The Real Option Approach for Assessment of Big Data Asset Based on Prospect Theory

Abstract

This paper combines prospect theory with real option pricing model to construct a new value assessment model for big data assets. For the high uncertainty of future earnings and risk of big data assets, this paper analyzes that their value characteristics are in line with the American call option firstly. On this basis, we use the value function in the prospect theory to calculate decision makers' subjective judgments on the value of underlying big data assets under each state, and use the weighting function to calculate the decision makers' subjective judgment on the weight of expansion right, downsize right and abandon right. In example, we use least-squares Monte Carlo simulation method to perform a simulation which verifies the real option pricing method based on perspective of prospect theory can obtain more reasonable assessment result for big data assets.