A Review of Quantitative Value

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In their book, Quantitative Value, + Web Site: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors (Wiley Finance), Wesley Gray and Tobias Carlisle attempt to create a quantitative investment strategy that mimics Warren Buffett’s investing style. It’s easy to dismiss the premise of their book as being difficult if not impossible to undertake. After reading the book it becomes clear that they have succeeded in creating a quantitative methodology that utilizes the teachings of Graham, Buffett and Greenblatt to produce a system that can beat the overall market. More importantly they have thoroughly back-tested their results and even found a few methods to improve upon the “magic formula.” Yes, I’m referring to the “magic formula” described in Joel Greenblatt’s, The Little Book That Still Beats the Market (Little Books. Big Profits). Gray and Carlisle use the model described in Greenblatt’s book as the basis of their quantitative model and then improve upon it.

There are two primary themes in the book. The first major theme is that undervalued stocks have historically outperformed the overall stock market. The authors provide numerous academic studies as evidence to support this thesis. In addition, they provide their own detailed back-testing results to provide further validation. Ultimately, they come to the conclusion that EBIT/TEV (total enterprise value) is the best fundamental price ratio to use in determining the cheapness of a stock. The authors prove through extensive back-testing that EBIT/TEV outperforms all other price ratio fundamentals including price-to-earnings (P/E), price-to-book (P/B) and EBITDA/TEV. Based on the author’s findings, it’s not surprising that Joel Greenblatt also uses EBIT/TEV as the main valuation component in his “magic formula.” The second major theme is the importance in investing in high quality stocks as defined by Buffett. Essentially, Buffett likes to buy companies that have high returns on capital and that maintain a sustainable competitive advantage. As an aside, it’s interesting to analyze Buffett’s transition from a “cigar-butt” investor under the tutelage of Benjamin Graham to his current incarnation of a value investor focused on businesses with strong franchises. Under the influence of Charlie Munger, Buffett finally made the realization that it was better to buy a “wonderful company at a fair price than a fair company at a wonderful price.” Gray and Carlisle essentially have developed a quantitative method to identify companies that have economic moats. They identify these companies by incorporating their own quality criteria along with metrics defined in the latest academic studies into a comprehensive quantitative methodology.

In addition to incorporating quality criteria into their screening process, Gray and Carlisle also utilize a financial strength model. Joseph Piotroski, an associate professor of accounting at Stanford’s Graduate School of Business wrote a groundbreaking paper titled, “Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers”, in which he identified nine accounting metrics that could help value investors separate “high quality” value stocks from “low quality” value stocks. Piotroski combined his accounting based criteria into a single metric called the F_SCORE. According to the authors, Piotroski found that the majority of low price-to-book value stocks tend to under-perform the market. Stocks that are exceptionally cheap tend to have very obvious problems that can be terminal. The trick is to find the cheap stocks that have solid balance sheets and will be able to survive until business improves or management is able to turn things around. Piotroski’s F_SCORE is a quantitative measure of the financial strength of a company. By identifying companies that were both cheap and in a strong financial position, Piotroski was able to improve the return of a low price-to-book portfolio by 7.5% per year. It’s clear that a combination of a cheap valuation along with financial strength is a formula for success in investing. The authors go a step further and improve upon the F_SCORE by creating their own financial strength score which they title the FS_SCORE. The FS_SCORE metrics can be divided into three main categories: current profitability, stability and recent operational improvements. Interestingly, Gray and Carlisle ran the FS_SCORE on Lubrizol using annual data from 2010, the year before Warren Buffett purchased the company. They found that the company scored an 8 out of 10 on their FS_SCORE index and traded at a relatively cheap 6.8x TEV/EBIT multiple. Thus, their FS_SCORE model was able to successfully identify a company that Warren Buffett eventually purchased.

Quantitative Value has much in common with other books on value investing. Despite following a quantitative investment process, the investment methodology in the book focuses on the timeless value investing principles of purchasing shares in high quality businesses at cheap valuation levels. The brilliance of their approach is that it removes emotions from the investment decision making process. Legendary value investor Seth Klarman has noted that, “the economics, the valuation of the business, is not hard. The psychology — How much do you buy? Do you buy it at this price? Do you wait for a lower price? What do you do when it looks like the world might end? Those are the harder things.” From Klarman’s perspective the difficulty in becoming a successful investor is not only about your technical skills but also your ability to control your emotions. In my view, all investors should develop an investment process that attempts to minimize the error produced by our cognitive biases. Ultimately, I think success in investing is not about raw intelligence but the ability to control your emotions and stick to your investment process.

The biggest critique that I have about the book is that to fully replicate the quantitative model you need to have access to extremely specialized investment management tools such as FactSet or Bloomberg. Clearly, both options are cost prohibitive for most retail investors. Fortunately for US investors, the authors have created a website where you can run the model and see a list of companies as the output. Unfortunately, the authors didn’t run their model on international markets so we can’t assume with certainty that the model will work outside the US. However, there have been a number of studies done globally that show value investing works in both developed and emerging markets outside of the US.

Overall, I believe Quantitative Value should be read by any investor looking to improve their investment process. At a minimum, the quantitative model produced in the book could easily be an effective screening tool to identify interesting investment opportunities. Even if you’re a fundamentally driven investor who does his or her own analysis, you’ll still find value in the book from the significant back-testing the authors have done on various value and quality metrics. If you enjoyed the The Little Book That Still Beats the Market, you definitely shouldn’t miss reading Quantitative Value, which actually improves upon Joel Greenblatt’s original model.

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