Man Versus Machine
One of the most common arguments I hear against passive investing (which we can define as the use of a systematic approach to gain exposure to a factor or factors) goes like this: How can good management that is “thinking” not be superior to “nonthinking” management? I have found most investors harbor a strong opinion on this question.
Fortunately, we have evidence to help settle this matter. We’ll begin with a study by Lewis Goldberg, a psychology professor, who in 1968 analyzed the Minnesota Multiphasic Personality Inventory (MMPI) test responses of more than 1,000 patients and their final diagnoses as neurotic or psychotic.
As I discussed last week, Goldberg used this data to develop a simple model to predict the final diagnosis based on the MMPI test results. He found that, out-of-sample, his model had a 70% accuracy rate. He then gave the MMPI scores to experienced as well as inexperienced clinical psychologists and asked them to diagnose the patient. Goldberg found that his simple model outperformed even the most experienced psychologists.
Taking it one step further, Goldberg reran the test, this time providing the clinical psychologists with the model’s predictions. Goldberg was shocked that, while their performance did improve, they still underperformed the model, even armed with the benefit of its predictions.
The conclusion one might draw is that the results of quantitative models may be a performance ceiling from which humans are more likely to subtract (due to our behavioral biases, such as overconfidence) than exceed.
But, does the field of investing produce the same results in the contest of man versus machine?
Man Vs. Machine: Hedge Funds
Campbell Harvey, Sandy Rattray, Andrew Sinclair and Otto Van Hemert provide evidence on the subject with their December 2016 paper, “Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance.”
They analyzed and contrasted the performance of systematic hedge funds, which use rules‐based strategies involving little or no daily intervention by humans, with the performance of discretionary hedge funds, which rely on human skills to interpret new information and make the day‐to‐day investment decisions.
The study covered the period 1996 through 2014, and included data on more than 9,000 macro and equity hedge funds. To adjust returns for exposure to common factors, they used stock factors (beta, size, value and momentum) and bond factors (term and credit), as well as FX carry and volatility.
Investors have a clear preference for discretionary funds, given they make up about 70% of the hedge fund universe and control approximately 75% of the assets under management. However, the authors found no evidence to support such a preference.
For equity hedge funds, they found both that, after adjusting for exposure to well‐known risk factors, risk‐adjusted performances were similar, and that for discretionary funds (in aggregate), more of the average return and volatility of returns can be explained by risk factors.
In addition, when looking at what they called the “appraisal ratio” (the ratio of the average risk‐adjusted return to its volatility), the authors found that systematic funds outperformed 0.35 to 0.25. For macro funds, they found systematic funds outperformed discretionary funds both on an unadjusted and on a risk‐adjusted basis. The appraisal ratios were 0.44 for systematic funds and just 0.31 for discretionary funds. They concluded “the lack of confidence in systematic funds is not justified.”
Systematic Strategies Protect Investors (From Themselves)
In their excellent book, “Quantitative Value,” Wesley Gray and Tobias Carlisle provide further support for the power found in systematic, quantitative investing. They write that the objectiveness of the approach acts as a shield, protecting us against our own biases, while also acting as a sword, allowing us to exploit the cognitive biases of others.
To make this point, they presented the following example from Joel Greenblatt. Greenblatt’s firm, Gotham Capital, had compounded at a phenomenal rate of 40% annually, before fees, for the 10 years from Gotham’s formation in 1985 to its return of outside capital to investors in 1995.
In his own book, “The Little Book That Beats the Market,” Greenblatt describes an experiment he conducted in 2002. He wanted to know if Warren Buffett’s investment strategy could be quantified. He studied Buffett’s annual shareholder letters and developed his “magic formula,” which he published.
Gray and Carlisle show that study after study has found “the model is the ceiling of performance from which the expert detracts, rather than the floor to which the expert adds. Even Greenblatt has said the he cannot outperform the Magic Formula.”
We can perform another test in the ongoing battle of “machine (systematic) versus man (discretionary)” by examining the relative performances of two leading providers of passively managed funds, Dimensional Fund Advisors (DFA) and Vanguard. (Full disclosure: My firm, Buckingham, recommends DFA funds in constructing client portfolios.)
The following table shows the percentile rankings compiled by Morningstar for the 15-year period ending Dec. 7, 2016. Note that Morningstar’s data contains survivorship bias, as it compares only returns of the funds that have survived the full period.
What’s more, that bias is significant, because about 7% of actively managed funds disappear every year, with their returns being buried in the mutual fund graveyard. Thus, the longer the period, the worse the survivorship bias becomes. At 15 years, it’s quite large.
The average 15-year ranking of the seven Vanguard index funds put them in the 36th percentile. The average 15-year ranking of the 13 passively managed DFA funds put them in the 16th percentile, meaning they outperformed 84% of surviving funds. If Morningstar were to account for survivorship bias, these rankings would almost certainly be considerably higher.
It’s also important to note the rankings are based on pretax returns. In most cases, index and other passively managed funds will be more tax efficient, due to their typically lower turnover. And ETF versions would further enhance the tax efficiency of index funds.
Another important observation is that the highest rankings earned by the DFA funds were in the very asset classes that proponents of active management say are the most inefficient (and thus where discretion can add the most value): international small and small value stocks, and emerging market equities.
In fact, both DFA’s international small value fund (DISVX) and their emerging market small-cap fund (DEMSX) achieved a first-percentile ranking. This comparison provides strong evidence against the argument that actively managed funds are more likely to outperform in “inefficient” markets. In reality, that is just another myth the mutual fund industry tries to perpetuate, as is the superiority of the discretionary (man) over the systematic (machine) approach.
This commentary originally appeared December 16 on ETF.com
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