Adjustable Price Line Size with Countdown Timer (Larger)Adjustable Size and Color for the Price Line and Timer so I Can See it Better From Across the Room...
Adjustments include: Price Line Width Size and Color (Small, Normal, Large, Huge)
Adjustment for: Solid Line, Dashed or Dotted Line
Countdown Timer: ON/OFF
I Can Now See The Price and Price Line From Across the Room!!
Penunjuk dan strategi
MACD Histogram Expansion Alerts (Scalp)Purpose: Alerts when MACD histogram is expanding (momentum increasing) rather than simply crossing. Designed for 1-minute scalping and intraday momentum confirmation.
This script is for traders who are tired of late MACD cross alerts.
Instead of firing when MACD lines cross (which often happens after the move), this indicator alerts when the MACD histogram is expanding — meaning momentum is actually increasing right now, not rolling over.
I use it as a “heads up” alert, not a buy/sell signal. When it fires, I check price action, volume, VWAP, support/resistance, etc., to see if the move is worth trading.
Best suited for 1-minute charts, scalping, and fast intraday momentum.
MACD Histogram Expansion Alerts (Scalp) is a lightweight alert-focused indicator designed for intraday traders and scalpers, particularly on lower timeframes such as the 1-minute chart.
Rather than triggering alerts on standard MACD line crossovers (which tend to lag in fast or volatile markets), this script detects MACD histogram expansion — a condition that indicates momentum acceleration, not just direction.
🔍 What this script does
Uses a fast MACD configuration suitable for lower timeframes
Monitors the MACD histogram slope and magnitude
Triggers alerts only when the histogram expands for multiple consecutive bars
Alerts are fired on bar close only, reducing noise and false intrabar signals
🚀 Why focus on histogram expansion?
Histogram expansion highlights when momentum is building, which can be useful for:
Continuation setups
Early momentum confirmation
Avoiding entries when momentum is already fading
This approach is especially helpful in small caps, news-driven stocks, and volatile intraday instruments, where traditional MACD cross alerts can arrive too late.
🔔 Alert Types
Bullish MACD Histogram Expansion
Bearish MACD Histogram Expansion
Each alert can be enabled independently and is intended as an attention signal, not a standalone trading system.
⚙️ Customizable Inputs
MACD Fast / Slow / Signal lengths
Number of consecutive expanding histogram bars required
Optional minimum histogram magnitude filter
Optional directional filter (above/below zero line)
⚠️ Important Notes!!!!
This script does not place trades
Alerts should be used with additional context, such as price action, volume, VWAP, or support/resistance
Not designed for higher-timeframe or swing trading use .
If you find this helpful, feel free to adapt it to your own trading style or timeframe. This script is meant to be simple, flexible, and non-opinionated.
Minervini Ultimate +VCPMinervini Ultimate Suite (SEPA Dashboard)
This indicator implements Mark Minervini's "Trend Template" criteria combined with a Volatility Contraction Pattern (VCP) detector and a custom Relative Strength rating. It is designed to help traders visualize the technical health of a stock based on stage analysis concepts.
This indicator serves as a complete Control System (Dashboard) for Mark Minervini's SEPA trading strategy. Instead of manually checking five different metrics on every chart, this indicator performs the mathematical calculations and presents the "bottom line" in a single, organized table.
1. What This Indicator Does
The goal is to ensure you never enter a trade blindly. It verifies the stock against Minervini's strict requirements:
Trend: Is the stock in a healthy Stage 2 Uptrend?
Relative Strength: Is it stronger than the general market?
Buy Risk: Is it the right time to buy, or is the price extended?
Pressure: Are institutions accumulating or distributing?
VCP: Is there a breakout opportunity (volatility contraction) right now?
2. Key Benefits
Time-Saving: Instead of drawing lines and calculating percentages manually, you get immediate visual feedback (Green/Red).
Discipline: The indicator will flag "Extended" (Red) if you attempt to buy a stock that has run up too much, saving you from late entries and unnecessary losses.
Precision Timing: The VCP feature (Blue Dots) helps you identify the "calm before the storm"—the exact moment volatility contracts, which often precedes a major breakout.
3. Indicator Parameters & Features
A. Minervini Pressure (Buying vs. Selling)
What it checks: Money flow over the last 20 days.
Calculation: Sums up volume on "Up Days" (Green) versus volume on "Down Days" (Red).
Meaning:
🟢 Buying: More money is entering than leaving. A sign of institutional accumulation.
🔴 Selling: Selling pressure dominates. The price may be rising, but without strong volume backing.
B. Buy Risk (Price Extension)
What it checks: The distance of the current price from the 50-Day Moving Average. Minervini strictly warns against "chasing" stocks.
Signals:
🟢 Low Risk: Price is within 0% – 15% of the 50MA. This is the ideal "Buy Zone".
🟡 Caution: Price is 15% – 25% away. Buy with increased caution.
🔴 Extended: Price is >25% from the MA. Do not buy. The probability of a pullback is high.
⚪ Broken: Price is below the 50MA. The short-term trend is damaged.
C. TPR - Trend Template (Trend Power Rating)
What it checks: Is the stock in a Stage 2 Uptrend?
Strict Rules (All must be true for a PASS):
Price > 50MA > 150MA > 200MA.
The 200MA is trending UP (positive slope).
Price is near the 52-Week High (within 25%).
Price is above the 52-Week Low (at least 25%).
Meaning:
🟢 PASSED: Technically healthy and ready to move.
🔴 FAILED: The trend structure is broken (e.g., MAs are entangled).
D. RPR Score (Relative Performance Rating)
What it checks: How strong the stock is compared to the general market (S&P 500 / SPY).
Calculation: Weighted performance over 3, 6, 9, and 12 months vs. the SPY. The score ranges from 1 to 99.
Meaning:
🟢 80-99: Market Leader. These are the stocks Minervini targets.
🟡 70-80: Good, but not elite.
⚪ Below 70: Laggard (weaker than the market).
E. VCP Action (Volatility Contraction Pattern)
What it checks: Monitors price tightness. It calculates the range between the highest close and lowest close over the last 5 days.
Meaning:
🔵 SQUEEZE (Blue Text + Blue Dot on Chart): The price range has contracted to less than 2.5%.
Why it matters: When a stock stops moving wildly and trades in a tight range ("Flat Line"), it indicates supply has dried up. A high-volume breakout often follows immediately.
Momentum Pro (Tuned v6)Momentum Pro (Tuned v6) is an intraday momentum strategy designed to capture high-quality continuation moves while aggressively filtering out chop and low-participation setups. It combines trend alignment, volume confirmation, momentum strength, and volatility-based risk control into a single rules-driven system.
The strategy is optimized for 1–5 minute charts on liquid stocks and ETFs and is intended for short-term trading, not mean reversion or scalping.
Momentum Pro requires price to be above session VWAP and EMA(8) to be above EMA(18), ensuring trades align with the dominant intraday trend. Momentum quality is confirmed using the MACD histogram and an RSI entry band that favors strength without chasing overextended moves. Relative Volume must exceed a strict threshold to ensure real participation, and ADX is used to avoid low-trend, choppy conditions.
Entries occur only on confirmed breakouts above recent highs, reducing false signals during consolidation. Risk is managed using an ATR-based stop that adapts to volatility, paired with a fixed reward-to-risk profit target to enforce positive expectancy. Optional early exits are included to protect profits if momentum fades or price loses VWAP.
This strategy is not predictive and does not attempt to call tops or bottoms. It is designed to trade only when multiple conditions align, favoring fewer, higher-quality trades over frequency. It works best when used with a higher-timeframe market bias and strict risk discipline.
NQ Scalp EMA Reclaim EMA Momentum Pullback Indicator
What it does (typical EMA method used for momentum trading):
Trend filter: Fast EMA above Slow EMA = bullish bias; below = bearish bias
Entry: In bullish bias, wait for a pullback to the EMA “zone”, then a reclaim candle → BUY
In bearish bias, pullback into zone then rejection → SELL
Optional 200 EMA filter (only take longs above 200, shorts below 200)
Bullish Engulfing at Daily Support (Pivot Low) - R Target (v6)1. What this strategy really is (in human terms)
This strategy is not about predicting the market.
It’s about waiting for proof that buyers are stepping in at a price where they already should.
Think of it like this:
“I only buy when price falls into a known ‘floor’ and buyers visibly take control.”
That’s it.
Everything in the script enforces that idea.
2. The two ingredients (nothing else)
Ingredient #1: Daily Support (the location)
Support is an area where price previously fell and then reversed upward.
In the script:
Support is defined as the most recent confirmed daily swing low
A swing low means:
Price went down
Stopped
Then went up enough to prove that buyers defended that level
This matters because:
You’re not guessing where support might be
You’re using a level where buyers already proved themselves
“At support” doesn’t mean exact
Markets don’t bounce off perfect lines.
So the script allows a small zone (the “support tolerance”):
Example: 0.5% tolerance
If support is at 100
Anywhere between ~99.5–100.5 counts
This prevents missing good trades just because price was off by a few ticks.
Ingredient #2: Bullish Engulfing Candle (the trigger)
This is the confirmation.
A bullish engulfing candle means:
Sellers were in control
Buyers stepped in hard enough to fully overpower them
The bullish candle’s body “swallows” the previous candle
Psychologically, it says:
“Sellers tried, failed, and buyers just took control.”
That’s why this candle works only at support.
A bullish engulfing in the middle of nowhere means nothing.
3. Why daily timeframe matters
The daily chart:
Filters out noise
Reflects decisions made by institutions, not random scalpers
Produces fewer but higher-quality signals
That’s why:
The script uses daily data
You typically get very few trades per month
Most days: no trade
That “boredom” is the edge.
4. When a trade is taken (exact conditions)
A trade happens only if ALL are true:
Price drops into a recent daily support zone
A bullish engulfing candle forms on the daily chart
Risk is clearly defined (entry, stop, target)
If any one is missing → no trade
5. How risk is controlled (this is crucial)
The stop loss (where you admit you’re wrong)
The stop is placed:
Below the support level
Or below the low of the engulfing candle
With a small ATR buffer so normal noise doesn’t stop you out
Meaning:
“If price breaks below this area, buyers were wrong. I’m out.”
No hoping. No moving stops. No exceptions.
Position sizing (why this strategy survives losing streaks)
Each trade risks a fixed % of your account (default 1%).
So:
Big stop = smaller position
Small stop = larger position
This keeps every trade equal in risk, not equal in size.
That’s professional behavior.
6. The take-profit logic (why 2.8R matters)
Instead of guessing targets:
The strategy uses a multiple of risk (R)
Example:
Risk = $1
Target = $2.80
You can lose many times and still come out ahead.
This is why:
Win rate ≈ 60% is more than enough
Even 40–45% could still work if discipline is perfect
7. Why patience is the real edge (not the pattern)
The bullish engulfing is common.
Bullish engulfing at daily support is rare.
Most people fail because they:
Trade engulfings everywhere
Ignore location
Lower standards when bored
Add “just one more indicator”
Your edge is:
Saying no 95% of the time
Taking only trades that look obvious after they work
8. How to use this strategy effectively (rules to follow)
Rule 1: Only take “clean” setups
Skip trades when:
Support is messy or unclear
Price is chopping sideways
The engulfing candle is tiny
The market is news-chaotic (earnings, FOMC, etc.)
If you have to convince yourself, skip it.
Rule 2: One trade at a time
This strategy works best when:
You’re not stacked in multiple correlated trades
You treat each setup like it matters
Quality > quantity.
Rule 3: Journal screenshots, not just numbers
After each trade, save:
Daily chart screenshot
Support level marked
Entry / stop / target
After 50–100 trades, patterns jump out:
Best tolerance %
Best stop buffer
Markets that behave well vs poorly
That’s how the original trader refined it.
Rule 4: Expect boredom and drawdowns
You will have:
Weeks with zero trades
Clusters of losses
Long flat periods
That’s normal.
If you “fix” it by adding more trades:
You destroy the edge.
9. Who this strategy is perfect for
This fits you if:
You don’t want screen addiction
You prefer process over excitement
You’re okay being wrong often
You want something you can execute for years
It is not for:
Scalpers
Indicator collectors
People who need action every day
10. The mindset shift (the real lesson of that story)
The money didn’t come from bullish engulfings.
It came from:
Defining one repeatable behavior
Removing everything else
Trusting math + patience
Doing nothing most of the time
If you want, next we can:
Walk through real example trades bar-by-bar
Optimize settings for a specific market you trade
Add filters that increase quality without adding complexity
BBQ Levels - Options Spread Diversification GridOverview
BBQ Levels (also known as "The Grill") is a price-level tracking indicator designed for options traders who use iron condors, put credit spreads, or other spread strategies. It divides the price chart into horizontal zones and tracks which "level" the market currently occupies, helping traders diversify their positions across different price ranges rather than concentrating risk at a single strike.
The indicator uses a playful Star Wars naming convention: upward-trending levels are called "Jedi Levels" (JL) and downward-trending levels are called "Sith Levels" (SL). This terminology originated from a trading mentor who found it easier to remember than directional abbreviations.
How It Works
Level Grid System
The indicator creates a grid of horizontal price levels based on your chosen spacing (default: 10 points). Each level represents a price zone where you might consider placing a spread trade.
Trend State Tracking
The indicator operates in one of two modes:
Jedi Mode (Bullish): When price is advancing upward through levels. Each time price breaks above the current level's top boundary, the indicator advances to the next Jedi Level (JL1 to JL2 to JL3, etc.).
Sith Mode (Bearish): When price is declining through levels. Each time price breaks below the current level's bottom boundary, the indicator advances to the next Sith Level (SL1 to SL2 to SL3, etc.).
Level Transitions
Transitions between modes occur when price reverses and touches the opposing level boundary. The indicator uses high/low touches (not closes) to determine level breaks, providing faster signals.
Trade Visualization Boxes
You can overlay up to 10 colored rectangles representing your actual options positions. Each box shows:
- Opening date (when you entered the trade)
- Expiration date (when the options expire)
- Upper and lower strikes (defining your spread's range)
- Custom label (e.g., "Jan IC" or "Feb Put Spread")
This lets you see at a glance which price zones you have covered and where gaps exist in your "grill."
Practical Application
Vertical Diversification Strategy
The core idea is to diversify iron condors across multiple price levels rather than placing all trades at the current market price:
When market reaches extended Jedi Levels (JL3 or higher): Consider reducing delta on new put credit spreads, as the market may be overextended to the upside.
When market reaches extended Sith Levels (SL3 or higher): Consider increasing delta on new positions, anticipating potential mean reversion.
Coverage Visualization
By drawing boxes for your active positions, you can see which price ranges are "protected" by existing spreads and identify gaps where additional positions might provide better coverage.
Settings Guide
Main Settings
Level Spacing - Distance between horizontal levels in price points. Default is 10. For SPY, 10 points creates meaningful zones; for SPX, consider 50-100 points.
Trade Boxes (1-10)
Each trade slot has these settings:
Show Trade - Toggle visibility of this position box
Label - Custom name for the trade (e.g., "Jan 17 IC")
Opening Date - When you entered the position
Expiration Date - Options expiration date
Upper Strike - Top of your spread range
Lower Strike - Bottom of your spread range
Visual Elements
Green labels (JL1, JL2...) - Mark upward level progressions
Red labels (SL1, SL2...) - Mark downward level progressions
Blue labels - Mark trend reversal points (JL1 after Sith mode, SL1 after Jedi mode)
Dashed blue grid lines - Show level boundaries extending into the future
Colored boxes - Your configured trade positions
Status table (top right) - Current price, level, and trend direction
What Makes This Different
Unlike standard support/resistance indicators, BBQ Levels is specifically designed for options spread traders. It provides:
A systematic framework for diversifying positions across price levels
Visual overlay of actual trade positions against the level grid
State-based tracking that distinguishes between bullish and bearish market phases
Actionable context for adjusting spread deltas based on market extension
Best Used On
SPY, SPX, or other index products where you trade iron condors
Daily or 4-hour timeframes for position planning
Lower timeframes (1H, 15m) for timing entries within levels
Limitations
This indicator does not predict price direction - it only tracks which level price currently occupies
The level spacing is fixed and does not adapt to volatility
Trade boxes are manual inputs - you must update them as you open/close positions
Level progression rules may generate frequent signals during choppy, range-bound markets
This is a visualization and organizational tool, not a trading signal generator
Disclaimer
This indicator is for educational and organizational purposes only. It does not constitute financial advice and should not be used as the sole basis for trading decisions.
Options trading involves substantial risk and is not suitable for all investors
Past performance does not guarantee future results
Iron condors and credit spreads have defined risk but can still result in significant losses
Always conduct your own research and consider consulting a financial professional
The author is not responsible for any trading losses incurred using this tool
Version History
v1.0 - Initial release with level tracking
v1.1 - Bug fix: levels now update on touch, not close
v1.2 - Added trade visualization boxes (up to 10 positions)
v1.3 - Fixed expiration date rendering for trade boxes
SMA Indicator Signals [MK]Overview
The SMA Indicator Signals indicator is designed to identify high-probability trend-following entries using a dual SMA system and RSI filtering. Unlike traditional crossover indicators that rely on ta.crossover (which often fails during volatile market gaps), this script uses state-based logic to capture signals even when the price "jumps" over the moving average.
The "Gap-Over" Problem Solved
In fast-moving markets or at market open, price often gaps significantly. If the price opens above the SMA 20 after being below it, a standard indicator usually misses the signal because no "physical" cross occurred on the chart.
This indicator compares the current state to the previous state. If the price is now above the SMA while previously being below, the signal triggers regardless of the gap.
Key Features
Persistent Signals: Unlike strategies that hide signals while a trade is active, this indicator plots an icon for every valid occurrence, allowing you to scale into positions or identify secondary entries.
Trend-Filtered: Long signals only appear when the 20 SMA is above the 50 SMA (and vice-versa for shorts).
RSI Guardrail: Built-in RSI logic prevents you from chasing "Longs" into overbought territory or "Shorts" into oversold conditions.
Universal Alerts: Includes pre-configured alertcondition calls for Longs, Shorts, or both.
How to Trade it
The Signal: Look for the Green (Long) or Red (Short) triangles.
User Discretion: Since this version removes automated ADX/Expansion filters, the trader should look at the "width" of the gap between the Blue (20) and Orange (50) SMAs. Wider gaps usually indicate stronger momentum.
Alerts: Create an alert and select "Any SSMA Signal" to be notified on your phone or desktop the moment a setup forms.
Settings
Fast SMA (20): Your primary trigger line.
Slow SMA (50): Your primary trend filter.
RSI Thresholds: Customize how "early" or "late" you want to be filtered out of a move based on momentum.
Adaptive Quant RSI [ML + MTF]This is an advanced momentum indicator that integrates Machine Learning (K-Means Clustering) with Multi-Timeframe (MTF) analysis. Unlike traditional RSI which uses fixed 70/30 levels, this script dynamically calculates support and resistance zones based on real-time historical data distribution.
Key Features:
🤖 ML Dynamic Thresholds: Uses K-Means clustering to segment RSI data into clusters, automatically plotting dynamic long/short thresholds that adapt to market volatility.
⏳ MTF Trend Background: The background color changes based on a Higher Timeframe (e.g., 5-min) RSI trend, helping you align with the broader market direction.
📊 Extreme Statistics: Incorporates percentile analysis (95th/5th) and historical pivots to identify extreme overbought/oversold conditions with high reversal probability.
📈 Probability Analysis: Displays the statistical probability of the current RSI value being at the top or bottom of its historical range.
Usage: Look for confluence between the dynamic ML thresholds and the MTF background color to identify high-probability reversal setups.
Pasha Chat by Mike. 3 candle box)Quick indicator for Pasha chat member wanting to test a system that has 3 same colour candles, looking for continuation. Self explanatory. Will only show first 3 same colour candles in any leg. For bull and bear sequence
Intuitive Predictive MACD TargetsThis indicator uses Reverse Engineering math to calculate the exact price the market needs to reach for specific MACD events to happen on the current bar.
Standard MACD is a lagging indicator—you usually wait for the candle to close to confirm a signal. This script changes that by drawing "Finish Lines" on your chart, showing you exactly where price must go right now to trigger a Crossover or a Momentum Hook.
The "Reverse Engineering" Concept
Instead of calculating MACD from Price, we calculate the Required Price from the Target MACD.
Q: "At what price will the MACD line cross the Signal line?"
A: The script solves this and draws the Green/Red "Crossover" Line.
Key Features
1. Three Distinct Targets
Crossover Target (PCO/NCO): The exact price needed to trigger a Buy/Sell signal on the current candle.
Dynamic Coloring: Turns Green if price needs to go UP to cross, Red if price needs to go DOWN.
Settlement Target (The Hook): The exact price where the MACD momentum flattens out (Angle = 0). If price touches this Orange Dashed Line, the trend is likely pausing or preparing to reverse.
Zero Cross Target: The price needed for MACD to reclaim the Zero Line.
2. Smart "Staggered" Labels (No Overlap)
Unlike other scripts where text piles up and becomes unreadable, this indicator automatically spreads labels horizontally.
Crossover info stays near the price.
Settlement info is shifted to the right.
Zero info is shifted further right.
Result: You can read all three targets clearly, even if the prices are almost identical.
3. Full Customization
Line Length: Choose "Infinite" to see targets as Support/Resistance levels across the screen, or "Short" to keep your chart background clean.
Text Visibility: Option to force text to White or Black for high contrast on Dark/Light themes.
Styles: Fully adjustable colors, line widths, and styles (Solid, Dashed, Dotted) for each target type.
How to Use
The "Finish Line" Strategy: If you are Long, and the Red NCO Line appears just below the current price, be cautious. It means a very small drop will confirm a Bearish Cross.
Momentum Checks: Watch the Orange "Settlement" Line.
If price is moving away from the Orange line, the trend is accelerating (Safe to hold).
If price touches the Orange line, momentum has died (Consider taking profit).
Settings
Visual Settings: Change Line Length (Infinite/Short) and Text Color.
MACD Settings: Standard inputs (Default 12, 26, 9).
Toggles: Option to show/hide the Zero Line target.
MA 6hour line green redUse the 6-hour chart for futures.
If the chart is above this line, go long.
Do not go long while it's below.
It's simple, but please follow this rule.
Trend Force Index (HTF Momentum)📌 Description
Trend Force Index • HTF Momentum (TFI-HTF) is a market context and trend-strength indicator designed to help traders understand directional force, momentum quality, and higher-timeframe bias.
This tool measures directional impulse and trend pressure using a dual-average force model, normalized by volatility. Instead of producing buy or sell signals, it focuses on how strong a move is, which side controls the market, and whether price is in a trending or compressing state.
🔍 What This Indicator Shows
Directional Force: Identifies bullish, bearish, and neutral force zones
Momentum Quality: Differentiates strong trends from weak or fading moves
Compression Zones: Highlights low-force environments where trades are often lower quality
Higher-Timeframe Context (HTF): Displays directional bias from a higher timeframe for alignment
Volatility Normalization: Adapts to changing market conditions using ATR
🧭 How to Use
Use force direction to confirm price action or structure-based setups
Trade in alignment with HTF bias for higher-probability context
Avoid entries during compression / low-force zones
Best used alongside price action, market structure, VWAP, or support & resistance
🎛 UI Presets
PRO Mode: Clean, subdued visuals for experienced traders
BEGINNER Mode: Higher contrast visuals for easier interpretation
⚠️ Important Notes
This indicator does NOT generate buy or sell signals.It is intended for analysis, confirmation, and market context only. Always combine with your own trading plan and risk management
⚠️ Disclaimer
This indicator is provided for educational and analytical purposes only.It does not constitute financial advice or trade recommendations.All trading decisions and associated risks remain the sole responsibility of the user.Past market behavior does not guarantee future results.
Stacked 3 Stochastics [Wonniewant]Stacked 3 Stochastics
This indicator is designed for traders who need multi-timeframe momentum analysis in a single, compact view. Instead of cluttering your screen with three separate oscillator panes, this script stacks three Stochastic Oscillators vertically within one panel using an offset technique.
It provides a clear hierarchy of market momentum, from slow trends to fast execution signals, without overlapping lines.
Key Features:
Triple Layered View (Stacked):
Top Layer (Slow): Default 20-12-12. Best for identifying major trend direction and reversals.
Middle Layer (Medium): Default 10-6-6. Acts as a bridge between the trend and entry signals.
Bottom Layer (Fast): Default 5-3-3. Ideal for pinpointing precise entry and exit timing.
Clean Visualization:
Each Stochastic has its own dedicated zone (0-100, 125-225, 250-350), so the lines never get messy or confused.
Reference Lines: Clearly marked 80 (Overbought) and 20 (Oversold) levels for each individual layer directly on the chart.
Separators: Distinct white lines separate the layers for better readability.
Full Customization:
Toggle visibility for any layer.
Customize K & D Lengths, Smoothness, Colors, and Line Widths for each Stochastic independently via the settings menu.
How to Use:
Top Layer (Slow): Watch for crosses in the overbought/oversold zones to gauge the overall market sentiment.
Bottom Layer (Fast): Use for short-term trade execution when aligned with the upper layers.
Divergence: Compare the three layers to spot momentum divergence across different time horizons.
Author: Wonniewant
Timeframe WatermarkA clean, minimal watermark indicator that displays the current chart timeframe as a large, semi-transparent text overlay.
Features:
Automatically formats timeframes (1M, 15M, 1H, 4H, 1D, 1W, etc.)
Fully customizable appearance
9 position options (corners, edges, center)
Adjustable transparency for non-intrusive display
Works on all chart types and timeframes
Settings:
Appearance
Color : Watermark text color (default: gray)
Transparency : 0 = solid, 100 = invisible (default: 85)
Size : Tiny / Small / Normal / Large / Huge
Position
Vertical : Top / Middle / Bottom
Horizontal : Left / Center / Right
Use Cases:
Quick timeframe reference when analyzing multiple charts
Screenshot clarity for sharing chart analysis
Multi-monitor setups where timeframe visibility matters
Lightweight overlay indicator with zero impact on chart performance.
Session High/Low [gdad]There are many strategies that use the 5 min, 10 min or 15 min opening candle. There are also strategies that look at the behavior of other markets such as Tokyo and London as well as the pre-market. Along with these strategies, there is one by The Rumers (@the.rumers) that also looks at the Day ATR with his Padder Scalp strategy.
I trade Futures and like to see how the market has done for varying trading sessions.
I found it was time consuming and distracting to my trading to manually mark all these different things up. This indicator takes TradingView's Trading Sessions indicator and combined ideas borrowed the idea of taking the opening range breakout and extending it to the end of the trading session from Opening Range & Prior Day High/Low along with some additional enhancements and provided information.
It comes pre-built with eight different sessions:
Session 1: Futures Session
Session 2: Tokyo
Session 3: London
Session 4: NY Pre-Market
Session 5: New York
Session 6: 5 min open
Session 7: 10 min open
Session 8: 15 min open
The names, time spans, time zones, colors, whether to show the mid-line or averages and whether and how far to extend them are all customizable once you click Show Session. You can show none, one or multiple sessions. You can also choose which text shows up in the text box (the same will show for each session).
Warning: The Extend to Time range must start during the Session Time. You cannot have a Session Time of 9:30-9:45 and an Extend Time from 10:00-4:00.
Average is calculated by the sum of the close divided by the number of bars for the session.
IV Rank & Percentile Suite V1.0What This Indicator Does
The IV Rank & Percentile Suite provides the volatility context options traders need to time entries. It calculates two complementary metrics—IV Rank and IV Percentile—using historical volatility as a proxy, then displays clear visual zones to identify favorable conditions for premium selling strategies.
Stop guessing if volatility is "high" or "low." This indicator tells you exactly where current volatility sits relative to recent history.
The Two Metrics Explained
IV Rank (0-100) Measures where current volatility sits within its 52-week high-low range.
IV Rank = (Current HV - 52w Low) / (52w High - 52w Low) × 100
70 means current volatility is 70% of the way between the yearly low and high
Sensitive to extreme spikes (a single high reading affects the range)
IV Percentile (0-100) Measures what percentage of days in the lookback period had lower volatility than today.
IV Percentile = (Days with lower HV / Total days) × 100
70 means volatility was lower than today on 70% of days in the past year
More stable, less affected by outlier spikes
Why Both?
IV Rank reacts faster to volatility changes. IV Percentile is more stable and statistically robust. When both agree (e.g., both above 50), you have stronger confirmation. Divergence between them can signal transitional periods.
Zone System
The indicator divides readings into three zones:
Zone ------- Default Range ---- Meaning ------------------ Premium Selling
🟢 High ≥ 50 Elevated volatility Favorable
🟡 Neutral 25-50 Normal volatility Selective
🔴 Low ≤ 25 Compressed volatility Avoid
An additional Extreme threshold (default 75) highlights prime conditions when volatility is significantly elevated.
Zone thresholds are fully customizable in settings.
How to Use It
For Premium Sellers (Iron Condors, Credit Spreads, Strangles)
Wait for IV Rank to enter the green zone (≥50)
Confirm IV Percentile agrees (also elevated)
Enter premium selling positions when both metrics align
Avoid initiating new positions when in the red zone
For Premium Buyers (Long Options, Debit Spreads)
Low IV Rank/Percentile means cheaper options
Red zone can favor directional debit strategies
Avoid buying premium when both metrics are in the green zone
General Principle:
Sell premium when volatility is high (it tends to revert to mean). Buy premium when volatility is low (if you have a directional thesis).
Inputs
Volatility Calculation
HV Period — Lookback for historical volatility calculation (default: 20)
Trading Days/Year — 252 for stocks, 365 for crypto
Lookback Periods
IV Rank Lookback — Period for high/low range (default: 252 = 1 year)
IV Percentile Lookback — Period for percentile calculation (default: 252)
Zone Thresholds
High IV Zone — Readings above this are highlighted green (default: 50)
Low IV Zone — Readings below this are highlighted red (default: 25)
Extreme High — Threshold for "prime" conditions alert (default: 75)
Display Options
Toggle IV Rank, IV Percentile, and raw HV display
Show/hide zone backgrounds
Show/hide info panel
Panel position selection
Info Panel
The panel displays:
Field ------- Description
IV Rank ------- Current reading with color coding
IV Pctl ------- Current percentile with color coding
HV 20d ------- Raw historical volatility percentage
52w Range ------- Lowest to highest HV in lookback period
Zone ------- Current zone status
Premium ------- Signal quality for premium selling
Lookback ------- Days used for calculations
R/P Spread ------- Difference between Rank and Percentile
Alerts
Six alerts are available:
Zone Transitions
IV Entered High Zone — Favorable for premium selling
IV Reached Extreme Levels — Prime conditions
IV Dropped to Low Zone — Caution for premium sellers
Threshold Crosses
IV Rank Crossed Above High Threshold
IV Rank Crossed Below Low Threshold
IV Percentile Above 75
IV Percentile Below 25
Set up alerts to get notified when conditions change without watching charts.
Technical Notes
Volatility Calculation Method
This indicator uses close-to-close historical volatility as an IV proxy:
Calculate log returns: ln(Close / Previous Close)
Take standard deviation over HV Period
Annualize: multiply by √(Trading Days)
This method correlates well with implied volatility for most liquid instruments. On highly liquid options underlyings (SPY, QQQ, major stocks), HV and IV tend to move together, making this a reliable proxy for IV Rank analysis.
Non-Repainting
All calculations use confirmed bar data. Values are fixed once a bar closes.
Lookback Requirement
The indicator needs sufficient history to calculate accurately. For a 252-day lookback, ensure your chart has at least 300+ bars of data.
Best Used On
ETFs: SPY, QQQ, IWM, DIA
Indices: SPX, NDX
High-volume stocks: AAPL, TSLA, NVDA, AMD, META
Timeframe: Daily (recommended), Weekly for longer-term view
The indicator works on any instrument but is most meaningful on underlyings with active options markets.
Important Notes
⚠️ This indicator uses historical volatility as a proxy for implied volatility. While HV and IV are correlated, they are not identical. For precise IV data, consult your options broker's platform.
⚠️ High IV Rank does not guarantee profitable premium selling. It indicates favorable conditions, not guaranteed outcomes. Position sizing and risk management remain essential.
⚠️ Past volatility patterns do not guarantee future behavior. Volatility regimes can shift, and historical ranges may not predict future ranges.
Suggested Workflow
Add to daily chart of your preferred underlying
Set up alert for "IV Entered High Zone"
When alerted, check both IV Rank and IV Percentile
If both elevated, evaluate premium selling opportunities
Use your broker's actual IV data for final entry decisions
Questions? Leave a comment below.
MAG7 Market Cap Weighted Index [Reflex]Summary
A synthetic intraday index built from the MAG7, weighted by market cap and plotted as true OHLC candles.
Usage
This indicator was designed for market breadth analyses. Since it uses market cap weighting, it behaves like any other index (eg. SPX).
It shows where mega-cap leadership is actually trading, making it useful for trend confirmation, divergence analysis versus NQ/ES, and contextualizing the breadth of the market.
The index is intentionally gated to the NY RTH session to avoid distorted behavior when component data is unavailable.
[GYTS] VolatilityToolkit LibraryVolatilityToolkit Library
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What Does This Library Contain?
VolatilityToolkit provides a comprehensive suite of volatility estimation functions derived from academic research in financial econometrics. Rather than relying on simplistic measures, this library implements range-based estimators that extract maximum information from OHLC data — delivering estimates that are 5–14× more efficient than traditional close-to-close methods.
The library spans the full volatility workflow: estimation, smoothing, and regime detection.
💮 Key Categories
• Range-Based Estimators — Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang (academically-grounded variance estimators)
• Classical Measures — Close-to-Close, ATR, Chaikin Volatility (baseline and price-unit measures)
• Smoothing & Post-Processing — Asymmetric EWMA for differential decay rates
• Aggregation & Regime Detection — Multi-horizon blending, MTF aggregation, Volatility Burst Ratio
💮 Originality
To the best of our knowledge, no other TradingView script combines range-based estimators (Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang), classical measures, and regime detection tools in a single package. Unlike typical volatility implementations that offer only a single method, this library:
• Implements four academically-grounded range-based estimators with proper mathematical foundations
• Handles drift bias and overnight gaps, issues that plague simpler estimators in trending markets
• Integrates with GYTS FiltersToolkit for advanced smoothing (10 filter types vs. typical SMA-only)
• Provides regime detection tools (Burst Ratio, MTF aggregation) for systematic strategy integration
• Standardises output units for seamless estimator comparison and swapping
🌸 --------- ADDED VALUE --------- 🌸
💮 Academic Rigour
Each estimator implements peer-reviewed methodologies with proper mathematical foundations. The library handles aspects that are easily missed, e.g. drift independence, overnight gap adjustment, and optimal weighting factors. All functions include guards against edge cases (division by zero, negative variance floors, warmup handling).
💮 Statistical Efficiency
Range-based estimators extract more information from the same data. Yang-Zhang achieves up to 14× the efficiency of close-to-close variance, meaning you can achieve the same estimation accuracy with far fewer bars — critical for adapting quickly to changing market conditions.
💮 Flexible Smoothing
All estimators support configurable smoothing via the GYTS FiltersToolkit integration. Choose from 10 filter types to balance responsiveness against noise reduction:
• Ultimate Smoother (2-Pole / 3-Pole) — Near-zero lag; the 3-pole variant is a GYTS design with tunable overshoot
• Super Smoother (2-Pole / 3-Pole) — Excellent noise reduction with minimal lag
• BiQuad — Second-order IIR filter with quality factor control
• ADXvma — Adaptive smoothing based on directional volatility
• MAMA — Cycle-adaptive moving average
• A2RMA — Adaptive autonomous recursive moving average
• SMA / EMA — Classical averages (SMA is default for most estimators)
Using Infinite Impulse Response (IIR) filters (e.g. Super Smoother, Ultimate Smoother) instead of SMA avoids the "drop-off artefact" where volatility readings crash when old spikes exit the window.
💮 Plug-and-Play Integration
Standardised output units (per-bar log-return volatility) make it trivial to swap estimators. The annualize() helper converts to yearly volatility with a single call. All functions work seamlessly with other GYTS components.
🌸 --------- RANGE-BASED ESTIMATORS --------- 🌸
These estimators utilise High, Low, Open, and Close prices to extract significantly more information about the underlying diffusion process than close-only methods.
💮 parkinson()
The Extreme Value Method -- approximately 5× more efficient than close-to-close, requiring about 80% less data for equivalent accuracy. Uses only the High-Low range, making it simple and robust.
• Assumption: Zero drift (random walk). May be biased in strongly trending markets.
• Best for: Quick volatility reads when drift is minimal.
• Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7)
Source: Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI
💮 garman_klass()
Extends Parkinson by incorporating Open and Close prices, achieving approximately 7.4× efficiency over close-to-close. Implements the "practical" analytic estimator (σ̂²₅) which avoids cross-product terms whilst maintaining near-optimal efficiency.
• Assumption: Zero drift, continuous trading (no gaps).
• Best for: Markets with minimal overnight gaps and ranging conditions.
• Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7)
Source: Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI
💮 rogers_satchell()
The drift-independent estimator correctly isolates variance even in strongly trending markets where Parkinson and Garman-Klass become significantly biased. Uses the formula: ln(H/C)·ln(H/O) + ln(L/C)·ln(L/O).
• Key advantage: Unbiased regardless of trend direction or magnitude.
• Best for: Trending markets, crypto (24/7 trading with minimal gaps), general-purpose use.
• Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7)
Source: Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI
💮 yang_zhang()
The minimum-variance composite estimator — both drift-independent AND gap-aware. Combines overnight returns, open-to-close returns, and the Rogers-Satchell component with optimal weighting to minimise estimator variance. Up to 14× more efficient than close-to-close.
• Parameters: lookback (default 14, minimum 2), alpha (default 1.34, optimised for equities).
• Best for: Equity markets with significant overnight gaps, highest-quality volatility estimation.
• Note: Unlike other estimators, Yang-Zhang does not support custom filter types — it uses rolling sample variance internally.
Source: Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI
🌸 --------- CLASSICAL MEASURES --------- 🌸
💮 close_to_close()
Classical sample variance of logarithmic returns. Provided primarily as a baseline benchmark — it is approximately 5–8× less efficient than range-based estimators, requiring proportionally more data for the same accuracy.
• Parameters: lookback (default 14), filter_type (default SMA), smoothing_factor (default 0.7)
• Use case: Comparison baseline, situations requiring strict methodological consistency with academic literature.
💮 atr()
Average True Range -- measures volatility in price units rather than log-returns. Directly interpretable for stop-loss placement (e.g., "2× ATR trailing stop") and handles gaps naturally via the True Range formula.
• Output: Price units (not comparable across different price levels).
• Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7)
• Best for: Position sizing, trailing stops, any application requiring volatility in currency terms.
Source: Wilder, J.W. (1978). New Concepts in Technical Trading Systems . Trend Research.
💮 chaikin_volatility()
Rate of Change of the smoothed trading range. Unlike level-based measures, Chaikin Volatility shows whether volatility is expanding or contracting relative to recent history.
• Output: Percentage change (oscillates around zero).
• Parameters: length (default 10), roc_length (default 10), filter_type (default EMA), smoothing_factor (default 0.7)
• Interpretation: High values suggest nervous, wide-ranging markets; low values indicate compression.
• Best for: Detecting volatility regime shifts, breakout anticipation.
🌸 --------- SMOOTHING & POST-PROCESSING --------- 🌸
💮 asymmetric_ewma()
Differential smoothing with separate alphas for rising versus falling volatility. Allows volatility to spike quickly (fast reaction to shocks) whilst decaying slowly (stability). Essential for trailing stops that should widen rapidly during turbulence but narrow gradually.
• Parameters: alpha_up (default 0.1), alpha_down (default 0.02).
• Note: Stateful function — call exactly once per bar.
💮 annualize()
Converts per-bar volatility to annualised volatility using the square-root-of-time rule: σ_annual = σ_bar × √(periods_per_year).
• Parameters: vol (series float), periods (default 252 for daily equity bars).
• Common values: 365 (crypto), 52 (weekly), 12 (monthly).
🌸 --------- AGGREGATION & REGIME DETECTION --------- 🌸
💮 weighted_horizon_volatility()
Blends volatility readings across short, medium, and long lookback horizons. Inspired by the Heterogeneous Autoregressive (HAR-RV) model's recognition that market participants operate on different time scales.
• Default horizons: 1-bar (short), 5-bar (medium), 22-bar (long).
• Default weights: 0.5, 0.3, 0.2.
• Note: This is a weighted trailing average, not a forecasting regression. For true HAR-RV forecasting, it would be required to fit regression coefficients.
Inspired by: Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics .
💮 volatility_mtf()
Multi-timeframe aggregation for intraday charts. Combines base volatility with higher-timeframe (Daily, Weekly, Monthly) readings, automatically scaling HTF volatilities down to the current timeframe's magnitude using the square-root-of-time rule.
• Usage: Calculate HTF volatilities via request.security() externally, then pass to this function.
• Behaviour: Returns base volatility unchanged on Daily+ timeframes (MTF aggregation not applicable).
💮 volatility_burst_ratio()
Regime shift detector comparing short-term to long-term volatility.
• Parameters: short_period (default 8), long_period (default 50), filter_type (default Super Smoother 2-Pole), smoothing_factor (default 0.7)
• Interpretation: Ratio > 1.0 indicates expanding volatility; values > 1.5 often precede or accompany explosive breakouts.
• Best for: Filtering entries (e.g., "only enter if volatility is expanding"), dynamic risk adjustment, breakout confirmation.
🌸 --------- PRACTICAL USAGE NOTES --------- 🌸
💮 Choosing an Estimator
• Trending equities with gaps: yang_zhang() — handles both drift and overnight gaps optimally.
• Crypto (24/7 trading): rogers_satchell() — drift-independent without the lag of Yang-Zhang's multi-period window.
• Ranging markets: garman_klass() or parkinson() — simpler, no drift adjustment needed.
• Price-based stops: atr() — output in price units, directly usable for stop distances.
• Regime detection: Combine any estimator with volatility_burst_ratio().
💮 Output Units
All range-based estimators output per-bar volatility in log-return units (standard deviation). To convert to annualised percentage volatility (the convention in options and risk management), use:
vol_annual = annualize(yang_zhang(14), 252) // For daily bars
vol_percent = vol_annual * 100 // Express as percentage
💮 Smoothing Selection
The library integrates with FiltersToolkit for flexible smoothing. General guidance:
• SMA: Classical, statistically valid, but suffers from "drop-off" artefacts when spikes exit the window.
• Super Smoother / Ultimate Smoother / BiQuad: Natural decay, reduced lag — preferred for trading applications.
• MAMA / ADXvma / A2RMA: Adaptive smoothing, sometimes interesting for highly dynamic environments.
💮 Edge Cases and Limitations
• Flat candles: Guards prevent log(0) errors, but single-tick bars produce near-zero variance readings.
• Illiquid assets: Discretisation bias causes underestimation when ticks-per-bar is small. Use higher timeframes for more reliable estimates.
• Yang-Zhang minimum: Requires lookback ≥ 2 (enforced internally). Cannot produce instantaneous readings.
• Drift in Parkinson/GK: These estimators overestimate variance in trending conditions — switch to Rogers-Satchell or Yang-Zhang.
Note: This library is actively maintained. Suggestions for additional estimators or improvements are welcome.
Smart Money Flow Oscillator [MarkitTick]💡This script introduces a sophisticated method for analyzing market liquidity and institutional order flow. Unlike traditional volume indicators that treat all market activity equally, the Smart Money Flow Oscillator (SMFO) employs a Logic Flow Architecture (LFA) to filter out market noise and "churn," focusing exclusively on high-impact, high-efficiency price movements. By synthesizing price action, volume, and relative efficiency, this tool aims to visualize the accumulation and distribution activities that are often attributed to "smart money" participants.
✨ Originality and Utility
Standard indicators like On-Balance Volume (OBV) or Money Flow Index (MFI) often suffer from noise because they aggregate volume based simply on the close price relative to the previous close, regardless of the quality of the move. This script differentiates itself by introducing an "Efficiency Multiplier" and a "Momentum Threshold." It only registers volume flow when a price move is considered statistically significant and structurally efficient. This creates a cleaner signal that highlights genuine supply and demand imbalances while ignoring indecisive trading ranges. It combines the trend-following nature of cumulative delta with the mean-reverting insights of an In/Out ratio, offering a dual-mode perspective on market dynamics.
🔬 Methodology
The underlying calculation of the SMFO relies on several distinct quantitative layers:
• Efficiency Analysis
The script calculates a "Relative Efficiency" ratio for every candle. This compares the current price displacement (body size) per unit of volume against the historical average.
If price moves significantly with relatively low volume, or proportional volume, it is deemed "efficient."
If significant volume occurs with little price movement (churn/absorption), the efficiency score drops.
This score is clamped between a user-defined minimum and maximum (Efficiency Cap) to prevent outliers from distorting the data.
• Momentum Thresholding
Before adding any data to the flow, the script checks if the current price change exceeds a volatility threshold derived from the previous candle's open-close range. This acts as a gatekeeper, ensuring that only "strong" moves contribute to the oscillator.
• Variable Flow Calculation
If a move passes the threshold, the script calculates the flow value by multiplying the Typical Price and Volume (Money Flow) by the calculated Efficiency Multiplier.
Bullish Flow: Strong upward movement adds to the positive delta.
Bearish Flow: Strong downward movement adds to the negative delta.
Neutral: Bars that fail the momentum threshold contribute zero flow, effectively flattening the line during consolidation.
• Calculation Modes
Cumulative Delta Flow (CDF): Sums the flow values over a rolling period. This creates a trend-following oscillator similar to OBV but smoother and more responsive to real momentum.
In/Out Ratio: Calculates the percentage of bullish inflow relative to the total absolute flow over the period. This oscillates between 0 and 100, useful for identifying overextended conditions.
📖 How to Use
Traders can utilize this oscillator to identify trend strength and potential reversals through the following signals:
• Signal Line Crossovers
The indicator plots the main Flow line (colored gradient) and a Signal line (grey).
Bullish (Green Cloud): When the Flow line crosses above the Signal line, it suggests rising buying pressure and efficient upward movement.
Bearish (Red Cloud): When the Flow line crosses below the Signal line, it suggests dominating selling pressure.
• Divergences
The script automatically detects and plots divergences between price and the oscillator:
Regular Divergence (Solid Lines): Suggests a potential trend reversal (e.g., Price makes a Lower Low while Oscillator makes a Higher Low).
Hidden Divergence (Dashed Lines): Suggests a potential trend continuation (e.g., Price makes a Higher Low while Oscillator makes a Lower Low).
"R" labels denote Regular, and "H" labels denote Hidden divergences.
• Dashboard
A dashboard table is displayed on the chart, providing real-time metrics including the current Efficiency Multiplier, Net Flow value, and the active mode status.
• In/Out Ratio Levels
When using the Ratio mode:
Values above 50 indicate net buying pressure.
Values below 50 indicate net selling pressure.
Approaching 70 or 30 can indicate overbought or oversold conditions involving volume exhaustion.
⚙️ Inputs and Settings
Calculation Mode: Choose between "Cumulative Delta Flow" (Trend focus) or "In/Out Ratio" (Oscillator focus).
Auto-Adjust Period: If enabled, automatically sets the lookback period based on the chart timeframe (e.g., 21 for Daily, 52 for Weekly).
Manual Period: The rolling lookback length for calculations if Auto-Adjust is disabled.
Efficiency Length: The period used to calculate the average body and volume for the efficiency baseline.
Eff. Min/Max Cap: Limits the impact of the efficiency multiplier to prevent extreme skewing during anomaly candles.
Momentum Threshold: A factor determining how much price must move relative to the previous candle to be considered a "strong" move.
Show Dashboard/Divergences: Toggles for visual elements.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
This indicator represents a hybrid synthesis of academic Market Microstructure theory and classical technical analysis. It utilizes an advanced algorithm to quantify "Price Impact," leveraging the following theoretical frameworks:
• 1. The Amihud Illiquidity Ratio (2002)
The core logic (calculating body / volume) functions as a dynamic implementation of Yakov Amihud’s Illiquidity Ratio. It measures price displacement per unit of volume. A high efficiency score indicates that "Smart Money" has moved the price significantly with minimal resistance, effectively highlighting liquidity gaps or institutional control.
• 2. Kyle’s Lambda (1985) & Market Depth
Drawing from Albert Kyle’s research on market microstructure, the indicator approximates Kyle's Lambda to measure the elasticity of price in response to order flow. By analyzing the "efficiency" of a move, it identifies asymmetries—specifically where price reacts disproportionately to low volume—signaling potential manipulation or specific Market Maker activity.
• 3. Wyckoff’s Law of Effort vs. Result
From a classical perspective, the algorithm codifies Richard Wyckoff’s "Effort vs. Result" logic. It acts as an oscillator that detects anomalies where "Effort" (Volume) diverges from the "Result" (Price Range), predicting potential reversals.
• 4. Quantitative Advantage: Efficiency-Weighted Volume
Unlike linear indicators such as OBV or Chaikin Money Flow—which treat all volume equally—this indicator (LFA) utilizes Efficiency-Weighted Volume. By applying the efficiency_mult factor, the algorithm filters out market noise and assigns higher weight to volume that drives structural price changes, adopting a modern quantitative approach to flow analysis.
● Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
