Theory and Practice of Quantitative Investment Strategies

Abstract

This paper provides an overview of the theory and practice of quantitative investment strategies, beginning with the definition of quantitative investment, its history of development, and its importance in financial markets. It then delves into the theoretical foundations of quantitative investment, including financial market theory, the application of mathematical and statistical methods, and the theory of risk management and portfolio optimisation. Common quantitative investment strategies, such as spread trading, momentum strategy, mean reversion strategy, etc., are then detailed, as well as the design, implementation process and practical application of these strategies. Examples of successful and failed strategies are further analysed, as well as the challenges and problems faced, such as data quality, model overfitting, and market changes. Finally, future trends in quantitative investing are looked at, including the application of artificial intelligence and big data, advances in algorithmic trading, changes in the regulatory environment, and the impact of sustainable investing and ESG factors. This paper aims to provide investors, researchers and market regulators with a comprehensive understanding and outlook of quantitative investing.