Risk Estimation on High Frequency Financial Data: Empirical Analysis of the DAX 30 (BestMasters) - Softcover

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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.

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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.