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Quantitative Investing
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In this chapter, we introduce major concepts and layout of the book. The industrial practice of quantitative investing emerged in the 1960s developed rapidly in the 1990s and became on par with traditional fundamental investing in the 2000s. Naturally, mathematical and statistical modeling plays a critical role in quantitative investing. Major factors contributing to the development of quantitative strategies are the rise of modern investment theory, large-scale use of computers, greater availability of data sets, and development of programming languages. While building a successful quantitative strategy is not easy, it is achievable and requires a fundamental understanding of the market, strong knowledge of investment theory, mastery of quantitative methodologies, and proficiency in data analysis and programming. These constitute the four pillars of successful quantitative investment described in this book. In this chapter, we introduce quantitative investing and present a hall of fame for modern investment theory and quantitative methods. We then share industry insights with readers and briefly introduce R programming.

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  1. 1.

    We discuss the US stock market’s performance in Chap. 2.

  2. 2.

    I am very grateful to Dr. Ronald Kahn for the data and terms in his talk “Quant Investing: Past, Present, Future” in the 26th Annual Investment Seminar in London on September 10, 2012.

  3. 3.

    See the books by John Chambers and his co-authors.

  4. 4.

    R introduction by W.N. Venables, D.M. Smith and the R Core Team.


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Ma, L. (2020). Introduction. In: Quantitative Investing. Springer, Cham.

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