Risk-adjusted valuation for real option decisions

Alexander, Carol, Chen, Xi and Ward, Charles (2021) Risk-adjusted valuation for real option decisions. Journal of Economic Behavior and Organization, 191. pp. 1046-1064. ISSN 0167-2681

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Abstract

We model investor heterogeneity using different required returns on an investment and evaluate the impact on the valuation of an investment. By assuming no disagreement on the cash flows, we emphasize how risk preferences in particular, but also the costs of capital, influence a subjective evaluation of the decision to invest now or retain the option to invest in future. We propose a risk-adjusted valuation model to facilitate investors’ subjective decision making, in response to the market valuation of an investment opportunity. The investor’s subjective assessment arises from their perceived misvaluation of the investment by the market, so projected cash flows are discounted using two different rates representing the investor’s and the market’s view. This liberates our model from perfect or imperfect hedging assumptions and instead, we are able to illustrate the hedging effect on the real option value when perceptions of risk premia diverge. During crises periods, delaying an investment becomes more valuable as the idiosyncratic risk of future cash flows increases, but the decision-maker may rush to invest too quickly when the risk level is exceptionally high. Our model verifies features established by classical real-option valuation models and provides many new insights about the importance of modelling divergences in decision-makers risk premia, especially during crisis periods. It also has many practical advantages because it requires no more parameter inputs than basic discounted cash flow approaches, such as the marketed asset disclaimer method, but the outputs are much richer. They allow for complex interactions between cost and revenue uncertainties as well as an easy exploration of the effects of hedgeable and un-hedgeable risks on the real option value. Furthermore, we provide fully-adjustable Python code in which all parameter values can be chosen by the user.

Item Type: Article
Schools and Departments: University of Sussex Business School > Accounting and Finance
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 17 Sep 2021 15:22
Last Modified: 25 Oct 2021 08:00
URI: http://sro.sussex.ac.uk/id/eprint/101747

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