ORCID
http://orcid.org/0000-0002-9349-3304
Date of Award
Spring 5-15-2020
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,
Recommended Citation
Zdinak, Michael G., "Information and the Risk-Neutral Probability, Essays in Financial Econometrics" (2020). Arts & Sciences Electronic Theses and Dissertations. 2260.
https://openscholarship.wustl.edu/art_sci_etds/2260