What Are You Implying? Deriving the Market’s Political Predictions with Policy Impact Indices

3 Pages Posted: 11 Sep 2020

See all articles by John Nay

John Nay

Stanford University - CodeX - Center for Legal Informatics; New York University (NYU)

Date Written: July 22, 2020

Abstract

Markets are the ultimate information processors. Emergent prices encapsulate the wisdom of the crowd and its views on events that could impact future value. Liquid securities are not directly linked to social and political events, but are affected by them. Isolating event-anticipating price changes can provide implied predictions of the events. We apply our methodology for isolating event-anticipating price changes to the 2016 and 2020 U.S. elections. As an election approaches, companies that would be positively affected by the expected outcome are more likely to have a positive price impact compared to those that would be negatively affected by that outcome. With estimates of the potential impacts of a political party on every company based on the policies proposed by the parties, the spread between the returns of the long and short holdings can reveal the market’s expected outcome of the election. A simulation supports the hypothesis that our approach captures the intended political exposures. The Republican index outperformed the Democratic index in the lead-up to and, especially, during the aftermath of the 2016 election. Contrary to the consensus view prior to the election, these indices implied a Republican win. The Democratic index outperformed the Republican index in 2020 before the polls reflected the information.

Keywords: machine learning, financial markets, political opinion, policy analysis, political economy

Suggested Citation

Nay, John, What Are You Implying? Deriving the Market’s Political Predictions with Policy Impact Indices (July 22, 2020). Available at SSRN: https://ssrn.com/abstract=3664381 or http://dx.doi.org/10.2139/ssrn.3664381

John Nay (Contact Author)

Stanford University - CodeX - Center for Legal Informatics ( email )

HOME PAGE: http://law.stanford.edu/directory/john-nay/

New York University (NYU) ( email )

Bobst Library, E-resource Acquisitions
20 Cooper Square 3rd Floor
New York, NY 10003-711
United States

HOME PAGE: http://nyu.edu

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