High Watermarks of Market Risks
AbstractWe present several estimates of measures of risk amongst the most well-known, using both high and low frequency data. The aim of the article is to show which lower frequency measures can be an acceptable substitute to the high precision measures, when transaction data is unavailable for a long history. We also study the distribution of the volatility, focusing more precisely on the slopee of the tail of the various risk measure distributions, in order to define the high watermarks of market risks. Based on estimates of the tail index of a Generalized Extreme Value density backed-out from the high frequency CAC 40 series in the period 1997-2006, using both Maximum Likelihood and L-moment Methods, we, finally find no evidence for the need of a specification with heavier tails than in the case of the traditional log-normal hypothesis.
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Bibliographic InfoPaper provided by Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne in its series Documents de travail du Centre d'Economie de la Sorbonne with number 09054.
Length: 27 pages
Date of creation: Aug 2009
Date of revision:
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Financial crisis; volatility estimator distributions; range-based volatility; extreme value; high frequency data.;
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Find related papers by JEL classification:
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-10-24 (All new papers)
- NEP-ECM-2009-10-24 (Econometrics)
- NEP-MST-2009-10-24 (Market Microstructure)
- NEP-RMG-2009-10-24 (Risk Management)
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- Bertrand B. Maillet & Jean-Philippe R. Médecin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
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