In the theory of asset pricing, investors demand a higher return for taking on greater risk. This principle underlies the capital asset pricing model (CAPM) and virtually every framework used to develop the cost of equity capital in a business valuation. One of the most well-documented and empirically persistent sources of excess risk in equity markets is company size: smaller companies - measured by market capitalization - have historically generated higher returns than their larger counterparts, even after controlling for systematic market risk (beta). This excess return is the size premium, and it plays a central role in the discount rates used to value private companies.
The size premium was first documented by Rolf Banz in 1981 and has been the subject of extensive academic and practitioner research since. The most widely referenced source for size premium data in business valuation practice is the Duff & Phelps Cost of Capital Navigator (formerly the CRSP Decile Size Premia study). This database partitions the public equity market into deciles by market capitalization and calculates the excess return generated by each decile relative to what CAPM would predict. The smallest deciles - micro-cap and nano-cap companies - have historically generated excess returns of 4–8 percentage points or more annually, a substantial premium that must be incorporated into any discount rate applied to a small private company.
Business appraisers most commonly develop the cost of equity for a private company using the build-up method, which layers risk premiums on top of the risk-free rate. The components are: (1) the risk-free rate, typically the yield on long-term U.S. Treasury bonds; (2) the equity risk premium, the expected excess return of equities over the risk-free rate; (3) the size premium, derived from the Duff & Phelps data for the appropriate size category; and (4) a company-specific risk premium, which captures all idiosyncratic risks not reflected in the first three components. For very small private businesses - which typically fall in the nano-cap range or below - the size premium alone can add 6–10 percentage points to the cost of equity.
To understand the valuation impact, consider two businesses generating the same $500,000 of normalized earnings. If one is large enough that the appraiser applies a 15% cost of equity, the indicated value is $3.33 million. If the other is small, pushing the cost of equity to 22% after the size premium and company-specific adjustments, the indicated value is $2.27 million - a $1 million difference from size alone. This explains a fundamental market reality: smaller businesses sell at lower multiples than larger ones, all else being equal, and the size premium is the theoretical underpinning of that market observation.
The size premium and the company-specific risk premium (CSRP) serve different purposes in the discount rate build-up and should not be double-counted. The size premium is a systematic, market-observed risk factor tied to the size decile into which the company falls based on equity market capitalization. The CSRP, by contrast, captures risks that are specific to the subject company and are not already reflected in the size decile data - things like customer concentration, key man dependency, limited management depth, thin operating margins, or geographic limitations. Both adjustments are legitimate and necessary; the discipline lies in applying them without redundancy.
In practice, appraisers sometimes face criticism that the size premium is being phased out of professional standards or that the empirical evidence for it has weakened in recent years. The debate is real - some researchers argue that the size effect has diminished or reversed since the 1980s in public markets. However, the profession's prevailing view, supported by the Duff & Phelps evidence and by market transaction data, is that size remains a meaningful risk factor for private companies, particularly in the lower middle market and micro-cap range. ValuEdge appraisers carefully document the basis for every size premium applied, citing current data sources and reconciling the implied total return with observable market multiples to ensure the discount rate is internally consistent and empirically supportable.
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