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Dealmakers take heed: CAPM can cause significant valuation errors

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Determining the right price for a business on the auction block can often befuddle even the most experienced valuation professionals.

For decades, the Capital Asset Pricing Model (CAPM) has been used by business school professors, CFOs, and valuation experts to gain valuable information on risk and price. Unfortunately, the method, which predicts the expected return of an asset as a function of its beta, is not always accurate.

While the CAPM’s limits are widely known, new research shows the extent to which using the method can cause significant errors in the valuation of a company that’s up for sale.

By examining 12,000 takeover bids for private companies between 1977 and 2015, the authors of a forthcoming study show that using the CAPM to value targets leads to valuation errors that correspond to an average range of 12% to 33% of deal values.

The researchers arrived at their results by developing a model that assessed the cumulative abnormal return of the bidder’s stock in response to the bid; the value of the target’s equity as assessed by the market; and the price paid by the bidder.

“The CAPM formula doesn’t work — it doesn’t give the right price of risk,” saidone of the study’s authors and an MIT Sloan professor of financial economics. “It becomes a problem to actually evaluate businesses when we want to buy them, because we don’t know the price of risk, and we’re using that formula.”

Experts have used the CAPM for years, especially in business schools when introducing ideas of risk and return, portfolio theory, diversification, and other fundamental concepts. The authors estimated in their research that between 73.5% and 90% of CFOs and valuation professionals still use the CAPM.

“We have been teaching that method for the past 30 years for lack of a better alternative,” Thesmar said. “Problems arise either when limitations of the model are not clearly laid out at the same time the model is introduced or when students or professionals are seduced by the simplicity of the tool and forget about the limitations they have been taught.”

Implications of CAPM for buyers and sellers

Valuation professionals using the CAPM tend to undervalue assets or firms in high beta industries — that is, those with higher volatility than the market average. Likewise, CAPM can lead to the overvalue of assets or firms in low beta industries compared to market valuations, Thesmar said.

Knowing this, buyers and sellers may want to exert caution in deal-making and even consider counterarguments when the CAPM is being used, knowing that it might not be giving the right price of risk.

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For example, if you operate in a high beta industry, such as tech, and you’re the acquirer, “You want to pay the cheap price,” Thesmar said. “But if you are the seller of the business, then you should probably bargain it a bit more.” The CAPM-derived price “is likely to be too low,” he said.

This explains another key finding of the authors’ research: Valuation errors also caused reactions in the bidder’s stock price. When a deal was announced, a bidder’s stock price reacted significantly more positively when purchasing a high beta target at too low a price than when buying a low beta company at too high a price.

Want a more accurate valuation? Try this alternative

Thesmar said that no one model correctly defines the relationship between risk and expected returns.

One alternative, however, is to start with the CAPM but shrink beta estimates, as suggested in previous research done by Levi and Welch (2017). To produce a valuation range for the target, those results could then be complemented with estimates from multifactor models; from models that exploit information in option prices; or with valuations based on multiples.

“Do not rely blindly on that [CAPM] formula, but try to have some kind of mixture in between,” Thesmar said. “You should try to shrink the cost of risk you come up with.”

Thesmar conducted the study “CAPM-Based Company (Mis)valuations” with co-authors Olivier Dessaint (University of Toronto), Jacques Olivier (HEC Paris), and Clemens Otto (Singapore Management University).

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