Corporate executives often bemoan the cost of high regulation, but new research show that greater federal regulatory scrutiny has historically correlated with better stock performance.

The regulation of business comes with benefits and costs. For example, on the positive side, regulations increase market safety and stability, and limit the concentration of market power. However, regulations also impose costs that reduce profits. And high costs of regulation can reduce competition by creating high barriers to entry – since most regulatory costs are fixed, such as capital expenditures, information costs, reporting and recordkeeping. As a result, the fixed-cost component of regulations gives rise to economies of scale, favoring larger companies. By increasing fixed costs, regulations increase operating leverage and thus also increase risk for companies with low operating margins and high operating leverage – prospects of a firm with high operating leverage are more dependent on business cycles. Such companies are more exposed to systematic risk (less flexibility to lower costs in recessions), implying that regulatory fixed costs that contribute to operating leverage should generate a risk premium.

Baris Ince and Han Ozsoylev contribute to the asset-pricing literature with their July 2020 study, “Price of Regulations: Regulatory Costs and the Cross-section of Stock Returns.” To explore whether such a regulatory risk-premium exists, the authors introduced a measure of regulatory operating leverage (ROL) that reflects the importance of regulatory fixed costs in a firm’s cost structure. To create ROL, they relied on “RegData 3.0,” a database that quantifies the incidence of regulatory restrictions imposed on industries based on a text analysis of federal regulatory code. They defined ROL as the ratio of fixed costs attributable to regulatory restrictions over selling, general and administrative (SG&A) expenses. Built on the fixed-cost channel, they investigated the cross-sectional predictive power of federal-level regulations on future stock returns. They sorted stocks into decile portfolios by their ROL measure during the previous quarter and examined the monthly returns on the resulting portfolios from April 1991 to December 2016. Following is a summary of their findings:

  • ROL predicts stock returns – stocks in the highest regulatory operating leverage decile generated 6.84% (5.28%) more equal- (value)-weighted annualized returns compared to the stocks in the lowest ROL decile.
  • The equal- (value)-weighted four-factor (beta, size, value and momentum) alpha increased from -9 (-14) to 38 (30) basis points per month, moving from the lowest to the highest ROL decile portfolio. The high-low equal- (value)-weighted ROL strategy produced 47 (44) basis points alpha per month with a t-statistic of 3.76 (2.93).
  • After controlling for the market, size, book-to-market, momentum, investment and profitability factors, the difference between the returns on the portfolios with the highest and the lowest ROL remained economically and statistically significantly positive.
  • The value premium is driven both by inter-industry operating leverage (asset heaviness) differences and intra-industry operating margin spreads. There is a strong relationship between ROL and subsequent stock returns within subgroups of low operating margin and high operating leverage stocks – providing risk-based explanations for the premium.
  • ROL triggers future cash flow volatility both during recessionary and non-recessionary periods, and the positive association between ROL and cash-flow volatility is stronger during recessions.
  • The relation between ROL and cash-flow volatility is most pronounced among small-cap firms because they lack economies of scale – large firms can spread their fixed costs over larger outputs, so that their costs per unit of output decrease. Since larger firms have higher weights in value-weighted strategies than in equal-weighted strategies, moving from equal-weighted ROL to value-weighted ROL sorts, the return spread between the extreme ROL decile portfolios decreases.
  • There was a positive and significant relation between ROL and subsequent stock returns within the small-cap and midcap stock subsamples. The same strategy generated positive, albeit insignificant, one-month-ahead alpha within the highest market capitalization tier.
  • While the high-low ROL strategy produced positive and significant risk-adjusted returns within the lowest and medium operating margin subgroups, it generated positive, albeit insignificant, alpha within the highest operating margin tier.
  • There was a significant relationship between ROL and future stock returns within all analyst coverage subsamples. However, the relationship was strongest in the low analyst coverage subsample.
  • ROL is uncorrelated with market beta, financial leverage and idiosyncratic volatility.

Summary

Their findings led Ince and Ozsoylev to conclude that ROL offers a firm-level measure that captures the firm’s exposure to fixed regulatory costs, predicts stock returns and provides a rational risk-based explanation for the prediction that ROL contributes to systematic risk – investors demand extra compensation to hold stocks with high ROL. As a result, high ROL stocks generate positive and significant excess and risk-adjusted returns.

This finding is consistent with that of many other studies, which have found that factor premiums are greater in small stocks. Their findings also add to the research providing risk-based explanations for the value premium.

Larry Swedroe is the chief research officer for Buckingham Strategic Wealth and Buckingham Strategic Partners.

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