Real option analysis of investment and pricing decisions under jumps and asymmetric information

Abstract

This thesis deals with the problems of formulating optimal investment and pricing decisions under uncertainty in the presence of sudden changes in state variables and of asymmetry in the available information. The standard real option modelling framework of investment under uncertainty is augmented by allowing state variables to follow jump diffusion process. Also, a general pricing modelling approach is developed which accounts for changes in the available information that can be exploited by informed agents. With respect to the effect of jumps, the model developed is applied to the problem of formulating optimal environmental investment decisions under the possibility of extreme variations in pollutant stock levels and in socioeconomic costs. Using a realistic parameterisation of the problem a variety of implications for decision makers are drawn and it is shown that ignoring the impact of jumps may lead to a suboptimal timing of investment decisions. Regarding the impact of information uncertainty on pricing decisions, the proposed methodology is adapted and applied to two well-known problems in finance in the context of the betting markets and of Initial Public Offerings (IPOs), respectively. Firstly, an innovative equilibrium pricing model for fixed-odds betting markets is derived. The model provides an information-based explanation for the longstanding favourite-longshot bias and has important implications regarding agent behaviour and market efficiency. An empirical analysis of an extensive dataset of fixed-odds from European football is undertaken in order to demonstrate the model implications and provide an estimate of the degree of informed betting. Secondly, the methodology is adapted in developing a novel pricing model for Initial Public Offerings (IPOs). An option-based formula for the optimal offer price is derived along with a measure of informed trading which can provide an explanation for the IPO underpricing puzzle. Empirical evidence using data from the Chinese IPO market supports the major implications of the model, namely that greater uncertainty and greater time between offering and listing are associated with higher underpricing.