‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables

dc.contributor.authorPaye, Bradley S.en
dc.date.accessioned2017-06-12T18:57:57Zen
dc.date.available2017-06-12T18:57:57Zen
dc.date.issued2012-12en
dc.description.abstractAggregate stock return volatility is both persistent and countercyclical. This paper tests whether it is possible to improve volatility forecasts at monthly and quarterly horizons by conditioning on additional macroeconomic variables. I find that several variables related to macroeconomic uncertainty, time-varying expected stock returns, and credit conditions Granger cause volatility. It is more difficult to find evidence that forecasts exploiting macroeconomic variables outperform a univariate benchmark out-of-sample. The most successful approaches involve simple combinations of individual forecasts. Predictive power associated with macroeconomic variables appears to concentrate around the onset of recessions.en
dc.description.notesPost-print version of paper.en
dc.description.versionPublished versionen
dc.format.extent527 - 546 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifier.issue3en
dc.identifier.urihttp://hdl.handle.net/10919/78015en
dc.identifier.volume106en
dc.language.isoenen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.title‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variablesen
dc.title.serialJournal of Financial Economicsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Pamplin College of Businessen
pubs.organisational-group/Virginia Tech/Pamplin College of Business/Finance, Insurance, and Business Lawen
pubs.organisational-group/Virginia Tech/Pamplin College of Business/PCOB T&R Facultyen

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