Forecasting DAX Volatility: A Comparison of Time Series Models and Implied Volatilities

Weiß, Harald

Forecasting DAX Volatility: A Comparison of Time Series Models and Implied Volatilities

dc.contributor.advisor	Wagenhals, Gerhard	de
dc.contributor.author	Weiß, Harald	de
dc.date.accepted	2016-09-11
dc.date.accessioned	2024-04-08T08:53:46Z
dc.date.available	2024-04-08T08:53:46Z
dc.date.created	2017-01-20
dc.date.issued	2016
dc.description.abstract	This study provides a comprehensive comparison of different forecasting approaches for the German stock market. Additionally, this thesis presents an application of the MCS approach to evaluate DAX volatility forecasts based on high-frequency data. Furthermore, the effects of the 2008 financial crisis on the prediction of DAX volatility are analysed. The empirical analysis is based on data that contain all recorded transactions of DAX options and DAX futures traded on the EUREX from January 2002 to December 2009. The volatility prediction models employed in this study to forecast DAX volatility are selected based on the results of the general features of the forecasting models, and the analysis of the considered DAX time series. Within the class of time series models, the GARCH, the Exponential GARCH (EGARCH), the ARFIMA, and the Heterogeneous Autoregressive (HAR) model are chosen to fit the DAX return and realised volatility series. Additionally, the Britten-Jones and Neuberger (2000) approach is applied to produce DAX implied volatility forecasts because it is based on a broader information set than the BS model. Finally, the BS model is employed as a benchmark model in this study. As the empirical analysis in this study demonstrates that DAX volatility changes considerably over the long sample period, it investigates whether structural breaks induce long memory effects. The effects are separately analysed by performing different structural break tests for the prediction models. A discussion of the impact on the applied forecasting methodology, and how it is accounted for, is also presented. Based on the MCS approach, the DAX volatility forecasts are separately evaluated for the full sample and the subperiod that excludes the two most volatile months of the financial crisis. Because the objective of this work is to provide information to investment and risk managers regarding which forecasting method delivers superior DAX volatility forecasts, the volatilities are predicted for one day, two weeks, and one month. Finally, the evaluation results are compared with previous findings in the literature for each forecast horizon.	en
dc.description.abstract	Umfassender Vergleich verschiedener Ansätze zur Prognose von Volatilitäten auf Basis des Model Confidence Set Ansatzes für den Deutschen Aktienmarkt	de
dc.identifier.swb	482149256
dc.identifier.uri	https://hohpublica.uni-hohenheim.de/handle/123456789/6106
dc.identifier.urn	urn:nbn:de:bsz:100-opus-13070
dc.language.iso	eng
dc.rights.license	publ-ohne-pod	en
dc.rights.license	publ-ohne-pod	de
dc.rights.uri	http://opus.uni-hohenheim.de/doku/lic_ubh.php
dc.subject	Implied volatility	en
dc.subject	Model confidence set	en
dc.subject	Time series models	en
dc.subject	Realized volatility	en
dc.subject	Implizite Volatilität	de
dc.subject	Realisierte Volatilität	de
dc.subject	Zeitreihenmodelle	de
dc.subject.ddc	330
dc.subject.gnd	Volatilität	de
dc.subject.gnd	Deutscher Aktienindex	de
dc.subject.gnd	Prognose	de
dc.subject.gnd	Evaluation	de
dc.title	Forecasting DAX Volatility: A Comparison of Time Series Models and Implied Volatilities	de
dc.title.dissertation	Prognose von DAX Volatilitäten: Ein Vergleich von Zeitreihenmodellen und Impliziten Volatilitäten	de
dc.type.dcmi	Text	de
dc.type.dini	DoctoralThesis	de
local.access	uneingeschränkter Zugriff	en
local.access	uneingeschränkter Zugriff	de
local.bibliographicCitation.publisherPlace	Universität Hohenheim	de
local.faculty.number	3	de
local.institute.number	520	de
local.opus.number	1307
local.university	Universität Hohenheim	de
local.university.faculty	Faculty of Business, Economics and Social Sciences	en
local.university.faculty	Fakultät Wirtschafts- und Sozialwissenschaften	de
local.university.institute	Institute for Economics	en
local.university.institute	Institut für Volkswirtschaftslehre	de
thesis.degree.level	thesis.doctoral

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