Predictable dynamics in implied volatility smirk slope : evidence from the S&P 500 options

buir.advisorSalih, Aslıhan Altay
dc.contributor.authorOnan, Mustafa
dc.date.accessioned2016-01-08T18:19:46Z
dc.date.available2016-01-08T18:19:46Z
dc.date.issued2012
dc.departmentDepartment of Managementen_US
dc.descriptionAnkara : The Department of Management, İhsan Doğramacı Bilkent University, 2012.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2012.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractThis 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.en_US
dc.description.degreeM.B.Aen_US
dc.description.statementofresponsibilityOnan, Mustafaen_US
dc.format.extentix, 73 leavesen_US
dc.identifier.urihttp://hdl.handle.net/11693/15521
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectImplied Volatility Smirken_US
dc.subjectS&P 500en_US
dc.subjectHigh-Frequencyen_US
dc.subject.lccHG6024.A3 O53 2012en_US
dc.subject.lcshOptions (Finance)--Econometric models.en_US
dc.subject.lcshFinancial futures.en_US
dc.subject.lcshRisk management.en_US
dc.subject.lcshEconomic forecasting--Econometric models.en_US
dc.titlePredictable dynamics in implied volatility smirk slope : evidence from the S&P 500 optionsen_US
dc.typeThesisen_US

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