We use measures of neural activity provided by functional magnetic resonance imaging (fMRI) to test the "realization utility" theory of investor behavior, which posits that people derive utility directly from the act of realizing gains and losses. Subjects traded stocks in an experimental market...

Financial decision making is the outcome of complex neurophysiological processes involving, among others, constant re-evaluation of the statistics of the problem at hand, balancing of the various emotional aspects, and computation of the very value signals that are at the core of modern economic...

Extensive research in neuroscience proves that rational decision-making depends on accurate anticipative emotions. We test this proposition in the context of financial markets. We replicate a multi-period trading game that reliably generates bubbles, while tracking participants' heart rate and...

We study information aggregation in financial markets. We introduce two new stability concepts: absolute stability (sensitivity of rational expectations equilibrium prices to signals (bits) that are lost or garbled), and relative stability (the difference between prices in the rational...

The cross-section of average annual returns on German common stock in the period of 1881-1913 exhibits several of the patterns that have been observed in more recent U.S. data. Market beta is hardly important, and its explanatory power is swamped by size and the ratio of book value to market...

We report on six large-scale financial markets experiments that were designed to test two of the most basic propositions of modern asset pricing theory, namely, that the interaction between risk averse agents in a competitive market leads to equilibration, and that, in equilibrium, risk premia...

We report on experiments of simple, repeated asset markets in two risky securities and one risk-free security, set up to test the Capital Asset Pricing Model (CAPM), which embeds the two most essential principles of modern asset pricing theory, namely, (i) financial markets equilibrate, (ii) in...

Execution of complex cognitive tasks is often analyzed as an exercise of information acquisition and belief updating. We challenge this view in the context of a non-incremental task, namely, the knapsack problem. First, we provide a theoretical argument why Bayesian updating makes little sense...

Consider the Rational Expectations price history of an Arrow-Debreu security that matures in the money: p(1), p(2), ..., p(T). Past information can be used to predict the return (p(t+1)-p(t))/p(t). Now consider a simple alternative performance measure: (p(t+1)-p(t))/p(t+1). It differs from the...

In traditional Reinforcement Learning (RL), agents learn to optimize actions in a dynamic context based on recursive estimation of expected values. We show that this form of machine learning fails when rewards (returns) are affected by tail risk, i.e., leptokurtosis. Here, we adapt a recent...