Muller U. A., A. Dacorogna M. M. and Pictet, O. V. (1998) Heavy tails in high-frequency financial data. In: R.J. Adler, R. E. Feldman and M. S. Taqqu (Eds.) A Practical Guide to Heavy Tails: Statistical Techniques for Analysing Heavy Tailed Distributions, pp. 55-77. Birkhauser, Boston, MA. Home/Search Document Not in Database Summary Related Articles Check |
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Effective Calibration - Gallant (2001) (Correct)
....and calibrations can vary markedly from sample to sample and exhibit large uctuations when the time span of a sample is changed. The application of Section 5 is an instance where one might be concerned about the reliability of method of moments calibrations because the empirical results of M uller, Dacorogna, and Picter (1998) and citations therein indicate that a presumption of existence of moments past the second is dubious for data from nancial markets. But why take a chance on the existence of any moment when the assumption is unnecessary A structural problem with method of moments calibration is a lack of ....
Muller, U. A., M. M. Dacorogna, and O. V. Picter (1998), \Heavy Tails in High-Frequency Financial Data," in R. J. Adler, R. E. Feldman, and M. S. Taqqu, eds., A Practical Guide to Heavy Tails: Statistical Techniques and Applications, Birkhauser, Boston.
Long range dependence effects and ARCH modelling - Thomas Mikosch, Catalin Starica (2000) (Correct)
....GARCH model (i.e. an integrated or almost integrated GARCH) as generating process for log returns presupposes a tail index of (or close to) 2. However the existing statistical evidence shows quite convincingly that the tails of real log returns are not so heavy; see for example Muller et al. [28] and Embrechts et al. 17] We can offer two alternative explanations for the deviation of from 2. 9 ffl The statistical estimates of are poor. ffl The IGARCH effect is spurious and occurs because the GARCH process is not a suitable model for the data. The first fact has been discussed in ....
M uller, U.A., Dacorogna, M.M. and Pictet, O.V. (1998) Heavy tails in high-frequency financial data. In: Adler, R.J., Feldman, R.E. and Taqqu, M.S. (Eds.) A Practical Guide to Heavy Tails, Birkhauser, Boston, pp. 55--78.
Modelling, Estimation and Visualization of - Multivariate Dependence For (Correct)
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Muller U. A., A. Dacorogna M. M. and Pictet, O. V. (1998) Heavy tails in high-frequency financial data. In: R.J. Adler, R. E. Feldman and M. S. Taqqu (Eds.) A Practical Guide to Heavy Tails: Statistical Techniques for Analysing Heavy Tailed Distributions, pp. 55-77. Birkhauser, Boston, MA.
Intraday Value-At-Risk - Giot (2000) (Correct)
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Muller, U.A., Dacorogna, M.M. and Pictet, O.V. (1996). Heavy tails in highfrequency financial data. Olsen Preprint
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