I will backtest and validate your trading strategy in python
About this gig
Got a trading strategy idea but no real proof it works? I'll build a proper backtest in Python and give you honest numbers not a curve-fitted result that falls apart live.
What you get:
- Historical backtest on your strategy rules (your data, or I can source it as an add-on)
- Key stats: win rate, average R, expectancy, max drawdown, Sharpe
- Walk-forward testing so results aren't just fit to one period
- Optional Monte Carlo simulation to stress-test worst-case outcomes
- A clear written summary no jargon, just whether this works and how confident you should be
I recently validated a futures strategy this way across 16 years of data and multiple prop-firm risk models before trusting it with real capital that's the level of rigor I bring to yours.
Get to know Toast
Data driven proof for trading strategies, before you risk real money
- FromUnited Kingdom
- Member sinceJun 2026
- Avg. response time1 hour
Languages
English
My Portfolio
FAQ
Do I need to provide historical data?
Yes, if you have your own historical data, that's included in all packages. If you don't have data, I can source it for you as an add-on — sourcing quality data takes extra time depending on the instrument/timeframe.
What languages/platforms?
Python (pandas/numpy), can adapt to your broker's data format.
Can you help build the live/automated version after validation?
Yes, as a custom-quoted add-on.
What if the backtest shows the strategy doesn't work?
I'll tell you honestly — that's the point of the service. A "no" is still a valuable, money-saving result.
Can you tell me if this would pass a specific prop firm's challenge?
Yes, as an add-on (Premium package). I model your strategy against that firm's actual rules to estimate real pass rate and expected income, not just a generic assumption.

