Abstract
This chapter gives detailed insights into the methodological approach and used data for all upcoming analysis. Section 3.1 presents characterisitics for the data set. Section 3.2 describes transformation of the data which is applied to remove the intraday volatility profile. Subsequently, ARMA-GARCH and FIGARCH models with different innovation distribution assumptions are compared in their modeling capabilities. The special case of tempered infinitely divisible innovation distributions is investigated further to find dependencies between the corresponding parameter values and the frequency on which log-returns are constructed. The forecasting performance of the respective models is investigated in a Value-at-Risk backtest.
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© 2015 Springer Fachmedien Wiesbaden
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Jacob, F. (2015). Data and Methodology. In: Risk Estimation on High Frequency Financial Data. BestMasters. Springer Spektrum, Wiesbaden. https://doi.org/10.1007/978-3-658-09389-1_3
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DOI: https://doi.org/10.1007/978-3-658-09389-1_3
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Publisher Name: Springer Spektrum, Wiesbaden
Print ISBN: 978-3-658-09388-4
Online ISBN: 978-3-658-09389-1
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