| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Volatility and risk estimation with linear and nonlinear methods based on high frequency data |
| Autor/-in: | Dettling, Marcel Bühlmann, Peter |
| DOI: | 10.1080/0960310042000243556 |
| Erschienen in: | Applied Financial Economics |
| Band(Heft): | 14 |
| Heft: | 10 |
| Seite(n): | 717 |
| Seiten bis: | 729 |
| Erscheinungsdatum: | 2004 |
| Verlag / Hrsg. Institution: | Routledge |
| Verlag / Hrsg. Institution: | London |
| ISSN: | 0960-3107 |
| Sprache: | Englisch |
| Schlagwörter: | IDP |
| Fachgebiet (DDC): | 332: Finanzwirtschaft |
| Zusammenfassung: | Accurate volatility predictions are crucial for the successful implementation of risk management. The use of high frequency data approximately renders volatility from a latent to an observable quantity, and opens new directions to forecast future volatilities. The goals in this paper are: (i) to select an accurate forecasting procedure for predicting volatilities based on high frequency data from various standard models and modern prediction tools; (ii) to evaluate the predictive potential of those volatility forecasts for both the realized and the true latent volatility; and (iii) to quantify the differences using volatility forecasts based on high frequency data and using a GARCH model for low frequency (e.g. daily) data, and study its implication in risk management for two widely used risk measures. The pay-off using high frequency data for the true latent volatility is empirically found to be still present, but magnitudes smaller than suggested by simple analysis. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/4667 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Datenanalyse und Prozessdesign (IDP) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
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Dettling, M., & Bühlmann, P. (2004). Volatility and risk estimation with linear and nonlinear methods based on high frequency data. Applied Financial Economics, 14(10), 717–729. https://doi.org/10.1080/0960310042000243556
Dettling, M. and Bühlmann, P. (2004) ‘Volatility and risk estimation with linear and nonlinear methods based on high frequency data’, Applied Financial Economics, 14(10), pp. 717–729. Available at: https://doi.org/10.1080/0960310042000243556.
M. Dettling and P. Bühlmann, “Volatility and risk estimation with linear and nonlinear methods based on high frequency data,” Applied Financial Economics, vol. 14, no. 10, pp. 717–729, 2004, doi: 10.1080/0960310042000243556.
DETTLING, Marcel und Peter BÜHLMANN, 2004. Volatility and risk estimation with linear and nonlinear methods based on high frequency data. Applied Financial Economics. 2004. Bd. 14, Nr. 10, S. 717–729. DOI 10.1080/0960310042000243556
Dettling, Marcel, and Peter Bühlmann. 2004. “Volatility and Risk Estimation with Linear and Nonlinear Methods Based on High Frequency Data.” Applied Financial Economics 14 (10): 717–29. https://doi.org/10.1080/0960310042000243556.
Dettling, Marcel, and Peter Bühlmann. “Volatility and Risk Estimation with Linear and Nonlinear Methods Based on High Frequency Data.” Applied Financial Economics, vol. 14, no. 10, 2004, pp. 717–29, https://doi.org/10.1080/0960310042000243556.
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