000806506 000__ 03527cam\a2200517Ii\4500
000806506 001__ 806506
000806506 005__ 20230306143818.0
000806506 006__ m\\\\\o\\d\\\\\\\\
000806506 007__ cr\cn\nnnunnun
000806506 008__ 160211s2016\\\\gw\\\\\\obm\\\000\0\eng\d
000806506 019__ $$a985040584
000806506 020__ $$a9783658125967$$q(electronic book)
000806506 020__ $$a3658125969$$q(electronic book)
000806506 020__ $$a3658125950
000806506 020__ $$a9783658125950
000806506 020__ $$z9783658125950
000806506 035__ $$aSP(OCoLC)ocn938557473
000806506 035__ $$aSP(OCoLC)938557473$$z(OCoLC)985040584
000806506 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dYDXCP$$dIDEBK$$dAZU$$dSNK$$dOCLCF$$dCOO$$dOCLCO$$dUIU$$dVT2$$dESU$$dZ5A$$dMERER$$dOCLCQ
000806506 049__ $$aISEA
000806506 050_4 $$aHG6024.A3
000806506 08204 $$a332.63/2042
000806506 1001_ $$aKömm, Holger,$$eauthor.
000806506 24510 $$aForecasting high-frequency volatility shocks :$$ban analytical real-time monitoring system /$$cHolger Kömm.
000806506 264_1 $$aFachmedien ;$$aWiesbaden :$$bSpringer Gabler,$$c[2016]
000806506 300__ $$a1 online resource (xxix, 171 pages).
000806506 336__ $$atext$$btxt$$2rdacontent
000806506 337__ $$acomputer$$bc$$2rdamedia
000806506 338__ $$aonline resource$$bcr$$2rdacarrier
000806506 4901_ $$aSpringer Gabler Research
000806506 502__ $$bPh. D.$$cCatholic University Eichstätt-Ingolstadt$$d2015
000806506 504__ $$aIncludes bibliographical references (pages 159-171).
000806506 5050_ $$aIntegrated Volatility -- Zero-inflated Data Generation Processes -- Algorithmic Text Forecasting.
000806506 506__ $$aAccess limited to authorized users.
000806506 520__ $$aThis thesis presents a new strategy that unites qualitative and quantitative mass data in form of text news and tick-by-tick asset prices to forecast the risk of upcoming volatility shocks. Holger K©œmm embeds the proposed strategy in a monitoring system, using first, a sequence of competing estimators to compute the unobservable volatility; second, a new two-state Markov switching mixture model for autoregressive and zero-inflated time-series to identify structural breaks in a latent data generation process and third, a selection of competing pattern recognition algorithms to classify the potential information embedded in unexpected, but public observable text data in shock and nonshock information. The monitor is trained, tested, and evaluated on a two year survey on the prime standard assets listed in the indices DAX, MDAX, SDAX and TecDAX. Contents ℓ́Ø Integrated Volatility ℓ́Ø Zero-inflated Data Generation Processes ℓ́Ø Algorithmic Text Forecasting Target Groups ℓ́Ø Teachers and students of economic science with a focus on financial econometrics<ℓ́Ø Executives and consultants in the field of business informatics and advanced statistics About the Author Dr. Holger K©œmm is research associate at the chair of statistics and quantitative methods in the economics & business department of the Catholic University Eichst©Þtt-Ingolstadt.
000806506 588__ $$aOnline resource; title from PDF title page (viewed February 12, 2016).
000806506 650_0 $$aFinancial institutions.
000806506 650_0 $$aEconomic forecasting.
000806506 650_0 $$aStock price forecasting.
000806506 650_0 $$aRisk management.
000806506 77608 $$iPrint version:$$aKömm, Holger.$$tForecasting high-frequency volatility shocks : an analytical real-time monitoring system.$$dWiesbaden, [Germany] : Springer Gabler, ©2016$$z9783658125950
000806506 830_0 $$aSpringer Gabler research.
000806506 852__ $$bebk
000806506 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-658-12596-7$$zOnline Access$$91397441.1
000806506 909CO $$ooai:library.usi.edu:806506$$pGLOBAL_SET
000806506 980__ $$aEBOOK
000806506 980__ $$aBIB
000806506 982__ $$aEbook
000806506 983__ $$aOnline
000806506 994__ $$a92$$bISE