Heuristic Rules in Real Options Applications

Abstract

The purpose of this paper is two fold. Firstly, we intend to shorten the theory-practice gap by translating real options frameworks into common capital investment practices. Secondly, we explore how arbitrage rules of thumb can approximate real options into these valuation techniques and provide the results close to optimality. In the paper, the equivalent expressions of capital budgeting techniques under uncertainty are first derived, given various stochastic process assumptions such as geometric Brownian motion (GBM), mixed diffusion-jump, and mean reversion. These equivalent valuation techniques include NPV, hurdle rate, profitability index, cash flow trigger, and (discounted) payback. The heuristic decision rules are then proposed to approximate real options valuation. Under the GBM assumption, the heuristic hurdle rate can be easily derived by the "4-8 rule", i.e. the sum of 0.4 times project volatility and 0.8 times discount rate. Similarly, the "3-9 rule" and the "2-10 rule" can also apply to the mixed diffusion-jump projects and the mean-reverting projects, respectively. Monte Carlo simulation reveals that these heuristic investment rules provide a robust performance close to the optimal rules with forecast errors minimized. The implication is that corporate practitioners can accommodate sophisticated real options to common valuation practices without involving complicated real options techniques.