dorsal/arxiv
View SchemaA Non-Gaussian Approach to Risk Measures
| Authors | G. Bormetti, E. Cisana, G. Montagna, O. Nicrosini |
|---|---|
| Categories | |
| ArXiv ID | physics/0605146 |
| URL | https://arxiv.org/abs/physics/0605146 |
| DOI | 10.1016/j.physa.2006.10.008 |
| Journal | Physica A, 376 (2007) p. 532-542 |
Abstract
Reliable calculations of financial risk require that the fat-tailed nature of prices changes is included in risk measures. To this end, a non-Gaussian approach to financial risk management is presented, modeling the power-law tails of the returns distribution in terms of a Student-t distribution. Non-Gaussian closed-form solutions for Value-at-Risk and Expected Shortfall are obtained and standard formulae known in the literature under the normality assumption are recovered as a special case. The implications of the approach for risk management are demonstrated through an empirical analysis of financial time series from the Italian stock market and in comparison with the results of the most widely used procedures of quantitative finance. Particular attention is paid to quantify the size of the errors affecting the market risk measures obtained according to different methodologies, by employing a bootstrap technique.
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"abstract": "Reliable calculations of financial risk require that the fat-tailed nature of\nprices changes is included in risk measures. To this end, a non-Gaussian\napproach to financial risk management is presented, modeling the power-law\ntails of the returns distribution in terms of a Student-t distribution.\nNon-Gaussian closed-form solutions for Value-at-Risk and Expected Shortfall are\nobtained and standard formulae known in the literature under the normality\nassumption are recovered as a special case. The implications of the approach\nfor risk management are demonstrated through an empirical analysis of financial\ntime series from the Italian stock market and in comparison with the results of\nthe most widely used procedures of quantitative finance. Particular attention\nis paid to quantify the size of the errors affecting the market risk measures\nobtained according to different methodologies, by employing a bootstrap\ntechnique.",
"arxiv_id": "physics/0605146",
"authors": [
"G. Bormetti",
"E. Cisana",
"G. Montagna",
"O. Nicrosini"
],
"categories": [
"physics.soc-ph",
"physics.data-an",
"q-fin.RM"
],
"doi": "10.1016/j.physa.2006.10.008",
"journal_ref": "Physica A, 376 (2007) p. 532-542",
"title": "A Non-Gaussian Approach to Risk Measures",
"url": "https://arxiv.org/abs/physics/0605146"
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