u/yaboiq27 ·
Reddit — r/algotrading
· June 16, 2026 at 16:46
· ⬆ 25 pts
· 💬 17 comments
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AI Summary
Summary
The author, a game developer, built a rule-based crypto trading bot using RSI, Fibonacci levels, and volume filters, tuned with a genetic algorithm and walk-forward testing.
Backtests claim 504% returns on trained coins and 250% on unseen coins over 5 years; bot is now in paper trading and moving to live on a Raspberry Pi.
No specific coins, market analysis, or external data are provided; the post is a progress update rather than a researched investment thesis.
Quality assessment: Speculation / self-promotion. The claims lack verifiable details, risk metrics, or peer review, and are based solely on the author’s own backtests.
Score25
Comments17
Upvote %77%
▶ Full Post Text
I'm a game programmer as my day job, and have been working on this crypto algo bot on my nights off and weekends for a few weeks now. After hours and hours of debugging, backtesting, and stopping the bot from seeing into the future I have this. 504% returns over the last 5 years on trained coins, and 250% on a sampling of untrained coins. I've also done many more tests not shown in this post, and they all look good. Running paper now then live on a Raspberry Pi, wish me luck!
Stack: Python bot on a Raspberry Pi, trading [Binance.US](http://Binance.US) spot (long-only) on 4h candles. Strategy is a rule-based cycle system (RSI, Fib levels, trend/volume/breadth filters, etc.) - not ML. Parameters were tuned with a genetic evolver and walk-forward fitness across multiple years (including 2022). One shared portfolio rotates across 6 coins with realistic fees/slippage in backtest. Live stack: CCXT for data/orders, FastAPI dashboard for monitoring. Charts shown are 2021–present backtests on coins the preset was trained on vs coins it never saw in evolution.