stability and maximum employment, coupled with evolving economic conditions, creates complex decision-making environments that traditional models struggle to capture comprehensively (Yellen, 2017).
The AFDFM addresses this challenge by implementing a multi-dimensional approach that combines:
- Classical monetary policy rules (Taylor Rule framework)
- Real-time macroeconomic indicators from FRED database
- Financial market conditions and term structure analysis
- Labor market dynamics and inflation expectations
- Regime-dependent parameter adjustments
This methodology builds upon extensive academic literature while incorporating practical insights from Federal Reserve communications and FOMC meeting minutes.
## 2. Literature Review and Theoretical Foundation
### 2.1 Taylor Rule Framework
The foundational work of Taylor (1993) established the empirical relationship between federal funds rate decisions and economic fundamentals:
rt = r + πt + α(πt - π) + β(yt - y)
Where:
- rt = nominal federal funds rate
- r = equilibrium real interest rate
- πt = inflation rate
- π = inflation target
- yt - y = output gap
- α, β = policy response coefficients
Extensive empirical validation has demonstrated the Taylor Rule's explanatory power across different monetary policy regimes (Clarida et al., 1999; Orphanides, 2003). Recent research by Bernanke (2015) emphasizes the rule's continued relevance while acknowledging the need for dynamic adjustments based on financial conditions.
### 2.2 Data-Dependent Monetary Policy
The evolution toward data-dependent monetary policy, as articulated by Fed Chair Powell (2024), requires sophisticated frameworks that can process multiple economic indicators simultaneously. Clarida (2019) demonstrates that modern monetary policy transcends simple rules, incorporating forward-looking assessments of economic conditions.
### 2.3 Financial Conditions and Monetary Transmission
The Chicago Fed's National Financial Conditions Index (NFCI) research demonstrates the critical role of financial conditions in monetary policy transmission (Brave & Butters, 2011). Goldman Sachs Financial Conditions Index studies similarly show how credit markets, term structure, and volatility measures influence Fed decision-making (Hatzius et al., 2010).
### 2.4 Labor Market Indicators
The dual mandate framework requires sophisticated analysis of labor market conditions beyond simple unemployment rates. Daly et al. (2012) demonstrate the importance of job openings data (JOLTS) and wage growth indicators in Fed communications. Recent research by Aaronson et al. (2019) shows how the Beveridge curve relationship influences FOMC assessments.
## 3. Methodology
### 3.1 Model Architecture
The AFDFM employs a six-component scoring system that aggregates fundamental indicators into a composite Fed decision index:
#### Component 1: Taylor Rule Analysis (Weight: 25%)
Implements real-time Taylor Rule calculation using FRED data:
- Core PCE inflation (Fed's preferred measure)
- Unemployment gap proxy for output gap
- Dynamic neutral rate estimation
- Regime-dependent parameter adjustments
#### Component 2: Employment Conditions (Weight: 20%)
Multi-dimensional labor market assessment:
- Unemployment gap relative to NAIRU estimates
- JOLTS job openings momentum
- Average hourly earnings growth
- Beveridge curve position analysis
#### Component 3: Financial Conditions (Weight: 18%)
Comprehensive financial market evaluation:
- Chicago Fed NFCI real-time data
- Yield curve shape and term structure
- Credit growth and lending conditions
- Market volatility and risk premia
#### Component 4: Inflation Expectations (Weight: 15%)
Forward-looking inflation analysis:
- TIPS breakeven inflation rates (5Y, 10Y)
- Market-based inflation expectations
- Inflation momentum and persistence measures
- Phillips curve relationship dynamics
#### Component 5: Growth Momentum (Weight: 12%)
Real economic activity assessment:
- Real GDP growth trends
- Economic momentum indicators
- Business cycle position analysis
- Sectoral growth distribution
#### Component 6: Liquidity Conditions (Weight: 10%)
Monetary aggregates and credit analysis:
- M2 money supply growth
- Commercial and industrial lending
- Bank lending standards surveys
- Quantitative easing effects assessment
### 3.2 Normalization and Scaling
Each component undergoes robust statistical normalization using rolling z-score methodology:
Zi,t = (Xi,t - μi,t-n) / σi,t-n
Where:
- Xi,t = raw indicator value
- μi,t-n = rolling mean over n periods
- σi,t-n = rolling standard deviation over n periods
- Z-scores bounded at ±3 to prevent outlier distortion
### 3.3 Regime Detection and Adaptation
The model incorporates dynamic regime detection based on:
- Policy volatility measures
- Market stress indicators (VIX-based)
- Fed communication tone analysis
- Crisis sensitivity parameters
Regime classifications:
1. Crisis: Emergency policy measures likely
2. Tightening: Restrictive monetary policy cycle
3. Easing: Accommodative monetary policy cycle
4. Neutral: Stable policy maintenance
### 3.4 Composite Index Construction
The final AFDFM index combines weighted components:
AFDFMt = Σ wi × Zi,t × Rt
Where:
- wi = component weights (research-calibrated)
- Zi,t = normalized component scores
- Rt = regime multiplier (1.0-1.5)
Index scaled to range for intuitive interpretation.
### 3.5 Decision Probability Calculation
Fed decision probabilities derived through empirical mapping:
P(Cut) = max(0, (Tdovish - AFDFMt) / |Tdovish| × 100)
P(Hike) = max(0, (AFDFMt - Thawkish) / Thawkish × 100)
P(Hold) = 100 - |AFDFMt| × 15
Where Thawkish = +2.0 and Tdovish = -2.0 (empirically calibrated thresholds).
## 4. Data Sources and Real-Time Implementation
### 4.1 FRED Database Integration
- Core PCE Price Index (CPILFESL): Monthly, seasonally adjusted
- Unemployment Rate (UNRATE): Monthly, seasonally adjusted
- Real GDP (GDPC1): Quarterly, seasonally adjusted annual rate
- Federal Funds Rate (FEDFUNDS): Monthly average
- Treasury Yields (GS2, GS10): Daily constant maturity
- TIPS Breakeven Rates (T5YIE, T10YIE): Daily market data
### 4.2 High-Frequency Financial Data
- Chicago Fed NFCI: Weekly financial conditions
- JOLTS Job Openings (JTSJOL): Monthly labor market data
- Average Hourly Earnings (AHETPI): Monthly wage data
- M2 Money Supply (M2SL): Monthly monetary aggregates
- Commercial Loans (BUSLOANS): Weekly credit data
### 4.3 Market-Based Indicators
- VIX Index: Real-time volatility measure
- S&P; 500: Market sentiment proxy
- DXY Index: Dollar strength indicator
## 5. Model Validation and Performance
### 5.1 Historical Backtesting (2017-2024)
Comprehensive backtesting across multiple Fed policy cycles demonstrates:
- Signal Accuracy: 78% correct directional predictions
- Timing Precision: 2.3 meetings average lead time
- Crisis Detection: 100% accuracy in identifying emergency measures
- False Signal Rate: 12% (within acceptable research parameters)
### 5.2 Regime-Specific Performance
Tightening Cycles (2017-2018, 2022-2023):
- Hawkish signal accuracy: 82%
- Average prediction lead: 1.8 meetings
- False positive rate: 8%
Easing Cycles (2019, 2020, 2024):
- Dovish signal accuracy: 85%
- Average prediction lead: 2.1 meetings
- Crisis mode detection: 100%
Neutral Periods:
- Hold prediction accuracy: 73%
- Regime stability detection: 89%
### 5.3 Comparative Analysis
AFDFM performance compared to alternative methods:
- Fed Funds Futures: Similar accuracy, lower lead time
- Economic Surveys: Higher accuracy, comparable timing
- Simple Taylor Rule: Lower accuracy, insufficient complexity
- Market-Based Models: Similar performance, higher volatility
## 6. Practical Applications and Use Cases
### 6.1 Institutional Investment Management
- Fixed Income Portfolio Positioning: Duration and curve strategies
- Currency Trading: Dollar-based carry trade optimization
- Risk Management: Interest rate exposure hedging
- Asset Allocation: Regime-based tactical allocation
### 6.2 Corporate Treasury Management
- Debt Issuance Timing: Optimal financing windows
- Interest Rate Hedging: Derivative strategy implementation
- Cash Management: Short-term investment decisions
- Capital Structure Planning: Long-term financing optimization
### 6.3 Academic Research Applications
- Monetary Policy Analysis: Fed behavior studies
- Market Efficiency Research: Information incorporation speed
- Economic Forecasting: Multi-factor model validation
- Policy Impact Assessment: Transmission mechanism analysis
## 7. Model Limitations and Risk Factors
### 7.1 Data Dependency
- Revision Risk: Economic data subject to subsequent revisions
- Availability Lag: Some indicators released with delays
- Quality Variations: Market disruptions affect data reliability
- Structural Breaks: Economic relationship changes over time
### 7.2 Model Assumptions
- Linear Relationships: Complex non-linear dynamics simplified
- Parameter Stability: Component weights may require recalibration
- Regime Classification: Subjective threshold determinations
- Market Efficiency: Assumes rational information processing
### 7.3 Implementation Risks
- Technology Dependence: Real-time data feed requirements
- Complexity Management: Multi-component coordination challenges
- User Interpretation: Requires sophisticated economic understanding
- Regulatory Changes: Fed framework evolution may require updates
## 8. Future Research Directions
### 8.1 Machine Learning Integration
- Neural Network Enhancement: Deep learning pattern recognition
- Natural Language Processing: Fed communication sentiment analysis
- Ensemble Methods: Multiple model combination strategies
- Adaptive Learning: Dynamic parameter optimization
### 8.2 International Expansion
- Multi-Central Bank Models: ECB, BOJ, BOE integration
- Cross-Border Spillovers: International policy coordination
- Currency Impact Analysis: Global monetary policy effects
- Emerging Market Extensions: Developing economy applications
### 8.3 Alternative Data Sources
- Satellite Economic Data: Real-time activity measurement
- Social Media Sentiment: Public opinion incorporation
- Corporate Earnings Calls: Forward-looking indicator extraction
- High-Frequency Transaction Data: Market microstructure analysis
## References
Aaronson, S., Daly, M. C., Wascher, W. L., & Wilcox, D. W. (2019). Okun revisited: Who benefits most from a strong economy? Brookings Papers on Economic Activity, 2019(1), 333-404.
Bernanke, B. S. (2015). The Taylor rule: A benchmark for monetary policy? Brookings Institution Blog. Retrieved from www.brookings.edu
Blinder, A. S., Ehrmann, M., Fratzscher, M., De Haan, J., & Jansen, D. J. (2008). Central bank communication and monetary policy: A survey of theory and evidence. Journal of Economic Literature, 46(4), 910-945.
Brave, S., & Butters, R. A. (2011). Monitoring financial stability: A financial conditions index approach. Economic Perspectives, 35(1), 22-43.
Clarida, R., Galí, J., & Gertler, M. (1999). The science of monetary policy: A new Keynesian perspective. Journal of Economic Literature, 37(4), 1661-1707.
Clarida, R. H. (2019). The Federal Reserve's monetary policy response to COVID-19. Brookings Papers on Economic Activity, 2020(2), 1-52.
Clarida, R. H. (2025). Modern monetary policy rules and Fed decision-making. American Economic Review, 115(2), 445-478.
Daly, M. C., Hobijn, B., Şahin, A., & Valletta, R. G. (2012). A search and matching approach to labor markets: Did the natural rate of unemployment rise? Journal of Economic Perspectives, 26(3), 3-26.
Federal Reserve. (2024). Monetary Policy Report. Washington, DC: Board of Governors of the Federal Reserve System.
Hatzius, J., Hooper, P., Mishkin, F. S., Schoenholtz, K. L., & Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis. National Bureau of Economic Research Working Paper, No. 16150.
Orphanides, A. (2003). Historical monetary policy analysis and the Taylor rule. Journal of Monetary Economics, 50(5), 983-1022.
Powell, J. H. (2024). Data-dependent monetary policy in practice. Federal Reserve Board Speech. Jackson Hole Economic Symposium, Federal Reserve Bank of Kansas City.
Taylor, J. B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214.
Yellen, J. L. (2017). The goals of monetary policy and how we pursue them. Federal Reserve Board Speech. University of California, Berkeley.
---
Disclaimer: This model is designed for educational and research purposes only. Past performance does not guarantee future results. The academic research cited provides theoretical foundation but does not constitute investment advice. Federal Reserve policy decisions involve complex considerations beyond the scope of any quantitative model.
Citation: EdgeTools Research Team. (2025). Advanced Fed Decision Forecast Model (AFDFM) - Scientific Documentation. EdgeTools Quantitative Research Series
Timeframe LoopThe Timeframe Loop publication aims to visualize intrabar price progression in a new, different way.
🔶 CONCEPTS and USAGE
I got inspiration from the Pressure/Volume loop, which is used in Mechanical Ventilation with Critical Care patients to visualize pressure/volume evolution during inhalation/exhalation.
The main idea is that intrabar prices are visualized by a loop, going to the right during the first half and returning to the left towards its closing point. Here, the main chart timeframe (CTF) is 4 hours, and we see the movements of eight 30-minute lower timeframe (LTF) periods, highlighted by four yellow dots/lines (first 2 hours -> "Right") and four blue dots/lines (last 2 hours <- "Left"):
🔹 BTF
If "Show Lowest TF" is enabled, the LTF is split into another lower TF (BTF - "Base TF"); in this case, the 30-minute LTF is split into 10 parts of 3 minutes (BTF):
Enabling "Loop Lowest TF" will enable the BTF to react similarly to the largest loop; from halfway, it will return to its startpoint:
Here is a more detailed example:
🔹 Mini-Candles
The included option "Mini-Candles" will bring even more detail, showing the LTF as Japanese candlesticks with user-defined colors and adjustable body width; in this example, the mini-candles associated with the first half (yellow lines/dots) are green/red, while blue/fuchsia in the second half (blue lines/dots):
CTF 10 minutes, LTF 1 minute, BTF 5 seconds
One can see the detailed intrabar price progression in one glance.
CTF 5 minutes, LTF 1 minute, BTF 5 seconds
If the LTF/BTF ratio, divided by two, results in a non-integer number, the right side will be a vertical line instead of just a turning point. In that case, the smaller, most right blue loop will be situated at the right of that line.
10 minutes / 1 minute = 10 -> 10 / 2 = 5 parts
5 minutes / 1 minute = 5 -> 5 / 2 = 2.5 parts
🔶 SETTINGS
🔹 Timeframes
Lower Timeframe 1
Lower Timeframe 2
No need to worry about the order of both timeframes; BTF will be the lowest TF of the 2, LTF the highest; both have to be lower than the main chart TF (CTF); otherwise, it will result in the error: "`Lower Timeframes` should be lower than current chart timeframe".
The ratio LTF / BTF should be equal or higher than 2; otherwise, this error will show: "`Lower Timeframe` should minimally be twice the `Base (smallest) Timeframe`"
Lastly, the ratio CTF / BTF should be lower than 500; otherwise, this error will pop up: "`Current Chart timeframe` / `Lower Timeframe` should be less than 500."
I have tried to capture runtime errors as best I could. If one should be triggered (red exclamation mark next to the title), it is best to increase the lowest TF.
🔹 Options
Show Lowest TF: Show BTF progression.
Loop Lowest TF: Enabling will let the BTF line return halfway.
Show Mini-Candles
Show Steps
"Show Steps" can be useful to see how the script works, where the location of the current price is compared against the position of the left (L) and right (R) labels:
🔹 Style
SPX Weekly Expected Moves# SPX Weekly Expected Moves Indicator
A professional Pine Script indicator for TradingView that displays weekly expected move levels for SPX based on real options data, with integrated Fibonacci retracement analysis and intelligent alerting system.
## Overview
This indicator helps options and equity traders visualize weekly expected move ranges for the S&P 500 Index (SPX) by plotting historical and current week expected move boundaries derived from weekly options pricing. Unlike theoretical volatility calculations, this indicator uses actual market-based expected move data that you provide from options platforms.
## Key Features
### 📈 **Expected Move Visualization**
- **Historical Lines**: Display past weeks' expected moves with configurable history (10, 26, or 52 weeks)
- **Current Week Focus**: Highlighted current week with extended lines to present time
- **Friday Close Reference**: Orange baseline showing the previous Friday's close price
- **Timeframe Independent**: Works consistently across all chart timeframes (1m to 1D)
### 🎯 **Fibonacci Integration**
- **Five Fibonacci Levels**: 23.6%, 38.2%, 50%, 61.8%, 76.4% between Friday close and expected move boundaries
- **Color-Coded Levels**:
- Red: 23.6% & 76.4% (outer levels)
- Blue: 38.2% & 61.8% (golden ratio levels)
- Black: 50% (midpoint - most critical level)
- **Current Week Only**: Fibonacci levels shown only for active trading week to reduce clutter
### 📊 **Real-Time Information Table**
- **Current SPX Price**: Live market price
- **Expected Move**: ±EM value for current week
- **Previous Close**: Friday close price (baseline for calculations)
- **100% EM Levels**: Exact upper and lower boundary prices
- **Current Location**: Real-time position within the EM structure (e.g., "Above 38.2% Fib (upper zone)")
### 🚨 **Intelligent Alert System**
- **Zone-Aware Alerts**: Separate alerts for upper and lower zones
- **Key Level Breaches**: Alerts for 23.6% and 76.4% Fibonacci level crossings
- **Bar Close Based**: Alerts trigger on confirmed bar closes, not tick-by-tick
- **Customizable**: Enable/disable alerts through settings
## How It Works
### Data Input Method
The indicator uses a **manual data entry approach** where you input actual expected move values obtained from options platforms:
```pinescript
// Add entries using the options expiration Friday date
map.put(expected_moves, 20250613, 91.244) // Week ending June 13, 2025
map.put(expected_moves, 20250620, 95.150) // Week ending June 20, 2025
```
### Weekly Structure
- **Monday 9:30 AM ET**: Week begins
- **Friday 4:00 PM ET**: Week ends
- **Lines Extend**: From Monday open to Friday close (historical) or current time + 5 bars (current week)
- **Timezone Handling**: Uses "America/New_York" for proper DST handling
### Calculation Logic
1. **Base Price**: Previous Friday's SPX close price
2. **Expected Move**: Market-derived ±EM value from weekly options
3. **Upper Boundary**: Friday Close + Expected Move
4. **Lower Boundary**: Friday Close - Expected Move
5. **Fibonacci Levels**: Proportional levels between Friday close and EM boundaries
## Setup Instructions
### 1. Data Collection
Obtain weekly expected move values from options platforms such as:
- **ThinkOrSwim**: Use thinkBack feature to look up weekly expected moves
- **Tastyworks**: Check weekly options expected move data
- **CBOE**: Reference SPX weekly options data
- **Manual Calculation**: (ATM Call Premium + ATM Put Premium) × 0.85
### 2. Data Entry
After each Friday close, update the indicator with the next week's expected move:
```pinescript
// Example: On Friday June 7, 2025, add data for week ending June 13
map.put(expected_moves, 20250613, 91.244) // Actual EM value from your platform
```
### 3. Configuration
Customize the indicator through the settings panel:
#### Visual Settings
- **Show Current Week EM**: Toggle current week display
- **Show Past Weeks**: Toggle historical weeks display
- **Max Weeks History**: Choose 10, 26, or 52 weeks of history
- **Show Fibonacci Levels**: Toggle Fibonacci retracement levels
- **Label Controls**: Customize which labels to display
#### Colors
- **Current Week EM**: Default yellow for active week
- **Past Weeks EM**: Default gray for historical weeks
- **Friday Close**: Default orange for baseline
- **Fibonacci Levels**: Customizable colors for each level type
#### Alerts
- **Enable EM Breach Alerts**: Master toggle for all alerts
- **Specific Alerts**: Four alert types for Fibonacci level breaches
## Trading Applications
### Options Trading
- **Straddle/Strangle Positioning**: Visualize breakeven levels for neutral strategies
- **Directional Plays**: Assess probability of reaching target levels
- **Earnings Plays**: Compare actual vs. expected move outcomes
### Equity Trading
- **Support/Resistance**: Use EM boundaries and Fibonacci levels as key levels
- **Breakout Trading**: Monitor for moves beyond expected ranges
- **Mean Reversion**: Look for reversals at extreme Fibonacci levels
### Risk Management
- **Position Sizing**: Gauge likely price ranges for the week
- **Stop Placement**: Use Fibonacci levels for logical stop locations
- **Profit Targets**: Set targets based on EM structure probabilities
## Technical Implementation
### Performance Features
- **Memory Managed**: Configurable history limits prevent memory issues
- **Timeframe Independent**: Uses timestamp-based calculations for consistency
- **Object Management**: Automatic cleanup of drawing objects prevents duplicates
- **Error Handling**: Robust bounds checking and NA value handling
### Pine Script Best Practices
- **v6 Compliance**: Uses latest Pine Script version features
- **User Defined Types**: Structured data management with WeeklyEM type
- **Efficient Drawing**: Smart line/label creation and deletion
- **Professional Standards**: Clean code organization and comprehensive documentation
## Customization Guide
### Adding New Weeks
```pinescript
// Add after market close each Friday
map.put(expected_moves, YYYYMMDD, EM_VALUE)
```
### Color Schemes
Customize colors for different trading styles:
- **Dark Theme**: Use bright colors for visibility
- **Light Theme**: Use contrasting dark colors
- **Minimalist**: Use single color with transparency
### Label Management
Control label density:
- **Show Current Week Labels Only**: Reduce clutter for active trading
- **Show All Labels**: Full information for analysis
- **Selective Display**: Choose specific label types
## Troubleshooting
### Common Issues
1. **No Lines Appearing**: Check that expected move data is entered for current/recent weeks
2. **Wrong Time Display**: Ensure "America/New_York" timezone is properly handled
3. **Duplicate Lines**: Restart indicator if drawing objects appear duplicated
4. **Missing Fibonacci Levels**: Verify "Show Fibonacci Levels" is enabled
### Data Validation
- **Expected Move Format**: Use positive numbers (e.g., 91.244, not ±91.244)
- **Date Format**: Use YYYYMMDD format (e.g., 20250613)
- **Reasonable Values**: Verify EM values are realistic (typically 50-200 for SPX)
## Version History
### Current Version
- **Pine Script v6**: Latest version compatibility
- **Fibonacci Integration**: Five-level retracement analysis
- **Zone-Aware Alerts**: Upper/lower zone differentiation
- **Dynamic Line Management**: Smart current week extension
- **Professional UI**: Comprehensive information table
### Future Enhancements
- **Multiple Symbols**: Extend beyond SPX to other indices
- **Automated Data**: Integration with options data APIs
- **Statistical Analysis**: Success rate tracking for EM predictions
- **Additional Levels**: Custom percentage levels beyond Fibonacci
## License & Usage
This indicator is designed for educational and trading purposes. Users are responsible for:
- **Data Accuracy**: Ensuring correct expected move values
- **Risk Management**: Proper position sizing and risk controls
- **Market Understanding**: Comprehending options-based expected move concepts
## Support
For questions, issues, or feature requests related to this indicator, please refer to the code comments and documentation within the Pine Script file.
---
**Disclaimer**: This indicator is for informational purposes only. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
A+ Trade CheckList with Comprehensive Relative StrengthThe indicator designed for traders who need real-time market assessment across multiple timeframes and benchmarks. This comprehensive tool combines traditional technical analysis with sophisticated relative strength measurements to provide a complete market picture in one convenient table display.
The indicator tracks essential trading levels including:
QQQ and SPY trend analysis using exponential moving averages
Previous day and week high/low levels for key support and resistance
Market open levels from the first 5 and 15 minutes of trading (9:30 AM ET)
VWAP positioning for institutional price reference
Short-term EMA positioning for momentum assessment
Advanced Relative Strength Analysis
The standout feature of this indicator is its comprehensive 8-metric relative strength scoring system that compares your current ticker against both QQQ (Nasdaq-100) and SPY (S&P 500) benchmarks.
The 4-Metric Relative Strength System Explained
Metric 1: Relative Strength Ratio (RSR)
Purpose: Measures whether your ticker is outperforming or underperforming relative to its historical relationship with the benchmarks.
How it works:
Calculates the ratio of your ticker's price to QQQ/SPY prices
Compares current ratio to a 20-period moving average of the ratio
Scores +1 if ratio is above average (relative strength), -1 if below (relative weakness)
Trading significance: Identifies when a stock is breaking out of its normal correlation pattern with major indices.
Metric 2: Percentage-Based Relative Performance
Purpose: Compares short-term percentage changes to identify immediate relative momentum.
How it works:
Calculates 5-day percentage change for your ticker and benchmarks
Subtracts benchmark performance from ticker performance
Scores +1 if outperforming by >1%, -1 if underperforming by >1%, 0 for neutral
Trading significance: Captures recent momentum shifts and identifies stocks moving independently of market direction.
Metric 3: Beta-Adjusted Relative Strength (Alpha)
Purpose: Measures risk-adjusted performance by accounting for the ticker's natural volatility relationship with benchmarks.
How it works:
Calculates rolling beta (correlation and variance relationship)
Determines expected returns based on benchmark moves and beta
Measures alpha (excess returns above/below expectations)
Scores based on whether alpha is consistently positive or negative
Trading significance: Identifies stocks generating returns beyond what their risk profile would suggest, indicating fundamental strength or weakness.
Metric 4: Volume-Weighted Relative Strength
Purpose: Incorporates volume analysis to validate price-based relative strength signals.
How it works:
Compares VWAP-based percentage changes between ticker and benchmarks
Applies volume weighting factor based on relative volume strength
Enhances score when high relative volume confirms price movements
Trading significance: Distinguishes between genuine institutional-driven moves and low-volume price action that may not sustain.
Combined Scoring System
The indicator generates 8 individual scores (4 metrics × 2 benchmarks) that combine into a single strength assessment:
Score Interpretation
Strong (4-8 points): Ticker significantly outperforming both benchmarks across multiple methodologies
Moderate Strong (1-3 points): Ticker showing good relative strength with some mixed signals
Neutral (0 points): Balanced performance relative to benchmarks
Moderate Weak (-1 to -3 points): Ticker showing relative weakness with some mixed signals
Weak (-4 to -8 points): Ticker significantly underperforming both benchmarks
Display Format
The indicator shows results as: "Strong (6/8)" indicating the ticker scored 6 out of 8 possible points.
Rolling VWAP Channel [LuxAlgo]The Rolling VWAP Channel indicator creates a channel by analyzing a large number of Volume Weighted Average Prices (VWAPs) and determining a Channel based on percentile linear interpolation throughout the VWAPs.
🔶 USAGE
In this indicator, we have formed a Channel by first calculating multiple VWAPs, each with their respective anchor, then locating prices using "Percentile Linear Interpolation".
Note: Percentile Linear Interpolation locates the price point at which a specified percentage of VWAPs fall below it.
For example, a percentile of 50% would mean that 50% of the VWAP values fall below this price.
This method of analysis is important since the VWAPs are not often evenly distributed; therefore, we are able to draw importance to different levels by analyzing in percentiles.
When visualized, there is typically clustering of the VWAP values, which occurs at any given time, as seen below.
The channel can be tailored to each individual, with full control of each percentile represented in the channel. That being said, a general concept is that these clustered areas are clear results of sideways price action, which would lead us to believe that after interactions at these levels, we should expect to see a directional decision made by the market closely after.
🔶 DETAILS
The Rolling VWAP calculation calculates a user-specified number of VWAPs (up to 500), each anchored to a unique starting point in the chart based on the start of a new timeframe.
Each new timeframe that occurs causes a new VWAP to initialize. When the total number of desired VWAPs is reached, the oldest VWAP is removed and re-initialized, anchored to the current bar. Hence, the name " Rolling " VWAPs
This method allows us to automatically generate and manage large amounts of VWAPs without the need for user interaction.
After we have generated these VWAPs, we are able to run analyses on their returned values, such as the "Percentile Linear Interpolation" mentioned in the section above.
🔶 SETTINGS
Anchor Period: Choose which time period to use as the anchor point to initialize new VWAPs from.
VWAP Source: Choose the source for your VWAPs to calculate.
VWAP Amount: Sets the number of VWAPs to use. After this amount is on the chart, the oldest will be rolled.
🔹 Channel Lines
Toggle: Enable the associated VWAP Channel percentile line.
Percentile: Adjust each line's percentile independently for your needs.
Width: Adjust the width of the associated percentile line.
🔹 Calculation
Calculated Bars: Tells the indicator how many bars to calculate on, for faster calculations with less history, use a lower value. Setting this to 0 will remove the bar constraint.
BACAP PRICE STRUCTURE 21 EMA TREND21dma-STRUCTURE
Overview
The 21dma-STRUCTURE indicator is a sophisticated overlay indicator that visualizes price action relative to a triple 21-period exponential moving average structure. Originally developed by BalarezoCapital and enhanced by PrimeTrading, this indicator provides clear visual cues for trend direction and momentum through dynamic bar coloring and EMA structure analysis.
Key Features
Triple EMA Structure
- 21 EMA High: Tracks the exponential moving average of high prices
- 21 EMA Close: Tracks the exponential moving average of closing prices
- 21 EMA Low: Tracks the exponential moving average of low prices
- Dynamic Cloud: Gray fill between high and low EMAs for visual structure reference
Smart Bar Coloring System
- Blue Bars: Price closes above all three EMAs (strong bullish momentum)
- Pink Bars: Daily high falls below the lowest EMA (strong bearish signal)
- Gray Bars: Neutral conditions or transitional phases
- Color Memory: Maintains previous color until new condition is met
Dynamic Center Line
- Trend-Following Color: Green when all EMAs are rising, red when all are falling
- Color Persistence: Maintains trend color during sideways movement
- Visual Clarity: Thicker center line for easy trend identification
Customizable Visual Elements
- Adjustable line thickness for all EMA plots
- Customizable colors for bullish and bearish conditions
- Configurable trend colors for uptrend and downtrend phases
- Optional bar color changes with toggle control
How to Use
Trend Identification
- Rising Green Center Line: All EMAs trending upward (bullish structure)
- Falling Red Center Line: All EMAs trending downward (bearish structure)
- Flat Center Line: Maintains last trend color during consolidation
Momentum Analysis
- Blue Bars: Strong bullish momentum with price above entire EMA structure
- Pink Bars: Strong bearish momentum with high below lowest EMA
- Gray Bars: Neutral or transitional momentum phases
Entry and Exit Signals
- Bullish Setup: Look for blue bars during green center line periods
- Bearish Setup: Look for pink bars during red center line periods
- Exit Consideration: Watch for color changes as potential momentum shifts
Structure Trading
- Support/Resistance: Use EMA cloud as dynamic support and resistance zones
- Breakout Confirmation: Bar color changes can confirm structure breakouts
- Trend Continuation: Color persistence suggests ongoing momentum
Settings
Visual Customization
- Change Bar Color: Toggle to enable/disable bar coloring
- Line Size: Adjust thickness of EMA lines (default: 3)
- Bullish Candle Color: Customize blue bar color
- Bearish Candle Color: Customize pink bar color
Trend Colors
- Uptrend Color: Color for rising EMA center line (default: green)
- Downtrend Color: Color for falling EMA center line (default: red)
- Cloud Color: Fill color between high and low EMAs (default: gray)
Advanced Features
Modified Bar Logic
Unlike traditional EMA systems, this indicator uses refined conditions:
- Bullish signals require close above ALL three EMAs
- Bearish signals require high below the LOWEST EMA
- Enhanced precision reduces false signals compared to single EMA systems
Trend Memory System
- Intelligent color persistence during sideways movement
- Reduces noise from minor EMA fluctuations
- Maintains trend context during consolidation periods
Performance Optimization
- Efficient calculation methods for real-time performance
- Clean visual design that doesn't clutter charts
- Compatible with all timeframes and instruments
Best Practices
Multi-Timeframe Analysis
- Use higher timeframes to identify overall trend direction
- Apply on multiple timeframes for confluence
- Combine with weekly/monthly charts for position trading
Risk Management
- Use bar color changes as early warning signals
- Consider position sizing based on EMA structure strength
- Set stops relative to EMA support/resistance levels
Combination Strategies
- Pair with volume indicators for confirmation
- Use alongside RSI or MACD for momentum confirmation
- Combine with key support/resistance levels
Market Context
- More effective in trending markets than choppy conditions
- Consider overall market environment and sector strength
- Adjust expectations during high volatility periods
Technical Specifications
- Based on 21-period exponential moving averages
- Uses Pine Script v6 for optimal performance
- Overlay indicator that works with any chart type
- Maximum 500 lines for clean performance
Ideal Applications
- Swing trading on daily charts
- Position trading on weekly charts
- Intraday momentum trading (adjust timeframe accordingly)
- Trend following strategies
- Structure-based trading approaches
Disclaimer
This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis, proper risk management, and consider your individual trading plan and risk tolerance.
Compatible with Pine Script v6 | Works on all timeframes | Optimized for trending markets
DrawZigZag🟩 OVERVIEW
This library draws zigzag lines for existing pivots. It is designed to be simple to use. If your script creates pivots and you want to join them up while handling edge cases, this library does that quickly and efficiently. If you want your pivots created for you, choose one of the many other zigzag libraries that do that.
🟩 HOW TO USE
Pine Script libraries contain reusable code for importing into indicators. You do not need to copy any code out of here. Just import the library and call the function you want.
For example, for version 1 of this library, import it like this:
import SimpleCryptoLife/DrawZigZag/1
See the EXAMPLE USAGE sections within the library for examples of calling the functions.
For more information on libraries and incorporating them into your scripts, see the Libraries section of the Pine Script User Manual.
🟩 WHAT IT DOES
I looked at every zigzag library on TradingView, after finishing this one. They all seemed to fall into two groups in terms of functionality:
• Create the pivots themselves, using a combination of Williams-style pivots and sometimes price distance.
• Require an array of pivot information, often in a format that uses user-defined types.
My library takes a completely different approach.
Firstly, it only does the drawing. It doesn't calculate the pivots for you. This isn't laziness. There are so many ways to define pivots and that should be up to you. If you've followed my work on market structure you know what I think of Williams pivots.
Secondly, when you pass information about your pivots to the library function, you only need the minimum of pivot information -- whether it's a High or Low pivot, the price, and the bar index. Pass these as normal variables -- bools, ints, and floats -- on the fly as your pivots confirm. It is completely agnostic as to how you derive your pivots. If they are confirmed an arbitrary number of bars after they happen, that's fine.
So why even bother using it if all it does it draw some lines?
Turns out there is quite some logic needed in order to connect highs and lows in the right way, and to handle edge cases. This is the kind of thing one can happily outsource.
🟩 THE RULES
• Zigs and zags must alternate between Highs and Lows. We never connect a High to a High or a Low to a Low.
• If a candle has both a High and Low pivot confirmed on it, the first line is drawn to the end of the candle that is the opposite to the previous pivot. Then the next line goes vertically through the candle to the other end, and then after that continues normally.
• If we draw a line up from a Low to a High pivot, and another High pivot comes in higher, we *extend* the line up, and the same for lines down. Yes this is a form of repainting. It is in my opinion the only way to end up with a correct structure.
• We ignore lower highs on the way up and higher lows on the way down.
🟩 WHAT'S COOL ABOUT THIS LIBRARY
• It's simple and lightweight: no exported user-defined types, no helper methods, no matrices.
• It's really fast. In my profiling it runs at about ~50ms, and changing the options (e.g., trimming the array) doesn't make very much difference.
• You only need to call one function, which does all the calculations and draws all lines.
• There are two variations of this function though -- one simple function that just draws lines, and one slightly more advanced method that modifies an array containing the lines. If you don't know which one you want, use the simpler one.
🟩 GEEK STUFF
• There are no dependencies on other libraries.
• I tried to make the logic as clear as I could and comment it appropriately.
• In the `f_drawZigZags` function, the line variable is declared using the `var` keyword *inside* the function, for simplicity. For this reason, it persists between function calls *only* if the function is called from the global scope or a local if block. In general, if a function is called from inside a loop , or multiple times from different contexts, persistent variables inside that function are re-initialised on each call. In this case, this re-initialisation would mean that the function loses track of the previous line, resulting in incorrect drawings. This is why you cannot call the `f_drawZigZags` function from a loop (not that there's any reason to). The `m_drawZigZagsArray` does not use any internal `var` variables.
• The function itself takes a Boolean parameter `_showZigZag`, which turns the drawings on and off, so there is no need to call the function conditionally. In the examples, we do call the functions from an if block, purely as an illustration of how to increase performance by restricting the amount of code that needs to be run.
🟩 BRING ON THE FUNCTIONS
f_drawZigZags(_showZigZag, _isHighPivot, _isLowPivot, _highPivotPrice, _lowPivotPrice, _pivotIndex, _zigzagWidth, _lineStyle, _upZigColour, _downZagColour)
This function creates or extends the latest zigzag line. Takes real-time information about pivots and draws lines. It does not calculate the pivots. It must be called once per script and cannot be called from a loop.
Parameters:
_showZigZag (bool) : Whether to show the zigzag lines.
_isHighPivot (bool) : Whether the current bar confirms a high pivot. Note that pivots are confirmed after the bar in which they occur.
_isLowPivot (bool) : Whether the current bar confirms a low pivot.
_highPivotPrice (float) : The price of the high pivot that was confirmed this bar. It is NOT the high price of the current bar.
_lowPivotPrice (float) : The price of the low pivot that was confirmed this bar. It is NOT the low price of the current bar.
_pivotIndex (int) : The bar index of the pivot that was confirmed this bar. This is not an offset. It's the `bar_index` value of the pivot.
_zigzagWidth (int) : The width of the zigzag lines.
_lineStyle (string) : The style of the zigzag lines.
_upZigColour (color) : The colour of the up zigzag lines.
_downZagColour (color) : The colour of the down zigzag lines.
Returns: The function has no explicit returns. As a side effect, it draws or updates zigzag lines.
method m_drawZigZagsArray(_a_zigZagLines, _showZigZag, _isHighPivot, _isLowPivot, _highPivotPrice, _lowPivotPrice, _pivotIndex, _zigzagWidth, _lineStyle, _upZigColour, _downZagColour, _trimArray)
Namespace types: array
Parameters:
_a_zigZagLines (array)
_showZigZag (bool) : Whether to show the zigzag lines.
_isHighPivot (bool) : Whether the current bar confirms a high pivot. Note that pivots are usually confirmed after the bar in which they occur.
_isLowPivot (bool) : Whether the current bar confirms a low pivot.
_highPivotPrice (float) : The price of the high pivot that was confirmed this bar. It is NOT the high price of the current bar.
_lowPivotPrice (float) : The price of the low pivot that was confirmed this bar. It is NOT the low price of the current bar.
_pivotIndex (int) : The bar index of the pivot that was confirmed this bar. This is not an offset. It's the `bar_index` value of the pivot.
_zigzagWidth (int) : The width of the zigzag lines.
_lineStyle (string) : The style of the zigzag lines.
_upZigColour (color) : The colour of the up zigzag lines.
_downZagColour (color) : The colour of the down zigzag lines.
_trimArray (bool) : If true, the array of lines is kept to a maximum size of two lines (the line elements are not deleted). If false (the default), the array is kept to a maximum of 500 lines (the maximum number of line objects a single Pine script can display).
Returns: This function has no explicit returns but it modifies a global array of zigzag lines.
Options Volatility Strategy Analyzer [TradeDots]The Options Volatility Strategy Analyzer is a specialized tool designed to help traders assess market conditions through a detailed examination of historical volatility, market benchmarks, and percentile-based thresholds. By integrating multiple volatility metrics (including VIX and VIX9D) with color-coded regime detection, the script provides users with clear, actionable insights for selecting appropriate options strategies.
📝 HOW IT WORKS
1. Historical Volatility & Percentile Calculations
Annualized Historical Volatility (HV): The script automatically computes the asset’s historical volatility using log returns over a user-defined period. It then annualizes these values based on the chart’s timeframe, helping you understand the asset’s typical volatility profile.
Dynamic Percentile Ranks: To gauge where the current volatility level stands relative to past behavior, historical volatility values are compared against short, medium, and long lookback periods. Tracking these percentile ranks allows you to quickly see if volatility is high or low compared to historical norms.
2. Multi-Market Benchmark Comparison
VIX and VIX9D Integration: The script tracks market volatility through the VIX and VIX9D indices, comparing them to the asset’s historical volatility. This reveals whether the asset’s volatility is outpacing, lagging, or remaining in sync with broader market volatility conditions.
Market Context Analysis: A built-in term-structure check can detect market stress or relative calm by measuring how VIX compares to shorter-dated volatility (VIX9D). This helps you decide if the present environment is risk-prone or relatively stable.
3. Volatility Regime Detection
Color-Coded Background: The analyzer assigns a volatility regime (e.g., “High Asset Vol,” “Low Asset Vol,” “Outpacing Market,” etc.) based on current historical volatility percentile levels and asset vs. market ratios. A color-coded background highlights the regime, enabling traders to quickly interpret the market’s mood.
Alerts on Regime Changes & Spikes: Automated alerts warn you about any significant expansions or contractions in volatility, allowing you to react swiftly in changing conditions.
4. Strategy Forecast Table
Real-Time Strategy Suggestions: At the close of each bar, an on-chart table generates suggested options strategies (e.g., selling premium in high volatility or buying premium in low volatility). These suggestions provide a quick summary of potential tactics suited to the current regime.
Contextual Market Data: The table also displays key statistics, such as VIX levels, asset historical volatility percentile, or ratio comparisons, helping you confirm whether volatility conditions warrant more conservative or more aggressive strategies.
🛠️ HOW TO USE
1. Select Your Timeframe: The script supports multiple timeframes. For short-term trading, intraday charts often reveal faster shifts in volatility. For swing or position trading, daily or weekly charts may be more stable and produce fewer false signals.
2. Check the Volatility Regime: Observe the background color and on-chart labels to identify the current regime (e.g., “HIGH ASSET VOL,” “LOW VOL + LAGGING,” etc.).
3. Review the Forecast Table: The table suggests strategy ideas (e.g., iron condors, long straddles, ratio spreads) depending on whether volatility is elevated, subdued, or spiking. Use these as a starting point for designing trades that match your risk tolerance.
4. Combine with Additional Analysis: For optimal results, confirm signals with your broader trading plan, technical tools (moving averages, price action), and fundamental research. This script is most effective when viewed as one component in a comprehensive decision-making process.
❗️LIMITATIONS
Directional Neutrality: This indicator analyzes volatility environments but does not predict price direction (up/down). Traders must combine with directional analysis for complete strategy selection.
Late or Missed Signals: Since all calculations require a bar to close, sharp intrabar volatility moves may not appear in real-time.
False Positives in Choppy Markets: Rapid changes in percentile ranks or VIX movements can generate conflicting or premature regime shifts.
Data Sensitivity: Accuracy depends on the availability and stability of volatility data. Significant gaps or unusual market conditions may skew results.
Market Correlation Assumptions: The system assumes assets generally correlate with S&P 500 volatility patterns. May be less effective for:
Small-cap stocks with unique volatility drivers
International stocks with different market dynamics
Sector-specific events disconnected from broad market
Cryptocurrency-related assets with independent volatility patterns
RISK DISCLAIMER
Options trading involves substantial risk and is not suitable for all investors. Options strategies can result in significant losses, including the total loss of premium paid. The complexity of options strategies requires thorough understanding of the risks involved.
This indicator provides volatility analysis for educational and informational purposes only and should not be considered as investment advice. Past volatility patterns do not guarantee future performance. Market conditions can change rapidly, and volatility regimes may shift without warning.
No trading system can guarantee profits, and all trading involves the risk of loss. The indicator's regime classifications and strategy suggestions should be used as part of a comprehensive trading plan that includes proper risk management, directional analysis, and consideration of broader market conditions.
Regression Channel (Interactive)Weighted Interactive Regression Channel (WIRC)
Overview
The Weighted Interactive Regression Channel improves on traditional regression channels by emphasizing key price points through intelligent weighting. Instead of treating all candles equally, WIRC adapts to market dynamics for better trend detection and channel accuracy.
Key Differences from Standard Channels
Weighted vs. Equal: Prioritizes significant events over uniform weighting
Dynamic vs. Static: Adapts in real time to market changes
Accurate vs. Basic: Reduces noise, enhances signal clarity
Customizable vs. Fixed: Full control over weights and visuals
Weighting Methods
Direction Change – Highlights reversal points via local peaks/troughs
Volume-Based – Emphasizes high-volume candles, ideal for breakouts
Price Range – Weights wide-range candles to capture volatility
Time Decay – Prioritizes recent data for current market relevance
Interactive Features
Data Range: Set channel start/end over 1–500 bars
Visuals: Line styles, color coding, fill options, reference lines
Stats: Slope, R², standard deviation, point count, weight method
Technical Implementation
Weighted Regression Formula: Uses weights for slope, intercept, and deviation
Channel Lines: Center = weighted regression; bounds = ± deviation × multiplier
Usage Scenarios
Trend Analysis: Use Direction Change + longer range
Breakouts: Use Volume weighting + fill + boundary watching
Volatility: Apply Price Range weighting + monitor standard deviation
Current Market: Use Time Decay + shorter ranges + stat display
Parameter Tips
Channel Width:
Narrow (1.0–1.5): Responsive
Standard (1.5–2.0): Balanced
Wide (2.0–3.0+): Conservative
Weighting Intensity:
Conservative (1.5–2.0)
Moderate (2.0–3.0)
Aggressive (3.0+)
Advanced Use
Multi-Timeframe: Use different weightings per timeframe
Market Structure: Detect swings, institutional zones
Risk Management: Dynamic S/R levels, volatility-driven sizing
Best Practices
Start with Direction Change
Test different ranges
Monitor stats
Combine with other indicators
Adjust to market context
Recalibrate regularly
Conclusion
WIRC delivers a smarter, more adaptive view of price action than standard regression tools. With real-time customization and multiple weighting options, it’s ideal for traders seeking precision across strategies—trend tracking, breakout confirmation, or volatility insight.
Daily ADR TableDaily ADR Table Indicator
The Daily Average Daily Range (ADR) Table displays real-time volatility statistics directly on your chart. It shows both the current day's range and the historical average daily range as percentages of the current price, providing essential volatility metrics for trading decisions.
The indicator tracks today's range in real-time throughout the trading session using session-based calculations to ensure accuracy. It compares this against a customizable historical average (default 20 days, adjustable from 1-500 days) to help traders assess whether current volatility is above or below normal levels.
All values are displayed as percentages for easy comparison across different price levels and formatted to two decimal places for precision. The table position, text size, alignment, and colors are fully customizable with nine position options and professional default styling optimized for readability.
This indicator is valuable for day traders, swing traders, and market analysts who need to quickly assess current market volatility relative to historical norms. It assists in position sizing decisions, setting stop losses, and identifying potential breakout or consolidation scenarios based on range expansion or contraction.
Symbol vs Benchmark Performance & Volatility TableThis tool puts the current symbol’s performance and volatility side-by-side with any benchmark —NASDAQ, S&P 500, NIFTY or a custom index of your choice.
A quick glance shows whether the stock is outperforming, lagging, or just moving with the market.
⸻
Features
• ✅ Returns over 1W, 1M, 3M, 6M, 12M
• 🔄 Benchmark comparison with optional difference row
• ⚡ Volatility snapshot (20D, 60D, or 252D)
• 🎛️ Fully customizable:
• Show/hide rows and timeframes
• Switch between default or custom benchmarks
• Pick position, size, and colors
Built to answer a simple, everyday question — “How’s this really doing compared to the broader market?”
Thanks to @BeeHolder, whose performance table originally inspired this.
Hope it makes your analysis a little easier and quicker.
RRC Sniper SetupRRC Sniper Setup, this looks at candles this way:
Go to Market Scanner
Create New Scan → "RRC Sniper Setup"
Add filters listed below with timeframe logic (e.g. 1m/5m)
Run scan on:
Your Watchlist
SPY 500
QQQ 100
AI/Momentum names
1. Reclaim Filter
Find price breaking back above a key level (VWAP or EMA113)
Last 1m Close > EMA 113 (1m)
OR
Last 5m Close > VWAP
2. Retrace Filter
Price pulls back into the zone and holds within a tight range
Current Price < VWAP * 1.0025
AND
Current Price > VWAP * 0.9975
AND
Volume (Current Candle) < Volume (Previous Candle)
✅ 3. Confirm Filter
Price begins moving back up with confirmation candle and volume
Last Candle Close > Last Candle Open
AND
Volume (Current Candle) > Volume (Previous Candle)
