Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/203669 
Year of Publication: 
2019
Series/Report no.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2019: 30 Jahre Mauerfall - Demokratie und Marktwirtschaft - Session: Financial Econometrics II No. D23-V3
Publisher: 
ZBW - Leibniz-Informationszentrum Wirtschaft, Kiel, Hamburg
Abstract: 
This paper proposes a novel and simple approach to compute daily Value at Risk (VaR) and Expected Shortfall (ES) directly from high-frequency data. It assumes that financial logarithm prices are subordinated unifractal processes in the intrinsic time, which stochastically transforms the clock time in accordance with the markets activity. This is a very general assumption that allows for a simple computation of daily VaR and ES by scaling up their intraday counterparts computed from data sampled in intrinsic time. In the empirical exercise, we discuss the statistical and dynamic properties of the resulting daily VaR and ES estimates and show that our method outperforms standard ones in accurately estimating and forecasting VaR and ES.
Subjects: 
Value at Risk
Expected Shortfall
Intrinsic Time
Subordinated Process
High-Frequency Data
Scaling Law
JEL: 
C1
C4
C5
Document Type: 
Conference Paper

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