A complete understanding of security markets requires a simultaneous explanation of price behavior, trading volume, portfolio composition (ie., asset allocation), and bid‐ask spreads. In this paper, these variables are observed in a controlled setting—a computerized double auction market, similar to NASDAQ. Our laboratory allows experimental control of information arrival—whether simultaneously or sequentially received, and whether homogeneous or heterogeneous. We compare the price, volume, and share allocations of three market equilibrium models: telepathic rational expectations, which assumes that traders can read each others minds (strong‐form market efficiency); ordinary rational expectations, which assumes traders can use (some) market price information, (a type of semi‐strong form efficiency); and private information, where traders use no market information. We conclude 1) that stronger‐form market models predict equilibrium prices better than weaker‐form models, 2) that there were fewer misallocation forecasts in simultaneous information arrival ( SIM ) environments, 3) that trading volume was significantly higher in SIM environments, 4) and that bid‐ask spreads widen significantly when traders are exposed to price uncertainty resulting from information heterogeneity.

This paper reports a laboratory experiment that examines price formation in the single call market. The experiment design is intended to enhance the predictive power of the Bayesian Nash equilibrium (BNE) theory for this trading institution. The data support several qualitative implications of the BNE, especially when subjects compete against Nash 'robot' opponents, but subjects' behavior is not as responsive to changes in the pricing rule as the BNE predictions. Offers tend to reveal more of the underlying values and costs than predicted, particularly when subjects are experienced. A simple learning model accounts for several of the deviations from BNE.

We study prisoners' dilemmas played in continuous time with flow payoffs accumulated over 60 seconds. In most cases, the median rate of mutual cooperation is about 90 percent. Control sessions with repeated matchings over eight subperiods achieve less than half as much cooperation, and cooperation rates approach zero in one-shot sessions. In follow-up sessions with a variable number of subperiods, cooperation rates increase nearly linearly as the grid size decreases, and, with one-second subperiods, they approach continuous levels. Our data support a strand of theory that explains how capacity to respond rapidly stabilizes cooperation and destabilizes defection in the prisoner's dilemma.

This paper develops a nonparametric theory of preferences over one's own and others' monetary payoffs. We introduce ?more altruistic than? (MAT), a partial ordering over such preferences, and interpret it with known parametric models. We also introduce and illustrate ?more generous than? (MGT), a partial ordering over opportunity sets. Several recent studies focus on two-player extensive form games of complete information in which the first mover (FM) chooses a more or less generous opportunity set for the second mover (SM). Here reciprocity can be formalized as the assertion that an MGT choice by the FM will elicit MAT preferences in the SM. A further assertion is that the effect on preferences is stronger for acts of commission by FM than for acts of omission. We state and prove propositions on the observable consequences of these assertions. Finally, empirical support for the propositions is found in existing data from investment and dictator games, the carrot and stick game, and the Stackelberg duopoly game and in new data from Stackelberg mini-games.

Human subjects decide when to sink a fixed cost C to seize an irreversible investment opportunity whose value V is governed by Brownian motion. The optimal policy is to invest when V first crosses a threshold V* = (1 + w*)C, where the wait option premium w* depends on drift, volatility, and expiration hazard parameters. Subjects in the Low w* treatment on average invest at values quite close to optimum. Subjects in the two Medium and the High w* treatments invested at values below optimum, but with the predicted ordering, and values approached the optimum by the last block of 20 periods.

A fundamental difficulty in devising any test of general efficient market hypotheses is the specification of the relevant public and private information sets of traders. Without a consensus as to reasonable empirical specifications, tests of the hypotheses remain minimal or controversial. In this study we examine the efficiency of experimental asset markets in which one may unambiguously identify the public and private information sets of traders. We focus on how market efficiency is affected by the presence of futures markets in settings that incorporate different types of uncertainty and inside information. Our experimental results support four conclusions: (1) market outcomes tend to evolve toward strong-form informationally efficient equilibria, whether or not futures markets and/or event uncertainty are present; (2) the presence of futures markets clearly stabilizes spot prices; (3) the presence of futures markets tends to speed the evolution of asset markets to more efficient equilibria where there is event uncertainty; and (4) futures markets promote the "leakage" of inside information, with strong-form predictions outperforming semi-strong-form predictions.

Several impatient investors with private costs C i face an indivisible irreversible investment opportunity whose value V is governed by geometric Brownian motion. The first investor i to seize the opportunity receives the entire payoff, V-C i . We characterize the symmetric Bayesian Nash equilibrium for this game. A laboratory experiment confirms the model's main qualitative predictions: competition drastically lowers the value at which investment occurs; usually the lowest-cost investor preempts the other investors; observed investment patterns in competition (unlike monopoly) are quite insensitive to changes in the Brownian parameters. Support is more qualified for the prediction that markups decline with cost.

We report a continuous-time experiment studying the Burdett-Judd model, whose unique Nash equilibrium (NE) features dispersed prices. Adaptive dynamics predict that the NE is stable for one of our parameter sets and unstable for another. The empirical price distribution is close to the NE distribution for the stable parameter set, but for the unstable parameter set it skews toward higher prices in its NE support interval. We offer an empirical definition of price cycles in terms of changes over time in robust measures of central tendency and dispersion, by which the data exhibit persistent cycles in both treatments but larger cycles for the unstable parameters. Results are roughly similar for professional and student sellers and for limited-information treatments.