By LARRY SWEDROE
Quantitative funds (funds that use systematic, rules-based strategies) are a large and growing player in the U.S. equity market. In 2019 The Economist reported that they accounted for 35 percent of U.S. stock market ownership, 60 percent of institutional equity assets under management and 60 percent of trading volume. Others (here and here) have estimated that quantitative funds account for 20-30 percent of assets.
Travis Dyer, Nicholas Guest and Elisha Yu, authors of the November 2021 study New Accounting Standards and the Performance of Quantitative Investors, examined quantitative investors’ ability to navigate occasional material changes to accounting standards — standards that impact the financial data-generating process and can cause additional transactions costs. Balance sheet data are a particularly critical ingredient for value strategies. However, they are not critical for small-cap and momentum strategies, which depend on market prices, not accounting rules.
Their main analyses exploited three recent U.S. standards affecting the accounting for pensions (SFAS 158 in 2006), non controlling interests (SFAS 160/141R in 2008) and leases (ASC 842 in 2018)—each of which materially affected balance sheet numbers that form the basis of many quantitative (and discretionary) investors’ trading decisions. Their database covered U.S. mutual fund performance from 2003 through 2020 using the CRSP Survivor-Bias-Free Mutual Fund Database. Following is a summary of their findings:
- Quantitative fund returns declined significantly relative to discretionary fund returns in the year following each of the three standards. On an annual basis, this underperformance translates to a statistically significant 2.73 percent. This evidence is consistent with revisions to accounting regulation creating incremental adjustment costs for quantitative investors.
- The underperformance was substantial during the first year following changes in accounting standards but nonexistent in the second year—the underperformance was temporary. Similarly, excess turnover lasted for one year following the standards’ implementation.
- Quantitative underperformance was stronger among funds tilted toward high book-to-market (their measure of value) stocks.
- There were no differences between quantitative and discretionary funds with high momentum or size exposure following the implementation of the new standards.
- There was increased portfolio turnover for quantitative investors following changes in accounting standards—resulting in higher transactions costs and reduced returns.
- Their results were concentrated among funds holding more stocks, meaning they likely must engage in more transactions when adjusting their models.
Their findings led Dyer, Guest and Yu to conclude: “Compared to more traditional discretionary strategies, rules-based strategies using algorithms and backtesting appear to lack flexibility and be less timely in adjusting to changing accounting policies.” However, they did add: “We observe that the effect is temporary, consistent with quantitative funds updating their models to ameliorate temporary underperformance.”
It is worth noting that while their paper claims that quant funds using value strategies tend to suffer relative to discretionary funds after accounting standards changes, it is also possible that quant funds lag discretionary funds whenever value lags—not just after changes in accounting standards. A likely explanation is that quant funds might tend to have deeper value exposure. (Dyer, Guest and Yu did find that non-value quant funds underperformed on average.) It would have been interesting to see a factor regression analysis to determine if this was the case. Alternatively, one could run the “placebo” case of value lagging but with no regulatory changes occurring.
Dyer, Guest and Yu’s findings highlight a potential negative (one that is often overlooked) of indexes and other quantitative (systematic) funds. Funds that replicate public indexes or publish their own (so that their trading is transparent) run the risk of exploitation through front-running—high-frequency traders and other active managers can exploit the knowledge that they must trade on certain dates. Structured portfolios that utilize quantitative strategies can avoid this risk by not trading in a manner that simply replicates the return of their index. Instead, they can create buy-and-hold ranges (which reduce turnover and trading costs), and they can also engage in patient trading (hiding their trading activities from the public).
In her November 2021 study, “Should Passive Investors Actively Manage Their Trades?,” Sida Li found that trading costs can vary depending on the degree of transparency of the fund’s trading strategy—the more transparent, the greater the implementation costs. Thus, investors should consider more than just the expense ratio when making fund selection decisions. For example, while their fund construction strategies are transparent, the implementation of the trading strategies of fund families such as AQR, Bridgeway and Dimensional are opaque. In addition, they also use multiple value metrics (as opposed to just book-to-market) and other factors (such as profitability/quality and momentum) to determine their eligible universe. These all serve to minimize the risks that changes in accounting rules might have on implementation costs.
This last point raises an interesting question related to the fact that correlation is not the same as causality. For example, the relative performance of quantitative value funds (particularly those using book-to-market as the sole measure of value) may have deteriorated after the three accounting changes studied, but that doesn’t necessarily mean the changes caused the deterioration. The authors could have investigated how other measures of value performed that were not affected by those changes. For example, price-to-sales is an oft-used value metric and is unaffected by accounting standards, as is the five-year reversal metric. If measures of value unaffected by accounting standards behaved similarly to book-to-market, it may be that quantitative value is just doing poorly, and not because of accounting rule changes.
It would also have been interesting to see the extent of the impacts of the new standards on book value—did they tend to cause major changes, or minor adjustments? On average, did book value change by 10 percent or 20 percent, or perhaps just a fraction of a percent? If these changes were small, it is hard to understand how they could have been the cause of the relative decline in quantitative value’s performance over the next year. With that said, Dyer, Guest and Yu did note that non-controlling interests amounted to 4 percent of book equity and that off-balance sheet lease commitments were about $2.8 trillion.
Another point to consider is that given the risk of researchers cherry picking and data mining, it would have been interesting if Dyer, Guest and Yu were able to include an analysis of the important accounting changes that were made in 2001 (FASB 141, which addressed accounting for business combinations, and FASB 142, which addressed accounting for intangibles). Unfortunately, the CRSP data was not available. With that said, it is worth noting that over the following six years, quantitative value strategies experienced one of their strongest historical runs.
Postscript: A note of thanks to my friend and co-author Andrew Berkin, the head of research for Bridgeway Capital Management, for his always helpful insights and suggestions.
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LARRY SWEDROE is Chief Research Officer at Buckingham Strategic Wealth and the author of numerous books on investing.
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