A Prediction Market for Toxic Assets

2010 ◽  
pp. 164-173
Author(s):  
Alan Holland
Keyword(s):  
Prediction Market

scholarly journals Prediction Markets for Crowdsourcing

2018 ◽  
Author(s):  
Christian Horn ◽  
Marcel Bogers ◽  
Alexander Brem*
Keyword(s):  
Stock Market ◽  
Open Innovation ◽  
Innovation Process ◽  
Business Practice ◽  
Prediction Markets ◽  
Knowledge Sources ◽  
Prediction Market ◽  
Online Platform ◽  
External Knowledge ◽  
Opening Up

Crowdsourcing is an increasingly important phenomenon that is fundamentally changing how companies create and capture value. There are still important questions with respect to how crowdsourcing works and can be applied in practice, especially in business practice. In this chapter, we focus on prediction markets as a mechanism and tool to tap into a crowd in the early stages of an innovation process. The act of opening up to external knowledge sources is also in line with the growing interest in open innovation. One example of a prediction market, a virtual stock market, is applied to open innovation through an online platform. We show that use of mechanisms of internal crowdsourcing with prediction markets can outperform use of external crowds.

A Prediction Market-Based Gamified Approach to Enhance Knowledge Sharing in Organizations

2019 ◽  
Vol 50 (5) ◽  
pp. 572-597 ◽  
Author(s):  
Hajime Mizuyama ◽  
Seiyu Yamaguchi ◽  
Mizuho Sato
Keyword(s):  
Knowledge Sharing ◽  
Web Application ◽  
Evaluation System ◽  
Future Research ◽  
Collective Knowledge ◽  
Prediction Market ◽  
Binary Event ◽  
Private Knowledge ◽  
Future Research Directions

Background. Knowledge sharing among the members of an organization is crucial for enhancing the organization’s performance. However, knowing how to motivate and direct members to effectively and efficiently share their relevant private knowledge concerning the organization’s activities is not entirely a straightforward matter. Aim. This study aims to propose a gamified approach not only for motivating truthful sharing and collective evaluation of knowledge among the members of an organization but also for properly directing those actions so as to maximize the usefulness of the shared knowledge. A case study is also conducted to understand how the proposed approach works in a live business scenario. Method. A prediction market game on a binary event on whether the specified activity will be completed successfully is devised. The game utilizes an original comment aggregation and evaluation system through which relevant knowledge can be shared verbally and evaluated collectively by the players themselves. Players’ behavior is driven toward a desirable direction with the associated incentive framework realized by three game scores. Results. The proposed gamified approach was implemented as a web application and verified with a laboratory experiment. The game was also played by four participants who deliberated on an actual sales proposal in a real company. It was observed that the various valuable knowledge elements that were successfully collected from the participants could be utilized for refining the sales proposal. Conclusions. The game induced motivation through gamification, and some of the designed game scores worked in directing the players’ behavior as desired. The players learned from others’ comments, which brought about a snowball effect and enriched collective knowledge. Future research directions include how to transform this knowledge into an easy-to-comprehend representation.

AN EXAMINATION OF PREDICTION MARKET EFFICIENCY: NBA CONTRACTS ON TRADESPORTS

2012 ◽  
Vol 3 (2) ◽  
pp. 65-77
Author(s):  
Richard Borghesi
Keyword(s):  
Market Efficiency ◽  
Theoretical Work ◽  
Relative Price ◽  
Event Data ◽  
Prediction Market ◽  
Price Efficiency ◽  
The Absolute ◽  
Fundamental Values ◽  
Vaughan Williams

In this paper I examine the absolute and relative price efficiency of NBA options listed on Tradesports.com.  I find that contracts within specific price bands are misvalued, but also demonstrate that this market is more efficient than is the market for NFL options.  Specifically, I show that contracts priced around $25 win (expire at $100) at a rate less than expected, while those priced around $75 win at a rate greater than expected.  The magnitudes of these deviations between prices and fundamental values are less than those in the NFL market.  Also, while prior theoretical work predicts that low-priced contracts should be overpriced, I instead find that NBA contracts priced near $2.50 win more frequently than expected.I thank Rob Dougherty and Brijesh Patel for assistance with the NBA event data, and Leighton Vaughan Williams for meaningful suggestions throughout.  Any errors are strictly my own.

The Structure of Prediction Market Research: Important Publications and Research Clusters

2017 ◽  
Vol 11 (1) ◽  
pp. 51-65
Author(s):  
Frank M. A. Klingert
Keyword(s):  
Market Research ◽  
A Priori ◽  
Information Aggregation ◽  
Research Paper ◽  
Prediction Market ◽  
Main Research ◽  
Literature Reviews ◽  
Efficient Information ◽  
Number Of Publications ◽  
Selection Of

This research paper identifies the most important publications and research clusters in the field of prediction markets. Two literature reviews in 2007 and 2014 have already shown a rising number of publications and classified them into several classes. However, the a priori selection of classes limited the analysis. Furthermore, it is still not quantitatively measured which publications have influenced prediction market research most. This research paper extends the existing literature based on the analysis of more than 18,000 citations. Thus, it identifies the most important publications and relevant research topics. It indicates that prediction market research relies primarily on publications within its own field. This paper concludes that some publications have already become “classic” and four main research clusters have emerged: Efficient information aggregation, manipulation, innovation markets and forecasting elections.

A STATISTICAL MODEL OF CLAIM PRICES IN PREDICTION MARKETS

2012 ◽  
Vol 4 (3) ◽  
pp. 85-93
Author(s):  
Russ Ray
Keyword(s):  
Statistical Model ◽  
Financial Markets ◽  
Poisson Distribution ◽  
Prediction Markets ◽  
Inside Information ◽  
Prediction Market ◽  
The World ◽  
Global Agreement ◽  
High Degree

This paper finds that claim prices in prediction markets, a new genre of financial markets, follow a Poisson distribution. The significance of this finding is that as soon as a claim in a prediction market is created and thereafter flushes out expert and inside information from around the world regarding that particular claim, claim prices immediately begin forming bell-shaped distributions, implying global agreement regarding the probabilities of claims being realized. This is an interesting finding, implying a surprisingly high degree of global homogeneity of inside information in predictions markets, even though such information is scattered in disconnected and secretive pockets around the world. This finding could also imply that cultural diversities do not significantly affect the interpretation of information in prediction markets. 

Evidencing the Forecasting Performance of Predication Markets: An Empirical Comparative Study

2018 ◽  
Vol 11 (2) ◽  
pp. 60-76
Author(s):  
Patrick Buckley
Keyword(s):  
Empirical Studies ◽  
Academic Research ◽  
Relevant Information ◽  
Prediction Markets ◽  
Problem Space ◽  
Prediction Market ◽  
Forecasting Performance ◽  
Planning Processes ◽  
Uncertain Outcomes ◽  
Aid Decision

Accurately forecasting uncertain outcomes to inform planning processes and aid decision making is a perennial organisational challenge, and the focus of a substantial body of research in management science, information systems and related disciplines. Academic research suggests that prediction markets may be of significant benefit to organisations in meeting this challenge. However most of the empirical studies assessing prediction market performance are laboratory based and suffer from limits to their generalizability. Recent literature has called for research which analyses the performance of prediction markets in ecologically valid settings in order to evidence their effectiveness to potential organisational users. This paper answers these calls by designing a prediction market to forecast an uncertain real world event. The study then compares the forecasting performance of the prediction market with a number of more traditional forecasting approaches regularly used by organisations. The study is contextually situated in a low information heterogeneity problem space, where relevant information is freely available. The results suggest that in this context prediction markets outperform the other forecasting methods studied.

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