The Blog, for everything in finance.
Guides, researches, and market ideas. Read them, or publish your own.
Guides, researches, and market ideas. Read them, or publish your own.
An honest guide to the best AI for trading in 2026 by category: chat assistants, AI powered backtesting, code generation, screeners, sentiment models and bots.
What is quantitative trading and how do I start? A beginner's guide to algo trading basics, the five parts of every system, and starting without code.
Sharpe ratio metrics for backtesters: what a good Sharpe looks like, why the deflated Sharpe ratio exists, and the six backtest numbers to read in order.
Where to place stop loss targets and take profit levels, what each method assumes, how to size risk per trade in R multiples, and how to backtest the exits.
Walk forward analysis explained: why the in sample vs out of sample split matters, how to read a result window by window, and how to run one without code.
What is backtesting in trading and why does it matter? What a backtest measures, how to run one step by step, and the questions no backtest can answer.

An honest audit of our own backtest corpus: 4,096 distinct strategies, how many were profitable, how few survived a minimum Sharpe and profit factor bar, and the paired test showing that switching on trading costs flipped one in five winners into losers.

A practical guide to backtesting a trading strategy without writing code: what a valid backtest requires, how to run one in plain English, and the mistakes that quietly invalidate your results.

How to backtest trading strategies on EGX stocks: the Egyptian Exchange's market structure quirks, where the data comes from, and how to adapt standard strategies to EGX conditions.

A good-looking backtest proves almost nothing. This guide covers real trading strategy validation: the multiple-testing problem, deflated Sharpe, walk-forward analysis, Monte Carlo, and why a DISCARD verdict is a feature.
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