Predictive Power of Markets - Prediction Accuracy, Incentive Schemes, and Traders\u27 Biases

Accurate predictions are essential in many areas such as business and sports forecasting. Prediction markets are a promising approach for predicting uncertain future events and developments. This work demonstrates that markets are accurate predictors beyond the field of political stock markets. Moreover, the findings on trader\u27 biases and incentive schemes are valuable for designing future prediction markets

Information and predictability: bookmakers, prediction markets and tipsters as forecasters

The more information is available, and the more predictable are events, the better forecasts ought to be. In this paper forecasts by bookmakers, prediction markets and tipsters are evaluated for a range of events with varying degrees of predictability and information availability. All three types of forecast represent different structures of information processing and as such would be expected to perform differently. By and large, events that are more predictable, and for which more information is available, do tend to be forecast better

Do Gamblers Think That Teams Tank? Evidence from the NBA

A growing body of literature indicates that sports teams face incentives to lose games at the end of the season. This incentive arises from league entry draft policy. We use data from betting markets to confirm the existence of tanking, or the perception of tanking, in the NBA. Results from a SUR model of point spreads and point differences in NBA games indicate that betting markets believe that tanking takes place in the NBA, even though the evidence that tanking actually exists is mixed. NBA policy changes also affect betting market outcomes.incentives; betting markets; tanking

Prediction Markets:A literature review 2014

In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article provides a comprehensive review and classification of the literature related to the topic of Prediction Markets. Overall, 304 relevant articles, published in the timeframe from 2007 through 2013, were identified and assigned to a herein presented classification scheme, differentiating between descriptive works, articles of theoretical nature, application-oriented studies and articles dealing with the topic of law and policy. The analysis of the research results reveals that more than half of the literature pool deals with the application and actual function tests of Prediction Markets. The results are further compared to two previous works published by Zhao, Wagner and Chen (2008) and Tziralis and Tatsiopoulos (2007a). The article concludes with an extended bibliography section and may therefore serve as a guidance and basis for further research. (250 WORDS

The Regression Tournament: A Novel Approach to Prediction Model Assessment

Standard methods to assess the statistical quality of econometric models implicitly assume there is only one person in the world, namely the forecaster with her model(s), and that there exists an objective and independent reality to which the model predictions may be compared. However, on many occasions, the reality with which we compare our predictions and in which we take our actions is co-determined and changed constantly by actions taken by other actors based on their own models. We propose a new method, called a regression tournament, to assess the utility of forecasting models and taking these interactions into account. We present an empirical case of betting on Australian Rules Football matches where the most accurate predictive model does not yield the highest betting return, or, in our terms, does not win a regression tournament.

Betting on Climate Policy: Using Prediction Markets to Address Global Warming

Global warming, sea level rise, and extreme weather events have made climate change a top priority for policymakers across the globe. But which policies are best suited to tackle the enormous challenges presented by our changing climate? This Article proposes that policymakers turn to prediction markets to answer that crucial question. Prediction markets have a strong track record of outperforming other forecasting mechanisms across a wide range of contexts — from predicting election outcomes and economic trends to guessing Oscar winners. In the context of climate change, market participants could, for example, bet on important climate outcomes conditioned on the adoption of particular policies. These prediction markets would aggregate policy-relevant information from a variety of sources to improve upon existing decision-making methods, including expert deliberation, peer review, and cost-benefit analysis. Prediction markets also have the potential to overcome resistance to climate change mitigation efforts, particularly among market-oriented conservatives. We explain how both the federal and state governments could use prediction markets to help resolve high-profile controversies, such as how best to allocate subsidies to promote clean technology innovation and which policy strategy promises the greatest reduction in carbon emissions

The importance of betting early

We evaluate the impact of timing on decision outcomes when both the timing and the relevant decision are chosen under uncertainty. Sports betting provides the testing ground, as we exploit an original dataset containing more than one million online bets on games of the Italian Major Soccer League. We find that individuals perform systematically better when they place their bets farther away from the game day. The better performance of early bettors holds controlling for (time-invariant) unobservable ability, learning during the season, and timing of the odds. We attribute this result to the increase of noisy information on game day, which hampers the capacity of late (non-professional) bettors to use very simple prediction methods, such as team rankings or last game results. We also find that more successful bettors tend to bet in advance, focus on a smaller set of events, and prefer games associated with smaller betting odds

The Importance of Betting Early

We evaluate the impact of timing on decision outcomes when both the timing and the relevant decision are chosen under uncertainty. Sports betting provides the testing ground, as we exploit an original dataset containing more than one million online bets on games of the Italian Major Soccer League. We find that individuals perform systematically better when they place their bets farther away from the game day. The better performance of early bettors holds controlling for (time-invariant) unobservable ability, learning during the season, and timing of the odds. We attribute this result to the increase of noisy information on game day, which hampers the capacity of late (non-professional) bettors to use very simple prediction methods, such as team rankings or last game results. We also find that more successful bettors tend to bet in advance, focus on a smaller set of events, and prefer games associated with smaller betting odds

To what extent can new web-based technology improve forecasts? Assessing the economic value of information derived from Virtual Globes and its rate of diffusion in a financial market

As the rate of information availability increases, the ability to use web-based technology to improve forecasting becomes increasingly important. We examine Virtual Globe technology and show how the arrival of unprecedented types of web-based information enhances the ability to forecast and can lead to significant, measurable economic benefits. Specifically, we use market prices in a betting market over an eighteen-year period to examine how new elevation data from Virtual Globes (VG) enabled improved forecasting decisions and we explore how this information diffused through the betting market. The results demonstrate how short-lived, profitable opportunities arise from the arrival of novel information, and the speed at which markets adapt over time to account fully for new data