Compare Strength with SLOPE Description
This indicator compares the relative strength between the current asset and a benchmark (e.g., BTC vs. ETH or AAPL vs. SPY) using a linear regression slope of their ratio over time.
The ratio is calculated as: close / benchmark
A linear regression slope is computed over a user-defined window
The slope represents trend strength: if it’s rising, the current asset is outperforming the benchmark
Plots
Gray Line: The raw ratio between the asset and benchmark
Orange Line: The slope of the ratio (shows momentum)
Background Color :
Green: The asset is significantly stronger than the benchmark
Red: The asset is significantly weaker than the benchmark
No color: No clear trend
Settings
Slope Window Length: Number of candles used in the regression (default = 10)
Slope Threshold: Sensitivity of trend detection. Smaller values detect weaker trends.
Example Use Cases
Style Rotation Strategy: Use the slope to determine whether "Growth" or "Value" style is leading.
Pair Trading / Relative Performance: Track which asset is leading in a pair (e.g., BTC vs ETH).
Factor Timing: Serve as a timing model to allocate between different sectors or factors.
Happy trading!
ค้นหาในสคริปต์สำหรับ "墨尔本城vs西部联"
Volume_volatility_24)📊 TechData24h (24h Technical Metrics)
This TradingView indicator displays and alerts on key daily metrics for the current trading instrument, including:
Volume (24h, Yesterday, Day Before Yesterday)
Price Change (%) over 24h
Volatility (%) over 24h
Volume Change (%) vs Yesterday and Day Before
Correlation with BTC (custom symbol & timeframe)
🔔 Custom Alerts:
You can define your own percentage thresholds for both positive and negative changes. Alerts will trigger when:
Price change exceeds or drops below a set threshold
Volatility crosses a threshold
Volume increases or decreases significantly
Correlation with BTC moves beyond limits
📋 Table Dashboard:
All selected metrics are shown in a 2-column dashboard at the bottom left of the chart, with color-coded values based on increase/decrease.
Market Session Boxes with Volume Delta [algo_aakash]This script highlights four key forex trading sessions — Tokyo, London, New York, and Sydney — by drawing color-coded boxes directly on the chart. For each session, it shows:
High and low of the session
Total volume traded
Volume delta (bullish vs bearish pressure)
Optional extension of session highs/lows into future candles
Cleanly labeled time range and stats
Users can:
Select which sessions to display
Customize session times (in UTC+0)
Choose colors per session
Toggle session labels and extension lines
Use Case: Designed to help intraday and short-term traders visualize market rhythm, liquidity zones, and session-based volatility. The volume delta metric adds an extra layer of sentiment analysis.
This tool works best on intraday timeframes like 15m, 30m, or 1H.
Disclaimer:
This indicator is for educational and visual analysis purposes. It does not constitute trading advice or guarantee results. Always conduct your own analysis before making trading decisions.
Volume Range Profile with Fair Value (Zeiierman)█ Overview
The Volume Range Profile with Fair Value (Zeiierman) is a precision-built volume-mapping tool designed to help traders visualize where institutional-level activity is occurring within the price range — and how that volume behavior shifts over time.
Unlike traditional volume profiles that rely on fixed session boundaries or static anchors, this tool dynamically calculates and displays volume zones across both the upper and lower ends of a price range, revealing point-of-control (POC) levels, directional volume flow, and a fair value drift line that updates live with each candle.
You’re not just looking at volume anymore. You’re dissecting who’s in control — and at what price.
⚪ In simple terms:
Upper Zone = The upper portion of the price range, showing concentrated volume activity — typically where selling or distribution may occur
Lower Zone = The lower portion of the price range, highlighting areas of high volume — often associated with buying or accumulation
POC Bin = The bin (price level) with the highest traded volume in the zone — considered the most accepted price by the market
Fair Value Trend = A dynamic trend line tracking the average POC price over time — visualizing the evolving fair value
Zone Labels = Display real-time breakdown of buy/sell volume within each zone and inside the POC — revealing who’s in control
█ How It Works
⚪ Volume Zones
Upper Zone: Anchored at the highest high in the lookback period
Lower Zone: Anchored at the lowest low in the lookback period
Width is user-defined via % of range
Each zone is divided into a series of volume bins
⚪ Volume Bins (Histograms)
Each zone is split into N bins that show how much volume occurred at each level:
Taller = More volume
The POC bin (Point of Control) is highlighted
Labels show % of volume in the POC relative to the whole zone
⚪ Buy vs Sell Breakdown
Each volume bin is split by:
Buy Volume = Close ≥ Open
Sell Volume = Close < Open
The script accumulates these and displays total Buy/Sell volume per zone.
⚪ Fair Value Drift Line
A POC trend is plotted over time:
Represents where volume was most active across each range
Color changes dynamically — green for rising, red for falling
Serves as a real-time fair value anchor across changing market structure
█ How to Use
⚪ Identify Key Control Zones
Use Upper/Lower Zone structures to understand where supply and demand is building.
Zones automatically adapt to recent highs/lows and re-center volume accordingly.
⚪ Follow Institutional Activity
Watch for POC clustering near price tops or bottoms.
Large volumes near extremes may indicate accumulation or distribution.
⚪ Spot Fair Value Drift
The fair value trend line (average POC price) gives insight into market equilibrium.
One strategy can be to trade a re-test of the fair value trend, trades are taken in the direction of the current trend.
█ Understanding Buy & Sell Volume Labels (Zone Totals)
These labels show the total buy and sell volume accumulated within each zone over the selected lookback period:
Buy Vol (green label) → Total volume where candles closed bullish
Sell Vol (red label) → Total volume where candles closed bearish
Together, they tell you which side dominated:
Higher Buy Vol → Bullish accumulation zone
Higher Sell Vol → Bearish distribution zone
This gives a quick visual insight into who controlled the zone, helping you spot areas of demand or supply imbalance.
█ Understanding POC Volume Labels
The POC (Point of Control) represents the price level where the most volume occurred within the zone. These labels break down that volume into:
Buy % – How much of the volume was buying (price closed up)
Sell % – How much was selling (price closed down)
Total % – How much of the entire zone’s volume happened at the POC
Use it to spot strong demand or supply zones:
High Buy % + High Total % → Strong buying interest = likely support
High Sell % + High Total % → Strong selling pressure = likely resistance
It gives a deeper look into who was in control at the most important price level.
█ Why It’s Useful
Track where fair value is truly forming
Detect aggressive volume accumulation or dumping
Visually split buyer/seller control at the most relevant price levels
Adapt volume structures to current trend direction
█ Settings Explained
Lookback Period: Number of bars to scan for highs/lows. Higher = smoother zones, Lower = reactive.
Zone Width (% of Range): Controls how much of the range is used to define each zone. Higher = broader zones.
Bins per Zone: Number of volume slices per zone. Higher = more detail, but heavier on resources.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Multi Timeframe Altered Money Flow Index by CoffeeShopCryptoMoney Flow Index is a long used tool in trading markets, understanding to where money is moving and most importantly when its going there.
One of the biggest challenges was the when part. Because seeing it on your current trading chart timeframe is easy but it gets difficult if youre attempting a top-down-analysis of market structure vs price performance.
The new formula presented by @CoffeeshopCrypto is a key solution to this timeframe analysis issue. Seems like I may have solved the "glitch-In-The-Matrix".
The issue was always setting a secondary MFI on your chart and telling the system you wanted to watch the 1 hour MFI from a 5 minute chart.
To do this you need to wait for 12 candles to close on your 5 minute chart before you can get a 1hour MFI value. The move may have already happend and you may be too late. If there was only a better faster way to see the changing values of the High Timeframe Money Flow Index in real time without changing chart times and losing place......oh wait.....there is one now!
This tool allows you to tell it what timeframe you are looking at,
and what you want to compare it to.
It runs the calculation in the background automatically to give you the real time values of your High Timeframe chart setting on the chart you are looking at.
How to trade Long
When both the LFT and HTF Money flow cross above ZERO, they are both in uptrend
How to trade Short
When both the LFT and HTF Money flow cross below ZERO, they are both in downtrend
What happens when Low timeframe is inside the high timeframe:
If High timeframe MFI is below zero but the LFT MFI is above it and still below zero, you have lost your short term downtrend. The opposite is true when the high timeframe MFI is above zero.
A strong constant comparative trend is when your low timeframe MFI is leading your High timeframe MFI.
Personal Settings:
In my usage, i find it best to multiply my trading chart timeframe by 3 and use that number as my high timeframe MFI setting
This works on ANY chart time you want. For example you are not locked to the standard built TradingView chart times.
If you trade on a 7 minute timeframe, you can set your HTF to 21.
7 * 3 = 21
Dskyz (DAFE) Turning Point Indicator - Dskyz (DAFE) Turning Point Indicator — Smart Reversal Signals
Inspired by the intelligent logic of a pervious indicator I saw. This script represents a next-generation reversal detection system—completely re-engineered with cutting-edge filters, adaptive logic, and intelligent dashboards.
The Dskyz (DAFE) Turning Point Indicator
🧠 What Is It?
is designed to identify key market reversal zones with extraordinary accuracy by combining trend direction, volatility confirmation, price action patterns, and smart filtering layers—all visualized in a highly interactive and informative chart overlay.
This isn’t just a signal generator—it’s a decision-making assistant.
⚙️ Inputs & How to Use Them
All input fields are grouped for ease-of-use and explanation:
🔸 Reversal Logic Settings
Source: The price source used for signal generation (default: hlcc4). Can be changed to any standard price formula (open, close, hl2, etc.).
ATR Period: Used for determining volatility and dynamic trailing stop logic.
Supertrend Factor / Period: Calculates directional movement to detect trending vs choppy zones.
Reversal Sensitivity Thresholds: Internal logic filters minor pullbacks from true reversals.
🔸 Filters
Trend Filter: Enables trend-only signals (optional).
Volume Spike Filter: Confirms reversals with significant volume activity.
Volatility Zone Coloring: Visually highlights high-volatility areas to avoid late entries or fakeouts.
Custom High/Low Detection: Smart local top/bottom scanning to reinforce accuracy.
🔸 Visual & Dashboard Options
Signal Labels: Toggle signal labels on the chart.
Color Theme: Choose your visual theme for easier visibility.
Dashboard Toggle: Activate a compact dashboard summarizing strategy health (win rate, drawdown, trend state, volatility).
🧩 Functions Used
ta.supertrend(): Determines trend direction for signal confirmation and filtering.
ta.atr(): Calculates real-time volatility to determine trailing stop exits and visual zones.
ta.rsi() (internally optimized): Helps filter overbought/oversold conditions.
Local High/Low Scanner: Tracks recent pivots using a custom dynamic lookback.
Signal Engine: Consolidates multiple confirmation layers before plotting.
🚀 What Makes It Unique?
Unlike traditional reversal indicators, this one combines:
Multi-factor signal validation: No single indicator makes the call—volume, trend, price action, and volatility all contribute.
Adaptive filtering: The indicator evolves with the market—less noise, smarter signals.
Visual volatility heatmap zones: Avoid entering during uncertainty or manipulation spikes.
Interactive trend dashboard: Immediate insight into the strength and condition of the current market phase.
Highly customizable: Turn features on/off to match your trading style—scalping, swing, or trend-following.
Precision timing: Uses optimized versions of RSI and ATR that adjust automatically with price context.
🧬 Recommended for:
Commodity: Futures, Forex, Crypto
Timeframes: 1m to 1h for active traders. 4h+ for swing trades.
Pair With: Support/resistance zones, Fibonacci levels, and smart money concepts for additional confluence.
🎯 Why It Works
- Traditional reversal signals suffer from lag and noise. This system filters both by:
- Using multi-source confirmation, not just price movement.
-Tracking volatility directly, not assuming static markets.
-Detecting exhaustion, not just divergence.
-Keeping your screen clean, with only the most relevant data shown.
🧾 Credit & Acknowledgement
🧠 Original Concept Inspiration: This project was deeply inspired by the work of Enes_Yetkin_ and their approach to reversal detection. This version expands on the concept with additional technical layers, updated visuals, and real-time adaptability.
📌 Final Thoughts
This is more than a reversal tool. It's a market condition interpreter, entry/exit planner, and risk assistant all in one. Every aspect is engineered to give you an edge—especially when timing means everything.
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
AI-123's BTC vs Gold (Lag Correlation)
DISCLAIMER
I made this indicator with the help of ChatGPT and using what I have learned so far from The Pine Script Mastery Course, LOTS of edits based on what I have learned so far had to be made as well as additions and modifications to my liking thanks to what I have learned so far. I am aware this already exists but I have done my best to make a first ever script/indicator while learning how to properly publish as well, so please bear that in mind.
Overview
This indicator analyzes the correlation between Bitcoin (BTC) and Gold (XAUUSD), with a customizable lag applied to the Gold price, providing insight into the macro relationship between these two assets.
It is designed for traders and investors who want to track how Bitcoin and Gold move in relation to each other, particularly when Gold is lagged by a specific number of days.
Key Features:
BTC and Gold (Lagged) Price Overlay: Display Bitcoin (BTC) and Gold (XAUUSD) prices on the chart, with an adjustable lag applied to the Gold price.
Rolling Correlation Calculation: Measures the correlation between Bitcoin and lagged Gold prices over a customizable lookback period.
Adjustable Lag: The number of days that Gold is lagged relative to Bitcoin is fully customizable (default: 20 days).
Customizable Correlation Length: Allows you to choose the lookback period for the correlation (default: 50 days), providing flexibility for short-term or long-term analysis.
Normalized Plotting: Prices of Bitcoin and Gold are normalized for better visual alignment with the correlation values. BTC is divided by 1000, and Gold by 100.
Correlation Scaling: The correlation value is amplified by 10 for better visual clarity and comparison with price data.
Zero Line: Horizontal line representing a correlation of 0, making it easier to identify positive or negative correlation shifts.
Maximum Correlation Lines: Horizontal lines at +10 and -10 values for extreme correlation scenarios.
Input Settings:
Gold Symbol: Customize the Gold ticker (default: OANDA:XAUUSD).
Bitcoin Symbol: Customize the Bitcoin ticker (default: BINANCE:BTCUSDT).
Lag (in trading days): Adjust the number of trading days to lag the Gold price relative to Bitcoin (default: 20).
Correlation Length (days): Set the number of days over which the rolling correlation is calculated (default: 50).
How to Use:
Price Comparison: The BTC (Spot) and Lagged Gold plots give you a side-by-side visual comparison of the two assets, normalized for clarity.
Correlation Line: The correlation line helps you gauge the strength and direction of the relationship between BTC and lagged Gold. Positive values indicate a strong positive correlation, while negative values indicate a negative correlation.
Visual Analysis: Watch how the correlation shifts with changes in lag and correlation length to identify potential market dynamics between Bitcoin and Gold.
Potential Applications:
Macro Trading: Track how Bitcoin and Gold behave in relation to each other during periods of economic uncertainty or inflation.
Sentiment Analysis: Use the correlation data to understand the sentiment between digital and traditional assets.
Strategic Timing: Identify potential opportunities where Bitcoin and Gold show a strong correlation or diverge based on the lag adjustment.
Understanding Macro Trends/Correlations.
Disclaimer:
This indicator is for informational purposes only. The correlation between Bitcoin and Gold does not guarantee future performance, and users should conduct their own research and use risk management strategies when making trading decisions.
Notes: This script uses historical data, so results may vary across different timeframes.
Customization options allow users to adjust the lag and correlation length to better fit their trading strategy.
Future Enhancements: Additional Correlation Line: A second correlation line for different lengths of lag or different assets.
Color-Coding of Correlation: Future updates may include color-coded correlation strength, visually indicating positive or negative correlation more effectively.
Intraday vs Overnight Change TrackerThis indicator tracks a synthetic price path based on either intraday or overnight return behavior, allowing users to analyze which component of daily price movement is contributing more to long-term performance.
***THIS INDICATOR ONLY WORKS ON THE DAILY TIMEFRAME***
Intraday mode compounds price change from market open to close: close / open
Overnight mode compounds price change from previous close to current open: open / close
The user can select one of these two modes using a dropdown input. The synthetic price series starts from the second bar of the chart and compounds forward bar-by-bar using the selected return type. The result is a line that reflects cumulative return based solely on either intraday or overnight activity.
⚙️ Inputs
Synthetic Price Type: Select between "Intraday" or "Overnight" to visualize the respective compounded price series.
📈 Usage Notes
This indicator is intended for visual comparison of intraday vs. overnight price dynamics over time. It can be useful for identifying behavioral patterns, session-based return anomalies, or testing session bias strategies.
Only one synthetic line is shown at a time based on user selection.
If you want to view both intraday and overnight lines, then you can add the indicator twice, which is shown above.
ATR % Oscillator - DolphinTradeBot1️⃣ Overview
🔸 This is a simplified version of ATR and TR that shows volatility as percentage changes , making it easier to compare two symbols.
🔸 The indicator compares the volatility of two different assets by calculating the percentage-based price ranges and their moving averages .
📌 This is especially useful for pair traders, as it helps identify which symbol is more volatile, allowing for strategic decisions based on relative movement rather than overall market direction.
2️⃣ How Is It Work?
🔸 For each symbol, it calculates the absolute percentage difference between either:
• Close and Open (net price change), or
• High and Low (daily price range).
🔸 The results are visualized as column bars — the taller the bar, the higher the volatility.
🔸 It also plots a moving average line (SMA) based on the selected range length.
📌 These calculations are independent of the chart you're on — they work purely based on the two selected symbols.
If no symbols are selected, it defaults to using the current chart's symbol.
3️⃣ How to Use It?
With this indicator, you can:
🔸 Compare the volatility between two assets.
🔸 Detect sudden volatility spikes that may signal upcoming momentum.
🔸 Support spread, arbitrage, or correlation-based strategies .
🔸 See which symbol is gaining market attention (a larger difference = more activity).
Example: Compare BTC vs ETH to see which one is dominating in terms of price action or volatility.
4️⃣⚙️ Settings
🔸 Symbol Settings
• Symbol-1 / Symbol-2: Choose the two assets to compare.
• Checkboxes: Enable/disable visibility for each symbol's data.
🔸 Calculation Settings
• Range Average: The number of bars used for the moving average.
• Calculation Source:
- Close-Open: Measures net price movement.
- High-Low: Measures total price range.
ZVOL — Z-Score Volume Heatmapⓩ ZVOL transforms raw volume into a statistically calibrated heatmap using Z-score thresholds. Unlike classic volume indicators that rely on fixed MA comparisons, ZVOL calculates how many standard deviations each volume bar deviates from its mean. This makes the reading adaptive across timeframes and assets, in order to distinguish meaningful crowd behavior from random volatility.
📊 The core display is a five-zone histogram, each encoded by color and statistical depth. Optional background shading mirrors these zones across the entire pane, revealing subtle compression or structural rhythm shifts across time. By grounding the volume reading in volatility-adjusted context, ZVOL inhibits impulsive trading tactics by compelling the structure, not the sentiment, to dictate the signal.
🥵 Heatmap Coloration:
🌚 Suppressed volume — congestion, coiling phases
🩱 Stable flow — early trend or resting volume
🏀 High activity — emerging pressure
💔 Extreme — possible climax or institutional print
🎗️ A dynamic Fibonacci-based 21:34-period EMA ribbon overlays the histogram. The fill area inverts color on crossover, providing a real-time read on tempo, expansion, or divergence between price structure and crowd effort.
💡 LTF Usage Suggestions:
• Confirm breakout legs when orange or red zones align with range exits
• Fade overextended moves when red bars appear into resistance
• Watch for rising EMAs and orange volume to front-run impulsive moves
• Combine with volatility suppression (e.g. ATR) to catch compression → expansion transitions
🥂 Ideal Pairings:
• OBVX Conviction Bias — to confirm directional intent behind volume shifts
• SUPeR TReND 2.718 — for directional filters
• ATR Turbulence Ribbon — to detect compression phases
👥 The OBVX Conviction Bias adds a second dimension to ZVOL by revealing whether crowd effort is aligning with price direction or diverging beneath the surface. While ZVOL identifies statistical anomalies in raw volume, OBVX tracks directional commitment using cumulative volume and moving average cross logic. Use them together to spot fake-outs, anticipate structure-confirmed breakouts, or time pullbacks with volume-based conviction.
🔬 ZVOL isn’t just a volume filter — it’s a structural lens. It reveals when crowd effort is meaningful, when it's fading, and when something is about to shift. Designed for structure-aware traders who care about context, not noise.
Sahid Strategy v2This script identifies potential buy/sell signals using:
Pivot Points - Detects swing highs/lows (price reversals)
Confirmation Filters - Reduces false signals using:
RSI (momentum)
Moving Average (trend direction)
Optional MACD (trend confirmation)
Key Features
Signal Type Trigger Conditions
BUY - Price makes a swing low (pivot)
Copy
- RSI ≤ 30 (oversold)
- Price above trend MA
- MACD bullish (optional) |
| SELL | - Price makes a swing high (pivot)
- RSI ≥ 70 (overbought)
- Price below trend MA
- MACD bearish (optional) |
Visual Signals
Green "BUY" labels below price bars
Red "SELL" labels above price bars
Purple trend line (20-period EMA/SMA)
Orange/blue circles showing raw pivot points
Optional Tools
Debug Table (top-right): Shows real-time:
RSI value
Price vs MA position
MACD status
Alerts - Triggers audible/visual notifications
Customization
Adjust in settings:
Pivot sensitivity (left/right bars)
RSI levels (30/70 by default)
MA type/length (20-period EMA/SMA)
Toggle MACD filter on/off
Best For: Swing trading in trending markets (1H-4H timeframes). Signals appear faster than classic pivot strategies but still require confirmation from other analysis tools.
Market Push Meter - CoffeeStyleMarket Push Meter - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the Market Push Meter indicator, a sophisticated volume analysis tool developed by CoffeeKiller with the help and assistance of FindBetterTrades that measures and visualizes the ongoing battle between buyers and sellers through volume pressure analysis.
🔔 **Warning: This Is Not a Standard Volume Indicator** 🔔 This indicator analyzes volume pressure in a unique way, combining directional volume with price action to identify market imbalances between buyers and sellers. All credit for the core logic for this indicator goes to FindBetterTrades and his/hers Volume Pressure Histogram (Normalized) (this is my adaptation and style added to that core logic, thus the CoffeeStyle name was added).
Core Concept: Volume Pressure Analysis
The foundation of this indicator lies in measuring the imbalance between buying and selling volume, providing insights into which market participants are exerting more pressure on price movements.
Volume Pressure Columns: Buying vs Selling Force
- Positive Green Columns: Net buying pressure
- Negative Red Columns: Net selling pressure
- Color intensity varies based on pressure strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during buying phases
- Low Marker Line (Cyan): Tracks the lowest point reached during selling phases
- Creates visual boundaries showing pressure extremes
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important pressure peaks
- Helps identify potential reversal points and pressure exhaustion
Reference Lines:
- Overbought Level: Threshold for extreme selling pressure
- Oversold Level: Threshold for extreme buying pressure
- Used to identify potential reversal zones
Core Components
1. Volume Pressure Calculation
- Separation of up-volume and down-volume
- Calculation of net volume pressure
- Smoothing for consistent visualization
- Normalization against total volume for percentage scaling
2. Boundary Tracking System
- Automatic detection of highest values in buying phases
- Automatic detection of lowest values in selling phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Threshold Settings
- Extreme threshold multiplier for identifying significant pressure
- Overbought/oversold levels for potential reversals
- Dynamic color coding based on pressure intensity
- Alert conditions for key pressure levels
Main Features
Volume Analysis Settings
- Customizable volume MA length
- Signal smoothing for clearer readings
- Optional log scale for handling wide range variations
- Adjustable threshold multiplier for sensitivity
Visual Elements
- Color-coded columns showing pressure direction and strength
- Dynamic marker lines for pressure boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
- Overbought/oversold reference lines
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for pressure strength
- Peak formation for potential reversals
- Color changes for pressure direction and intensity
- Alert conditions for extreme pressure levels
Customization Options
- Volume analysis parameters
- Marker line visibility and colors
- Peak marker display options
- Log scale toggle for handling various markets
- Overbought/oversold threshold adjustments
Trading Applications
1. Trend Identification
- Volume pressure crossing above zero: buying pressure emerging
- Volume pressure crossing below zero: selling pressure emerging
- Column color: indicates pressure direction
- Column height: indicates pressure strength
- Signal line: confirms overall trend direction
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Volume pressure approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing pressure
- Readings beyond overbought/oversold levels: potential reversal zones
3. Pressure Analysis
- Breaking above previous high boundary: accelerating buying pressure
- Breaking below previous low boundary: accelerating selling pressure
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Extreme readings: potential climactic buying/selling
4. Market Structure Assessment
- Consecutive higher peaks: strengthening buying structure
- Consecutive lower troughs: strengthening selling structure
- Peak comparisons: relative strength of pressure phases
- Boundary line steps: market structure levels
Optimization Guide
1. Volume Analysis Settings
- Volume MA Length: Default 25 provides balanced signals
- Lower values (10-15): More responsive, potentially noisier
- Higher values (30-50): Smoother, fewer false signals
- Signal Smoothing Length: Default 8 provides good balance
- Lower values: More responsive to pressure changes
- Higher values: Smoother trend identification
2. Threshold Settings
- Extreme Threshold Multiplier: Default 20.0
- Lower values: More signals, potentially more noise
- Higher values: Fewer signals, but more significant
- Overbought/Oversold Levels: Defaults at 20/-20
- Adjust based on instrument volatility
- Wider settings for more volatile instruments
3. Visual Customization
- Marker Line Colors: Adjust for visibility on your chart
- Peak Marker Color: Default yellow provides good contrast
- Enable/disable background highlights based on preference
- Consider log scale for instruments with wide volume ranges
4. Alert Settings
- Configure alerts for high buying pressure
- Configure alerts for high selling pressure
- Set additional alerts for zero-line crosses
- Consider timeframe when setting alert sensitivity
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm pressure changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong pressure
- Use with price action for entry/exit precision
- Consider extreme threshold crossings as significant signals
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Multiple timeframes: confirm signals across time horizons
- Match to your trading style and holding period
3. Market Context
- Strong buying phase: positive columns breaking above marker line
- Strong selling phase: negative columns breaking below marker line
- Columns approaching zero: potential pressure shift
- Columns beyond overbought/oversold: extreme conditions, potential reversal
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with price action oscillators for divergence detection
- Combine with traditional volume indicators for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when volume pressure breaks above previous high marker line
- Enter short when volume pressure breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in buying phases for shorting opportunities
- Look for consecutive higher troughs in selling phases for buying opportunities
- Use zero-line crosses as confirmation
3. Extreme Reading Strategy
- Look for volume pressure beyond overbought/oversold levels
- Watch for color changes and peak formations
- Enter counter-trend positions after confirmed peaks
- Use tight stops due to extreme market conditions
4. Volume Color Strategy
- Enter long when columns turn bright green (increasing buying pressure)
- Enter short when columns turn bright red (increasing selling pressure)
- Exit when color intensity fades (decreasing pressure)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Volume pressure crosses above zero line
- Green columns grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant buying pressure peaks
Bearish Market Scenario
- Volume pressure crosses below zero line
- Red columns grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant selling pressure troughs
Consolidation Scenario
- Volume pressure oscillates around zero line
- Column colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Pressure values remain small
Understanding Market Dynamics Through Market Push Meter
At its core, this indicator provides a unique lens to visualize market pressure through volume analysis:
1. Volume Imbalance: By separating and comparing buying volume (up candles) from selling volume (down candles), the indicator provides insights into which side is exerting more pressure in the market.
2. Normalized Pressure: The indicator normalizes volume pressure as a percentage of total volume, making it more comparable across different market conditions and instruments.
3. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of pressure in both directions, helping to identify when markets are making new pressure extremes.
4. Exhaustion Signals: The peak detection system highlights moments where pressure has reached a local maximum or minimum, often precursors to reversals or consolidations.
Remember:
- Combine signals from volume pressure, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences and market
- Consider overall market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
RSI + MFI Momentum Mapper - CoffeeKillerRSI + MFI Momentum Mapper - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the RSI + MFI Momentum Mapper indicator, an innovative market analysis tool developed by CoffeeKiller that combines two powerful oscillators to create a comprehensive momentum visualization system.
🔔 **Warning: This Is Not a Standard RSI or MFI Indicator** 🔔 This indicator combines and normalizes RSI and MFI data to create a unified momentum representation with boundary detection and peak signaling features.
Core Concept: Combined Momentum Analysis
The foundation of this indicator lies in merging the strengths of two complementary oscillators - Relative Strength Index (RSI) and Money Flow Index (MFI) - to provide a more robust momentum signal that accounts for both price action and volume.
Directional Columns: Momentum Strength
- Positive Green Columns: Bullish momentum
- Negative Red Columns: Bearish momentum
- Color intensity varies based on momentum strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during a bullish phase
- Low Marker Line (Cyan): Tracks the lowest point reached during a bearish phase
- Creates visual boundaries showing momentum extremes
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important momentum peaks
- Helps identify potential reversal points and momentum exhaustion
Reference Lines:
- Zero Line (Gray): Divides bullish from bearish momentum
- High Line (+1): Upper threshold for extremely bullish conditions
- Low Line (-1): Lower threshold for extremely bearish conditions
Core Components
1. Oscillator Normalization
- RSI and MFI values centered around zero
- Values scaled to create consistent visualization
- Normalized range typically between -1 and +1
- Combination of indicators for signal reliability
2. Boundary Tracking System
- Automatic detection of highest values in bullish phases
- Automatic detection of lowest values in bearish phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Signal Smoothing
- Signal line calculation via SMA
- Helps filter noise and identify trends
- Provides confirmation of momentum direction
Main Features
Oscillator Settings
- Customizable RSI length for sensitivity control
- Customizable MFI length for sensitivity control
- Normalized display for consistent visualization
- Signal smoothing for clearer readings
Visual Elements
- Color-coded columns showing momentum direction and strength
- Dynamic marker lines for momentum boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
- Reference lines for momentum threshold levels
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for momentum strength
- Peak formation for potential reversals
- Color changes for momentum direction and acceleration
Customization Options
- RSI and MFI length parameters
- Marker line visibility and colors
- Peak marker color selection
- Peak background display options
Trading Applications
1. Trend Identification
- Directional line crossing above zero: bullish trend beginning
- Directional line crossing below zero: bearish trend beginning
- Column color: indicates momentum direction
- Column height: indicates momentum strength
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Directional line approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing momentum
3. Momentum Analysis
- Breaking above previous high boundary: accelerating bullish momentum
- Breaking below previous low boundary: accelerating bearish momentum
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Approaching +1/-1 lines: extreme momentum conditions
4. Market Structure Assessment
- Consecutive higher peaks: strengthening bullish structure
- Consecutive lower troughs: strengthening bearish structure
- Peak comparisons: relative strength of momentum phases
- Boundary line steps: market structure levels
Optimization Guide
1. Oscillator Settings
- RSI Length: Default 14 provides balanced signals
- Lower values (7-10): More responsive, potentially noisier
- Higher values (20-30): Smoother, fewer false signals
- MFI Length: Default 14 provides balanced signals
- Lower values: More responsive to volume changes
- Higher values: Less sensitive to short-term volume spikes
2. Visual Customization
- Marker Line Colors: Adjust for visibility on your chart
- Peak Marker Color: Default yellow provides good contrast
- Enable/disable background highlights based on preference
- Consider chart background when selecting colors
3. Signal Interpretation
- Stronger signals: When directional line approaches +1/-1
- Confirmation: When peaks form after extended momentum
- Early warnings: When color intensity changes before direction
- Trend strength: Distance between zero line and current reading
4. Reference Line Usage
- Zero line: Primary trend divider
- +1/-1 lines: Extreme momentum thresholds
- Marker lines: Dynamic support/resistance levels
- Distance from reference: Momentum strength measure
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm trend changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong momentum
- Use with price action for entry/exit precision
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Multiple timeframes: confirm signals across time horizons
- Match to your trading style and holding period
3. Market Context
- Strong bullish phase: positive columns breaking above marker line
- Strong bearish phase: negative columns breaking below marker line
- Columns approaching zero: potential trend change
- Columns approaching +1/-1: extreme conditions, potential reversal
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with other oscillators for divergence detection
- Combine with volume analysis for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when directional line breaks above previous high marker line
- Enter short when directional line breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in bullish phases for shorting opportunities
- Look for consecutive higher troughs in bearish phases for buying opportunities
- Use zero-line crosses as confirmation
3. Extreme Reading Strategy
- Look for directional line approaching +1/-1 lines
- Watch for color changes and peak formations
- Enter counter-trend positions after confirmed peaks
- Use tight stops due to extreme momentum conditions
4. Column Color Strategy
- Enter long when columns turn bright green (increasing momentum)
- Enter short when columns turn bright red (increasing momentum)
- Exit when color intensity fades (decreasing momentum)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Directional line crosses above zero line
- Green columns grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant momentum peaks
Bearish Market Scenario
- Directional line crosses below zero line
- Red columns grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant momentum troughs
Consolidation Scenario
- Directional line oscillates around zero line
- Column colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Directional values remain small
Understanding Market Dynamics Through RSI + MFI Momentum Mapper
At its core, this indicator provides a unique lens to visualize market momentum by combining two complementary oscillators:
1. Combined Strength: By averaging RSI (price-based) and MFI (volume-based), the indicator provides a more comprehensive view of market momentum that considers both price action and buying/selling pressure.
2. Normalized Scale: The indicator normalizes values around zero, making it easier to identify bullish vs bearish conditions and the relative strength of momentum in either direction.
3. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of momentum in both directions, helping to identify when markets are making new momentum extremes.
4. Exhaustion Signals: The peak detection system highlights moments where momentum has reached a local maximum or minimum, often precursors to reversals or consolidations.
Remember:
- Combine signals from directional line, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences
- Consider market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
CVD Divergence Insights📘 CVD Divergence Insights – by Colicoid
Pine Script v6 | Volume Delta Divergence Oscillator with Spike Detection
⸻
🔍 Overview
CVD Divergence Insights is a volume-aware oscillator and divergence spike detector that helps you spot smart money activity, absorption, failed pressure, and hidden strength or weakness — even when price action alone gives little away.
It works by comparing normalized Cumulative Volume Delta (CVD) against normalized price movement, and optionally applying a volume-weighting layer to highlight when aggressive participation is truly behind the divergence. The result is a dynamic visual tool that identifies tension in the market, and helps you trade based on how that tension resolves.
⸻
🧠 Core Concept
• When price moves one way and CVD moves another, it reflects imbalance between aggression and result.
• Divergence is not a trigger — it’s a build-up of pressure.
• The real edge lies in the resolution of that pressure.
• Optional volume-weighting helps you ignore noise and focus on high-conviction moves only.
⸻
⚙️ How It Works
1. CVD Calculation
CVD is generated using lower-timeframe delta volume (buy vs. sell pressure), accumulated per bar.
2. Oscillator
A normalized divergence between the smoothed CVD and smoothed price.
3. Volume Weighting (optional)
Emphasizes divergences occurring on higher-than-normal volume, deprioritizes low-volume noise.
4. Signal Line (optional)
A short EMA of the oscillator to help track momentum shifts (hidden by default).
5. Divergence Spikes
Statistical spike detection using standard deviation — green/red dots highlight unusually large divergence activity.
⸻
🎛️ Inputs
Anchor Period
Higher timeframe where the CVD is accumulated and processed.
Lower Timeframe
Optional override for granularity of buy/sell volume data.
SMA Length
Used for smoothing both price and CVD before divergence is calculated.
Volume Weighted?
Enables adaptive weighting based on relative volume size.
Volume Normalization Length
Lookback period used to define what is “normal” volume.
Divergence Spike Threshold
StdDev-based threshold to detect abnormally large divergences.
Signal Line Length
Controls the EMA smoothing of the optional signal line (hidden by default).
⸻
📈 Trade Setup Example: Hidden Bullish Divergence
1. Price forms a higher low, but CVD forms a lower low — hidden bullish divergence.
2. This shows aggressive sellers are trying, but price is resilient — likely absorption.
3. You wait for a "convergent signal bar":
• A bullish candle with strong structure or body
• Confirmed by CVD starting to turn upward
4. That’s your trigger bar — the tension resolves upward.
⸻
🤝 Recommended Pairings
For best results, combine CVD Divergence Insights with the companion script:
🔗 Cumulative Volume Delta Line (also by Colicoid)
This lets you:
• See the raw CVD line and its SMA visually
• Spot standard and hidden divergences in price/CVD directly
• Use the Insights indicator to evaluate divergence quality and flag aggressive bull/bear behavior
• Use the same SMA length on both indicators for alignment
👉 Tip: To save screen space, drag the CVD Line indicator into the same panel as CVD Divergence Insights.
⸻
🧰 Why Use This?
• ✅ Catch absorption setups and failed pressure zones
• ✅ Filter out low-quality divergences using volume context
• ✅ Understand why price is hesitating or breaking out
• ✅ Add smart confirmation to breakout/reversal trades
• ✅ Align your execution with who’s actually in control
⸻
📎 Created by Colicoid
Built in Pine Script v6 for advanced price-volume analysis, with focus on effort vs result, market psychology, and smart money detection.
ES vs Bond ROCThis Pine Script plots the Relative Rate of Change (ROC) between the S&P 500 E-mini Futures (ES) and 30-Year Treasury Bond Futures (ZB) over a specified period. It helps identify when equities are overperforming or underperforming relative to long-term bonds—an insight often used to detect risk-on/risk-off sentiment shifts in the market.
[blackcat] L3 Composite Trading System with ControlOVERVIEW
This indicator combines three distinct trading strategies into a unified decision-making framework. Utilizing KDJ oscillators, MACD divergence analysis, and adaptive signal filtering techniques, it provides actionable buy/sell signals validated against multi-period momentum trends and structural support/resistance levels.
FEATURES
Integrated KDJ oscillator with weighted moving average smoothing
Dynamic MACD difference visualization normalized against price volatility
Multi-layered confirmation process: • Momentum convergence/divergence tracking
• Candle pattern recognition (Yellow/Fuchsia flags)
• SMAs cross-validation (20/60-day thresholds)
Adaptive risk controls via tunable α parameter adjustment
HOW TO USE
Set Alpha Period parameter matching market cycle characteristics
Monitor primary trend direction via candle coloring (green/red zones)
Confirm directional bias using: ▪️ KDJ-J line position relative to zero axis ▪️ MACD histogram slope persistence (>3 bar validation)
Execute trades only when: • Buy/Sell labels align across both oscillator panels • Coincide with candle flag transitions (e.g., red→yellow) • Validate against concurrent SMA breakout conditions
LIMITATIONS
Lag inherent in EMA-based components during rapid reversals
Requires minimum 60-bar history for full functionality
Sensitive to fractal scaling due to normalization methods
Does not account for liquidity/volume dynamics
NOTES
• Yellow/Fuchsia flags reflect relative strength changes vs prior session
• SMA crossover validations have 16-bar lookback memory retention
Multi-Anchored Linear Regression Channels [TANHEF]█ Overview:
The 'Multi-Anchored Linear Regression Channels ' plots multiple dynamic regression channels (or bands) with unique selectable calculation types for both regression and deviation. It leverages a variety of techniques, customizable anchor sources to determine regression lengths, and user-defined criteria to highlight potential opportunities.
Before getting started, it's worth exploring all sections, but make sure to review the Setup & Configuration section in particular. It covers key parameters like anchor type, regression length, bias, and signal criteria—essential for aligning the tool with your trading strategy.
█ Key Features:
⯁ Multi-Regression Capability:
Plot up to three distinct regression channels and/or bands simultaneously, each with customizable anchor types to define their length.
⯁ Regression & Deviation Methods:
Regressions Types:
Standard: Uses ordinary least squares to compute a simple linear trend by averaging the data and deriving a slope and endpoints over the lookback period.
Ridge: Introduces L2 regularization to stabilize the slope by penalizing large coefficients, which helps mitigate multicollinearity in the data.
Lasso: Uses L1 regularization through soft-thresholding to shrink less important coefficients, yielding a simpler model that highlights key trends.
Elastic Net: Combines L1 and L2 penalties to balance coefficient shrinkage and selection, producing a robust weighted slope that handles redundant predictors.
Huber: Implements the Huber loss with iteratively reweighted least squares (IRLS) and EMA-style weights to reduce the impact of outliers while estimating the slope.
Least Absolute Deviations (LAD): Reduces absolute errors using iteratively reweighted least squares (IRLS), yielding a slope less sensitive to outliers than squared-error methods.
Bayesian Linear: Merges prior beliefs with weighted data through Bayesian updating, balancing the prior slope with data evidence to derive a probabilistic trend.
Deviation Types:
Regressive Linear (Reverse): In reverse order (recent to oldest), compute weighted squared differences between the data and a line defined by a starting value and slope.
Progressive Linear (Forward): In forward order (oldest to recent), compute weighted squared differences between the data and a line defined by a starting value and slope.
Balanced Linear: In forward order (oldest to newest), compute regression, then pair to source data in reverse order (newest to oldest) to compute weighted squared differences.
Mean Absolute: Compute weighted absolute differences between each data point and its regression line value, then aggregate them to yield an average deviation.
Median Absolute: Determine the weighted median of the absolute differences between each data point and its regression line value to capture the central tendency of deviations.
Percent: Compute deviation as a percentage of a base value by multiplying that base by the specified percentage, yielding symmetric positive and negative deviations.
Fitted: Compare a regression line with high and low series values by computing weighted differences to determine the maximum upward and downward deviations.
Average True Range: Iteratively compute the weighted average of absolute differences between the data and its regression line to yield an ATR-style deviation measure.
Bias:
Bias: Applies EMA or inverse-EMA style weighting to both Regression and/or Deviation, emphasizing either recent or older data.
⯁ Customizable Regression Length via Anchors:
Anchor Types:
Fixed: Length.
Bar-Based: Bar Highest/Lowest, Volume Highest/Lowest, Spread Highest/Lowest.
Correlation: R Zero, R Highest, R Lowest, R Absolute.
Slope: Slope Zero, Slope Highest, Slope Lowest, Slope Absolute.
Indicator-Based: Indicators Highest/Lowest (ADX, ATR, BBW, CCI, MACD, RSI, Stoch).
Time-Based: Time (Day, Week, Month, Quarter, Year, Decade, Custom).
Session-Based: Session (Tokyo, London, New York, Sydney, Custom).
Event-Based: Earnings, Dividends, Splits.
External: Input Source Highest/Lowest.
Length Selection:
Maximum: The highest allowed regression length (also fixed value of “Length” anchor).
Minimum: The shortest allowed length, ensuring enough bars for a valid regression.
Step: The sampling interval (e.g., 1 checks every bar, 2 checks every other bar, etc.). Increasing the step reduces the loading time, most applicable to “Slope” and “R” anchors.
Adaptive lookback:
Adaptive Lookback: Enable to display regression regardless of too few historical bars.
⯁ Selecting Bias:
Bias applies separately to regression and deviation.
Positive values emphasize recent data (EMA-style), negative invert, and near-zero maintains balance. (e.g., a length 100, bias +1 gives the newest price ~7× more weight than the oldest).
It's best to apply bias to both (regression and deviation) or just the deviation. Biasing only regression may distort deviation visually, while biasing both keeps their relationship intuitive. Using bias only for deviation scales it without altering regression, offering unique analysis.
⯁ Scale Awareness:
Supports linear and logarithmic price scaling, the regression and deviations adjust accordingly.
⯁ Signal Generation & Alerts:
Customizable entry/exit signals and alerts, detailed in the dedicated section below.
⯁ Visual Enhancements & Real-World Examples:
Optional on-chart table display summarizing regression input criteria (display type, anchor type, source, regression type, regression bias, deviation type, deviation bias, deviation multiplier) and key calculated metrics (regression length, slope, Pearson’s R, percentage position within deviations, etc.) for quick reference.
█ Understanding R (Pearson Correlation Coefficient):
Pearson’s R gauges data alignment to a straight-line trend within the regression length:
Range: R varies between –1 and +1.
R = +1 → Perfect positive correlation (strong uptrend).
R = 0 → No linear relationship detected.
R = –1 → Perfect negative correlation (strong downtrend).
This script uses Pearson’s R as an anchor, adjusting regression length to target specific R traits. Strong R (±1) follows the regression channel, while weak R (0) shows inconsistency.
█ Understanding the Slope:
The slope is the direction and rate at which the regression line rises or falls per bar:
Positive Slope (>0): Uptrend – Steeper means faster increase.
Negative Slope (<0): Downtrend – Steeper means sharper drop.
Zero or Near-Zero Slope: Sideways – Indicating range-bound conditions.
This script uses highest and lowest slope as an anchor, where extremes highlight strong moves and trend lines, while values near zero indicate sideways action and possible support/resistance.
█ Setup & Configuration:
Whether you’re new to this script or want to quickly adjust all critical parameters, the panel below shows the main settings available. You can customize everything from the anchor type and maximum length to the bias, signal conditions, and more.
Scale (select Log Scale for logarithmic, otherwise linear scale).
Display (regression channel and/or bands).
Anchor (how regression length is determined).
Length (control bars analyzed):
• Max – Upper limit.
• Min – Prevents regression from becoming too short.
• Step – Controls scanning precision; increasing Step reduces load time.
Regression:
• Type – Calculation method.
• Bias – EMA-style emphasis (>0=new bars weighted more; <0=old bars weighted more).
Deviation:
• Type – Calculation method.
• Bias – EMA-style emphasis (>0=new bars weighted more; <0=old bars weighted more).
• Multiplier - Adjusts Upper and Lower Deviation.
Signal Criteria:
• % (Price vs Deviation) – (0% = lower deviation, 50% = regression, 100% = upper deviation).
• R – (0 = no correlation, ±1 = perfect correlation; >0 = +slope, <0 = -slope).
Table (analyze table of input settings, calculated results, and signal criteria).
Adaptive Lookback (display regression while too few historical bars).
Multiple Regressions (steps 2 to 7 apply to #1, #2, and #3 regressions).
█ Signal Generation & Alerts:
The script offers customizable entry and exit signals with flexible criteria and visual cues (background color, dots, or triangles). Alerts can also be triggered for these opportunities.
Percent Direction Criteria:
(0% = lower deviation, 50% = regression line, 100% = upper deviation)
Above %: Triggers if price is above a specified percent of the deviation channel.
Below %: Triggers if price is below a specified percent of the deviation channel.
(Blank): Ignores the percent‐based condition.
Pearson's R (Correlation) Direction Criteria:
(0 = no correlation, ±1 = perfect correlation; >0 = positive slope, <0 = negative slope)
Above R / Below R: Compares the correlation to a threshold.
Above│R│ / Below│R│: Uses absolute correlation to focus on strength, ignoring direction.
Zero to R: Checks if R is in the 0-to-threshold range.
(Blank): Ignores correlation-based conditions.
█ User Tips & Best Practices:
Choose an anchor type that suits your strategy, “Bar Highest/Lowest” automatically spots commonly used regression zones, while “│R│ Highest” targets strong linear trends.
Consider enabling or disabling the Adaptive Lookback feature to ensure you always have a plotted regression if your chart doesn’t meet the maximum-length requirement.
Use a small Step size (1) unless relying on R-correlation or slope-based anchors as the are time-consuming to calculate. Larger steps speed up calculations but reduce precision.
Fine-tune settings such as lookback periods, regression bias, and deviation multipliers, or trend strength. Small adjustments can significantly affect how channels and signals behave.
To reduce loading time , show only channels (not bands) and disable signals, this limits calculations to the last bar and supports more extreme criteria.
Use the table display to monitor anchor type, calculated length, slope, R value, and percent location at a glance—especially if you have multiple regressions visible simultaneously.
█ Conclusion:
With its blend of advanced regression techniques, flexible deviation options, and a wide range of anchor types, this indicator offers a highly adaptable linear regression channeling system. Whether you're anchoring to time, price extremes, correlation, slope, or external events, the tool can be shaped to fit a variety of strategies. Combined with customizable signals and alerts, it may help highlight areas of confluence and support a more structured approach to identifying potential opportunities.
Normalized FX Weighted Daily % Change vs DXYThis indicator tracks international liquidity flows by measuring the USD’s relative strength against major currencies—EUR, CNY, JPY, GBP, and CAD. It calculates the weighted percentage change of each pair over a specified interval. A positive reading means the USD is weakening (liquidity flowing out of the US), while a negative reading indicates the USD is strengthening (liquidity flowing in). Additionally, the indicator incorporates the DXY index and VIX, with all components normalized using Z-scores for clear, comparable insights into market dynamics.
Multi Swing Point ConnectionsMulti Swing Point Connections — Tool for custom Highs & Lows structure mapping. This indicator allows to create fully customizable connections between multiple types of swing points, offering advanced visual structure of price dynamics.
Features:
Dynamic Swing Detection using adjustable pivot period.
Connect up to 8 swing relationships, with individual controls for swing points: 🔴 Higher High, 🟠 Lower High, 🔵 Higher Low, 🟢 Lower Low
Countback customization (steps for historical/future reference)
Optional enabling/disabling per connection
Visual Structure Mapping with configurable line color and width.
Perfect for identifying key structure shifts
Mapping trending vs consolidating phases
Building your own internal order flow frameworks
Inputs:
Swing Period: Defines how many bars to the left/right are used to detect pivot highs/lows.
Line Customization: Adjust style, width and color for visual clarity.
Connection Parameters: Select which swing types to connect, and control how far back and forward to look when making the connection.
Connection Examples:
HH to LH - Mapping potential bearish transition. Often signals weakening bullish momentum and a potential bearish shift in structure.
LL to HL - Mapping potential bullish transition. Suggests buyers stepping in earlier and potential bullish momentum building.
HL to LH (or LH to HL) - these can indicate sideways structure — often in consolidating or compressing price action depending on custom steps.
HH to HH (or LL to LL) - Connecting successive HHs or LLs visualizes higher highs in uptrends or lower lows in downtrends — a classic trend-following perspective.
HL to HL (or LH to LH) - Connecting successive HLs (or LHs) can highlight the “internal” structure between impulse legs, often defining minor trend channels or short-term ranges within the larger trend.
iD EMARSI on ChartSCRIPT OVERVIEW
The EMARSI indicator is an advanced technical analysis tool that maps RSI values directly onto price charts. With adaptive scaling capabilities, it provides a unique visualization of momentum that flows naturally with price action, making it particularly valuable for FOREX and low-priced securities trading.
KEY FEATURES
1 PRICE MAPPED RSI VISUALIZATION
Unlike traditional RSI that displays in a separate window, EMARSI plots the RSI directly on the price chart, creating a flowing line that identifies momentum shifts within the context of price action:
// Map RSI to price chart with better scaling
mappedRsi = useAdaptiveScaling ?
median + ((rsi - 50) / 50 * (pQH - pQL) / 2 * math.min(1.0, 1/scalingFactor)) :
down == pQL ? pQH : up == pQL ? pQL : median - (median / (1 + up / down))
2 ADAPTIVE SCALING SYSTEM
The script features an intelligent scaling system that automatically adjusts to different market conditions and price levels:
// Calculate adaptive scaling factor based on selected method
scalingFactor = if scalingMethod == "ATR-Based"
math.min(maxScalingFactor, math.max(1.0, minTickSize / (atrValue/avgPrice)))
else if scalingMethod == "Price-Based"
math.min(maxScalingFactor, math.max(1.0, math.sqrt(100 / math.max(avgPrice, 0.01))))
else // Volume-Based
math.min(maxScalingFactor, math.max(1.0, math.sqrt(1000000 / math.max(volume, 100))))
3 MODIFIED RSI CALCULATION
EMARSI uses a specially formulated RSI calculation that works with an adaptive base value to maintain consistency across different price ranges:
// Adaptive RSI Base based on price levels to improve flow
adaptiveRsiBase = useAdaptiveScaling ? rsiBase * scalingFactor : rsiBase
// Calculate RSI components with adaptivity
up = ta.rma(math.max(ta.change(rsiSourceInput), adaptiveRsiBase), emaSlowLength)
down = ta.rma(-math.min(ta.change(rsiSourceInput), adaptiveRsiBase), rsiLengthInput)
// Improved RSI calculation with value constraint
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
4 MOVING AVERAGE CROSSOVER SYSTEM
The indicator creates a smooth moving average of the RSI line, enabling a crossover system that generates trading signals:
// Calculate MA of mapped RSI
rsiMA = ma(mappedRsi, emaSlowLength, maTypeInput)
// Strategy entries
if ta.crossover(mappedRsi, rsiMA)
strategy.entry("RSI Long", strategy.long)
if ta.crossunder(mappedRsi, rsiMA)
strategy.entry("RSI Short", strategy.short)
5 VISUAL REFERENCE FRAMEWORK
The script includes visual guides that help interpret the RSI movement within the context of recent price action:
// Calculate pivot high and low
pQH = ta.highest(high, hlLen)
pQL = ta.lowest(low, hlLen)
median = (pQH + pQL) / 2
// Plotting
plot(pQH, "Pivot High", color=color.rgb(82, 228, 102, 90))
plot(pQL, "Pivot Low", color=color.rgb(231, 65, 65, 90))
med = plot(median, style=plot.style_steplinebr, linewidth=1, color=color.rgb(238, 101, 59, 90))
6 DYNAMIC COLOR SYSTEM
The indicator uses color fills to clearly visualize the relationship between the RSI and its moving average:
// Color fills based on RSI vs MA
colUp = mappedRsi > rsiMA ? input.color(color.rgb(128, 255, 0), '', group= 'RSI > EMA', inline= 'up') :
input.color(color.rgb(240, 9, 9, 95), '', group= 'RSI < EMA', inline= 'dn')
colDn = mappedRsi > rsiMA ? input.color(color.rgb(0, 230, 35, 95), '', group= 'RSI > EMA', inline= 'up') :
input.color(color.rgb(255, 47, 0), '', group= 'RSI < EMA', inline= 'dn')
fill(rsiPlot, emarsi, mappedRsi > rsiMA ? pQH : rsiMA, mappedRsi > rsiMA ? rsiMA : pQL, colUp, colDn)
7 REAL TIME PARAMETER MONITORING
A transparent information panel provides real-time feedback on the adaptive parameters being applied:
// Information display
var table infoPanel = table.new(position.top_right, 2, 3, bgcolor=color.rgb(0, 0, 0, 80))
if barstate.islast
table.cell(infoPanel, 0, 0, "Current Scaling Factor", text_color=color.white)
table.cell(infoPanel, 1, 0, str.tostring(scalingFactor, "#.###"), text_color=color.white)
table.cell(infoPanel, 0, 1, "Adaptive RSI Base", text_color=color.white)
table.cell(infoPanel, 1, 1, str.tostring(adaptiveRsiBase, "#.####"), text_color=color.white)
BENEFITS FOR TRADERS
INTUITIVE MOMENTUM VISUALIZATION
By mapping RSI directly onto the price chart, traders can immediately see the relationship between momentum and price without switching between different indicator windows.
ADAPTIVE TO ANY MARKET CONDITION
The three scaling methods (ATR-Based, Price-Based, and Volume-Based) ensure the indicator performs consistently across different market conditions, volatility regimes, and price levels.
PREVENTS EXTREME VALUES
The adaptive scaling system prevents the RSI from generating extreme values that exceed chart boundaries when trading low-priced securities or during high volatility periods.
CLEAR TRADING SIGNALS
The RSI and moving average crossover system provides clear entry signals that are visually reinforced through color changes, making it easy to identify potential trading opportunities.
SUITABLE FOR MULTIPLE TIMEFRAMES
The indicator works effectively across multiple timeframes, from intraday to daily charts, making it versatile for different trading styles and strategies.
TRANSPARENT PARAMETER ADJUSTMENT
The information panel provides real-time feedback on how the adaptive system is adjusting to current market conditions, helping traders understand why the indicator is behaving as it is.
CUSTOMIZABLE VISUALIZATION
Multiple visualization options including Bollinger Bands, different moving average types, and customizable colors allow traders to adapt the indicator to their personal preferences.
CONCLUSION
The EMARSI indicator represents a significant advancement in RSI visualization by directly mapping momentum onto price charts with adaptive scaling. This approach makes momentum shifts more intuitive to identify and helps prevent the scaling issues that commonly affect RSI-based indicators when applied to low-priced securities or volatile markets.
VWAP Balance Zones - SessionsVWAP Balance Zones Sessions Version is an alternate take on the Original VWAP Balance Zones indicator. The Sessions version allows users to select a specific session to view the VWAP Balance Zones at while still utilizing the full ETH Data.
The Session version provides a better focused display while still maintaining the core functions of the original script with mindful optimizations.
Author's Note: "VBZ Sessions was made with logistics in mind, for the users who only trade within certain times of the day. While it displays the same core concepts, it is not as "Raw" of a display as the Original. For this reason, some users may prefer the Original VWAP Balance Zones, which is why I have opted to release this alternate version instead of updating the original."
> What are VWAP Balance Zones?
"VWAP Balance Zones" is an original concept aimed at identifying the equilibrium area between market participants within the current trend by averaging the Daily Extremes and the Daily VWAP.
Refer to the illustration below for a better understanding of exactly how VWAP Balance Zones are formed:
These zones are displayed for the Daily, Weekly, and Monthly VWAPs, with the most interactive timeframe being the Daily.
> Features
1. The Session Version uses ETH data at all times, and does not solely rely on the chart's data to create the VWAPs or Zones.
This allows the user to focus on a specific trading session, while not losing out on the full VBZ Calculation, with the notable benefit of a cleaner display.
The Original VBZ starts drawing at the beginning of the chart's "Day", and would produce different results when using an RTH chart vs an ETH chart. Along with creating a bird's nest of unusable data at the beginning of the day.
2. Session Start and End lines are displayed for easier identification of the designated trading session.
3. The extreme "Close" Lines are no longer displayed to reduce noise and redundancy.
4. Additionally, the interior VWAP lines are no longer displayed. Ultimately, this was to reduce noise and focus the script on the 50% zones.
5. Weekly and Monthly Zones are now displayed due to the reduced noise!
6. As with the original, the weekly display will yield to the daily, and the monthly display will yield to the weekly.
In the screenshot below, you can observe this behavior.
Enjoy!
ST -Dashboard Volume MTF , [Sese04]User Guide: ST - Dashboard Volume MTF
Introduction
This script displays a multi-timeframe (MTF) volume dashboard, tracking buy and sell volumes and the moving averages of volume. It is designed for traders using ICT (Inner Circle Trader) and SMC (Smart Money Concepts) to quickly visualize market dynamics across multiple timeframes.
Settings and Features
📌 User Inputs
Customizable settings allow traders to adjust the dashboard display and volume moving averages.
Volume Display per Timeframe
show_vol_1m: Show volume for 1-minute chart.
show_vol_5m: Show volume for 5-minute chart.
show_vol_15m: Show volume for 15-minute chart.
show_vol_1h: Show volume for 1-hour chart.
show_vol_4h: Show volume for 4-hour chart.
show_vol_1d: Show volume for 1-day chart.
Volume Moving Average Settings
ma_length_short: Length of the short-term moving average (default 5 periods).
ma_length_long: Length of the long-term moving average (default 14 periods).
Dashboard Customization
dashboard_position: Dashboard position (Bottom Right, Bottom Left, Top Right, Top Left).
text_color: Text color for the dashboard.
text_size: Text size (small, normal, large).
How the Script Works
🔹 1. Calculating Buy and Sell Volume
The calculate_buy_sell function separates buy and sell volume based on the candle's open and close price:
If the closing price is higher than the opening price → Buy volume 📈.
If the closing price is lower or equal to the opening price → Sell volume 📉.
🔹 2. Retrieving Volume Data Across Multiple Timeframes
The function get_volumes collects buy and sell volume data for different timeframes using request.security().
The available timeframes are: 1m, 5m, 15m, 1h, 4h, and 1d.
🔹 3. Calculating Volume Moving Averages
The script uses ta.sma() to compute moving averages for volume trends:
ma_vol_short: Short-term moving average (e.g., 5 periods).
ma_vol_long: Long-term moving average (e.g., 14 periods).
🔹 4. Creating and Displaying the Dashboard
A table (table.new()) is generated at the last bar (barstate.islast) to display the volume data:
A title “📊 Volume Dashboard (Buy vs Sell)” in purple.
Column headers:
TIMEFRAME (e.g., 1M, 5M, 15M, 1H, 4H, 1D).
BUY VOLUME (dark blue).
SELL VOLUME (dark red).
Buy and Sell Volume values are displayed in their respective cells for easy reading.
How to Use This Script on TradingView?
Adding the Script
Open TradingView.
Go to Pine Editor and paste the script.
Click "Add to Chart".
Configuring the Settings
Open the indicator settings.
Enable/disable the desired timeframes.
Adjust the moving average lengths if necessary.
Interpreting the Data
Increasing buy volume across timeframes may indicate bullish momentum.
Rising sell volume suggests a bearish reversal.
Crossovers of volume moving averages can help detect market shifts.
Conclusion
This script is a powerful tool for analyzing volume dynamics across multiple timeframes. It provides a quick overview of the balance between buyers and sellers, essential for ICT scalping and liquidity-based trading.
🚀 Pro Tip: Combine this dashboard with other SMC indicators (engulfing candles, pivot points) to refine your trading decisions.
Delta VolDelta Volume BTC - Multi Pair
Description The Delta Volume BTC - Multi Pair indicator visualizes the balance between buying and selling volume across multiple Bitcoin exchanges. By analyzing price action within each bar, it provides insight into underlying market pressure that traditional volume indicators miss. This indicator allows traders to:
Compare volume flow across Coinbase, Binance, and Binance Perpetual markets
Identify divergences between exchanges that may signal market shifts
Detect accumulation or distribution patterns through volume imbalances
View exchanges individually or in aggregate for comprehensive analysis
Calculation Methods The indicator offers three volume delta calculation methods:
VWAP Based (default):
price_range = high - low
buy_percent = (close - low) / price_range
sell_percent = (high - close) / price_range
delta = volume * (buy_percent - sell_percent)
This method distributes volume based on where price closed within the bar's range, providing a nuanced view of buying/selling pressure.
Tick Based :
delta = volume * sign(hlc3 - previous_hlc3)
This approach assigns volume based on the direction of typical price movement between bars, capturing momentum between periods.
Simple :
delta = close > open ? volume : close < open ? -volume : 0
A straightforward method that assigns positive volume to up bars and negative volume to down bars.
When Aggregate Mode is enabled, the indicator sums the volume deltas from all selected exchanges:
aggregate_delta = coinbase_delta + binance_delta + binance_perp_delta
Features
Multi-Exchange Support : Track volume delta across Coinbase, Binance, and Binance Perpetual futures
Advanced Calculation Methods : Choose between VWAP-based, tick-based, or simple volume delta algorithms
Flexible Display Options : Visualize as histogram, columns, area, or line charts
Customizable Colors : Distinct color schemes for each exchange and direction
Smoothing Options : Apply EMA, SMA, or WMA to reduce noise
Aggregate Mode : Combine all exchanges to see total market flow
How to Use
Individual Exchange Analysis : Uncheck "Aggregate Mode" to see each exchange separately, revealing where smart money may be positioning
Divergence Detection : Watch for one exchange showing buying while others show selling
Volume Trend Confirmation : Strong price moves should be accompanied by strong delta in the same direction
Liquidity Analysis : Compare spot vs futures volume delta to identify market sentiment shifts
The Delta Volume BTC - Multi Pair indicator helps identify the "hidden" buying and selling pressure that may not be apparent from price action alone, giving you an edge in understanding market dynamics across the Bitcoin ecosystem.
