The Effects of Options Markets on the Underlying Markets: Quasi-Experimental Evidence
type: CreativeWork
description: This dissertation consists of three essays in applied financial economics. The unifying theme is the use of financial regulation as quasi-experiments to understand the interrelationship between derivatives and the underlying assets. The first two essays use different quasi-experimental econometric techniques to answer the same research question: how does option listing affect the return volatility of the underlying stock? This question is difficult to answer empirically because being listed on an options exchange is not random. Volatility is one of the dimensions along which the options exchanges make their listing decisions. This selection bias confounds any causal effect that option listing may have. What is more, the options exchanges may list along unobservable dimensions. Such omitted variable bias can also confound any causal effect of option listing. My first essay overcomes these two biases by exploiting the exogenous variation in option listing that is created by the SEC-imposed option listing standards. Specifically, the SEC mandates that a stock must meet certain criteria in the underlying market before it can trade on an options exchange. For example, a stock needs to trade a total of 2.4 million shares over the previous 12 months before it can be listed. Since 2.4 million is an arbitrary number, stocks that are “just above” the 2.4 million threshold will be identical to stocks that are “just below” it, the sole difference being their probability of option listing. Accordingly, I use the 2.4 million threshold as an instrument for option listing in a fuzzy regression discontinuity design. I find that option listing causes a modest decrease in underlying volatility, a result that corroborates many previous empirical studies. My second essay attempts to estimate the effect of option listing for stocks that are “far away from” the 2.4 million threshold. I overcome the aforementioned omitted variable bias by fully exploiting the panel nature of the data. I co…
abstract: This dissertation consists of three essays in applied financial economics. The unifying theme is the use of financial regulation as quasi-experiments to understand the interrelationship between derivatives and the underlying assets. The first two essays use different quasi-experimental econometric techniques to answer the same research question: how does option listing affect the return volatility of the underlying stock? This question is difficult to answer empirically because being listed on an options exchange is not random. Volatility is one of the dimensions along which the options exchanges make their listing decisions. This selection bias confounds any causal effect that option listing may have. What is more, the options exchanges may list along unobservable dimensions. Such omitted variable bias can also confound any causal effect of option listing. My first essay overcomes these two biases by exploiting the exogenous variation in option listing that is created by the SEC-imposed option listing standards. Specifically, the SEC mandates that a stock must meet certain criteria in the underlying market before it can trade on an options exchange. For example, a stock needs to trade a total of 2.4 million shares over the previous 12 months before it can be listed. Since 2.4 million is an arbitrary number, stocks that are “just above” the 2.4 million threshold will be identical to stocks that are “just below” it, the sole difference being their probability of option listing. Accordingly, I use the 2.4 million threshold as an instrument for option listing in a fuzzy regression discontinuity design. I find that option listing causes a modest decrease in underlying volatility, a result that corroborates many previous empirical studies. My second essay attempts to estimate the effect of option listing for stocks that are “far away from” the 2.4 million threshold. I overcome the aforementioned omitted variable bias by fully exploiting the panel nature of the data. I co…
author: Mason, Brenden James
language: eng
keywords: Economics, Finance, Statistics, Fixed effects, Option listing, Price efficiency, Synthetic control, Tick size, Volatility
license: http://rightsstatements.org/vocab/InC/1.0/
date published: 2018
date modified: 2026-07-27T21:21:50Z
provider: Temple University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Temple University. Libraries

PropertyValue
property ID: Handle
value: http://hdl.handle.net/20.500.12613/3245