Volatility and risk estimation with linear and nonlinear methods based on high frequency data

Dettling, Marcel; Bühlmann, Peter

doi:10.1080/0960310042000243556

Publication type:	Article in scientific journal
Type of review:	Peer review (publication)
Title:	Volatility and risk estimation with linear and nonlinear methods based on high frequency data
Authors:	Dettling, Marcel Bühlmann, Peter
DOI:	10.1080/0960310042000243556
Published in:	Applied Financial Economics
Volume(Issue):	14
Issue:	10
Page(s):	717
Pages to:	729
Issue Date:	2004
Publisher / Ed. Institution:	Routledge
Publisher / Ed. Institution:	London
ISSN:	0960-3107
Language:	English
Subjects:	IDP
Subject (DDC):	332: Financial economics
Abstract:	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
Fulltext version:	Published version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Institute of Data Analysis and Process Design (IDP)
Appears in collections:	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.