Multi-Ticker Anchored CandlesMulti-Ticker Anchored Candles (MTAC) is a simple tool for overlaying up to 3 tickers onto the same chart. This is achieved by interpreting each symbol's OHLC data as percentages, then plotting their candle points relative to the main chart's open. This allows for a simple comparison of tickers to track performance or locate relationships between them.
> Background
The concept of multi-ticker analysis is not new, this type of analysis can be extremely helpful to get a gauge of the over all market, and it's sentiment. By analyzing more than one ticker at a time, relationships can often be observed between tickers as time progresses.
While seeing multiple charts on top of each other sounds like a good idea...each ticker has its own price scale, with some being only cents while others are thousands of dollars.
Directly overlaying these charts is not possible without modification to their sources.
By using a fixed point in time (Period Open) and percentage performance relative to that point for each ticker, we are able to directly overlay symbols regardless of their price scale differences.
The entire process used to make this indicator can be summed up into 2 keywords, "Scaling & Anchoring".
> Scaling
First, we start by determining a frame of reference for our analysis. The indicator uses timeframe inputs to determine sessions which are used, by default this is set to 1 day.
With this in place, we then determine our point of reference for scaling. While this could be any point in time, the most sensible for our application is the daily (or session) open.
Each symbol shares time, therefore, we can take a price point from a specified time (Opening Price) and use it to sync our analysis over each period.
Over the day, we track the percentage performance of each ticker's OHLC values relative to its daily open (% change from open).
Since each ticker's data is now tracked based on its opening price, all data is now using the same scale.
The scale is simply "% change from open".
> Anchoring
Now that we have our scaled data, we need to put it onto the chart.
Since each point of data is relative to it's daily open (anchor point), relatively speaking, all daily opens are now equal to each other.
By adding the scaled ticker data to the main chart's daily open, each of our resulting series will be properly scaled to the main chart's data based on percentages.
Congratulations, We have now accurately scaled multiple tickers onto one chart.
> Display
The indicator shows each requested ticker as different colored candlesticks plotted on top of the main chart.
Each ticker has an associated label in front of the current bar, each component of this label can be toggled on or off to allow only the desired information to be displayed.
To retain relevance, at the start of each session, a "Session Break" line is drawn, as well as the opening price for the session. These can also be toggled.
Note: The opening price is the opening price for ALL tickers, when a ticker crosses the open on the main chart, it is crossing its own opening price as well.
> Examples
In the chart below, we can see NYSE:MCD NASDAQ:WEN and NASDAQ:JACK overlaid on a NASDAQ:SBUX chart.
From this, we can see NASDAQ:JACK was the top gainer on the day. While this was the case, it also fell roughly 4% from its peak near lunchtime. Unlike the top gainer, we can see the other 3 tickers ended their day near their daily high.
In the explanations above, the daily timeframe is used since it is the default; however, the analysis is not constrained to only days. The anchoring period can be set to any timeframe period.
In the chart below, you can observe the Daily, Weekly, and Monthly anchored charts side-by-side.
This can be used on all tickers, timeframes, and markets. While a typical application may be comparing relevant assets... the script is not limited.
Below we have a chart tracking COMEX:GCV2026 , FX:EURUSD , and COINBASE:DOGEUSD on the AMEX:SPY chart.
While these tickers are not typically compared side-by-side, here it is simply a display of the capabilities of the script.
Enjoy!
Gestão de carteira
Relative Performance Analyzer [AstrideUnicorn]Relative Performance Analyzer (RPA) is a performance analysis tool inspired by the data comparison features found in professional trading terminals. The RPA replicates the analytical approach used by portfolio managers and institutional analysts who routinely compare multiple securities or other types of data to identify relative strength opportunities, make allocation decisions, choose the most optimal investment from several alternatives, and much more.
Key Features:
Multi-Symbol Comparison: Track up to 5 different symbols simultaneously across any asset class or dataset
Two Performance Calculation Methods: Choose between percentage returns or risk-adjusted returns
Interactive Analysis: Drag the start date line on the chart or manually choose the start date in the settings
Professional Visualization: High-contrast color scheme designed for both dark and light chart themes
Live Performance Table: Real-time display of current return values sorted from the top to the worst performers
Practical Use Cases:
ETF Selection: Compare similar ETFs (e.g., SPY vs IVV vs VOO) to identify the most efficient investment
Sector Rotation: Analyze which sectors are showing relative strength for strategic allocation
Competitive Analysis: Compare companies within the same industry to identify leaders (e.g., APPLE vs SAMSUNG vs XIAOMI)
Cross-Asset Allocation: Evaluate performance across stocks, bonds, commodities, and currencies to guide portfolio rebalancing
Risk-Adjusted Decisions: Use risk-adjusted performance to find investments with the best returns per unit of risk
Example Scenarios:
Analyze whether tech stocks are outperforming the broader market by comparing XLK to SPY
Evaluate which emerging market ETF (EEM vs VWO) has provided better risk-adjusted returns over the past year
HOW DOES IT WORK
The indicator calculates and visualizes performance from a user-defined starting point using two methodologies:
Percentage Returns: Standard total return calculation showing percentage change from the start date
Risk-Adjusted Returns: Cumulative returns divided by the volatility (standard deviation), providing insight into the efficiency of performance. An expanding window is used to calculate the volatility, ensuring accurate risk-adjusted comparisons throughout the analysis period.
HOW TO USE
Setup Your Comparison: Enable up to 5 assets and input their symbols in the settings
Set Analysis Period: When you first launch the indicator, select the start date by clicking on the price chart. The vertical start date line will appear. Drag it on the chart or manually input a specific date to change the start date.
Choose Return Type: Select between percentage or risk-adjusted returns based on your analysis needs
Interpret Results
Use the real-time table for precise current values
SETTINGS
Assets 1-5: Toggle on/off and input symbols for comparison (stocks, ETFs, indices, forex, crypto, fundamental data, etc.)
Start Date: Set the initial point for return calculations (drag on chart or input manually)
Return Type: Choose between "Percentage" or "Risk-Adjusted" performance.
Technology Stocks RSPSTechnology Stocks RSPS Indicator - TradingView Description
Overview
The Technology Stocks RSPS (Relative Strength Portfolio System) indicator is a sophisticated portfolio allocation tool designed specifically for technology sector stocks. It calculates relative strength positions and provides dynamic allocation recommendations based on technical price momentum analysis.
Key Features
- Relative Strength Analysis: Compares 15 major technology stocks and the XLK sector ETF
against each other and gold as a baseline
- Dynamic Portfolio Allocation: Automatically calculates optimal position sizes based on relative
performance
- Visual Portfolio Performance: Tracks cumulative portfolio returns with color-coded
performance indicators
- Customizable Table Display: Shows real-time allocation percentages and optional cash values
for each position
- Technical Momentum Filtering: Uses normalized indicators to identify strength and filter out
weak positions
Included Assets
Sector ETF: XLK
Major Tech Stocks: AAPL, MSFT, NVDA, AVGO, CRM, ORCL, CSCO, ADBE, ACN, AMD, IBM, INTC, NOW, TXN
Benchmark: Gold (TVC:GOLD)
How It Works
The indicator calculates a relative strength score for each asset by comparing it against:
Gold (baseline commodity)
All other technology stocks in the pool
The XLK sector ETF
Assets with positive relative strength receive portfolio allocations proportional to their strength scores. Weak or negative performers are automatically filtered out (allocated 0%).
Visual Elements
Red Area: Aggregate strength of major technology stocks
Navy Blue Area: Overall technical positioning index (TPI)
Performance Line: Cumulative portfolio return (blue = cash-heavy, red = equity-heavy)
Allocation Table: Bottom-left display showing current recommended positions
Important Limitations
This indicator primarily uses technical data and has significant limitations:
❌ No fundamental economic data (ISM, CLI, etc.)
❌ Limited monetary data - missing critical components:
comprehensive monetary data
Funding rates
Detailed bond spreads analysis
Collateral data
❌ No sentiment indicators
❌ No options flow or derivatives data
❌ No earnings or valuation metrics
The indicator focuses purely on price-based relative strength and technical momentum. Users should combine this tool with fundamental analysis, economic data, and proper risk management for complete investment decisions.
Settings
Plot Table: Toggle allocation table visibility
Use Cash: Enable to display dollar amounts based on portfolio size
Cash Amount: Set your total portfolio value for cash allocation calculations
Use Cases
Sector rotation within technology stocks
Relative strength-based portfolio rebalancing
Technical momentum screening for tech sector
Dynamic position sizing based on price trends
Technical Notes
The script avoids for-loops to reduce calculation errors and noise
Uses semi-individual calculations for each asset
Requires the Unicorpus/NormalizedIndicators/1 library for normalized momentum calculations
Maximum lookback: 100 bars
Disclaimer: This indicator is a technical tool only and should not be used as the sole basis for investment decisions. It does not incorporate fundamental, economic, or comprehensive monetary data. Always conduct thorough research and consider your risk tolerance before making investment decisions.
2s10s Bull/Bear Steepener/Flattener (Intraday bars)A simple indicator that tracks the curve of the US2y and US10y
Marcaj Ore 07:00 și 18:00 (Stabil v2)For backtesting and remember times that you can be active in the market.
Position Sizer (FinPip)Position Sizer (FinPip)
The Position Sizer (FinPip) indicator is a crucial, all-in-one risk management tool designed to calculate the precise trade size required to limit your risk to a predetermined percentage of your total account capital.
This indicator helps you consistently execute sound risk management, regardless of the instrument's volatility or the trade's price levels.
Key Features:
Calculates Position Size: Based on your configurable Account Capital, desired Risk Percentage (default 2.5%), and the price distance between your Entry and Stop-Loss levels.
Visual Trade Planning: Plots three clear levels directly on the chart for easy visualization:
Entry Price (Blue)
Stop-Loss Price (SL) (Red)
Profit Target (Lime Green, calculated using the Reward:Risk Ratio).
Custom Risk Management: Easily adjust the Risk Percentage and the Reward:Risk Ratio (default 4.0) in the indicator's settings.
Heads-Up Display (HUD): A clean, fixed table in the bottom-left corner of the chart clearly displays all calculated metrics, including your Required Position Size (in units/shares/contracts), Risk Amount, and Potential Profit.
How to Use:
Enter your Account Capital and desired Risk % in the settings panel.
Set your desired Entry Price and Stop-Loss Price.
The indicator immediately calculates and displays the exact number of units you need to trade to maintain your risk limit.
The Position Sizer (FinPip)The Position Sizer (FinPip) indicator is a crucial, all-in-one risk management tool designed to calculate the precise trade size required to limit your risk to a predetermined percentage of your total account capital.
This indicator helps you consistently execute sound risk management, regardless of the instrument's volatility or the trade's price levels.
Key Features:
Calculates Position Size: Based on your configurable Account Capital, desired Risk Percentage (default 2.5%), and the price distance between your Entry and Stop-Loss levels.
Visual Trade Planning: Plots three clear levels directly on the chart for easy visualization:
Entry Price (Blue)
Stop-Loss Price (SL) (Red)
Profit Target (Lime Green, calculated using the Reward:Risk Ratio).
Custom Risk Management: Easily adjust the Risk Percentage and the Reward:Risk Ratio (default 4.0) in the indicator's settings.
Heads-Up Display (HUD): A clean, fixed table in the bottom-left corner of the chart clearly displays all calculated metrics, including your Required Position Size (in units/shares/contracts), Risk Amount, and Potential Profit.
How to Use:
Enter your Account Capital and desired Risk % in the settings panel.
Set your desired Entry Price and Stop-Loss Price.
The indicator immediately calculates and displays the exact number of units you need to trade to maintain your risk limit.
Position Sizer (FinPip)The Position Sizer (FinPip) indicator is a crucial, all-in-one risk management tool designed to calculate the precise trade size required to limit your risk to a predetermined percentage of your total account capital.
This indicator helps you consistently execute sound risk management, regardless of the instrument's volatility or the trade's price levels.
Key Features:
Calculates Position Size: Based on your configurable Account Capital, desired Risk Percentage (default 2.5%), and the price distance between your Entry and Stop-Loss levels.
Visual Trade Planning: Plots three clear levels directly on the chart for easy visualization:
Entry Price (Blue)
Stop-Loss Price (SL) (Red)
Profit Target (Lime Green, calculated using the Reward:Risk Ratio).
Custom Risk Management: Easily adjust the Risk Percentage and the Reward:Risk Ratio (default 4.0) in the indicator's settings.
Heads-Up Display (HUD): A clean, fixed table in the bottom-left corner of the chart clearly displays all calculated metrics, including your Required Position Size (in units/shares/contracts), Risk Amount, and Potential Profit.
How to Use:
Enter your Account Capital and desired Risk % in the settings panel.
Set your desired Entry Price and Stop-Loss Price.
The indicator immediately calculates and displays the exact number of units you need to trade to maintain your risk limit.
Kill Zone GridCaca Poo-Poo Kill Zone (12pm–4pm) — Avoid the Death Hours
This indicator highlights the worst trading window of the day — the midday chop zone where liquidity dies, algo volume disappears, spreads widen, and your account slowly bleeds out from boredom and paper cuts.
From 12pm to 4pm (New York Time) the script:
• Shades the background with a bold kill-zone color
• Adds red gridline stripes to visually scream “STOP TRADING, YOU DONKEY”
• Makes the entire chart look hostile so you avoid revenge trading, boredom trading, and all forms of midday stupidity
Perfect for scalpers and trend traders who only want the clean morning moves and want a visual reminder to step away, go outside, touch grass, eat lunch, or hit the gym instead of forcing trades in garbage hours.
If you trade futures, options, or zero-day anything — this script will save you money, sanity, and years off your life.
Mini Checklist (Left-side, static)It's a mini checklist on the left side of the chart serving as a note for when you trade.
Pretty simple
calculator contracts MNQ PIPEGAVTRADESThis is a Risk Management indicator that calculates the exact contracts to trade based on your defined Max Risk ($) and Stop Loss Ticks.
It displays all key Position Sizing metrics (including Account Capital and Risk %) in a fixed table on the chart.
Price Drop CounterThe Price Drop Counter is a very basic statistical indicator.
See it as an analytical tool that tracks how many times an asset's price has dropped by a specified percentage from its recent peak within a defined date range.
The indicator monitors the highest price reached and counts each occurrence when the price falls by your chosen threshold, then resets its peak tracking point after each drop is registered.
Uses
Volatility Assessment: Measure how frequently significant price corrections occur during specific periods
Market Behavior Analysis: Compare drop frequency across different timeframes or market conditions
Risk Evaluation: Identify assets or periods with higher downside volatility
Historical Pattern Recognition: Study how often major pullbacks happened during bull or bear markets
Backtesting Support: Analyze how your strategy would perform based on the frequency of drawdowns
How to use it
Add the indicator to your TradingView chart
Configure the Percent Drop (%) to define your threshold (default: 10%). The indicator will count each time price falls by this percentage from the most recent high
IMPORTANT Set your Start Date and End Date to analyze a specific period of interest
The blue step-line plot shows the cumulative count of drops within your date range
Adjust the percentage threshold based on your analysis needs - use smaller values (2-5%) for more frequent signals or larger values (15-20%) for major corrections only
The counter resets its high-water mark after each qualifying drop, allowing it to track multiple sequential drops within the same period.
Rendement périodes (finary compass)Rendement sur une période donnée,
Outil de décision pour stratégie Momentum
Net Liquidity (WALCL - TGA - ON RRP)//@version=5
indicator("Net Liquidity (WALCL - TGA - ON RRP)", overlay=false, timeframe="W")
a = request.security("FRED:WALCL", "W", close) // Fed total assets (millions)
b = request.security("FRED:WTREGEN", "W", close) // TGA (millions)
c = request.security("FRED:RRPONTSYD","W", close) // ON RRP (millions)
netliq = (a - b - c) / 1000.0 // billions
plot(netliq, color=color.new(color.blue, 0), linewidth=2)
ATR Risk Display - Multi FuturesWhat This Does
I got tired of manually calculating my ATR stops and risk for different futures contracts, especially when switching between ES, NQ, and their micro versions. This indicator automatically detects what futures symbol you're trading and shows you the exact tick count and dollar risk for your stop loss.
The Problem It Solves
If you trade futures with ATR-based stops, you know the hassle:
Different contracts have different tick values
You need to calculate position risk in dollars
Switching between symbols means redoing all the math
Renko charts make it even more confusing since ATR needs to come from regular candles
This handles all of that automatically.
Key Features
Auto-detects futures symbols - ES, NQ, YM, RTY, GC, CL, and all the micros (MES, MNQ, etc.)
Shows everything you need in one line: ATR(timeframe) × multiplier = X ticks ($XXX)
Works on Renko charts - pulls ATR from regular timeframe charts (super important if you use Renko)
Adjustable position sizing - set your contract count and see total risk instantly
Clean, minimal display - just the info you need, no clutter
How to Use
Add it to any futures chart
Set your preferred ATR timeframe (I use 5-minute)
Set your ATR multiplier (I use 1.5x for my stops)
Set your contract size
That's it - the indicator handles the rest
The display will show something like: "ES ATR(5) × 1.5 = 12 ticks ($150)"
Settings Explained
ATR Timeframe: What timeframe to calculate ATR from (always uses regular candles, even on Renko)
ATR Multiplier: How many ATRs for your stop (1.5 is common, 2.0 for wider stops)
Number of Contracts: Your position size for risk calculation
Auto-Detect Symbol: Leave on unless you want to manually override
Supported Futures
Full size: ES, NQ, YM, RTY, GC, CL, ZB, ZN, 6E, 6J
Micros: MES, MNQ, MYM, M2K, MGC, MCL
Notes
Made this primarily for my own ES trading but figured others might find it useful
The tick values are based on standard CME specs
If you trade other futures, you can modify the code to add them
Works great alongside level indicators for risk management
Why This Exists
I use ATR trailing stops on all my trades and got tired of doing mental math every time I switched between charts or contracts. Especially useful if you trade both full-size and micro contracts - the risk difference is huge and easy to mess up.
Hope this helps your trading! Feel free to suggest improvements.
BEMFUNDING MAX LOT CALCULATION (Sakince)You can use this indicator to ensure you don't exceed the "Maximum Lot" limit. Because the required data varies from pair to pair, you should obtain the latest information from the BEM Funding platform.
Checklist (D1 / H4 / M15/30 BoS / VP / Fibo / S/R) This is a simple, visual checklist indicator that allows you to quickly assess how many of your strategy conditions are met, without affecting the chart itself. It is ideal for multi-timeframe strategies and point-by-point setup monitoring.
Tactical Holding [SwissAlgo]Tactical Holding
A visual framework for managing long-term positions across market cycles
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Purpose
Instead of holding a fixed position through all market conditions , you can use this framework to adjust your exposure tactically . By reducing positions during distribution phases and accumulating during favorable accumulation zones, you may end up holding more units of the asset over complete market cycles - even if you temporarily exit or reduce exposure during unfavorable periods. This approach aims to help you compound your holdings by taking advantage of market volatility rather than simply enduring it.
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Recommended Settings
Timeframe : Weekly (1W) chart
Chart Type : Standard candlesticks (select 'Bar' type Candles)
This indicator is designed for higher timeframe analysis. While it can be applied to other timeframes, the logic and signal generation are optimized for weekly charts to filter out short-term noise and focus on major market cycles.
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Key Features
♦ Market State Classification
The indicator aims to categorize potential market conditions into five color-coded states based on technical confluences:
* Bull (bright green): Multiple bullish indicators align
* Bull Retrace (teal): Bullish structure with temporary weakness
* Bull ⇆ Bear Reversal (yellow): Transitional phase between trends
* Bear (bright red): Multiple bearish indicators align
* Bear Retrace (Pale Red/Maroon): Bearish structure with temporary strength
♦ Visual Elements
* Candles change color based on the current market state
* A 50-period EMA tracks with the same color coding, providing visual trend context
* Small arrow markers appear when specific pattern conditions are met (zones for potential distribution or accumulation)
* A legend table (toggle on/off) explains the color system
* A label shows the current state name on the chart
♦ Pattern Recognition
The system monitors for two types of potential entry/exit zones:
1. State transition patterns after periods of market regime consistency
2. RSI divergence patterns (when price and momentum move in opposite directions)
♦ Customization
* Toggle the legend table visibility through settings
* All calculations are transparent and use standard technical analysis methods
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How It Works
Think of this indicator as a traffic light system for your portfolio:
♦ Green zones suggest the asset might be in an environment where long-term holders historically have remained invested
Bright green (Bull) : Multiple technical indicators align in a potentially strong bullish phase
Pale green (Bull Retrace) : Bullish structure remains intact, but momentum shows temporary weakness - often a pullback within an uptrend
♦ Red zones suggest conditions where long-term holders might consider reducing exposure or waiting for better entry points
Dark red (Bear) : Multiple technical indicators align in a potentially strong bearish phase
Pale red (Bear Retrace) : Bearish structure remains intact but shows temporary strength - often a bounce within a downtrend
♦ Yellow zones indicate the market is in transition between bull and bear regimes - a time for increased attention as the trend direction becomes uncertain
The system doesn't predict future prices. Instead, it helps you understand the current technical environment by doing the heavy lifting of analyzing multiple indicators at once and presenting them in a simple visual format.
Example: During the 2022 crypto bear market, the indicator would have displayed extended red periods, signaling defensive conditions for holders. When accumulation arrows appeared in late 2022-early 2023, it highlighted potential re-entry zones as the technical regime transitioned back toward green, before the 2024 recovery.
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Who This Is For
♦ Long-term investors who want to hold assets through cycles but prefer a systematic approach to position sizing and timing rather than buying and never selling .
♦ Portfolio managers looking for a visual tool to help determine when to increase or decrease exposure to specific assets based on technical regime changes.
♦ Swing traders on higher timeframes who want to align their positions with the broader market structure rather than fighting the trend.
This is not designed for:
* Day traders or scalpers
* Those seeking exact entry/exit prices
* Automated trading systems (this is a visual decision-support tool)
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Understanding the Visuals
When you apply Tactical Holding to a chart, you'll see:
1. Colored candles - Instantly see what market regime the asset is in
2. Colored EMA line (thick line) - Provides a dynamic support/resistance reference that changes color with market conditions
3. Small arrows (↑ ↓) - Mark bars where specific technical patterns complete
4. State label - Shows current market classification
5. Legend table (top right) - Quick reference guide for the color system
6. Warning banner (top center) - Reminds you to use weekly charts
The visual design prioritizes clarity over complexity. You should be able to glance at a chart and immediately understand the current technical environment.
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Important Limitations
This indicator cannot:
* Predict future price movements
* Guarantee profitable trades
* Work equally well on all assets or timeframes
* Replace your own research and risk management
Technical considerations:
* Divergence detection has a 3-bar confirmation lag (by design, to avoid false signals)
* State transitions require multiple technical confirmations, which may cause delayed reactions to rapid market changes
* The system is reactive, not predictive - it responds to price action after it occurs
* Performance varies significantly between trending assets (like Solana) and stable assets (like Apple)
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Practical Application
Consider using this indicator as one component of a broader investment framework:
♦ Understanding Position Context:
The color-coded states can help frame your thinking about current holdings:
Bull: Technical conditions that have historically been associated with sustained uptrends
Bull Retrace: Pullbacks within an overall bullish structure- these periods may offer opportunities to evaluate entry points or reassess existing positions
Reversal (Yellow): Transitional phases where the trend direction is unclear - periods that may warrant closer monitoring
Bear Retrace: Temporary strength within an overall bearish structure - rallies that historically have often faded
Bear: Technical conditions that have historically been associated with sustained downtrends
♦ Interpreting Signal Arrows:
Arrow markers indicate when specific technical pattern conditions have been met. These are observation points, not instructions:
A signal appearing doesn't mean immediate action is required
Treat arrows as prompts for further analysis rather than automatic triggers
Consider the broader context: fundamentals, your investment timeline, risk tolerance, and overall market conditions
Signals show when historical technical patterns have formed - not whether those patterns will lead to the same outcomes as in the past
The framework is designed to organize information visually, not to tell you what to do. Your investment decisions should incorporate this technical perspective alongside other factors relevant to your situation.
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Technical Methodology
For transparency, the indicator uses:
* RSI (14) with a 14-period SMA to assess momentum direction
* MACD (12,26,9) to confirm trend strength and histogram momentum
* Stochastic RSI with K and D line crossovers for additional confirmation
* 50-period EMA as the primary trend filter
* Linear regression-based slope analysis to detect flat/transitional periods
* Pivot-based divergence detection following standard technical analysis principles
All calculations use publicly available technical analysis formulas. Nothing is hidden or proprietary beyond the specific combination and weighting of these standard tools.
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Disclaimer
This indicator is an educational and analytical tool only. It is not financial advice.
* Trading and investing involve substantial risk of loss
* Past performance of any technical system does not indicate future results
* No indicator can predict market movements with certainty
* Always conduct your own research and consult with qualified financial professionals
* Never invest more than you can afford to lose
* The creators of this indicator are not responsible for any trading losses
* This tool is not affiliated with, endorsed by, or connected to TradingView, 3Commas, or any other trading platform
* Use of this indicator is at your own risk
Risk Management: Regardless of what any indicator shows, always use proper position sizing, stop losses, and risk management appropriate to your personal financial situation.
This indicator provides a framework for analysis. Your decisions, research, and risk management determine your results.
BTC CME Gaps Detector [SwissAlgo]BTC CME Gaps Detector
Track Unfilled Gaps & Identify Price Magnets
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Overview
The BTC CME Gap Detector identifies and tracks unfilled price gaps on any timeframe (1-minute recommended for scalping) to gauge potential trading bias.
Verify Gap Behavior Yourself : Use TradingView's Replay Mode on the 1-Minute chart to observe how the price interacts with gaps. Load the BTC1! ticker (Bitcoin CME Futures), enable Replay Mode, and play forward through time (for example: go back 15 days). You may observe patterns such as price frequently returning to fill gaps, nearest gaps acting as near-term targets, and gaps serving as potential support/resistance zones. Some gaps may fill quickly, while others may remain open for longer periods. This hands-on analysis lets you independently assess how gaps may influence price movement in real market conditions and whether you may use this indicator as a complement to your trading analysis.
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Purpose
Price gaps occur when there is a discontinuity between consecutive candles - when the current candle's low is above the previous candle's high (gap up), or when the current candle's high is below the previous candle's low (gap down).
This indicator identifies and tracks these gaps on any timeframe to help traders:
Identify gap zones that may attract price (potential "price magnets")
Monitor gap fill progression
Assess potential directional bias based on nearest unfilled gaps (long, short)
Analyze market structure and liquidity imbalances
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Why Use This Indicator?
Universal Gap Detection : Identifies all gaps on any timeframe (1-minute, hourly, daily, etc.)
Multi-Candle Mitigation Tracking : Detects gap fills that occur across multiple candles
Distance Analysis : Shows percentage distance to nearest bullish and bearish gaps
Visual Representation : Color-coded boxes indicate gap status (active vs. mitigated)
Age Filtering : Option to display only gaps within specified time periods (3/6/12/24 months), as older gaps may lose relevance
ATR-Based Sizing : Minimum gap size adjusts to instrument volatility to filter noise (i.e. small gaps)
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Trading Concept
Gaps represent price zones where no trading occurred. Historical market behavior suggests that unfilled gaps may attract price action as markets tend to revisit areas of incomplete price discovery. This phenomenon creates potential trading opportunities:
Bullish gaps (above current price) may act as upside targets where the price could move to fill the gap
Bearish gaps (below current price) may act as downside targets where price could move to fill the gap
The nearest gap often provides directional bias, as closer gaps may have a higher probability of being filled in the near term
This indicator helps quantify gap proximity and provides a visual reference for these potential target zones.
EXAMPLE
Step 1: Bearish Gaps Appear Below Price
Step 2: Price Getting Close to Fill Gap
Step 3: Gap Mitigated Gap
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Recommended Setup
Timeframe: 1-minute chart recommended for maximum gap detection frequency. Works on all timeframes (higher timeframes will show fewer, larger gaps).
Symbol: Any tradable instrument. Originally designed for BTC1! (CME Bitcoin Futures) but compatible with all symbols.
Settings:
ATR Length: 14 (default)
Min Gap Size: 0.5x ATR (adjust based on timeframe and noise level)
Gap Age Limit: 3 months (configurable)
Max Historical Gaps: 300 (adjustable 1-500)
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How It Works
Gap Detection : Identifies price discontinuities on every candle where:
Gap up: current candle low > previous candle high
Gap down: current candle high < previous candle low
Minimum gap size filter (ATR-based) eliminates insignificant gaps
Mitigation Tracking : Monitors when price touches both gap boundaries. A gap is marked as filled when the price has touched both the top and bottom of the gap zone, even if this occurs across multiple candles.
Visual Elements :
Green boxes: Unfilled gaps above current price (potential bullish targets)
Red boxes: Unfilled gaps below current price (potential bearish targets)
Gray boxes: Filled gaps (historical reference)
Labels: Display gap type, price level, and distance percentage
Analysis Table: Shows :
Distance % to nearest bullish gap (above price)
Distance % to nearest bearish gap (below price)
Trade bias (LONG if nearest gap is above, SHORT if nearest gap is below)
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Key Features
Detects gaps on any timeframe (1m, 5m, 1h, 1D, etc.)
Boxes extend 500 bars forward for active gaps, stop at the fill bar for mitigated gaps
Real-time distance calculations update on every candle
Configurable age filter removes outdated gaps
ATR multiplier ensures gap detection adapts to market volatility and timeframe
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Disclaimer
This indicator is provided for informational and educational purposes only.
It does not constitute financial advice, investment recommendations, or trading signals. The concept that gaps attract price is based on historical observation and does not guarantee future results.
Gap fills are not certain - gaps may remain unfilled indefinitely, or the price may reverse before reaching a gap. This indicator should not be used as the sole basis for trading decisions.
All trading involves substantial risk, including the potential loss of principal. Users should conduct their own research, apply proper risk management, test strategies thoroughly, and consult with qualified financial professionals before making trading decisions.
The authors and publishers are not responsible for any losses incurred through the use of this indicator.
Volatility-Targeted Momentum Portfolio [BackQuant]Volatility-Targeted Momentum Portfolio
A complete momentum portfolio engine that ranks assets, targets a user-defined volatility, builds long, short, or delta-neutral books, and reports performance with metrics, attribution, Monte Carlo scenarios, allocation pie, and efficiency scatter plots. This description explains the theory and the mechanics so you can configure, validate, and deploy it with intent.
Table of contents
What the script does at a glance
Momentum, what it is, how to know if it is present
Volatility targeting, why and how it is done here
Portfolio construction modes: Long Only, Short Only, Delta Neutral
Regime filter and when the strategy goes to cash
Transaction cost modelling in this script
Backtest metrics and definitions
Performance attribution chart
Monte Carlo simulation
Scatter plot analysis modes
Asset allocation pie chart
Inputs, presets, and deployment checklist
Suggested workflow
1) What the script does at a glance
Pulls a list of up to 15 tickers, computes a simple momentum score on each over a configurable lookback, then volatility-scales their bar-to-bar return stream to a target annualized volatility.
Ranks assets by raw momentum, selects the top 3 and bottom 3, builds positions according to the chosen mode, and gates exposure with a fast regime filter.
Accumulates a portfolio equity curve with risk and performance metrics, optional benchmark buy-and-hold for comparison, and a full alert suite.
Adds visual diagnostics: performance attribution bars, Monte Carlo forward paths, an allocation pie, and scatter plots for risk-return and factor views.
2) Momentum: definition, detection, and validation
Momentum is the tendency of assets that have performed well to continue to perform well, and of underperformers to continue underperforming, over a specific horizon. You operationalize it by selecting a horizon, defining a signal, ranking assets, and trading the leaders versus laggards subject to risk constraints.
Signal choices . Common signals include cumulative return over a lookback window, regression slope on log-price, or normalized rate-of-change. This script uses cumulative return over lookback bars for ranking (variable cr = price/price - 1). It keeps the ranking simple and lets volatility targeting handle risk normalization.
How to know momentum is present .
Leaders and laggards persist across adjacent windows rather than flipping every bar.
Spread between average momentum of leaders and laggards is materially positive in sample.
Cross-sectional dispersion is non-trivial. If everything is flat or highly correlated with no separation, momentum selection will be weak.
Your validation should include a diagnostic that measures whether returns are explained by a momentum regression on the timeseries.
Recommended diagnostic tool . Before running any momentum portfolio, verify that a timeseries exhibits stable directional drift. Use this indicator as a pre-check: It fits a regression to price, exposes slope and goodness-of-fit style context, and helps confirm if there is usable momentum before you force a ranking into a flat regime.
3) Volatility targeting: purpose and implementation here
Purpose . Volatility targeting seeks a more stable risk footprint. High-vol assets get sized down, low-vol assets get sized up, so each contributes more evenly to total risk.
Computation in this script (per asset, rolling):
Return series ret = log(price/price ).
Annualized volatility estimate vol = stdev(ret, lookback) * sqrt(tradingdays).
Leverage multiplier volMult = clamp(targetVol / vol, 0.1, 5.0).
This caps sizing so extremely low-vol assets don’t explode weight and extremely high-vol assets don’t go to zero.
Scaled return stream sr = ret * volMult. This is the per-bar, risk-adjusted building block used in the portfolio combinations.
Interpretation . You are not levering your account on the exchange, you are rescaling the contribution each asset’s daily move has on the modeled equity. In live trading you would reflect this with position sizing or notional exposure.
4) Portfolio construction modes
Cross-sectional ranking . Assets are sorted by cr over the chosen lookback. Top and bottom indices are extracted without ties.
Long Only . Averages the volatility-scaled returns of the top 3 assets: avgRet = mean(sr_top1, sr_top2, sr_top3). Position table shows per-asset leverages and weights proportional to their current volMult.
Short Only . Averages the negative of the volatility-scaled returns of the bottom 3: avgRet = mean(-sr_bot1, -sr_bot2, -sr_bot3). Position table shows short legs.
Delta Neutral . Long the top 3 and short the bottom 3 in equal book sizes. Each side is sized to 50 percent notional internally, with weights within each side proportional to volMult. The return stream mixes the two sides: avgRet = mean(sr_top1,sr_top2,sr_top3, -sr_bot1,-sr_bot2,-sr_bot3).
Notes .
The selection metric is raw momentum, the execution stream is volatility-scaled returns. This separation is deliberate. It avoids letting volatility dominate ranking while still enforcing risk parity at the return contribution stage.
If everything rallies together and dispersion collapses, Long Only may behave like a single beta. Delta Neutral is designed to extract cross-sectional momentum with low net beta.
5) Regime filter
A fast EMA(12) vs EMA(21) filter gates exposure.
Long Only active when EMA12 > EMA21. Otherwise the book is set to cash.
Short Only active when EMA12 < EMA21. Otherwise cash.
Delta Neutral is always active.
This prevents taking long momentum entries during obvious local downtrends and vice versa for shorts. When the filter is false, equity is held flat for that bar.
6) Transaction cost modelling
There are two cost touchpoints in the script.
Per-bar drag . When the regime filter is active, the per-bar return is reduced by fee_rate * avgRet inside netRet = avgRet - (fee_rate * avgRet). This models proportional friction relative to traded impact on that bar.
Turnover-linked fee . The script tracks changes in membership of the top and bottom baskets (top1..top3, bot1..bot3). The intent is to charge fees when composition changes. The template counts changes and scales a fee by change count divided by 6 for the six slots.
Use case: increase fee_rate to reflect taker fees and slippage if you rebalance every bar or trade illiquid assets. Reduce it if you rebalance less often or use maker orders.
Practical advice .
If you rebalance daily, start with 5–20 bps round-trip per switch on liquid futures and adjust per venue.
For crypto perp microcaps, stress higher cost assumptions and add slippage buffers.
If you only rotate on lookback boundaries or at signals, use alert-driven rebalances and lower per-bar drag.
7) Backtest metrics and definitions
The script computes a standard set of portfolio statistics once the start date is reached.
Net Profit percent over the full test.
Max Drawdown percent, tracked from running peaks.
Annualized Mean and Stdev using the chosen trading day count.
Variance is the square of annualized stdev.
Sharpe uses daily mean adjusted by risk-free rate and annualized.
Sortino uses downside stdev only.
Omega ratio of sum of gains to sum of losses.
Gain-to-Pain total gains divided by total losses absolute.
CAGR compounded annual growth from start date to now.
Alpha, Beta versus a user-selected benchmark. Beta from covariance of daily returns, Alpha from CAPM.
Skewness of daily returns.
VaR 95 linear-interpolated 5th percentile of daily returns.
CVaR average of the worst 5 percent of daily returns.
Benchmark Buy-and-Hold equity path for comparison.
8) Performance attribution
Cumulative contribution per asset, adjusted for whether it was held long or short and for its volatility multiplier, aggregated across the backtest. You can filter to winners only or show both sides. The panel is sorted by contribution and includes percent labels.
9) Monte Carlo simulation
The panel draws forward equity paths from either a Normal model parameterized by recent mean and stdev, or non-parametric bootstrap of recent daily returns. You control the sample length, number of simulations, forecast horizon, visibility of individual paths, confidence bands, and a reproducible seed.
Normal uses Box-Muller with your seed. Good for quick, smooth envelopes.
Bootstrap resamples realized returns, preserving fat tails and volatility clustering better than a Gaussian assumption.
Bands show 10th, 25th, 75th, 90th percentiles and the path mean.
10) Scatter plot analysis
Four point-cloud modes, each plotting all assets and a star for the current portfolio position, with quadrant guides and labels.
Risk-Return Efficiency . X is risk proxy from leverage, Y is expected return from annualized momentum. The star shows the current book’s composite.
Momentum vs Volatility . Visualizes whether leaders are also high vol, a cue for turnover and cost expectations.
Beta vs Alpha . X is a beta proxy, Y is risk-adjusted excess return proxy. Useful to see if leaders are just beta.
Leverage vs Momentum . X is volMult, Y is momentum. Shows how volatility targeting is redistributing risk.
11) Asset allocation pie chart
Builds a wheel of current allocations.
Long Only, weights are proportional to each long asset’s current volMult and sum to 100 percent.
Short Only, weights show the short book as positive slices that sum to 100 percent.
Delta Neutral, 50 percent long and 50 percent short books, each side leverage-proportional.
Labels can show asset, percent, and current leverage.
12) Inputs and quick presets
Core
Portfolio Strategy . Long Only, Short Only, Delta Neutral.
Initial Capital . For equity scaling in the panel.
Trading Days/Year . 252 for stocks, 365 for crypto.
Target Volatility . Annualized, drives volMult.
Transaction Fees . Per-bar drag and composition change penalty, see the modelling notes above.
Momentum Lookback . Ranking horizon. Shorter is more reactive, longer is steadier.
Start Date . Ensure every symbol has data back to this date to avoid bias.
Benchmark . Used for alpha, beta, and B&H line.
Diagnostics
Metrics, Equity, B&H, Curve labels, Daily return line, Rolling drawdown fill.
Attribution panel. Toggle winners only to focus on what matters.
Monte Carlo mode with Normal or Bootstrap and confidence bands.
Scatter plot type and styling, labels, and portfolio star.
Pie chart and labels for current allocation.
Presets
Crypto Daily, Long Only . Lookback 25, Target Vol 50 percent, Fees 10 bps, Regime filter on, Metrics and Drawdown on. Monte Carlo Bootstrap with Recent 200 bars for bands.
Crypto Daily, Delta Neutral . Lookback 25, Target Vol 50 percent, Fees 15–25 bps, Regime filter always active for this mode. Use Scatter Risk-Return to monitor efficiency and keep the star near upper left quadrants without drifting rightward.
Equities Daily, Long Only . Lookback 60–120, Target Vol 15–20 percent, Fees 5–10 bps, Regime filter on. Use Benchmark SPX and watch Alpha and Beta to keep the book from becoming index beta.
13) Suggested workflow
Universe sanity check . Pick liquid tickers with stable data. Thin assets distort vol estimates and fees.
Check momentum existence . Run on your timeframe. If slope and fit are weak, widen lookback or avoid that asset or timeframe.
Set risk budget . Choose a target volatility that matches your drawdown tolerance. Higher target increases turnover and cost sensitivity.
Pick mode . Long Only for bull regimes, Short Only for sustained downtrends, Delta Neutral for cross-sectional harvesting when index direction is unclear.
Tune lookback . If leaders rotate too often, lengthen it. If entries lag, shorten it.
Validate cost assumptions . Increase fee_rate and stress Monte Carlo. If the edge vanishes with modest friction, refine selection or lengthen rebalance cadence.
Run attribution . Confirm the strategy’s winners align with intuition and not one unstable outlier.
Use alerts . Enable position change, drawdown, volatility breach, regime, momentum shift, and crash alerts to supervise live runs.
Important implementation details mapped to code
Momentum measure . cr = price / price - 1 per symbol for ranking. Simplicity helps avoid overfitting.
Volatility targeting . vol = stdev(log returns, lookback) * sqrt(tradingdays), volMult = clamp(targetVol / vol, 0.1, 5), sr = ret * volMult.
Selection . Extract indices for top1..top3 and bot1..bot3. The arrays rets, scRets, lev_vals, and ticks_arr track momentum, scaled returns, leverage multipliers, and display tickers respectively.
Regime filter . EMA12 vs EMA21 switch determines if the strategy takes risk for Long or Short modes. Delta Neutral ignores the gate.
Equity update . Equity multiplies by 1 + netRet only when the regime was active in the prior bar. Buy-and-hold benchmark is computed separately for comparison.
Tables . Position tables show current top or bottom assets with leverage and weights. Metric table prints all risk and performance figures.
Visualization panels . Attribution, Monte Carlo, scatter, and pie use the last bars to draw overlays that update as the backtest proceeds.
Final notes
Momentum is a portfolio effect. The edge comes from cross-sectional dispersion, adequate risk normalization, and disciplined turnover control, not from a single best asset call.
Volatility targeting stabilizes path but does not fix selection. Use the momentum regression link above to confirm structure exists before you size into it.
Always test higher lag costs and slippage, then recheck metrics, attribution, and Monte Carlo envelopes. If the edge persists under stress, you have something robust.
ICT Sessions Ranges [SwissAlgo]ICT Session Ranges - ICT Liquidity Zones & Market Structure
OVERVIEW
This indicator identifies and visualizes key intraday trading sessions and liquidity zones based on Inner Circle Trader (ICT) methodology (AM, NY Lunch Raid, PM Session, London Raid). It tracks 'higher high' and 'lower low' price levels during specific time periods that may represent areas where market participants have placed orders (liquidity).
PURPOSE
The indicator helps traders observe:
Session-based price ranges during different market hours
Opening range gaps between market close and next day's open
Potential areas where liquidity may be concentrated and trigger price action
SESSIONS TRACKED
1. London Session (02:00-05:00 ET): Tracks price range during early London trading hours
2. AM Session (09:30-12:00 ET): Tracks price range during the morning New York session
3. NY Lunch Session (12:00-13:30 ET): Tracks price range during typical low-volume lunch period
4. PM Session (13:30-16:00 ET): Tracks price range during the afternoon New York session
CALCULATIONS
Session High/Low: The highest high and lowest low recorded during each active session period
Opening Range Gap: Calculated as the difference between the previous day's 16:00 close and the current day's 09:30 open
Gap Mitigation: A gap is considered mitigated when the price reaches 50% of the gap range
All times are based on America/New_York timezone (ET)
BACKGROUND INDICATORS
NY Trading Hours (09:30-16:00 ET): Optional gray background overlay
Asian Session (20:00-23:59 ET): Optional purple background overlay
VISUAL ELEMENTS
Horizontal lines mark session highs and lows
Subtle background boxes highlight each session range
Labels identify each session type
Orange shaded boxes indicate unmitigated opening range gaps
Dotted line at 50% gap level shows mitigation threshold
FEATURES
Toggle visibility for each session independently
Customizable colors for each session type
Automatic removal of mitigated gaps
All drawing objects use transparent backgrounds for chart clarity
ICT CONCEPTS
This tool relates to concepts discussed by Inner Circle Trader regarding liquidity pools, session-based analysis, and gap theory. The indicator assumes that session highs and lows may represent areas where liquidity is concentrated, and that opening range gaps may attract price until mitigated.
USAGE NOTES
Best used on intraday timeframes (1-15 minute charts)
All sessions are calculated based on actual price movement during specified time periods
Historical session data is preserved as new sessions develop
Gap detection only triggers at 09:30 ET market open
DISCLAIMER
This indicator is for educational and informational purposes only. It displays historical price levels and time-based calculations. Past performance of price levels is not indicative of future results. The identification of "liquidity zones" is a theoretical concept and does not guarantee that orders exist at these levels or that prices will react to them. Trading involves substantial risk of loss. Users should conduct their own analysis and risk assessment before making any trading decisions.
TIME ZONE
Set your timezone to: America/New_York (UTC-5)
Position Sizer (% of Acct & Shares Req)
This indicator calculates % position size and share quantity required based on total capital and user-defined risk percentages
This indicator differs from the Shares Qty indicator in that it is based on %'s rather than a user-defined, fixed dollar amount to risk (for those who prefer to calculate risk in this manner instead)
Tracks real-time Low of Day (LoD) during regular trading hours (RTH) for accurate stop placement
Current price as well as output rows 2 and 3 can be toggled on/off, per preference
Allows stop loss selection between LoD, Low of Week (LoW), and Prior Day Low (PDL)
Keeps data updating intraday to reflect changing LoD and price conditions
Provides a second “Stop Loss Compare” dropdown to compare two stop methods side by side
Displays all results in a dynamic on-chart table that updates with live prices
Shows capital amount, stop type, stop price, and share counts for three risk levels
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Risk rows displayed as: Risk of Cap Amt: ,
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Disclaimer:
This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis, proper risk management techniques, and consider your individual trading plan and risk tolerance. All calculations and outputs are provided as-is, and it is your responsibility to verify their accuracy before making any trading decisions.
Aquantprice: Institutional Structure MatrixSETUP GUIDE
Open TradingView
Go to Indicators
Search: Aquantprice: Institutional Structure Matrix
Click Add to Chart
Customize:
Min Buy = 10, Min Sell = 7
Show only PP, R1, S1, TC, BC
Set Decimals = 5 (Forex) or 8 (Crypto)
USE CASES & TRADING STRATEGIES
1. CPR Confluence Trading (Most Popular)
Rule: Enter when ≥3 timeframes show Buy ≥10/15 or Sell ≥7/13
text Example:
Daily: 12/15 Buy
Weekly: 11/15 Buy
Monthly: 10/15 Buy
→ **STRONG LONG BIAS**
Enter on pullback to nearest **S1 or L3**
2. Hot Zone Scalping (Forex & Indices)
Rule: Trade only when price is in Hot Zone (closest 2 levels)
text Hot: S1-PP → Expect bounce or breakout
Action:
- Buy at S1 if Buy Count ↑
- Sell at PP if Sell Count ↑
3. Institutional Reversal Setup
Rule: Price at H3/L3 + Reversal Condition
text Scenario:
Price touches **Monthly L3**
L3 in **Hot Zone**
Buy Count = 13/15
→ **High-Probability Reversal Long**
4. CPR Width Filter (Avoid Choppy Markets)
Rule: Trade only if CPR Label = "Strong Trend"
text CPR Size < 0.25 → Trending
CPR Size > 0.75 → Sideways (Avoid)
5. Multi-Timeframe Bias Dashboard
Use "Buy" and "Sell" columns as a sentiment meter
TimeframeBuySellBiasDaily123BullishWeekly89BearishMonthly112Bullish
→ Wait for alignment before entering
HOW TO READ THE TABLE
Column Meaning Time frame D, W, M, 3M, 6M, 12MOpen Price Current session open PP, TC, BC, etc. Pivot levels (color-coded if in Hot Zone) Buy X/15 conditions met (≥10 = Strong Buy)Sell X/13 conditions met (≥7 = Strong Sell)CPR Size Histogram + Label (Trend vs Range)Zone Hot: PP-S1, Med: S2-L3, etc. + PP Distance
PRO TIPS
Best on 5M–1H charts for entries
Use with volume or order flow for confirmation
Set alerts on Buy ≥12/15 or Sell ≥10/13
Hide unused levels to reduce clutter
Combine with AQuantPrice Dashboard (Small TF) for full system
IDEAL MARKETS
Forex (EURUSD, GBPUSD, USDJPY)
Indices (NAS100, SPX500, DAX)
Crypto (BTC, ETH – use 6–8 decimals)
Commodities (Gold, Oil)
🚀 **NEW INDICATOR ALERT**
**Aquantprice: Institutional Structure Matrix**
The **ALL-IN-ONE CPR Dashboard** used by smart money traders.
✅ **6 Timeframes in 1 Table** (Daily → Yearly)
✅ **15 Buy + 13 Sell Conditions** (Institutional Logic)
✅ **Hot Zones, CPR Width, PP Distance**
✅ **Fully Customizable – Show/Hide Any Level**
✅ **Real-Time Zone Detection** (Hot, Med, Low)
✅ **Precision up to 8 Decimals**
**No more switching charts. No more confusion.**
See **where institutions are positioned** — instantly.
👉 **Add to Chart Now**: Search **"Aquantprice: Institutional Structure Matrix"**
🔥 **Free Access | Pro-Level Insights**
*By AQuant – Trusted by 10,000+ Traders*
#CPR #PivotTrading #SmartMoney #TradingView
FINAL TAGLINE
"See What Institutions See — Before They Move."
Aquantprice: Institutional Structure Matrix
Your Edge. One Dashboard.
