Onan, Mustafa2016-01-082016-01-082012http://hdl.handle.net/11693/15521Ankara : The Department of Management, İhsan Doğramacı Bilkent University, 2012.Thesis (Master's) -- Bilkent University, 2012.Includes bibliographical references.This study aims to investigate whether there are predictable patterns in the dynamics of implied volatility smirk slopes extracted from the intraday market prices of S&P 500 index options. I compare forecasts obtained from a short memory ARMA model and a long memory ARFIMA model within an out-of-sample context over various forecasting horizons. I find that implied volatility smirk slopes can be statistically forecasted and there is no statistically significant difference among competing models. Furthermore, I investigate whether these implied volatility smirk slopes have predictive power for future index returns. I find that slope measures have predictive ability up to 20 minutes.ix, 73 leavesEnglishinfo:eu-repo/semantics/openAccessImplied Volatility SmirkS&P 500High-FrequencyHG6024.A3 O53 2012Options (Finance)--Econometric models.Financial futures.Risk management.Economic forecasting--Econometric models.Thesis