Analysing Financial Returns by Using Regression Models Based on Non-Symmetric Stable Distributions

The daily evolution of the price of Abbey National shares over a 10-week period is analysed by using regression models based on possibly non-symmetric stable distributions. These distributions, which are only known through their characteristic function, can be used in practice for interactive modelling of heavy-tailed processes. A regression model for the location parameter is proposed and shown to induce a similar model for the mode. Finally, regression models for the other three parameters of the stable distribution are introduced. The model found to fit best allows the skewness of the distribution, rather than the location or scale parameters, to vary over time. The most likely share return is thus changing over time although the region where most returns are observed is stationary.

[1]  John Teichmoeller A Note on the Distribution of Stock Price Changes , 1971 .

[2]  A. Paulson,et al.  The estimation of the parameters of the stable laws , 1975 .

[3]  E. Fama,et al.  Parameter Estimates for Symmetric Stable Distributions , 1971 .

[4]  Aleksander Weron,et al.  Can One See $\alpha$-Stable Variables and Processes? , 1994 .

[5]  Ioannis A. Koutrouvelis,et al.  Regression-Type Estimation of the Parameters of Stable Laws , 1980 .

[6]  Makoto Yamazato,et al.  Unimodality of Infinitely Divisible Distribution Functions of Class $L$ , 1978 .

[7]  M. Taqqu,et al.  Stable Non-Gaussian Random Processes : Stochastic Models with Infinite Variance , 1995 .

[8]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[9]  P. Hougaard Survival models for heterogeneous populations derived from stable distributions , 1986 .

[10]  C. Mallows,et al.  A Method for Simulating Stable Random Variables , 1976 .

[11]  E. Fama,et al.  Some Properties of Symmetric Stable Distributions , 1968 .

[12]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[13]  C. E. Rogers,et al.  Symbolic Description of Factorial Models for Analysis of Variance , 1973 .

[14]  C. Klüppelberg,et al.  Modelling Extremal Events , 1997 .

[15]  Robert A. Leitch,et al.  Estimation of Stable Law Parameters: Stock Price Behavior Application , 1975 .

[16]  Bruce D. Fielitz,et al.  Asymmetric Stable Distributions of Stock Price Changes , 1972 .

[17]  B. Mandelbrot The Variation of Certain Speculative Prices , 1963 .

[18]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[19]  D. Buckle Bayesian Inference for Stable Distributions , 1995 .

[20]  J. Hoffmann-jorgensen,et al.  Probability with a View Toward Statistics , 1994 .

[21]  Wolfgang Gawronski,et al.  ON THE BELL-SHAPE OF STABLE DENSITIES , 1984 .

[22]  S. James Press,et al.  Estimation in Univariate and Multivariate Stable Distributions , 1972 .

[23]  B. Brorsen,et al.  Maximum likelihood estimation of a GARCH‐stable model , 1995 .

[24]  James K. Lindsey,et al.  Parametric Statistical Inference , 1996 .

[25]  W. DuMouchel Stable Distributions in Statistical Inference: 1. Symmetric Stable Distributions Compared to other Symmetric Long-Tailed Distributions , 1973 .

[26]  W. DuMouchel Stable Distributions in Statistical Inference: 2. Information from Stably Distributed Samples , 1975 .