Emma Ran (7 results)
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Taschenbuch. Condition: Neu. Applications of Asymmetric GARCH Models with Conditional Distributions | The Empirical Case of the NASDAQ Computer Index's Daily Closing Returns | Emma Ran Li | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659260759 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Leng…ericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Li Emma RanI am a Statistics Master Candidate in Harvard University and I have Mathematics and Statistics Bachelor of Science Degrees from The Pennsylvania State University. In Penn State, I used to be…a Statistical Analyst in the De.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 price…s. 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.
