Stochastic Choice and Optimal Sequential Sampling

Stochastic Choice and Optimal Sequential Sampling

We model the joint distribution of choice probabilities and decision times in binary choice tasks as the solution to a problem of optimal sequential sampling, where the agent is uncertain of the utility of each action and pays a constant cost per unit time for gathering information. In the resulting optimal policy, the agent’s choices are more likely to be correct when the agent chooses to deci...

Online Appendix to Stochastic Choice and Optimal Sequential Sampling

Sequential sampling and paradoxes of risky choice.

The common-ratio, common-consequence, reflection, and event-splitting effects are some of the best-known findings in decision-making research. They represent robust violations of expected utility theory, and together form a benchmark against which descriptive theories of risky choice are tested. These effects are not currently predicted by sequential sampling models of risky choice, such as dec...

A Sequential Sampling Procedure for Stochastic Programming

We develop a sequential sampling procedure for a class of stochastic programs. We assume that a sequence of feasible solutions with an optimal limit point is given as input to our procedure. Such a sequence can be generated by solving a series of sampling problems with increasing sample size, or it can be found by any other viable method. Our procedure estimates the optimality gap of a candidat...

Optimal portfolio choice and stochastic volatility

In this paper we examine the effect of stochastic volatility on optimal portfolio choice in both partial and general equilibrium settings. In a partial equilibrium setting we derive an analog of the classic Samuelson–Merton optimal portfolio result and define volatility-adjusted risk aversion as the effective risk aversion of an individual investing in an asset with stochastic volatility. We ex...