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Reversion, seen over the past month. Why? Unclear given small movements in swing state polls. I would expect these odds to match, pretty closely, but they don't. Liquidity? Polymarket way off (segmented from US participants?). RealClearPolitics average doesn't include PredictIt (nor Kalshi). 538's prediction over time. Green line marks beginning last month of data. […]

Prediction markets sind generell bekannt als ein Sondertyp der Kapitalmärkte, an welchen der Wert der gehandelten Vermögenswerte durch den Ausgang von unsicheren, zukünftigen Ereignissen bedingt wird. Die Masterarbeit hat sich zum Ziel gesetzt, die berichtenswertesten Anwendungsbefunde in Bezug auf Prediction markets systematisch vorzustellen. Um dies zu verwirklichen wurde folgende Forschungsfrage formuliert: Was sind die berichtenswertesten Anwendungsbereiche für Prediction Markets und welche Verhaltensaspekte der Menschen zeigen sich bei der Verwendung derartiger Prognosemechanismen? Die Masterarbeit untersucht und stellt methodologisch zusammen sowohl die neuesten akademischen Ansätze, als auch die praktischen Implementationen von Prediction Markets mit dem Ziel, diesem wenig systematisierten Wissenschaftsfeld eine gewisse Kontinuität zu verschaffen. Politik, Sport und zahlreiche Anwendungen innerhalb verschiedenen Unternehmen stellen den Kern dieser Masterarbeit dar und liefern folgende Befunde: Im Bereich der Vorhersage politischer Ereignisse liefern Prediction Markets regelmäßig bessere Leistungen als Umfragen und Experten. Im Sportbereich sind Prediction Markets in der Lage, die allgemeine Auffassung über die Prognosefähigkeit der Wettquoten zu widerlegen. Anwendungsbeispiele aus der Praxis liefern glaubwürdige Belege dafür, dass Prediction Markets erfolgreich verstreute Information aggregieren können. Favorite longshot bias, reverse favorite longshot bias, herding bias und optimistic bias sind Verhaltensmuster, die durchgehend festgestellt werden können. Auf der negativen Seite sind das Nichtvorhandensein eines geeigneten Benchmark-Mechanismus, ein experimenteller Charakter und das Fehlen rechtlicher Rahmenbedingungen hervorzuheben. Die fehlende Übereinstimmung über theoretische Grundlagen, weitere konkrete Anwendungen und allgemeine Popularisierung der Thematik drängen sich schließlich als forschungsbedürftige Themen auf. ; Prediction markets are generally being referred to as a special case of asset markets where the value of the traded asset is contingent upon the outcome of some uncertain event at or before some pre-specified point in time. The master thesis aims at systematically presenting the newsworthiest application findings related to prediction markets. In order to succeed in such an endeavor, the following research question finds itself at the heart of the thesis: What are the newsworthiest prediction markets application fields, and which aspects of human behavior become apparent with the use of such forecasting mechanisms? The thesis compiles and methodically examines both the latest academic as well as practical efforts related to the application fields of prediction markets, with the aim of adding continuity to this still somewhat disorganized scientific field. Application fields of politics, sports and various types of corporate applications represent the core of the paper and provide the following findings: the field of politics shows that prediction markets are able to outperform polls and experts on a consistent basis. In the field of sports, prediction market studies refute the general belief that betting lines represent predictions. Numerous corporate applications provide substantial evidence for successful aggregation of scattered information and the use of collective wisdom. Behavioral patterns in the form of the favorite-longshot bias, reverse favorite-longshot bias, herding bias, and optimistic bias are consistently being detected throughout the different application fields. The frequent absence of an appropriate benchmark mechanism, an experimental character, and a deficiency of a legal framework come into the forefront on the negative side. To conclude, the thesis identifies the following topics as requiring further research: fundamental theoretical postulates, further practical implementations, and the popularization of the field. ; Miroslav Tepavac ; Zusammenfassungen in Deutsch und Englisch ; Karl-Franzens-Universität Graz, Masterarbeit, 2018 ; (VLID)2945882

It's of some interest to see how polls and prediction markets are viewing the presidential race, and how this links with economic sentiment. First polls and sentiment. Source: TheHill, accessed 4/17/2024. Source: U.Michigan via FRED, TradingEconomics, accessed 4/17/2024. Now, a prediction market. Below, I show PredictIt odds for Biden vs. Trump (omitting RFK Jr.), for […]

Prediction markets - markets used to forecast future events - have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by economic forecasters. We show that prediction markets have a number of attractive features: they quickly incorporate new information, are largely efficient, and impervious to manipulation. Moreover, markets generally exhibit lower statistical errors than professional forecasters and polls. Finally, we show how markets can be used to both uncover the economic model behind forecasts, as well as test existing economic models.

Prediction markets - markets used to forecast future events - have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by economic forecasters. We show that prediction markets have a number of attractive features: they quickly incorporate new information, are largely efficient, and impervious to manipulation. Moreover, markets generally exhibit lower statistical errors than professional forecasters and polls. Finally, we show how markets can be used to both uncover the economic model behind forecasts, as well as test existing economic models.