I will backtest your crypto strategy in python and give a deploy verdict
Developer and designer building websites, apps, AI chatbots, automation
About this Gig
Your backtest looks great. Then fees, slippage, and overfitting quietly erase the edge, and you learn that with real money instead of before.
I backtest your crypto strategy in Python and give you a straight deploy / don't-deploy verdict. Not a sales pitch, a verdict.
What you get:
- Equity curve, win rate, max drawdown, return, and trade count on your pair and timeframe.
- Realistic fees and slippage modeled in, the costs that quietly kill a paper-perfect strategy.
- An overfitting / parameter-sensitivity check so a curve-fit fluke doesn't get mistaken for an edge.
- Premium adds full walk-forward / out-of-sample testing and a Streamlit dashboard.
Why trust me at zero reviews: I ran walk-forward on my own strategy, it failed, and I say so in my public README instead of hiding it. That repo, 105 automated tests, and a live AWS bot are all public. GitHub is linked on my profile.
I won't call a losing strategy a winner to make a sale. If it won't survive out-of-sample, you'll hear it from me, not your balance.
Send me your strategy and the pair/period to test, and I'll tell you the right package.
Platform:
Custom
•
Binance
Development technology:
Python
My Portfolio
FAQ
What do you use for backtesting?
Walk-forward / out-of-sample analysis with realistic fees and slippage modeled in. Dry-run only, no live keys ever touch an exchange.
Will you make my strategy profitable?
No. I test whether it already holds up and give an honest verdict. I won't pretend to "optimize" a broken edge to make a sale.
What do I need to send you?
Your strategy rules or code, the trading pair(s), the timeframe, and the date range to test. Code can be Python or a clear written description.
What if the result is bad?
You still get the full report and verdict, that's the deliverable. Knowing a strategy fails before you deploy it is worth the price.
