In 1952, Harry Markowitz introduced a critical innovation in investment management—popularly referred to as modern portfolio theory—in which he suggested that investors should decide the allocation of their investment funds on the basis of the trade-off between portfolio risk, as measured by the standard deviation of investment returns, and portfolio return, as measured by the expected value of the investment return. Entire new research areas grew from his groundbreaking idea, which, with the spread of low-cost powerful computers, found important practical applications in several fields of finance. Developing the necessary inputs for constructing portfolios based on modern portfolio theory has been facilitated by the development of Bayesian statistics, shrinkage techniques, factor models, and robust portfolio optimization. Modern quantitative techniques have now made it possible to manage large investment portfolios with computer programs that look for the best risk-return trade-off available in the market.

This book shows you how to perform quantitative equity portfolio management using these modern techniques. It skillfully presents state-of-the-art advances in the theory and practice of quantitative equity portfolio management. Page by page, the expert authors—who have all worked closely with hedge fund and quantitative asset management firms—cover the most up-to-date techniques, tools, and strategies used in the industry today.

They begin by discussing the role and use of mathematical techniques in finance, offering sound theoretical arguments in support of finance as a rigorous science. They go on to provide extensive background material on one of the principal tools used in quantitative equity management—financial econometrics—covering modern regression theory, applications of Random Matrix Theory, dynamic time series models, vector autoregressive models, and cointegration analysis. The authors then look at financial engineering, the pitfalls of estimation, methods to control model risk, and the modern theory of factor models, including approximate and dynamic factor models. After laying a firm theoretical foundation, they provide practical advice on optimization techniques and trading strategies based on factors and factormodels, offering a modern view on how to construct factor models.