Risk averse preference models for normalised lotteries based on simulation

In this paper, we propose a new risk-preference model for ranking pairs of normalised lotteries, random variables, each represents a risk factor obtained by converting the outcomes of the lottery into its mean multiplied by a risk factor. With the existence of an expected utility model, the preference ordering over a pair of such lotteries is converted into a risk-preference ranking over their risk factors. The proposed model is an efficient approximation model based on cumulative distribution functions using simulation. It can be used for analysing preferences between pairs of uncertain alternatives representing financial investment for risk-averse investors. Furthermore, unlike other models, it can be applied to a variety of randomly distributed variables with different utility functions.