வணிகம் மற்றும் பொருளாதார இதழ்

Risk Tolerance Parametrics and the Maximal Value Frontier: The Value of Information for Risk-Averse Decision Making With Exponential Utility

Abstract

Ronald E Davis

When risk tolerance is varied from small to large values in a parametric programming study using CEV as the maxim and, a family of maximum value solutions are obtained that can be compactly summarized in policy region tabulations (in the discrete case) or asset allocation tabulations (in the continuous case). This gives the decision analyst an awareness of the full spectrum of solutions, from the one appropriate for the ultra-risk-averse decision maker, to the one appropriate for the risk neutral decision maker. When the interval of uncertainty from the least square risk tolerance estimation procedure is compared to the policy region tabulation or asset allocation tabulation, one obtains the solutions that are most preferred by the decision maker whose risk tolerance has just been estimated. From these solutions, all optimal in a neighborhood of the estimated risk tolerance, a final solution can be selected with complete awareness of what nearby optimal solutions would be like. In addition, for decision analyses involving an information option, parametric analysis reveals that the risk-averse CEVSI evaluation of information can be substantially greater than the risk neutral EVSI evaluation, which may lead to acquisition of information in cases where the risk neutral decision maker would pass it by. Hence use of EVSI for buy decisions about information may result in serious underutilization of information, leading to much greater downside risk than would be the case if CEVSI were used for those very same information buy decisions.