Determining the causality between U.S. presidential prediction markets and global financial markets

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Date

2020-08-14

Authors

Abolghasemi, Yaser
Dimitrov, Stanko

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Publisher

Wiley

Abstract

Prediction markets trade securities with final prices contingent on the outcome of future events, for example, who will win the next political election. We show how the outcome of a United States presidential election, information captured by prediction markets, impacts global financial markets. We investigate the existence of a causal relationship between various prediction markets and global financial markets time series for over 27 different countries and regions using Dow Jones Global Indexes. We construct vector auto‐regressive models and use the Toda–Yamamoto causality test to deal with non‐stationary time series. Preliminary results indicate that prediction markets may be used to predict some global financial markets.

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This is the peer reviewed version of the following article: Abolghasemi, Y, Dimitrov, S. Determining the causality between U.S. presidential prediction markets and global financial markets. Int J Fin Econ. 2020; 1– 23., which has been published in final form at https://doi.org/10.1002/ijfe.2029. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

Keywords

prediction market, U.S. presidential election, global financial market, time series analysis, Toda-Yamamoto causality test

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