1.1 Quantitative Trading

Quantitative trading refers to the use of advanced mathematical models to replace human

Quantitative trading refers to the use of advanced mathematical models to replace human subjective judgment. By leveraging computer technology, it sifts through vast amounts of historical data to identify a variety of "high-probability" events that can bring excess returns, thereby formulating strategies. This approach significantly reduces the impact of investors' emotional fluctuations and avoids irrational investment decisions made under extreme market euphoria or pessimism. Quantitative trading can also be referred to as "EA (Expert Advisor) intelligent trading."

Traditional investment methods rely entirely on the personal experience of investment managers, whose strategies are mainly divided into three types: fundamental analysis, technical analysis, and policy analysis. In contrast, quantitative investment primarily depends on statistical models and historical data to identify investment strategies and targets.

Of course, the quantitative approach of quantitative investment strategies is essentially the same as the qualitative investment of traditional trading strategies. Both are based on the weak-form efficient market hypothesis in economics. Investment managers can construct portfolios that generate excess returns by analyzing and researching various aspects of investment targets, such as fundamentals, growth potential, and valuation.

Traditional qualitative investment methods largely depend on the investigation and analysis of companies, and they also require the personal experience and subjective judgment of investment managers. However, quantitative investment is a process that quantifies traditional qualitative ideas.