Overview of Quantitative Trading Strategies › Overview of Quantitative Trading Strategies

Quantitative trading changes in how investment decisions are made: replacing human intuition with mathematical models, statistical analysis, and systematic rules. Rather than relying on subjective judgments about which stocks to buy or sell, you develop algorithms that identify patterns in data, generate trading signals, and execute positions according to predefined rules.

This approach has grown from a niche practice in the 1970s to a dominant force in modern finance. Today, quantitative and algorithmic strategies account for the majority of trading volume in equity markets, and systematic approaches have expanded into fixed income, commodities, currencies, and cryptocurrency markets. Finding a pattern that predicts future returns allows you to capture profits consistently while managing risk precisely.

But quantitative trading is far more than simply building a model and letting it run. The most challenging aspects involve distinguishing predictive signals from statistical noise and avoiding the trap of overfitting historical data. You must also account for the gap between backtested performance and live trading results. This chapter provides the conceptual foundation for understanding how quantitative strategies work, how they're developed, and how to evaluate whether a strategy is likely to succeed.