Last week I wrote about the performance of one of Benjamin Graham’s simple quantitative strategies over the 37 years he since he described it (Examining Benjamin Graham’s Record: Skill Or Luck?). In the original article Graham proposed two broad approaches, the second of which we examine in Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors. The first approach Graham detailed in the original 1934 edition of Security Analysis (my favorite edition)—“net current asset value”:
A decade ago, no one talked about tail risk hedge funds, which were a minuscule niche of the market. However, today many large investors, including pension funds and other institutions, have mandates that require the inclusion of tail risk protection. In a recent interview with ValueWalk, Kris Sidial of tail risk fund Ambrus Group, a Read More
My first, more limited, technique confines itself to the purchase of common stocks at less than their working-capital value, or net-current asset value, giving no weight to the plant and other fixed assets, and deducting all liabilities in full from the current assets. We used this approach extensively in managing investment funds, and over a 30-odd year period we must have earned an average of some 20 per cent per year from this source. For a while, however, after the mid-1950’s, this brand of buying opportunity became very scarce because of the pervasive bull market. But it has returned in quantity since the 1973–74 decline. In January 1976 we counted over 300 such issues in the Standard & Poor’s Stock Guide—about 10 per cent of the total. I consider it a foolproof method of systematic investment—once again, not on the basis of individual results but in terms of the expectable group outcome.
In 2010 I examined the performance of Graham’s net current asset value strategy with Sunil Mohanty and Jeffrey Oxman of the University of St. Thomas. The resulting paper is embedded below:
While Graham found this strategy was “almost unfailingly dependable and satisfactory,” it was “severely limited in its application” because the stocks were too small and infrequently available. This is still the case today. There are several other problems with both of Graham’s strategies. In Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors Wes and I discuss in detail industry and academic research into a variety of improved fundamental value investing methods, and simple quantitative value investment strategies. Weindependently backtest each method, and strategy, and combine the best into a sample quantitative value investment model.
[I am an Amazon Affiliate and receive a small commission for the sale of any book purchased through this site.]