Two AI-assisted bots ran on real market data for months — one on Ethereum, one on Bitcoin — trying every popular way to outsmart the market. Here's exactly what happened, with nothing hidden.
Same engine, same AI, pointed at the two biggest coins. Click either to explore its results below.
Nothing here is hidden. The full source for both bots — the trading engine, every strategy, the reinforcement-learning optimiser, the Claude AI advisor and the backtests behind these verdicts — is open on GitHub: https://github.com/joubja/PaperTradingBot. Read it, run it, or check our numbers yourself.
We didn't just test one idea. Pick any popular strategy and see how it did across real crashes, slow bear markets, flat chop and bull runs — every trade charged a realistic fee and slippage.
Each card shows the money you'd actually have after the run. Beating buy-and-hold in a downturn just means losing less — not making money.
These weren't dumb bots. Each one carried a self-learning optimiser (a multi-armed bandit that rewarded settings that made money) and a Claude AI advisor reading the market. People assume that's the missing ingredient. It isn't — and here's the honest reason why.
No — and we won't pretend otherwise. What loses is the popular kind: bots that try to predict short-term price direction. On crypto, and by the same logic on forex and stocks, those lose to simply holding once you pay real fees — which is why the large majority of retail algo and day traders end up underwater.
The strategies that genuinely survive the data don't predict at all. They're market-neutral — long-short and pairs trades that harvest the price gap between related instruments, carry that collects a structural yield instead of betting on direction, and true arbitrage and market-making. Those edges are real. They're also small, fiercely competed by funds with scale and near-zero costs, and at retail fees usually get eaten before you see them. So: not "bots can't work" — rather, the bots being sold to you, the ones that promise to call the market, are the ones that don't.
We're not selling signals, courses, or a "profitable bot." Almost every prediction strategy we tested lost to simply holding once you pay real fees. The boring options — hold, dollar-cost-average, and (if you want yield without betting on direction) transparent market-neutral carry — are the ones that survive the data.
If this saved you money or a bad idea and you'd like to say thanks:
Rather just have the code? It's all free and open: https://github.com/joubja/PaperTradingBot.
Educational analysis of historical data — not financial advice. Past results don't predict the future.