Risk Estimation on High Frequency Financial Data

Beschreibung

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.ContentsMultivariate Standard Normal Tempered Stable DistributionFIGARCHHigh Frequency Data and Risk ManagementTarget GroupsResearchers and students in the field of financePractitioners in this areaThe AuthorFlorian 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.
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.
Study in the field of natural sciences Includes supplementary material: sn.pub/extras

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Florian Jacob

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FIGARCH Finance Multivariate Standard Normal Tempered Stable Distribution Normal Tempered Stable (NTS) Model Risk Management

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