The author, unlike many others, views Benjamin Graham’s work as the origin of quantitative investing. He reviews the history of quantitative investing and uses Graham’s investment methodology to introduce such concepts as alpha, the Sharpe ratio, and the Fama–French model.
The roots of value investing can be traced back to the 1934 publication of Benjamin Graham and David Dodd’s classic, Security Analysis. Graham later disseminated his views to the general public in the highly regarded book The Intelligent Investor. The influence of Graham’s methodology is indisputable. His disciples represent a virtual who’s who of value investors, including Warren Buffett, Bill Ruane, and Walter Schloss. As a measure of his enduring impact on the field, a search of “Benjamin Graham" on Amazon.com yields more than 900 results concerning Graham’s writings and works about his investment philosophy. Given the success of the master and his students, it is no wonder that Graham remains an investor of immense interest to practitioners.
The title Ben Graham Was a Quant: Raising the IQ of the Intelligent Investor (Wiley Finance) will probably cause readers to envision a book that traces Graham’s remarkable life and dissects his use of quantitative techniques that have become prevalent in modern finance. In reality, Steven P. Greiner has written a very different type of book. Greiner, the head of Risk Research for FactSet Research Systems, is the stereotypical Wall Street quant, holding a bachelor’s degree in mathematics and chemistry from the University of Buffalo and a PhD in physical chemistry from the University of Rochester. Greiner’s background in the hard sciences is evident in the quotations from either Albert Einstein or Isaac Newton at the beginning of nearly every chapter and in the author’s extensive use of examples from the hard sciences.
Throughout the book, Greiner pays homage to Graham, using his investment philosophy as the catalyst for examining quantitative investing. In the early chapters of the book, however, Greiner focuses mostly on his own view of quantitative investing. In spite of his strong quantitative background, he does a good job of making his ideas accessible to readers with a wide variety of backgrounds.
Greiner starts with a review of the history of quantitative investing. In most accounts, the story begins with Harry Markowitz’s seminal work on portfolio theory in 1952. For Greiner, however, the origins of quantitative investing date back earlier, to the work of Benjamin Graham. Greiner points out that Graham’s 1949 classic, The Intelligent Investor, lists seven criteria that defined the “quantitatively tested portfolio." These criteria include such factors as the size of the enterprise, earnings stability, financial condition, dividend record, earnings growth, price-to-earnings ratio, and price-to-book ratio. As Greiner points out, the definition of a quant as someone who designs and implements mathematical models for the pricing of securities does not mention the use of a computer.
As the pages go by, the link between Graham’s methodology and quantitative analysis becomes clearer. Chapters 4–6 begin to delve into the quantitative factors that Graham used in formulating his investment philosophy. Throughout these chapters, Greiner tests the empirical validity of Graham’s factors with a Fama–French type of model. Greiner criticizes the factors used by many MBAs that are linked to academic theories but may have no empirical validity. He writes, “Empiricism suggests the main drivers of stock returns are often market trading forces more than business financials." In testing Graham’s model, Greiner finds that such factors as book-to-price ratio, price-to-earnings ratio, and dividend yield do extremely well in predicting performance.
Using the Graham factors, Greiner goes on to build a factor model for predicting returns. Because he cannot confer with Graham on which factors to include in the model, Greiner does not use stepwise regression to identify the best ones. Rather, he elects to use all the factors in order to remain true to the Graham methodology. Throughout the book, Greiner provides numerous tables and graphs to document the effectiveness of the Graham factors in predicting security returns and to support the fundamental tenet of the book—that empiricism should trump theory in modeling security returns.
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