Risk measures with non-Gaussian fluctuations

Physics – Physics and Society

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

revtex4, 10 pages, 3 figures, proceeding of Apfa5 Conference

Scientific paper

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-$t$ (or Tsallis) 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. Detailed comparison with the results of the widely used procedures of quantitative finance, such as parametric normal approach, RiskMetrics methodology and historical simulation, as well as with previous findings in the literature, are shown and commented. Particular attention is paid to quantify the size of the errors affecting the risk measures obtained according to different methodologies, by employing a bootstrap technique.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Risk measures with non-Gaussian fluctuations does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Risk measures with non-Gaussian fluctuations, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Risk measures with non-Gaussian fluctuations will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-250564

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.