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Abstract

Volatility is an integral and inescapable variable of financial engineering, modeling, and finance theory itself Classical financial economics proxies volatility for risk itself, as it becomes difficult to predict future price realizations of a given asset when that asset exhibits significant price volatility over a given time. However, the nature of volatility as it is explained by classical financial economics has been extensively questioned in the previous three decades, since it is characterized as a function of uncertainty aggregate market psychology-that is, as a function of fear, greed, exuberance, and other fundamental human instincts and emotions. While previous research has primarily focused on the asymmetries between stock market returns and realized volatility, this paper examines the extent to which implied volatility is asymmetrical with regards to the nature (positive or negative) of stock market returns in simultaneous periods. Analyses indicated that negative stock market returns create uniquely positive innovations to implied volatility not created during periods of positive stock market return. Additionally, this paper attempts to reconcile the asymmetry in implied volatility back into a cogent behavioral theory. Finally, the analyses described here explore how this asymmetry causes systemic error in predicting innovations to implied volatility and suggests a simple systemic error adjusted VXO model can be utilized with great efficacy to predict future innovations to realized volatility.

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