Partition-dependent framing effects in lab and field prediction markets

Many psychology experiments show that individually judged probabilities of the same event can vary depending on the partition of the state space (a framing effect called "partition-dependence"). We show that these biases transfer to competitive prediction markets in which multiple informed traders are provided economic incentives to bet on their beliefs about events. We report results of a short controlled lab study, a longer field experiment (betting on the NBA playoffs and the FIFA World Cup), and naturally-occurring trading in macro-economic derivatives. The combined evidence suggests that partition-dependence can exist and persist in lab and field prediction markets

Competitive Prediction-Aware Online Algorithms for Energy Generation Scheduling in Microgrids

Online decision-making in the presence of uncertain future information is abundant in many problem domains. In the critical problem of energy generation scheduling for microgrids, one needs to decide when to switch energy supply between a cheaper local generator with startup cost and the costlier on-demand external grid, considering intermittent renewable generation and fluctuating demands. Without knowledge of future input, competitive online algorithms are appealing as they provide optimality guarantees against the optimal offline solution. In practice, however, future input, e.g., wind generation, is often predictable within a limited time window, and can be exploited to further improve the competitiveness of online algorithms. In this paper, we exploit the structure of information in the prediction window to design a novel prediction-aware online algorithm for energy generation scheduling in microgrids. Our algorithm achieves the best competitive ratio to date for this important problem, which is at most $3-2/(1+\mathcal{O}(\frac{1}{w})),$ where $w$ is the prediction window size. We also characterize a non-trivial lower bound of the competitive ratio and show that the competitive ratio of our algorithm is only $9\%$ away from the lower bound, when a few hours of prediction is available. Simulation results based on real-world traces corroborate our theoretical analysis and highlight the advantage of our new prediction-aware design.Comment: This paper has been accepted into ACM e-Energy 2022 and will appear in the conference proceeding

Jeffreys's law for general games of prediction: in search of a theory

We are interested in the following version of Jeffreys's law: if two predictors are predicting the same sequence of events and either is doing a satisfactory job, they will make similar predictions in the long run. We give a classification of instances of Jeffreys's law, illustrated with examples.Comment: 12 page

Extracting Valuable Data from Classroom Trading Pits

Edward Chamberlin, who initiated classroom market experiments, used the results of these experiments to argue that competitive equilibrium performs poorly in explaining the outcomes of real markets. Vernon Smith altered the design of Chamberlin's experiment to increase the amount of price information available to traders and in classroom experiments with this design found that trading outcomes were close to those predicted by competitive theory. This paper examines results of classroom trading experiments using the design found in Experiments with Economic Principles, an introductory economics text by Ted Bergstrom and John Miller. The procedure in this experiment is intermediate between that of Chamberlin and that of Smith. We have collected data on transaction prices and quantities from a large number of classroom experiments using this design. We compare the experimental outcomes with the predictions made by competitive equilibriumtheory and by a simple profit-splitting theory. Evidence suggests that neither theory is entirely successful, though in the first rounds of trading there seems to be a significant amount of profit-splitting and as traders become more experienced, outcomes are closer to those predicted by competitive theory.experimental economics, classroom experiments, Edward Chamberlin, Vernon Smith, trading pits, demand and supply, profit- splitting, random matching, excess trading