Honing in on the right hurdle rate
Published on October 16, 2017
Stock prices can be predicted using the 52-week high in a way that suggests investors react irrationally to news. This affects a company’s cost of capital in ways that traditional models fail to capture. A Bauer professor’s research suggests that a new approach to estimating the hurdle or target rate on investment projects does better.
Finance Professor and Senior Associate Dean Tom George has teamed with two other researchers to look at whether companies factor in the impact of the 52-week high on expected returns when making investments such as plant expansions or entering a new line of business. The findings will be published in a forthcoming issue of The Journal of Financial Economics.
“When we estimate a simple model of how companies invest in growing their businesses, the estimates from the model imply that companies account for the extra returns associated with the 52-week high in making these investments,” George said. “The conclusion is that companies not only optimize, but they do so in a way that recognizes the impact of potentially irrational investors on their cost of capital when they make investment decisions.”
Research in this area is still relatively new, George said.
But it holds the potential for changing the approach that companies and investors use to estimate hurdle rates on their investment projects (the rate of return that a project must exceed to create value). Hurdle rates are critical in determining whether or not companies make investments in all sorts of things, including hiring more employees, buying equipment, and building new stores and plants, he said.
Current models are based on how a hypothetical investor would perceive the risk of the investment. The findings in this new research stream suggest looking instead at models based on how a hypothetical company would perceive the costs and benefits of the investment.
Further research will continue to refine the factors these new models use as inputs to estimate hurdle rates.
“If these models are shown to work better than existing models, their adoption will lead companies and investors to decisions that will create more value in the economy,” George said.