Question

Use the shape of Von Neumann-Morgenstern utility function to explain gambling behavior

Answer 1

Von Neumann–Morgenstern utility function, an extension of the theory of consumer preferences that incorporates a theory of behaviour toward risk variance. It was put forth by John von Neumann and Oskar Morgenstern in Theory of Games and Economic Behavior (and arises from the expected utility hypothesis. It shows that when a consumer is faced with a choice of items or outcomes subject to various levels of chance, the optimal decision will be the one that maximizes the expected value of the utility (i.e., satisfaction) derived from the choice made. Expected value is the sum of the products of the various utilities and their associated probabilities. The consumer is expected to be able to rank the items or outcomes in terms of preference, but the expected value will be conditioned by their probability of occurrence

In a gambling context, a risk averter puts higher utility on the expected value of the gamble than on taking the gamble itself. Conversely, a risk lover prefers to take the gamble rather than settle for a payoff equal to the expected value of that gamble. The implication of the expected utility hypothesis, therefore, is that consumers and firms seek to maximize the expectation of utility rather than monetary values alone. Since utility functions are subjective, different firms and people can approach any given risky event with quite different valuations. For example, a corporation’s board of directors might be more risk loving than its shareholders and, therefore, would evaluate the choice of corporate transactions and investments quite differently even when all monetary values are known by all parties.

Preferences may also be affected by the status of an item. There is, for example, a difference between something possessed (i.e., with certainty) and something sought out (i.e., subject to uncertainty); thus, a seller may overvalue the item being sold relative to the item’s potential buyer. This endowment effect, first noted by Richard Thaler, is also predicted by the prospect theory of Daniel Kahneman and Amos Tversky. It helps explain risk aversion in the sense that the disutility of risking the loss of $1 is higher than the utility of winning $1. A classic example of this risk aversion comes from the famous St. Petersburg Paradox, in which a bet has an exponentially increasing payoff—for example, with a 50 percent chance to win $1, a 25 percent chance to win $2, a 12.5 percent chance to win $4, and so on. The expected value of this gamble is infinitely large. It could be expected, however, that no sensible person would pay a very large sum for the privilege of taking the gamble. The fact that the amount (if any) that a person would pay would obviously be very small relative to the expected payoff shows that individuals do account for risk and evaluate the utility derived from accepting or rejecting it. Risk loving may also be explained in terms of status. Individuals may be more apt to take a risk if they see no other way to improve a given situation. For example, patients risking their lives with experimental drugs demonstrate a choice in which the risk is perceived as commensurate with the gravity of their illnesses

The von Neumann–Morgenstern utility function adds the dimension of risk assessment to the valuation of goods, services, and outcomes. As such, utility maximization is necessarily more subjective than when choices are subject to certainty