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

This paper uses regression analysis to examine the relationship between today\u27s implied volatility on AMD stock options with tomorrow\u27s return on the underlying. An economic analyis of the options markets\u27 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\u27 prices to accurately forecast returns on the underlying security. 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