Information Processing in the Brain and Financial Innovations

Abstract

Based on recent neuroscience findings, we consider the brain to be a Bayesian prediction engine operating under a resource constraint. It meets incoming information with predictions based on an internal model of the world. Finite brain resources are then spent on processing the gaps between incoming information and these predictions. In addition, adverse information may trigger a stress response, exacting a cost on the brain and the body. We argue that the brain, which ultimately is the seat of all decision-making, considers these costs while choosing among alternatives. We show that incorporating such costs enriches our understanding of the financial market behavior by providing a new approach to recent financial innovations, as well as pushing up the equity premium and making it countercyclical. Ignoring such costs may make certain and uncertain utility appear different from each other consistent with recent empirical findings.