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Fat-Tailed Models for Risk Estimation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Güner, Biliana S. Mitov, Ivan Racheva-Yotova, Boryana |
| Copyright Year | 2012 |
| Abstract | Accounting for the likelihood of observing extreme returns and for return asymmetry is paramount in financial modeling. In addition to recognizing essential features of the returns’ temporal dynamics, such as autocorrelations, volatility clustering, and long memory, a successful univariate model employs a distributional assumption flexible enough to accommodate various degrees of skewness and heavy-tailedness. At the same time, a model's usefulness depends on its scalability and practicality—the extent to which the univariate model can be extended to a multivariate one covering a large number of assets. Keywords: risk model; heavy-tailed; Student's; distribution; Pareto stable; autocorrelation; volatility clustering; skewness; Power-tail decay; Existence of raw moments; Stability; EVT; value-at-risk |
| File Format | PDF HTM / HTML |
| DOI | 10.1002/9781118182635.efm0085 |
| Alternate Webpage(s) | https://www.econstor.eu/bitstream/10419/45631/1/659400324.pdf |
| Alternate Webpage(s) | http://econpapers.wiwi.kit.edu/downloads/KITe_WP_30.pdf |
| Alternate Webpage(s) | https://doi.org/10.1002/9781118182635.efm0085 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
