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ORCID

http://orcid.org/0000-0002-9349-3304

Date of Award

Spring 5-15-2020

Author's School

Graduate School of Arts and Sciences

Author's Department

Economics

Degree Name

Doctor of Philosophy (PhD)

Degree Type

Dissertation

Abstract

This article introduces a new high-frequency analysis of six years of data for options written on the S&P 500 and traded on the Chicago Board of Exchange. I quantify in real time the information contained in the probability measure implied by option prices, using concepts developed in information theory. Here information is analogous to a reduction in uncertainty surrounding the future price of the underlying security. A simple nonparametric estimator allows us to measure the amount of information gained as an option approaches maturity. I then test for jumps in the expectation of said future price. I find the intraday flow of information in a large and important market is not continuous, and often increases in discrete intervals. This fact is used to identify events in which a large amount of information is revealed to investors.

Language

English (en)

Chair and Committee

Werner Ploberger

Committee Members

Gaetano Antinolfi, Siddhartha Chib, George-Levi Gayle, Todd Kuffner,

Available for download on Thursday, April 15, 2021

Included in

Economics Commons

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