An Analysis Of “Benjamin Graham’s Net Current Asset Values: A Performance Update”

A version of this paper can be found here


  • The study examined the performance of securities that were trading at no more than two-thirds of its Net Current Asset Value (“NAV”) during the 1970-82 period in the US
  • Net nets, on a gross basis, more than tripled the returns of the market (as measured by the S&P 500 TR)
  • Net nets, on a net basis (i.e. after commissions and potential taxes) more than doubled the returns of the market (as measured by the S&P 500 TR)
  • The study used data that excluded dividends; consequently, a number of findings within the study may not be reliable


As any hardcore investor knows, Ben Graham was the OG of value quant investing, where he used Warren Buffett and Walter Schloss as his “screeners” to find his own version of “net-nets.” In a previous post we took a look at net-net’s performance here.

The objective of this particular study was to examine the performance of securities that were trading at no more than two-thirds of its “net current asset value (NAV)” during the 1970-82 period in the US.

Our objective in this article is to analyze the study itself; determine its reliability, draw our own conclusions and glean, if any, actionable advice for the practitioner of the “net-net” method of investing. (1)

Key Methodology

  • Valuation metric:

 …sum of all liabilities and preferred stock and subtracted it from current assets; this result was then divided by the number of common shares outstanding to give NAV.

i.e. Net Current Asset Value per share = (Current Assets – (Total Liabilities + Preferred Shares))/Common Shares Outstanding

Our investor bought a security if its November closing price was no more than two-thirds of its NAV

  • Weighting: “equally weighted”
  • Purchase/rebalance date: “last business day of December of each year”
  • Holding/rebalancing period: “The securities were held for either 12 or 30 months, depending on the analysis.”


While there are numerous biases/errors that can be made when conducting studies/backtests, below we have analyzed those we deem most likely to impact a study of this nature:

  1. Survivorship bias

“All securities selected from the December 1970 through December 1972 and December 1978 through December 1982 Security Owner’s Stock Guide were evaluated. For the remaining years, we evaluated all NYSE securities as well as random samples of about 20 to 30 AMEX and OTC securities.

Given the use of “random” samples and the Security Owner’s Guide (as opposed to a large computerized database that might not include delisted stocks) the data source appears to be free from “survivorship bias”.

  • Look Ahead bias

Given the lag between when the “NAV” was calculated and the “date of purchase” this study does not appear to suffer from “look ahead” bias.

“Our investor bought a security if its November closing price was no more than two-thirds of its NAV… the date of purchase, the last business day of December of each year.”

Henry R. Oppenheimer

Furthermore, given the data was retrieved from a physical manual, logically, “look ahead” bias could not have occurred.

  • Time period bias

The study spans 13 years and we classify this as a “somewhat reliable” period.

For reference:

  • < 10 years; inadequate/unreliable
  • 11 to 20 years; somewhat reliable
  • > 20 years; more reliable
  • > 40 years; most reliable
  • Human error

Given this study was created in a rather manual and laborious manner we think it prudent to assume some errors may have occurred.

  • Journal rating/credibility(2)

Appearing in the Financial Analysts Journal adds credibility to the study in light of its reputation.

Reliability Assessment: Based on the above and considering the clarity with which the methodology was explained the study appears to be reliable. However, following further analysis (refer below), we conclude that a number of findings in the study may not be as reliable as they initially appear.

Results and Analysis

Annualized Return Analysis

Table IV is reproduced below:

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged and do not reflect management or trading fees, and one cannot invest directly in an index

Below we have adapted the data from Table IV and looked at the performance in both absolute and relative terms to the S&P 500 Total Return (TR, i.e. including dividends):

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Performance figures contained herein are hypothetical, unaudited and prepared by Alpha Architect, LLC; hypothetical results are intended for illustrative purposes only. Past performance is not ...

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