Modeling Dependency in Prediction Markets

8 Pages Posted: 6 Dec 2010

See all articles by Nikolay Archak

Nikolay Archak

New York University (NYU) - Leonard N. Stern School of Business

Panagiotis G. Ipeirotis

New York University - Leonard N. Stern School of Business

Date Written: December 2010

Abstract

In the last decade, prediction markets became popular forecasting toolsin areas ranging from election results to movie revenues and Oscarnominations. One of the features that make prediction marketsparticularly attractive for decision support applications is that theycan be used to answer what-if questions and estimate probabilities ofcomplex events. Traditional approach to answering such questionsinvolves running a combinatorial prediction market, what is not alwayspossible. In this paper, we present an alternative, statistical approachto pricing complex claims, which is based on analyzing co-movements ofprediction market prices for basis events. Experimental evaluation ofour technique on a collection of 51 InTrade contracts representing theDemocratic Party Nominee winning Electoral College Votes of a particularstate shows that the approach outperforms traditional forecastingmethods such as price and return regressions and can be used to extractmeaningful business intelligence from raw price data.

Suggested Citation

Archak, Nikolay and Ipeirotis, Panagiotis G., Modeling Dependency in Prediction Markets (December 2010). NYU Working Paper No. CEDER-10-05. Available at SSRN: https://ssrn.com/abstract=1718942

Nikolay Archak (Contact Author)

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

Panagiotis G. Ipeirotis

New York University - Leonard N. Stern School of Business ( email )

44 West Fourth Street
Ste 8-84
New York, NY 10012
United States
+1-212-998-0803 (Phone)

HOME PAGE: http://www.stern.nyu.edu/~panos

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