On the appropriateness of inappropriate VaR models
The Value-at-Risk calculation reduces the dimensionality of the risk factor space. The main reasons for such simplifications are, e.g., technical efficiency, the logic and statistical appropriateness of the model. In Chapter 2 we present three simple mappings: the mapping on the market index, the principal components model and the model with equally correlated risk factors. The comparison of these models in Chapter 3 is based on the literatere on the verification of weather forecasts (Murphy and Winkler 1992, Murphy 1997). Some considerations on the quantitative analysis are presented in the fourth chapter. In the last chapter, we present empirical analysis of the DAX data using XploRe.
(This abstract was borrowed from another version of this item.)
Volume (Year): 90 (2006)
Issue (Month): 2 (June)
|Contact details of provider:|| Web page: http://www.springer.com|
Web page: http://www.dstatg.de/de/startseite/
|Order Information:||Web: http://www.springer.com/statistics/journal/10182/PS2|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Murphy, Allan H. & Winkler, Robert L., 1992. "Diagnostic verification of probability forecasts," International Journal of Forecasting, Elsevier, vol. 7(4), pages 435-455, March.
When requesting a correction, please mention this item's handle: RePEc:spr:alstar:v:90:y:2006:i:2:p:273-297. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.