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Risk Estimation on High Frequency Financial Data : Empirical Analysis of the DAX 30 / / by Florian Jacob



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Autore: Jacob Florian Visualizza persona
Titolo: Risk Estimation on High Frequency Financial Data : Empirical Analysis of the DAX 30 / / by Florian Jacob Visualizza cluster
Pubblicazione: Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Spektrum, , 2015
Edizione: 1st ed. 2015.
Descrizione fisica: 1 online resource (78 p.)
Disciplina: 510
515
518
519.2
Soggetto topico: Probabilities
Mathematics - Data processing
Mathematical analysis
Probability Theory
Computational Mathematics and Numerical Analysis
Analysis
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: Multivariate Standard Normal Tempered Stable Distribution -- FIGARCH -- High Frequency Data and Risk Management.
Sommario/riassunto: By 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.
Titolo autorizzato: Risk estimation on high frequency financial data  Visualizza cluster
ISBN: 3-658-09389-7
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299777603321
Lo trovi qui: Univ. Federico II
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Serie: BestMasters, . 2625-3615