Modeling Heavy-Tailed Stock Index Returns Using the Generalized Hyperbolic Distribution
AbstractIn the present study, we estimate the parameters of the Generalized Hyperbolic Distribution for a series of stock index returns including the Romanian BETC and indexes from other two Eastern European countries, Hungary and the Czech Republic. Using different econometric techniques, we investigate whether the estimated Generalized Hyperbolic Distribution is an appropriate approximation for the empirical distribution computed by non-parametric kernel econometric methods. The main finding of the analysis is that the probability density function of the estimated Generalized Hyperbolic Distribution represents a very close approximation (at least up to the 4th order term) of the empirical probability distribution function.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Institute for Economic Forecasting in its journal Romanian Journal for Economic Forecasting.
Volume (Year): 6 (2009)
Issue (Month): 2 (June)
Contact details of provider:
Postal: Casa Academiei, Calea 13, Septembrie nr.13, sector 5, Bucureşti 761172
Phone: 004 021 3188148
Fax: 004 021 3188148
Web page: http://www.ipe.ro/
More information through EDIRC
Generalized Hyperbolic Distribution; heavy-tailed returns; non-parametric density estimation;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Necula, Ciprian, 2010. "Modeling the Dependency Structure of Stock Index Returns using a Copula Function Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 93-106, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Corina Saman).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.