Backtesting

Almanak launched its Agentic DeFi platform, where natural language lets 18 AI agents divide up the work to produce auditable, backtestable quant strategies that deploy on-chain, with funds staying in the user’s own Safe wallet the whole time. But the author warns that the Zodiac Role permission system only stops agents from moving funds around recklessly - it can’t guarantee the strategy itself is sound, and pretty backtest numbers can still just be an illusion of overfitting to historical price action.

This tutorial covers the five core steps of AI quantitative trading from scratch: data collection & cleaning, strategy design, backtesting, out-of-sample (OOS) validation, and deployment & monitoring. It explains three key advantages of AI over manual trading - emotional stability, processing speed, and consistency - and shares key techniques to avoid the backtest-to-live trading gap.

From an RSI idea to real money trading—where does AI actually speed things up, and where is it completely useless? Sharing our 5-line framework’s actual development journey and psychological hurdles.

87% annualized returns in backtesting? Congrats, but live trading is a completely different world. This article documents our quant system’s first month of real trading and the things backtests will never tell you.

A paper trading strategy with 87.5% apparent win rate fails statistical validation—Z-score yields p=0.24, no significant difference from coin flipping. Using Bayesian adjustment and Overfitting Index (OFI) with 33 real trades to establish a strategy validation logic that avoids the small-sample high-win-rate trap.

We developed a mean reversion strategy. Backtesting showed 3 out of 8 combinations hitting 100% win rate. Then we ran Out-of-Sample validation, and 100% crashed to 25%. Here’s what happened.

Why single-strategy systems are doomed to fail, how our four-strategy system auto-switches based on market regime, and why WFO validation is the quality gate you can’t skip.

We spent two weeks building a complete quantitative trading system from scratch — four strategies, eight Walk-Forward validations, Z-score statistical tests, Paper Trading. This article documents the entire process, including the biggest pitfalls we encountered.