Quantile correlations: Uncovering temporal dependencies in financial time series

dc.contributor.author	Schmitt, Thilo A.
dc.contributor.author	Schäfer, Rudi
dc.contributor.author	Dette, Holger
dc.contributor.author	Guhr, Thomas
dc.date.accessioned	2014-08-08T07:20:59Z
dc.date.available	2014-08-08T07:20:59Z
dc.date.issued	2014-08-08
dc.description.abstract	We conduct an empirical study using the quantile-based correlation function to uncover the temporal dependencies in financial time series. The study uses intraday data for the S&P 500 stocks from the New York Stock Exchange. After establishing an empirical overview we compare the quantile-based correlation function to stochastic processes from the GARCH family and find striking differences. This motivates us to propose the quantile-based correlation function as a powerful tool to assess the agreements between stochastic processes and empirical data.	en
dc.identifier.uri	http://hdl.handle.net/2003/33565
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-6675
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823;28/2014	en
dc.subject	time series	en
dc.subject	stochastic process	en
dc.subject	empirical data	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.title	Quantile correlations: Uncovering temporal dependencies in financial time series	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access

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