AgPa #56: The Equity Risk Premium of Small Businesses

Small Business Equity Returns: Empirical Evidence from the Business Credit Card Securitization Market (2023)
Matthias Fleckenstein, Francis A. Longstaff
The Journal of Finance 78(1), URL

In 2020, there were more than 31M small private businesses in the US. Even though the estimated value of those businesses is “just” $12T, the sheer number is astonishing when compared to about 4,000 tradable US stocks (excluding penny stocks). For stocks, we typically use measures like returns, multiples, and volatilities. But given the lack of daily prices, it is difficult to calculate those measures for small private businesses. This week’s AGNOSTIC Paper is an attempt to change that…

Everything that follows is only my summary of the original paper. So unless indicated otherwise, all tables and charts belong to the authors of the paper and I am just quoting them. The authors deserve full credit for creating this material, so please always cite the original source.

Setup and Idea

Although most of the equity value is concentrated in few very large companies, small private businesses play an important role in most economies. For example, the authors estimate that small businesses account for about 28% of private equity in the US. Most of the existing research either builds on surveys of households with stakes in private businesses, or on insights from the private equity and venture capital world. Both are imperfect and don’t necessarily give a representative picture. The authors of this week’s paper therefore use a different approach and estimate the equity characteristics of small businesses from securitized credit card debt.

Data and Methodology

The authors use a sample of securitized credit card debt from small businesses with less than $3M in annual revenues and fewer than 10 employees. Their sample period ranges from 2000 to 2018 and includes data from the two major business credit card providers Advanta and American Express. The data comes from Bloomberg and IHS Markit, two high-quality databases.

In the next step, the authors use this data to calibrate an inverted version of the well-known Merton (1974) framework. I will not go into the details on this model but the idea is to borrow concepts from option pricing and apply them to corporate finance. Specifically, the Merton model treats equity and debt as long-call and short-put options on the firm’s underlying asset value. Having the data on securitized credit card debt (and knowing a few geeky option formulas) therefore allows to estimate the implied equity values and expected returns of small private businesses.

Important Results and Takeaways

Small businesses had an equity risk premium of 10.7% and a volatility of 56%

The key result of the paper is the estimated small-business-equity-risk-premium which stands at 10.74% for the main calibration of the authors’ model. This is slightly lower than other estimates from the literature but still in the same range. For comparison, the realized equity risk premium for the CRSP value-weighted index, a proxy for the US stock market, between 2000 and 2018 is 5.24%. Interestingly, however, the realized equity risk premium for the smallest decile of stocks is 19.95%. So according to the results, the equity risk premium of small private businesses is larger than for the overall stock market (that’s intuitive) but smaller than for small and micro caps (that’s in my opinion not so intuitive).

Table V of Fleckenstein & Longstaff (2023).

The table above also shows the estimated volatility of small business equity. The estimate stands at a staggering 56.37% per year. This is considerably higher than the 45.7% average volatility of public stocks during the same time period. However, it is not so much larger as one might have thought.

The results clearly suggest that small private businesses are much riskier than a diversified portfolio of public stocks. I think this surprises no one but it is nice to have such specific estimates for their risk-return profile.1This are really just the main results of the paper. The authors do a lot of other analyses and explain their methodology and results in great detail.

Robustness: the model generates plausible results for S&P 500 stocks

To validate their methodology, the authors (among other things) use a very simple test. They apply their methodology to an index of investment-grade corporate bonds. They explain that the average issuer within this index is representative for a firm in the S&P 500 index. Therefore we can test the model by comparing its predictions with the actual data of the S&P 500. In my opinion, that’s a pretty cool validity test. The following table shows the results.

Table X of Fleckenstein & Longstaff (2023).

The estimated equity risk premium stands at 6.17% which is very similar to common estimates of equity risk premiums for the US stock market. The model further predicts an annualized volatility of 38.48% which is very close to the median volatility of stocks traded on the NYSE. Overall, the results are therefore pretty too close to what we actually observed from the US stock market. If the model works for public companies, it seems reasonable that it also works for small private businesses.

Conclusions and Further Ideas

Admittedly, this week’s paper was a bit different than what I am usually doing but I just found it interesting when I read it. We always talk about returns, volatilities, and correlations when analyzing stocks. However, I have never seen a private entrepreneur who tries to determine the volatility and expected risk premium of the equity in his company.2Which could be a sign that we finance guys are just a bit too nerdy… Now, this is most likely also not relevant for them. For investors, however, I think it is very interesting to “translate” small private businesses into the same language as publicly traded stocks to better compare them.

From a broader perspective, this week’s authors are probably one of the pioneers who develop approaches to foster transparency in private markets. In my opinion, such models help to make better decisions about the total portfolio. For example, a private entrepreneur could see that she is already running a very risky portfolio by just following her day-job. Obviously, you don’t need a volatility number to recognize that founding a private business is risky. But I do think it is helpful to see more specifically how it compares to holding an individual stock or a diversified portfolio. Similarly, it may help stock investors to see that holding an individual stock is (in terms of volatility) almost as risky as owning a private business. This is of course unsurprising because a stock is nothing but fractional ownership of a company…

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1 This are really just the main results of the paper. The authors do a lot of other analyses and explain their methodology and results in great detail.
2 Which could be a sign that we finance guys are just a bit too nerdy…