In this paper, we conduct a large-scale field experiment to investigate the manipulability of prediction markets. The main experiment involves randomly shocking prices across 817 separate markets; we then collect hourly price data to examine whether the effects of these shocks persist over time....

We estimate the value of the revolving door for firm executives and directors joining the cabinets of the Trump I and Biden administrations. By combining intraday stock and prediction market data, we take the degree of anticipation of political appointments into account and we offer estimates...

Recent survey evidence suggests that investors form beliefs about future stock returns by predominantly extrapolating their own experience: They overweight returns they have personally experienced while underweighting returns from earlier years and consequently expect high (low) stock market...

We estimate the value of the revolving door for firm executives and directors joining the cabinets of the Trump I and Biden administrations. By combining intraday stock and prediction market data, we take the degree of anticipation of political appointments into account and we offer estimates...

To study coordination in complex social systems such as financial markets, the authors introduce a new prediction market set-up that accounts for fundamental uncertainty. Nonetheless, the market is designed so that its total value is known, and thus its rationality can be evaluated. In two...

Prediction markets are a popular structure for a collective intelligence platform. The exact mechanism by which information known to the participating traders is incorporated into the market price is unknown. This paper demonstrates a novel method derived from the Kyle (1985) model for price...

Trading algorithms are an integral component of modern asset markets. In two experimental markets for long-lived correlated assets we examine the impact of alternative types of arbitrage-seeking algorithms. These arbitrage robot traders vary in their latency and whether they make or take market...

Prediction Markets (PMs) are markets in which agents trade event contingent assets. Enterprises use PMs to forecast revenues and project deadlines. This paper presents an Agent-based model, called Logarithmic Market Scoring Rule-Automated Market Maker (LMSR-ASM), to evaluate Prediction Markets....

We review the efficacy of three approaches to forecasting elections: econometric models that project outcomes on the basis of the state of the economy; public opinion polls; and election betting (prediction markets). We assess the efficacy of each in light of the 2004 Australian election. This...

This study will examine a dataset that contains 352 observations with 36 distinct variables. The dataset reflects people's thoughts and sentiments regarding a realistic fiction stock market game. The reason for analyzing this data is to identify any trends or patterns that might explain why...

This paper studies efficient market hypothesis in prediction markets and the results are illustrated for the in-play football betting market using the quoted odds for the English Premier League. Our analysis is based on the martingale property, where the last quoted probability should be the...

By now there are hundreds of scientific articles on experimental asset markets. Almost all of these experiments use a short and definite horizon. This may be one of the starkest differences to financial asset markets outside the laboratory, which usually have indefinite and comparatively long...

Interest in prediction markets has increased in the last decade, driven in part by the hope that these markets will prove to be valuable tools in forecasting, decision-making and risk management - in both the public and private sectors. This paper outlines five open questions in the literature,...

To study coordination in complex social systems such as financial markets, the authors introduce a new prediction market set-up that accounts for fundamental uncertainty. Nonetheless, the market is designed so that its total value is known, and thus its rationality can be evaluated. In two...

We study indefinitely-lived assets in experimental markets and find that the traded prices of these assets are on average about 40% of the risk neutral fundamental value. Neither uncertainty about the value of total dividend payments nor horizon uncertainty about the duration of trade can...

We conduct a lab experiment to investigate an important corporate prediction market setting: A manager needs information about the state of a project, which workers have, in order to make a state-dependent decision. Workers can potentially reveal this information by trading in a corporate...

This study analyzes the role that overconfidence plays in investor trading behavior. Using a unique measure of confidence (signature size) with an experimental economics approach, we find that those who are more confident bid significantly higher for assets in simulated trading exercises. This...

We use dynamic panel data models to generate density forecasts for daily Covid-19 infections for a panel of countries/regions. At the core of our model is a specification that assumes that the growth rate of active infections can be represented by autoregressive fluctuations around a downward...

We use dynamic panel data models to generate density forecasts for daily Covid-19 infections for a panel of countries/regions. At the core of our model is a specification that assumes that the growth rate of active infections can be represented by autoregressive fluctuations around a downward...

We propose a practical framework to detect mispricing, test informational efficiency and evaluate the behavioural biases within high-frequency prediction markets, especially in how prices react to news. We show this using betting exchange data for association football, exploiting the moment when...

Thanks to digital innovation, the wisdom of the crowd, which aims at gathering information (e.g. Wikipedia) and making a prediction (e.g. using prediction markets) from a group's aggregated inputs, has been widely appreciated. An innovative survey design, based on a Bayesian learning framework,...

Two regularities in financial economics are that prices underreact to news events and that they display short-term momentum. This paper tests for the presence of these regularities in prediction markets offered by the betting exchange Betfair on the 2008 Ryder Cup Golf Competition. Betfair...

To study coordination in complex social systems such as financial markets, the authors introduce a new prediction market set -up that accounts for fundamental uncertainty. Nonetheless, the market is designed so that its total value is known, and thus its rationality can be evaluated. In two...

A vast literature investigating behavioural underpinnings of financial bubbles and crashes relies on laboratory experiments. However, it is not yet clear how findings generated in a highly artificial environment relate to the human behaviour in the wild. It is of concern that the laboratory...

Markets are increasingly used as information aggregation mechanisms to predict future events. If policy makers make use markets, parties may attempt to manipulate the market in order to influence decisions. We experimentally find that policymakers could still benefit from following information...

Asset market bubbles and crashes are a major source of economic instability and inefficiency. Sometimes ascribed to animal spirits or irrational exuberance, their source remains imperfectly understood. Experimental methods can isolate systematic deviations from an asset's fundamental value in a...