This 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 Kömm 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.
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Dr. Holger Kömm is research associate at the chair of statistics and quantitative methods in the economics & business department of the Catholic University Eichstätt-Ingolstadt.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Holger Koemm is research associate at the chair of statistics and quantitative methods in the economics & business department of the Catholic University Eichstaett-Ingolstadt. Integrated Volatility.- Zero-inflated Data Generation Pr. Codice articolo 112604445
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This 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 Kömm 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. 204 pp. Englisch. Codice articolo 9783658125950
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This 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 Kömm 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. Codice articolo 9783658125950
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Taschenbuch. Condizione: Neu. Neuware -This 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 Kömm 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.Springer Gabler in Springer Science + Business Media, Tiergartenstr. 15-17, 69121 Heidelberg 204 pp. Englisch. Codice articolo 9783658125950
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