Volume Profile, Pivot Anchored by DGT - reviewedVolume Profile, Pivot Anchored by DGT - reviewed
This indicator, “Volume Profile, Pivot Anchored”, builds a volume profile between swing highs and lows (pivot points) to show where trading activity is concentrated.
It highlights:
Value Area (VAH / VAL) and Point of Control (POC)
Volume distribution by price level
Pivot-based labels showing price, % change, and volume
Optional colored candles based on volume strength relative to the average
Essentially, it visualizes how volume is distributed between market pivots to reveal key price zones and volume imbalances.
Statistics
Master Trend Strategy - by jake_thebossMaster Trend Strategy
This strategy combines multiple technical indicators to identify high-probability trend entries across all asset classes.
Core Signal Logic:
Entry triggered when EMA 4 crosses above/below EMA 5
Confirmation required from RSI (>50 for long, <50 for short)
Price must be above/below key moving averages: EMA 21, SMA 50, EMA 55, EMA 89, and EMA 750
Additional confirmation from Stochastic (>52 bullish, <48 bearish) or EMA 89 breakout or VWAP cross
Key Features:
VWAP filter: Only takes bullish signals above VWAP and bearish signals below VWAP
Optional pyramiding: Allows multiple entries in the same direction (up to 200 orders)
Individual stop loss and take profit management for each pyramid level
Time filter: Customizable trading hours with timezone offset
Risk management: Adjustable stop loss (default 0.3%) and take profit (default 0.6%)
Visualization:
Entry, stop loss, and take profit levels drawn as horizontal lines
Customizable signal markers (triangles) for bull/bear entries
Optional EMA overlay display
The strategy is designed for trend-following on lower timeframes, with strict multi-indicator confirmation to filter out false signals.
NY Session Range Box with Labeled Time MarkersShows opening time ny session by timing with lines to inform traders to avoid 11:30am to 1:30pm for choppy sessions and mark early and power hour .
Scalping m15 indicator RovTradingScalping Indicator Combining UT Bot and Linear Regression Candles.
UT Bot uses ATR Trailing Stop to identify entry points.
Linear Regression Candles smooth price action and provide trend signals.
The indicator is suitable for scalping trading on the M15 timeframe.
UTBotLibrary "UTBot"
is a powerful and flexible trading toolkit implemented in Pine Script. Based on the widely recognized UT Bot strategy originally developed by Yo_adriiiiaan with important enhancements by HPotter, this library provides users with customizable functions for dynamic trailing stop calculations using ATR (Average True Range), trend detection, and signal generation. It enables developers and traders to seamlessly integrate UT Bot logic into their own indicators and strategies without duplicating code.
Key features include:
Accurate ATR-based trailing stop and reversal detection
Multi-timeframe support for enhanced signal reliability
Clean and efficient API for easy integration and customization
Detailed documentation and examples for quick adoption
Open-source and community-friendly, encouraging collaboration and improvements
We sincerely thank Yo_adriiiiaan for the original UT Bot concept and HPotter for valuable improvements that have made this strategy even more robust. This library aims to honor their work by making the UT Bot methodology accessible to Pine Script developers worldwide.
This library is designed for Pine Script programmers looking to leverage the proven UT Bot methodology to build robust trading systems with minimal effort and maximum maintainability.
UTBot(h, l, c, multi, leng)
Parameters:
h (float) - high
l (float) - low
c (float)-close
multi (float)- multi for ATR
leng (int)-length for ATR
Returns:
xATRTS - ATR Based TrailingStop Value
pos - pos==1, long position, pos==-1, shot position
signal - 0 no signal, 1 buy, -1 sell
Nq/ES daily CME risk intervalReverse engineering the risk interval for CME (Chicago Mercantile Exchange) products based on margin requirements involves understanding the relationship between margin requirements, volatility, and the risk interval (price movement assumed for margin calculation)
The CME uses a methodology called SPAN (Standard Portfolio Analysis of Risk) to calculate margins. At a high level, the initial margin is derived from:
Initial Margin = Risk Interval × Contract Size × Volatility Adjustment Factor
Where:
Risk Interval: The price movement range used in the margin calculation.
Contract Size: The unit size of the futures contract.
Volatility Adjustment Factor: A measure of how much price fluctuation is expected, often tied to historical volatility.
To calculate an approximate of the daily CME risk interval, we need:
Initial Margin Requirement: Available on the CME Group website or broker platforms.
Contract Size: The size of one futures contract (e.g., for the S&P 500 E-mini, it is $50 × index points).
Volatility Adjustment Factor: This is derived from historical volatility or CME's implied volatility estimates.
As we do not have access to CME calculations , the volatility adjustment factor can be estimated using historical volatility: We calculate the standard deviation of daily returns over a specific period (e.g., 20 or 30 or 60 days).
Key Considerations
The exact formulas and parameters used by CME for CME's implied volatility estimates are proprietary, so this calculation based on standard deviation of daily returns is an approximation.
How to use:
Input the maintenance margin obtained from the CME website.
Adjust volatility period calculation.
The indicator displays the range high and low for the trading day.
1.Lines can be used as targets intraday
2.Market tends to snap back in between the lines and close the day in the range
Live Volume TickerGives current real-time volume of tick movements denoted in the timeframe of the current candle.
PPI Inflation Monitor (Change YoY & MoM)📊 PPI Inflation Monitor - Leading Inflation Indicator
The Producer Price Index (PPI) measures wholesale/producer-level prices and serves as a critical leading indicator for consumer inflation trends. This tool helps you anticipate CPI movements and identify corporate margin pressures before they show up in earnings.
🎯 KEY FEATURES:
- Dual Perspective Analysis:
- Year-over-Year (YoY): Histogram bars showing annual producer price inflation
- Month-over-Month (MoM): Line overlay showing monthly wholesale price changes
- Visual Reference System:
- Dashed line at 2% (typical target for producer price inflation)
- Dotted line at 0.17% (equivalent monthly target)
- Color-coded bars: Red above target, Green below target
- Real-Time Data Table:
- Current PPI Index value
- YoY inflation rate with color coding
- MoM inflation rate with color coding
- Deviation from target level
- Automated Alerts:
- YoY crosses above/below target
- MoM crosses above/below target
- Early warning system for inflation trends
📈 WHY PPI IS YOUR EARLY WARNING SYSTEM:
PPI typically leads CPI by 1-3 months because:
- Producers face cost increases first
- These costs are eventually passed to consumers
- Shows whether companies can maintain pricing power
Rising PPI with stable CPI = Margin compression → Bearish for stocks
Rising PPI followed by rising CPI = Broad inflation → Fed hawkishness incoming
Falling PPI = Disinflationary trend starting → Positive for risk assets
🔍 TRADING APPLICATIONS:
1. Lead Time Advantage: Position before CPI confirms PPI trends
2. Sector Rotation: High PPI = favor companies with pricing power
3. Margin Analysis: PPI-CPI divergence = margin pressure/expansion signals
4. Fed Anticipation: PPI acceleration = Fed likely to turn hawkish soon
💡 STRATEGIC USE CASES:
- Value vs. Growth: Rising PPI favors value stocks with pricing power
- Commodities: PPI often correlates with commodity price trends
- Small Caps: More vulnerable to input cost increases (high PPI = cautious)
- Corporate Earnings: Anticipate margin pressure before quarterly reports
🔄 COMBINE WITH:
- CPI: Confirm if producer costs reach consumers
- PCE: Validate Fed's preferred inflation metric response
- Fed Funds Rate: Assess if Fed is behind/ahead of curve
📊 DATA SOURCE:
Official PPI data from FRED (Federal Reserve Economic Data), updated monthly when new data releases occur.
🎨 CUSTOMIZATION:
Fully customizable:
- Toggle YoY/MoM displays
- Adjust reference target levels
- Customize colors
- Show/hide absolute PPI values
Perfect for: Macro traders, fundamental analysts, earnings traders, and investors seeking early inflation signals before they appear in consumer prices.
⚡ Remember: PPI leads CPI. Use this advantage to position ahead of the crowd.
PCE Inflation Monitor (Change YoY & MoM)📊 PCE Inflation Monitor - The Fed's Most Important Metric
Personal Consumption Expenditures (PCE) is the Federal Reserve's preferred inflation measure and THE metric they target for their 2% inflation goal. If you want to predict Fed policy, you need to watch PCE.
🎯 KEY FEATURES:
- Dual Perspective Analysis:
- Year-over-Year (YoY): Histogram bars showing annual PCE inflation
- Month-over-Month (MoM): Line overlay showing monthly consumption price changes
- Visual Reference System:
- Dashed line at 2% (Fed's official PCE inflation target)
- Dotted line at 0.17% (equivalent monthly target)
- Color-coded bars: Red above Fed target, Green below target
- Real-Time Data Table:
- Current PCE Index value
- YoY inflation rate vs. Fed's 2% target
- MoM inflation rate with color coding
- Exact deviation from Fed target (critical for policy predictions)
- Automated Alerts:
- PCE crosses Fed's 2% target (major policy signal!)
- MoM crosses monthly target
- Stay informed of Fed-relevant inflation changes
📈 WHY PCE IS DIFFERENT (AND MORE IMPORTANT):
PCE vs. CPI differences:
- Flexible basket: PCE adjusts for substitution (beef → chicken if prices rise)
- Broader coverage: Includes healthcare paid by insurance/government
- Lower readings: Typically 0.2-0.4% below CPI
- Fed's choice: Explicitly stated as their target metric
Most importantly: When Powell speaks about "our 2% target," he means PCE, not CPI!
🔍 TRADING IMPLICATIONS:
PCE Above 2% (Red Zone):
→ Fed under pressure to maintain/raise rates
→ Hawkish policy stance likely
→ Negative for growth stocks, crypto
→ Positive for USD, bearish for gold
PCE Below 2% (Green Zone):
→ Fed has flexibility to cut rates
→ Dovish policy stance possible
→ Positive for risk assets, growth stocks
→ Negative for USD, bullish for commodities
PCE Approaching 2% from Above:
→ Fed "mission accomplished" narrative
→ Rate cut cycle becomes possible
→ Major bullish signal for equities/crypto
💡 ADVANCED STRATEGIES:
1. Fed Meeting Preparation: Check PCE before FOMC meetings for policy clues
2. Dot Plot Predictions: PCE trend determines Fed's rate forecast updates
3. Pivot Timing: When PCE MoM turns negative, Fed pivot becomes realistic
4. Press Conference Analysis: Compare Powell's comments to PCE deviation
🎯 KEY LEVELS TO WATCH:
- 2.0% YoY: Fed's official target - crossing this level is major news
- 2.5% YoY: "Uncomfortably high" - Fed forced to stay restrictive
- 3.0% YoY: "Crisis mode" - Fed turns very hawkish
- 1.5% YoY: "Below target" - Rate cuts become likely
🔄 COMBINE WITH:
- CPI: Public perception vs. Fed's metric (often diverge)
- Core PCE: Even more important (excludes food/energy volatility)
- Fed Funds Rate: Is Fed responding appropriately to PCE?
📊 DATA SOURCE:
Official PCE data from FRED (Federal Reserve Economic Data), updated monthly typically in the last week of each month (after CPI/PPI releases).
🎨 CUSTOMIZATION:
Fully customizable:
- Toggle YoY/MoM displays
- Adjust Fed target if needed
- Customize colors
- Show/hide absolute PCE values
Perfect for: Fed watchers, macro traders, policy analysts, and serious investors who want to predict monetary policy changes before they happen.
⚠️ CRITICAL INSIGHT: While media focuses on CPI, the Fed focuses on PCE. Trade what the Fed trades, not what the headlines say.
🎓 Pro Tip: Fed members often mention "Core PCE" (excluding food/energy). Consider adding that indicator alongside this one for complete Fed policy analysis.
CPI Inflation Monitor (Change YoY & MoM)📊 CPI Inflation Monitor - Complete Macro Analysis Tool
This indicator provides a comprehensive view of Consumer Price Index (CPI) inflation trends, essential for understanding monetary policy, market conditions, and making informed trading decisions.
🎯 KEY FEATURES:
- Dual Perspective Analysis:
- Year-over-Year (YoY): Histogram bars showing annual inflation rate
- Month-over-Month (MoM): Line overlay showing monthly price changes
- Visual Reference System:
- Dashed line at 2% (Fed's official inflation target for YoY)
- Dotted line at 0.17% (equivalent monthly target for MoM)
- Color-coded bars: Red above target, Green below target
- Real-Time Data Table:
- Current CPI Index value
- YoY inflation rate with color coding
- MoM inflation rate with color coding
- Deviation from Fed target
- Automated Alerts:
- YoY crosses above/below 2% target
- MoM crosses above/below 0.17% target
- Perfect for staying informed without constant monitoring
📈 WHY THIS MATTERS FOR TRADERS:
CPI is the most widely reported inflation metric and directly influences:
- Federal Reserve interest rate decisions
- Bond yields and currency valuations
- Stock market sentiment (especially growth vs. value rotation)
- Cryptocurrency and risk asset performance
Rising inflation (red bars) typically leads to:
→ Higher interest rates → Negative for growth stocks, crypto
→ Stronger USD → Pressure on commodities
Falling inflation (green bars) typically leads to:
→ Rate cut expectations → Positive for growth stocks, crypto
→ Weaker USD → Support for commodities
🔍 HOW TO USE:
1. Strategic Positioning: Use YoY trend (thick bars) for long-term asset allocation
2. Tactical Timing: Use MoM trend (thin line) to identify turning points early
3. Divergence Trading: When MoM falls but YoY remains high, anticipate trend reversal
4. Fed Policy Prediction: Distance from 2% target indicates Fed's likely hawkishness
💡 PRO TIPS:
- Multiple months of MoM above 0.3% = Accelerating inflation → Fed turns hawkish
- MoM turning negative while YoY still elevated = Peak inflation → Position for pivot
- Compare with PPI and PCE indicators for complete inflation picture
- Use alerts to catch important threshold crossings automatically
📊 DATA SOURCE:
Official CPI data from FRED (Federal Reserve Economic Data), updated monthly mid-month when new data releases occur.
🎨 CUSTOMIZATION:
Fully customizable through settings:
- Toggle YoY/MoM displays
- Adjust target levels
- Customize colors for visual preference
- Show/hide absolute CPI values
Perfect for: Macro traders, swing traders, long-term investors, and anyone wanting to understand the inflation environment affecting their portfolio.
Note: This indicator works on any chart timeframe as it loads external monthly economic data.
CMF, RSI, CCI, MACD, OBV, Fisher, Stoch RSI, ADX (+DI/-DI)Eight normalized indicators are used in conjunction with the CMF, CCI, MACD, and Stoch RSI indicators. You can track buy and sell decisions by tracking swings. The zero line is for reversal tracking at -20, +20, +50, and +80. You can use any of the nine indicators individually or in combination.
Simplified Percentile ClusteringSimplified Percentile Clustering (SPC) is a clustering system for trend regime analysis.
Instead of relying on heavy iterative algorithms such as k-means, SPC takes a deterministic approach: it uses percentiles and running averages to form cluster centers directly from the data, producing smooth, interpretable market state segmentation that updates live with every bar.
Most clustering algorithms are designed for offline datasets, they require recomputation, multiple iterations, and fixed sample sizes.
SPC borrows from both statistical normalization and distance-based clustering theory , but simplifies them. Percentiles ensure that cluster centers are resistant to outliers , while the running mean provides a stable mid-point reference.
Unlike iterative methods, SPC’s centers evolve smoothly with time, ideal for charts that must update in real time without sudden reclassification noise.
SPC provides a simple yet powerful clustering heuristic that:
Runs continuously in a charting environment,
Remains interpretable and reproducible,
And allows traders to see how close the current market state is to transitioning between regimes.
Clustering by Percentiles
Traditional clustering methods find centers through iteration. SPC defines them deterministically using three simple statistics within a moving window:
Lower percentile (p_low) → captures the lower basin of feature values.
Upper percentile (p_high) → captures the upper basin.
Mean (mid) → represents the central tendency.
From these, SPC computes stable “centers”:
// K = 2 → two regimes (e.g., bullish / bearish)
=
// K = 3 → adds a neutral zone
=
These centers move gradually with the market, forming live regime boundaries without ever needing convergence steps.
Two clusters capture directional bias; three clusters add a neutral ‘range’ state.
Multi-Feature Fusion
While SPC can cluster a single feature such as RSI, CCI, Fisher Transform, DMI, Z-Score, or the price-to-MA ratio (MAR), its real strength lies in feature fusion. Each feature adds a unique lens to the clustering system. By toggling features on or off, traders can test how each dimension contributes to the regime structure.
In “Clusters” mode, SPC measures how far the current bar is from each cluster center across all enabled features, averages these distances, and assigns the bar to the nearest combined center. This effectively creates a multi-dimensional regime map , where each feature contributes equally to defining the overall market state.
The fusion distance is computed as:
dist := (rsi_d * on_off(use_rsi) + cci_d * on_off(use_cci) + fis_d * on_off(use_fis) + dmi_d * on_off(use_dmi) + zsc_d * on_off(use_zsc) + mar_d * on_off(use_mar)) / (on_off(use_rsi) + on_off(use_cci) + on_off(use_fis) + on_off(use_dmi) + on_off(use_zsc) + on_off(use_mar))
Because each feature can be standardized (Z-Score), the distances remain comparable across different scales.
Fusion mode combines multiple standardized features into a single smooth regime signal.
Visualizing Proximity - The Transition Gradient
Most indicators show binary or discrete conditions (e.g., bullish/bearish). SPC goes further, it quantifies how close the current value is to flipping into the next cluster.
It measures the distances to the two nearest cluster centers and interpolates between them:
rel_pos = min_dist / (min_dist + second_min_dist)
real_clust = cluster_val + (second_val - cluster_val) * rel_pos
This real_clust output forms a continuous line that moves smoothly between clusters:
Near 0.0 → firmly within the current regime
Around 0.5 → balanced between clusters (transition zone)
Near 1.0 → about to flip into the next regime
Smooth interpolation reveals when the market is close to a regime change.
How to Tune the Parameters
SPC includes intuitive parameters to adapt sensitivity and stability:
K Clusters (2–3): Defines the number of regimes. K = 2 for trend/range distinction, K = 3 for trend/neutral transitions.
Lookback: Determines the number of past bars used for percentile and mean calculations. Higher = smoother, more stable clusters. Lower = faster reaction to new trends.
Lower / Upper Percentiles: Define what counts as “low” and “high” states. Adjust to widen or tighten cluster ranges.
Shorter lookbacks react quickly to shifts; longer lookbacks smooth the clusters.
Visual Interpretation
In “Clusters” mode, SPC plots:
A colored histogram for each cluster (red, orange, green depending on K)
Horizontal guide lines separating cluster levels
Smooth proximity transitions between states
Each bar’s color also changes based on its assigned cluster, allowing quick recognition of when the market transitions between regimes.
Cluster bands visualize regime structure and transitions at a glance.
Practical Applications
Identify market regimes (bullish, neutral, bearish) in real time
Detect early transition phases before a trend flip occurs
Fuse multiple indicators into a single consistent signal
Engineer interpretable features for machine-learning research
Build adaptive filters or hybrid signals based on cluster proximity
Final Notes
Simplified Percentile Clustering (SPC) provides a balance between mathematical rigor and visual intuition. It replaces complex iterative algorithms with a clear, deterministic logic that any trader can understand, and yet retains the multidimensional insight of a fusion-based clustering system.
Use SPC to study how different indicators align, how regimes evolve, and how transitions emerge in real time. It’s not about predicting; it’s about seeing the structure of the market unfold.
Disclaimer
This indicator is intended for educational and analytical use.
It does not generate buy or sell signals.
Historical regime transitions are not indicative of future performance.
Always validate insights with independent analysis before making trading decisions.
Aggregated Open Interest Multi-Exchange (USD)This indicator aggregates Open Interest (OI) data from multiple major cryptocurrency exchanges into a single unified view in USD, using data available on TradingView. It automatically adapts to the asset you're viewing on the chart.
Features:
Aggregates OI from 7 major exchanges: Binance, Bybit, OKX, Bitget, Deribit, HTX, and Coinbase
All values converted to USD - unlike native OI which shows contracts/coins
Uses only data available on TradingView platform
Automatically detects the asset from your chart (BTC, ETH, SOL, etc.)
True apples-to-apples comparison across exchanges
Displays as candlesticks showing OI open, high, low, and close
Toggle exchanges on/off individually
Handles different contract types per exchange automatically
Why USD conversion matters:
Traditional OI indicators show values in contracts or crypto units, making it difficult to compare across exchanges. This indicator converts everything to USD, giving you the real dollar value of open positions across all exchanges.
How it works:
Simply add the indicator to any crypto perpetual futures chart. It will automatically fetch and aggregate OI data from all supported exchanges for that asset using TradingView's built-in data feeds, converting everything to USD.
Supported Exchanges:
Binance, Bybit, Bitget, HTX: USDT perpetuals
Deribit: BTC/ETH use USD contracts, others use USDC
OKX: Contract-based (automatically converted)
Coinbase: USDC perpetuals
Perfect for traders who want a comprehensive view of total market Open Interest in USD across exchanges using reliable TradingView data.
RPT Position Sizer🎯 Purpose
This indicator is a position sizing and stop-loss calculator designed to help traders instantly determine:
How many shares/contracts to buy,
How much risk (₹) they are taking per trade,
How much capital will be deployed, and
The precise stop-loss price level based on user-defined parameters.
It displays all key values in a compact on-chart table (bottom-left corner) for quick trade planning.
💡 Use Case
Perfect for discretionary swing traders, systematic position traders, and risk managers who want instant visual feedback of trade sizing metrics directly on the chart — eliminating manual calculations and improving discipline.
⚙️ Key Features
Dynamic Inputs
Trading Capital (₹) — total available capital for trading.
RPT % — risk-per-trade as a percentage of total capital.
SL % — stop-loss distance in percent below CMP (Current Market Price).
CMP Source — can be linked to close, hl2, etc.
Rounding Style — round position size to Nearest, Floor, or Ceil.
Decimals Show — control number formatting precision in the table.
Core Calculations
SL Points: CMP × SL%
SL Price: CMP − SL Points
Risk Amount (₹): Capital × RPT%
Position Size: Risk ÷ SL Points
Capital Used: Position Size × CMP
Clean On-Chart Table Display
Displays:
Trading Capital
RPT %
Risk Amount (₹)
Position Size (shares/contracts)
Capital Required (₹)
Stop-Loss % & SL Price
The table uses a minimalistic white-on-black design with clear labeling and rupee formatting for quick reference.
Data Window Integration
Plots hidden values (Position Size, Risk Amount, SL Points, Capital Used) for use in TradingView’s Data Window—ideal for strategy testing and exporting values.
Yuki Leverage RR Calculator**YUKI LEVERAGE RR CALCULATOR**
A professional-grade risk/reward calculator for leveraged crypto or forex trades.
Instantly visualizes entry, stop loss, targets, leverage, and risk-to-reward ratios — helping you plan precise positions with confidence.
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**WHAT IT DOES**
Calculates position value, quantity, stop-loss price, liquidation estimate, and per-target profit.
Displays everything in an on-chart table with optional price tags and alerts.
──────────────────────────────
**KEY FEATURES**
• Long / Short toggle (only one active at a time)
• Leverage-aware position sizing based on Position Cost ($) and Leverage
• Dynamic Stop Loss: input % → auto price + $ risk
• Up to 3 Take-Profit Targets with scaling logic
• Instant R:R ratios per target
• Liquidation estimate (approximation only)
• ENTRY / SL / T1 / T2 / T3 / LIQ visual tags
• Dark/Light mode, adjustable table and tag size
• Built-in alerts for Targets and Stop Loss
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**INPUTS**
• Long or Short selection
• Entry Price, Stop Loss %
• Target 1 / Target 2 / Target 3 + Take Profit %
• Position Cost ($), Leverage
• Visual preferences: show/hide table, table corner, font size, tag offset, text size
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**TABLE OUTPUTS**
Position Info: Type, Entry, Position Cost, Leverage, Value
Risk Section: Stop Loss %, Stop Loss Price, Total Risk ($), Liquidation % & Price
Targets 1–3: Profit ($), R:R, Take Profit ($), Runner % or PnL
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**ALERTS**
• Target 1 Hit – when price crosses T1
• Target 2 Hit – when price crosses T2
• Target 3 Hit – when price crosses T3
• Stop Loss Hit – triggers based on direction
(Use TradingView Alerts → Condition → Indicator → select desired alert)
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**HOW TO USE**
1. Choose Long or Short
2. Enter Entry Price, Stop Loss %, Position Cost, and Leverage
3. Add Targets 1–3 with optional Take Profit %
4. Adjust visuals as desired
5. Monitor table + alerts for live trade planning
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**NOTES**
• Liquidation values are estimates only
• Fees, slippage, and funding not included
• Designed for educational and planning purposes
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⚠️ **DISCLAIMER**
For educational use only — not financial advice.
Trading leveraged products involves high risk of loss.
Always confirm calculations with your exchange and trade responsibly.
Z-Score Momentum | MisinkoMasterThe Z-Score Momentum is a new trend analysis indicator designed to catch reversals, and shifts in trends by comparing the "positive" and "negative" momentum by using the Z-Score.
This approach helps traders and investors get unique insight into the market of not just Crypto, but any market.
A deeper dive into the indicator
First, I want to cover the "Why?", as I believe it will ease of the part of the calculation to make it easier to understand, as by then you will understand how it fits the puzzle.
I had an attempt to create a momentum oscillator that would catch reversals and provide high tier accuracy while maintaining the main part => the speed.
I thought back to many concepts, divergences between averages?
- Did not work
Maybe a MACD rework?
- Did not work with what I tried :(
So I thought about statistics, Standard Deviation, Z-Score, Sharpe/Sortino/Omega ratio...
Wait, was that the Z-Score? I only tried the For Loop version of it :O
So on my way back from school I formulated a concept (originaly not like this but to that later) that would attempt to use the Z-Score as an accurate momentum oscillator.
Many ideas were falling out of the blue, but not many worked.
After almost giving up on this, and going to go back to developing my strategies, I tried one last thing:
What if we use divergences in the average, formulated like a Z-score?
Surprise-surprise, it worked!
Now to explain what I have been so passionately yapping about, and to connect the pieces of the puzzle once and for all:
The indicator compares the "strength" of the bullish/bearish factors (could be said differently, but this is my "speach bubble", and I think this describes it the best)
What could we use for the "bullish/bearish" factors?
How about high & low?
I mean, these are by definitions the highest and lowest points in price, which I decided to interpret as: The highest the bull & bear "factors" achieved that bar.
The problem here is comparison, I mean high will ALWAYS > low, unless the asset decided to unplug itself and stop moving, but otherwise that would be unfair.
Now if I use my Z-score, it will get higher while low is going up, which is the opposite of what I want, the bearish "factor" is weaker while we go up!
So I sat on my ret*rded a*s for 25 minutes, completly ignoring the fact the number "-1" exists.
Surprise surprise, multiplying the Z-Score of the low by -1 did what I wanted!
Now it reversed itself (magically). Now while the low keeps going down, the bear factor increases, and while it goes up the bear factor lowers.
This was btw still too noisy, so instead of the classic formula:
a = current value
b = average value
c = standard deviation of a
Z = (a-b)/c
I used:
a = average value over n/2 period
b = average value over n period
c = standard deviation of a
Z = (a-b)/c
And then compared the Z-Score of High to the Z-Score of Low by basic subtraction, which gives us final result and shows us the strength of trend, the direction of the trend, and possibly more, which I may have not found.
As always, this script is open source, so make sure to play around with it, you may uncover the treasure that I did not :)
Enjoy Gs!
IB range + Breakout fibsThe IB High / Low + Auto-Fib indicator automatically plots the Initial Balance range and a Fibonacci projection for each trading day.
Define your IB start and end times (e.g., 09:30–10:30).
The indicator marks the IB High and IB Low from that session and extends them to the session close.
It keeps the last N days visible for context.
When price breaks outside the IB range, it automatically plots a Fibonacci retracement/extension from the opposite IB side to the breakout, using levels 0, 0.236, 0.382, 0.5, 0.618, 0.88, 1.
The Fib updates dynamically as the breakout extends, and labels are neatly aligned on the right side of the chart for clarity.
Ideal for traders who monitor Initial Balance breaks, range expansions, and Fibonacci reaction levels throughout the trading session.
Risk sizing toolHelps you manage risk per trade accurately.
Automatically adjusts position size if the stop-loss or account constraints are exceeded.
Gives a clear visual summary directly on your stock chart.
Prevents taking trades that are too large relative to your account.
Volume v4 (Dollar Value) by Koenigsegg📊 Volume v3 (Dollar Value) by Koenigsegg
🎯 Purpose:
Volume v3 (Dollar Value) by Koenigsegg transforms traditional raw-unit volume into dollar-denominated volume, revealing how much money actually flows through each candle.
Instead of measuring how many coins or contracts were traded, this version calculates the total traded value = volume × average price (hlc3), allowing traders to visually assess capital intensity and market participation within each move.
⚙️ Core Features
- Converts raw volume into USD-based traded value for each candle.
- Color-coded bars show bullish (green/teal) vs. bearish (red) activity.
- Built-in SMA and SMMA overlays highlight sustained shifts in value flow.
- Designed for visual clarity to support momentum, exhaustion, and divergence studies.
📖 How to Read It
Rising Dollar Volume — indicates growing market participation and strong capital flow, often aligning with impulsive waves in trend direction.
Falling Dollar Volume — signals waning interest or reduced participation, potentially hinting at correction or exhaustion phases.
Comparing Legs — when price makes new highs/lows but dollar volume weakens, it can reveal divergences between price movement and actual capital commitment.
SMA / SMMA Lines — use them to identify longer-term accumulation or depletion of market activity, separating short bursts from sustained inflows or outflows.
The goal is to visualize the strength of market moves in terms of capital energy, not just tick activity. This distinction helps traders interpret whether a trend is being driven by genuine money flow or low-liquidity drift.
⚠️ Disclaimer
This script is provided for research and educational purposes only.
It does not constitute financial advice, investment recommendations, or trading signals.
Always conduct your own analysis and manage your own risk when trading live markets.
The author accepts no liability for financial losses incurred from use of this tool.
🧠 Credits
Developed and published by Koenigsegg.
Written in Pine Script® v6, fully compliant with TradingView’s House Rules for Pine Scripts.
Licensed under the Mozilla Public License 2.0.
Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
