Advances in Active Portfolio Management
Richard C. Grinold and Ronald N. Kahn
October 28, 2020
Our new book, Advances in Active Portfolio Management, is a companion and successor book to Active Portfolio Management. Articles and essays we have written—together and separately, mainly since the publication of Active Portfolio Management—compose the chapters in this book. Several of these articles won Bernstein Fabozzi/Jacobs Levy Awards for top articles in the Journal of Portfolio Management. We have chosen articles mainly along three dimensions: a recap of Active Portfolio Management, advancing the Active Portfolio Management framework, and applying the Active Portfolio Management framework to newer problems. For each article or group of related articles, we have added an introduction reviewing the material with the benefit of time and providing context and background useful for reading the articles. One emerging theme that cuts across these articles is optimal portfolio design. This includes topics ranging from the trade-off between information turnover and trading costs, identifying where the active opportunities are greatest, the desirability of separating smart beta from pure alpha, how we must coordinate risk level and gearing for optimal implementation, how we can overdiversify multistrategy funds with surprisingly negative consequences in bad market states, and insights into structuring fees.
Another theme that cuts across the dimensions of this book and connects it to our prior book is the track record of quantitative investing. This was a fairly small endeavor in 1995. Today, quantitative investing is a substantial activity, especially if we include indexing—non-active quantitative investing. On quantitative active management, our books and articles have helped democratize the framework and approach and helped inform many new entrants into the field, sometimes with negative consequences as in 2007 when too much money chased very similar ideas. Beyond measuring quantitative equity assets, another track record metric is the general level of interest in the field as measured by organizations, conferences, and journals now devoted to quantitative investing. By this very different measure, interest in the field appears healthy and robust.
The principles of quantitative active management are centered on the analysis of return, risk, and cost. These principles were developed and described in Active Portfolio Management. In Advances in Active Portfolio Management, we have restated those principles in a more contemporary idiom and presented significant advances in the area of product design, portfolio analytics, and dynamic portfolio management.
The framework continues to evolve. We now have access to vast new sources of data. The age of big data has arrived. This profusion of data is accompanied by—indeed made possible by—dramatic increases in computing power. Machine learning and other advanced techniques are available. The quantitative active manager who can use these powerful tools wisely will prevail in the difficult challenge of active portfolio management.