A Beginner's Overview of Common Quantitative Strategy Types

The world of quantitative trading includes many strategy types, each built on different market assumptions and using different logic to construct trading signals. Below is a conceptual introduction to several common strategy categories, intended to help beginners build foundational understanding. This content is purely educational and does not recommend any specific strategy. Trend-following strategies assume that once a price starts moving in a certain direction, there's a reasonable probability it will continue for some time. These strategies typically use tools like moving averages or momentum indicators to identify trend direction, entering positions in the direction of an established trend and exiting when the trend appears to be reversing. The logic is relatively intuitive, but this approach tends to generate more false signals in choppy, directionless markets. Mean-reversion strategies operate on the opposite assumption: that when a price or spread deviates from its "normal" level in the short term, it tends to revert back toward that mean. These strategies typically take a contrarian position when price deviates significantly from its historical average, betting on a reversion. They can be effective in range-bound markets, but if a deviation turns out to be structural or long-lasting, the mean-reversion assumption may no longer hold. Statistical arbitrage strategies typically focus on the price relationship between multiple correlated assets, using statistical methods to identify historically stable correlations or spread patterns, and trading when that relationship deviates abnormally, expecting to profit once the deviation corrects. These strategies place high demands on model rigor and data quality. Market-making strategies don't predict price direction at all. Instead, they place buy and sell orders simultaneously to capture the bid-ask spread, while managing inventory risk and market impact costs — commonly seen in liquidity-provision contexts. The categories above are conceptual introductions from a technical-logic perspective. Different strategies perform very differently under different market conditions, and logic that worked historically doesn't guarantee it will work in the future. This article makes no promise or recommendation regarding the profitability of any strategy.