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Volume 6, Number 2 / June 2002 , Pages 65-130
Multinational Finance Journal, 2002, vol. 6, no. 2, pp. 65-98 |
Marco Corazza , University Ca’ Foscari of Venice, Italy    Corresponding Author
A. G. Malliaris , Loyola University Chicago, U.S.A.

Several empirical studies have shown the inadequacy of the standard Brownian motion (sBm) as a model of asset returns. To correct for this evidence some authors have conjectured that asset returns may be independently and identically Pareto-Lévy stable (PLs) distributed, whereas others have asserted that asset returns may be identically - but not independently - fractional Brownian motion (fBm) distributed with Hurst exponents, in both cases, that differ from 0.5. In this article we empirically explore such non-standard assumptions for both spot and (nearby) futures returns for five foreign currencies: the British Pound, the Canadian Dollar, the German Mark, the Swiss Franc, and the Japanese Yen.

Keywords : exponent of Hurst; fractional Brownian motion; multi-fractal market hypothesis; Pareto-Levy stable process; R/S analysis
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Multinational Finance Journal, 2002, vol. 6, no. 2, pp. 99-130 |
Mondher Bellalah , Université de Cergy-Pontoise, France    Corresponding Author
Marc Lavielle , Univsité Paris-Sud, France

The selection of an appropriate parameterization of data is a fundamental step in a majority of empirical research effort. Likewise, detecting or estimating features of non-stationarities in data sequences is a critical point in conducting credible research that uses data for inference. In this spirit, this paper presents a simple decomposition of the empirical return distributions of financial assets into the sum of various normal distributions. The decomposition is motivated by the fact that market participants expect distributions to be drawn from two or three possible scenarios. It is also motivated by the recent applications of the EM algorithm to financial data. A parametric and a nonparametric approach are proposed and applied to the empirical distribution of the CAC 40 index traded in the Paris Bourse. We estimate the parameters of the mixture and propose a decomposition into three Gaussian distributions which essentially differ by their variances. The decomposition fits the observed distribution. An alternative approach, which consists in detecting these changes and estimating the distribution of the returns between two changes is developed. The results are obtained using a segmentation method, which is applied to financial data. One of the main findings in this paper is that the two approaches show the same results and give support to the proposed decomposition. There exists three kinds of regimes in the Paris Bourse and the series of the returns jump from a regime to another one at some random instants. This work might be applied to other data sets or other data generating conditions. It can used for the valuation of standard and exotic derivatives.

Keywords : derivatives; distributions; EM algorithm; mixture
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