In this study we investigate various well-known time-independent models of asset returns being simple normal distribution, Student t-distribution, Levy, truncated Levy, general stable distribution. mixed diffusion jump, and compound normal distribution. For this we use Standard and Poor's 500 index data of the New York Stock Exchange, Helsinki Stock Exchange index data describing a small volatile market, and artificial data. The results indicate that all models, excluding the simple normal distribution, are, at least. quite reasonable descriptions of the data. Furthermore. the use of differences instead of logarithmic returns tends to make the data looking visually more Levy-type distributed than it is. This phenomenon is especially evident in the artificial data that has been generated by an inflated random walk process. (C) 2000 Elsevier Science B.V. All rights reserved.
|Number of pages||21|
|Journal||Physica A: Statistical Mechanics and its Applications|
|Publication status||Published - 1 Jul 2000|
|MoE publication type||A1 Journal article-refereed|