Real options in the laboratory: An experimental study of sequential investment decisions

Many real-life risky decisions in finance and management are dynamic and decision policies can be adapted as uncertainty is reduced by the arrival of new information. In this type of situation, called a real options problem, a decision maker must choose how much of his finite resources to invest in a dynamic risky environment. In two laboratory experiments, we test a well-defined decision problem with the central characteristics of a real options framework and do so in such a way that it is amendable to formal modeling. We find that people choose differently than the expected value maximizing policy, consistent with risk aversion and non-linear probability weighting. We conclude that although real options analysis is useful as a normative valuation method, its recommendations are sometimes contrary to people’s innate tendencies when making risky choices and this counterintuitiveness should be considered when implementing real options analysis in training and practice.