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Trading product for VPOC MonteCarlo Expected Value Indicator BTCUSD Forex, image 1
VPOC MonteCarlo Expected Value
Indicator
416 downloads
Version 1.0, Mar 2026
Windows, Mac
Trading product for VPOC MonteCarlo Expected Value Indicator BTCUSD Forex, image 2
Trading product for VPOC MonteCarlo Expected Value Indicator BTCUSD Forex, image 3
Since 03/10/2024
171
Sales
42.68K
Free installs

Description

๐Ÿ“Š VPOC MONTE CARLO EXPECTED VALUE

https://chartshots.spotware.com/c/69c558e2c68df


Integrated Market Analysis: Volume Profile + Statistical Projection ๐ŸŽฏ


๐ŸŽฏ WHAT IS IT?


VPOC Monte Carlo Expected Value is a quantitative analysis indicator that combines two professional trading methodologies:

  • Market Depth Profile (VPOC) - Identifies where volume is truly concentrated ๐Ÿฆ
  • Monte Carlo Simulation - Projects future scenarios based on statistical probabilities ๐Ÿ“ˆ
    The result is an analysis system that tells you where the money is (Point of Control) and where itโ€™s likely to go (projected Expected Value) ๐Ÿง 

โš™๏ธ HOW DOES IT WORK?


Module 1: Depth Profile (VPOC) ๐Ÿ“Š


The indicator analyzes the last 200 bars (configurable) and distributes volume across 30 price levels. It calculates:

  • Point of Control (PoC): The price with the highest traded volume - represents market consensus where buyers and sellers were most active โš–๏ธ
  • Delta: Difference between buying vs selling pressure at each level ๐Ÿ”„
  • Heatmap: Visualization of activity concentration ๐Ÿ”ฅ
    The logic: Price tends to revert toward the PoC because thatโ€™s where most pending liquidity resides. If price is far from the PoC, thereโ€™s a higher probability of return ๐Ÿ”„

Module 2: Statistical Projection (Monte Carlo) ๐ŸŽฒ


Uses stochastic simulations (1,000 iterations by default) to project future price:

  • Calculates the assetโ€™s historical trend and annualized volatility ๐Ÿ“‰๐Ÿ“ˆ
  • Generates random paths using a normal distribution (geometric Brownian motion model) ๐ŸŒŠ
  • Estimates Expected Value with standard deviation bands (ยฑ1 sigma) ๐Ÿ“
    Formula applied:
  • Drift per bar = Annualized return / trading days ๐Ÿงฎ
  • Volatility per bar = Annualized volatility / โˆšdays โšก
  • Projection = Current price ร— e^(total drift + normal random ร— total volatility) ๐Ÿ”ข

Module 3: Synergy ๐Ÿ”—


Combines both analyses to generate contextual signals:
Table
Signal Condition Meaning
BULLISH โ†‘ ๐ŸŸข Price > PoC + Positive projection Bullish trend confirmed by volume
BEARISH โ†“ ๐Ÿ”ด Price < PoC + Negative projection Bearish trend confirmed by volume
OPPORTUNITY โ˜… ๐Ÿ’ก Price < PoC + Positive projection Possible bounce from volume support
DIVERGENCE โš ๏ธ โš ๏ธ Price > PoC + Negative projection Warning of possible reversal

๐Ÿ“ˆ WHAT IS IT USED FOR?
โœ… Identify key volume levels - The PoC acts as a price magnet ๐Ÿงฒ
โœ… Estimate probabilities of success - Percentage of winning scenarios in the simulation ๐Ÿ†
โœ… Evaluate risk/reward - Projected Sharpe ratio and standard deviation ๐Ÿ“Š
โœ… Confirm trade direction - Synergy between position relative to PoC and statistical momentum ๐ŸŽฏ
โœ… Target projection - Expected price levels for the defined hold period ๐ŸŽฏ

๐ŸŽฎ CONFIGURATION AND USE
Main Parameters:
Table
Group Parameter Default Description
Depth Profile Analysis Period 200 bars History to calculate volume profile
Price Levels 30 Profile resolution (more levels = more detail) ๐Ÿ”
Horizontal Offset 5 Profile position on the chart ๐Ÿ“
Statistical Projection Max Operation Duration 252 bars Time horizon of the projection โฑ๏ธ
Invested Capital $1,000 Base for monetary calculations ๐Ÿ’ฐ
Simulations 1,000 Number of random paths (more = more accurate, slower) ๐Ÿ”„
Risk-Free Rate 5% For Sharpe Ratio calculation ๐Ÿ“‰
Historical Strategy Use TP/SL No Activate to simulate with fixed targets ๐ŸŽฏ
How to Interpret the Results Table:
plain
Copy
EXPECTED VALUE STATISTICS
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚ Method โ”‚ $ Amountโ”‚ % Returnโ”‚ Win Rateโ”‚ Sharpe โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚ Historical โ”‚ -$19.56 โ”‚ -1.96% โ”‚ 47.2% โ”‚ -1.24 โ”‚
โ”‚ Simulation โ”‚ -$54.05 โ”‚ -5.40% โ”‚ 21.4% โ”‚ -4.95 โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

  • Historical: Average performance of similar past trades ๐Ÿ“œ
  • Simulation: Average result of the 1,000 Monte Carlo simulations ๐ŸŽฒ
  • Win Rate: Percentage of scenarios with positive outcome โœ…
  • Sharpe: Risk-adjusted return (greater than 1 is good, negative is bad) ๐Ÿ“ˆ

๐Ÿ–ผ๏ธ Visual Elements on the Chart
Table
Element Color Meaning
Volume profile Orange/blue gradient Activity concentration by price level ๐ŸŽจ
PoC line Blue dotted Point of Control projected into the future ๐Ÿ”ต
EV projection line Green/Magenta Expected price trajectory ๐ŸŸข๐Ÿ”ด
ยฑ1ฯƒ band White dotted lines 68% confidence range ๐Ÿ“Š
Historical EV line Green dotted Expected value based on historical data ๐ŸŸข
Projection zone Translucent blue fill Probability area between bands ๐Ÿ”ต

โš ๏ธ IMPORTANT - Limitations

  • Not a buy/sell signal - Itโ€™s a probabilistic analysis tool ๐Ÿ› ๏ธ
  • Monte Carlo simulations assume historical distribution holds (does not predict black swan events) ๐ŸฆขโŒ
  • The PoC is dynamic - Recalculates on each new bar ๐Ÿ”„
  • Requires sufficient history - Minimum 252 bars for reliable projections ๐Ÿ“Š
  • Cryptocurrencies - The indicator automatically adjusts to 365 annual trading days vs 252 for traditional markets ๐Ÿช™

๐Ÿ’ก Recommended Usage Strategy

  • Look for OPPORTUNITY โ˜… ๐Ÿ’ก - Price below PoC but with positive projection (possible undervaluation)
  • Confirm with Win Rate > 50% - Higher statistical probability of success โœ…
  • Avoid DIVERGENCE โš ๏ธ โš ๏ธ - Overvalued price relative to actual volume
  • Use PoC as a reference - Stops or targets around this liquidity level ๐ŸŽฏ
  • Compare Historical vs Simulation - If they differ greatly, the market regime is changing ๐Ÿ”„

 

 

Summary

AI summary
VPOC Monte Carlo Expected Value is a quantitative trading indicator that integrates Volume Profile analysis with Monte Carlo statistical projections to provide market insights. It analyzes recent price bars to identify the Point of Control (PoC)โ€”the price level with the highest traded volumeโ€”indicating where market liquidity concentrates. The indicator visualizes volume distribution, buying vs. selling pressure (Delta), and activity heatmaps to assess market depth.

Using Monte Carlo simulations with default 1,000 iterations, it projects future price scenarios based on historical trends and volatility, applying a geometric Brownian motion model. This generates expected price trajectories with confidence bands (ยฑ1 standard deviation), estimating probabilities of success, risk-adjusted returns (Sharpe ratio), and potential target levels.

The combined analysis produces contextual signals such as Bullish, Bearish, Opportunity, and Divergence, based on price relation to PoC and projection direction. It supports various markets including Forex, stocks, commodities, indices, and cryptocurrencies, adjusting parameters like trading days accordingly.

Key configurable settings include analysis period, profile resolution, simulation count, and risk-free rate. Visual elements on the chart display volume profiles, PoC lines, expected value projections, and confidence intervals. The tool is designed for probabilistic market assessment and trade confirmation rather than direct buy/sell signals.
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Since 03/10/2024
171
Sales
42.68K
Free installs