Applications of Asymmetric GARCH Models with Conditional Distributions: The Empirical Case of the NASDAQ Computer Index's Daily Closing Returns - Softcover

Li, Emma Ran

 
9783659260759: Applications of Asymmetric GARCH Models with Conditional Distributions: The Empirical Case of the NASDAQ Computer Index's Daily Closing Returns
Softcover
ISBN 10: 3659260754 ISBN 13: 9783659260759
Verlag: LAP LAMBERT Academic Publishing, 2012

Inhaltsangabe

The purpose of this honors thesis is to find an appropriate GARCH (Generalized Autoregressive Conditional Heteroskedasticity) Model for the daily closing returns of the NASDAQ Computer Index, given a ten-year time series of closing prices. On the one hand, Standard GARCH Models are not sufficient enough, if consider the leverage effects, that is, the volatility responds to good news and bad news differently. In this case, asymmetric GARCH Models are better, and, in particular, Exponential GARCH (EGARCH) Model is the best. On the other hand, EGARCH Models with alternative conditional distributions perform better than that with the default Normal Conditional Distribution. In particular, the Skew Generalized Error Distribution is found to be a good fit that generate large P-values against the null hypotheses in various tests. In conclusion, among all of the models investigated, the EGARCH Model with the Skew Generalized Error Distribution is the best.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2012
Sprache
Englisch
ISBN 10 
3659260754
ISBN 13 
9783659260759
Einband
Taschenbuch
Anzahl der Seiten
52
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
Presses Academiques Francophones
customerservice@vdm-vsg.de

Brivibas gatve 197
Riga
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