OPEN-SOURCE SCRIPT
Monte Carlo Risk Geometry Simulator [Aslan]
Thanks to KioseffTrading for the polyline retracing system and the plotting system as a whole🙏
♦️ What This Script Does
This is a Monte Carlo simulator for visualising and calculating the probability of a return based on risk geometry of the model (Risk %, RR, WR). It assesses the probability of returns by generating hundreds or thousands of possible outcomes using your win rate, risk-reward, and position sizing. Each line you see is a different plausible “future,” showing how your account could realistically evolve.
🔶 How To Use It
Input your strategy stats, run a large number of simulations, and focus on three things: how wide the equity curves spread, how deep drawdowns get, and the percentage of profitable outcomes. Then adjust your model and repeat.
🔷 Application in Prop Firm evaluations
Using the threshold system, you can see what risk geometry is most likely to pass a prop firm evaluation. Suprisingly, the most probable geometry for passing an eval can sometimes have a negative expected value!
♦️ Bottom Line
This script helps you move from “how much can I make?” to “how likely am I to profit?”
🔎 Monte Carlo Simulations Explained
Monte Carlo simulations are a method of modeling uncertainty by running many random versions of the same system to see all possible outcomes. In trading, instead of assuming one fixed result, it repeatedly simulates sequences of wins and losses based on your strategy’s statistics (like win rate and risk-reward). This creates a distribution of potential equity curves, showing not just what did happen, but could happen. It’s essentially a way to test probability and survival under randomness rather than relying on a single backtest. Monte Carlo simulations are widely used on quant trading desks around the world to model uncertainty, test strategy robustness, and estimate the probability distribution of trading outcomes under real-world randomness.
♦️ What This Script Does
This is a Monte Carlo simulator for visualising and calculating the probability of a return based on risk geometry of the model (Risk %, RR, WR). It assesses the probability of returns by generating hundreds or thousands of possible outcomes using your win rate, risk-reward, and position sizing. Each line you see is a different plausible “future,” showing how your account could realistically evolve.
🔶 How To Use It
Input your strategy stats, run a large number of simulations, and focus on three things: how wide the equity curves spread, how deep drawdowns get, and the percentage of profitable outcomes. Then adjust your model and repeat.
🔷 Application in Prop Firm evaluations
Using the threshold system, you can see what risk geometry is most likely to pass a prop firm evaluation. Suprisingly, the most probable geometry for passing an eval can sometimes have a negative expected value!
♦️ Bottom Line
This script helps you move from “how much can I make?” to “how likely am I to profit?”
🔎 Monte Carlo Simulations Explained
Monte Carlo simulations are a method of modeling uncertainty by running many random versions of the same system to see all possible outcomes. In trading, instead of assuming one fixed result, it repeatedly simulates sequences of wins and losses based on your strategy’s statistics (like win rate and risk-reward). This creates a distribution of potential equity curves, showing not just what did happen, but could happen. It’s essentially a way to test probability and survival under randomness rather than relying on a single backtest. Monte Carlo simulations are widely used on quant trading desks around the world to model uncertainty, test strategy robustness, and estimate the probability distribution of trading outcomes under real-world randomness.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
🚀 Trader / Developer
💎 Premium Indicators: aslanalgo.com
All content provided is solely educational material.
💎 Premium Indicators: aslanalgo.com
All content provided is solely educational material.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
🚀 Trader / Developer
💎 Premium Indicators: aslanalgo.com
All content provided is solely educational material.
💎 Premium Indicators: aslanalgo.com
All content provided is solely educational material.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.