Investment under uncertainty : a real option model with jump processes

Prior studies on real options usually pay little attention to the differentiated effects of various unexpected events on making investment decisions. To fix this limit, this paper proposes a new computing method independent on definite distribution functions for the real option model with jump processes of randomly distributed frequency and amplitude. Based on this method, this paper also discusses the impacts of unexpected events on project investments. The results show that: 1) Ignoring the difference among various unexpected events by averaging their effects would lead to systematic mistakes in making investment decisions. 2) The moving direction of unexpected events is the key factor in decision making. In general, the more advantageous unexpected events look like, the higher value the real option has and the longer the firm should hold its project investment. 3) With the existence of various unexpected events, either missing one of them or assuming them to be homogeneous would cause significant errors in calculating the value of the real option, especially in the case that the project itself fluctuates greatly.School of Accounting and Financ