000726321 000__ 02787cam\a2200493Ii\4500 000726321 001__ 726321 000726321 005__ 20230306140724.0 000726321 006__ m\\\\\o\\d\\\\\\\\ 000726321 007__ cr\cn\nnnunnun 000726321 008__ 150331s2015\\\\gw\\\\\\ob\\\\000\0\eng\d 000726321 019__ $$a914434816 000726321 020__ $$a9783658093891$$qelectronic book 000726321 020__ $$a3658093897$$qelectronic book 000726321 020__ $$z9783658093884 000726321 0247_ $$a10.1007/978-3-658-09389-1$$2doi 000726321 035__ $$aSP(OCoLC)ocn905902713 000726321 035__ $$aSP(OCoLC)905902713$$z(OCoLC)914434816 000726321 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dGW5XE$$dE7B$$dUPM$$dCOO$$dYDXCP$$dCDX$$dOCLCF$$dEBLCP 000726321 043__ $$ae-gx--- 000726321 049__ $$aISEA 000726321 050_4 $$aHG5492 000726321 08204 $$a332.6780943$$223 000726321 1001_ $$aJacob, Florian,$$eauthor. 000726321 24510 $$aRisk estimation on high frequency financial data$$h[electronic resource] :$$bempirical analysis of the DAX 30 /$$cFlorian Jacob. 000726321 264_1 $$aWiesbaden :$$bSpringer Spektrum,$$c[2015] 000726321 300__ $$a1 online resource :$$billustrations. 000726321 336__ $$atext$$btxt$$2rdacontent 000726321 337__ $$acomputer$$bc$$2rdamedia 000726321 338__ $$aonline resource$$bcr$$2rdacarrier 000726321 4901_ $$aBestMasters 000726321 504__ $$aIncludes bibliographical references. 000726321 5050_ $$aMultivariate Standard Normal Tempered Stable Distribution -- FIGARCH -- High Frequency Data and Risk Management. 000726321 506__ $$aAccess limited to authorized users. 000726321 520__ $$aBy studying the ability of the Normal Tempered Stable (NTS) model to fit the statistical features of intraday data at a 5 min sampling frequency, Florian Jacobs extends the research on high frequency data as well as the appliance of tempered stable models. He examines the DAX30 returns using ARMA-GARCH NTS, ARMA-GARCH MNTS (Multivariate Normal Tempered Stable) and ARMA-FIGARCH (Fractionally Integrated GARCH) NTS. The models will be benchmarked through their goodness of fit and their VaR and AVaR, as well as in an historical Backtesting. Contents Multivariate Standard Normal Tempered Stable Distribution FIGARCH High Frequency Data and Risk Management Target Groups Researchers and students in the field of finance Practitioners in this area The Author Florian Jacob obtained his Master?s Degree in Business Engineering from the Karlsruhe Institute of Technology focusing on the application of tempered stable distributions on financial data and financial engineering. 000726321 650_0 $$aStock exchanges$$zGermany. 000726321 650_0 $$aElectronic trading of securities. 000726321 650_0 $$aInvestments$$xMathematical models. 000726321 650_0 $$aInvestment analysis. 000726321 77608 $$iPrint version:$$z9783658093884 000726321 830_0 $$aBestMasters. 000726321 852__ $$bebk 000726321 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-658-09389-1$$zOnline Access$$91397441.1 000726321 909CO $$ooai:library.usi.edu:726321$$pGLOBAL_SET 000726321 980__ $$aEBOOK 000726321 980__ $$aBIB 000726321 982__ $$aEbook 000726321 983__ $$aOnline 000726321 994__ $$a92$$bISE