Forecasting Short-Term Stock Returns Using Irregular Pricing Behavior in the Options Market

<p>This paper uses regression analysis to examine the relationship between today's implied volatility on AMD stock options with tomorrow's return on the underlying. An economic analyis of the options markets' micro-structure is discussed to establish the intuition and the basis behind the relationship. Four seperate models are developed to examine its statistical significance and the ability of options' prices to accurately forecast returns on the underlying security.</p> <p>The hypothesis of the paper is that daily changes in implied volatility can be used to earn higher than expected returns on the underlying stock. I find that implied volatility can be used to increase forecasting accuracy and may proved a means by which the Efficient Markets Hypothesis can be refuted.</p>

Name thesis:degree_name

Master of Arts in Economics

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Economics

Year dc:date.available

2014

Author dc:creator

• Sampson, Thomas W

Contributors dc:contributor

• Prof. Veitch
• Prof. Lau
• Prof. Wong

• Stock Market Forecasting
• Implied Volatility
• Regression
• Auto-Regressive
• Efficient Market Hypothesis
• Insider Trading
• Econometrics

Repository record dc:identifier

https://repository.usfca.edu/thes/81

OAI identifier oai:identifier

oai:repository.usfca.edu:thes-1088