A1 Refereed original research article in a scientific journal
Characteristic times in stock market indices
Authors: Kullmann L, Toyli J, Kertesz J, Kanto A, Kaski K
Publisher: ELSEVIER SCIENCE BV
Publication year: 1999
Journal: Physica A: Statistical Mechanics and its Applications
Journal name in source: PHYSICA A
Journal acronym: PHYSICA A
Volume: 269
Issue: 1
First page : 98
Last page: 110
Number of pages: 13
ISSN: 0378-4371
DOI: https://doi.org/10.1016/S0378-4371(99)00084-9
Abstract
In this study we analyze the Standard and Poor's 500 index data of the New York Stock Exchange far more than 32 years. Using a simple random walk model we demonstrate that the proper variable to look at is the logarithmic return. In the statistical analysis we have done fittings to the Livy distribution using either the index data as such or pre-processing it with ARCH, GARCH or IGARCH methods, which tend to remove the time-dependent variance. For short times the truncated Levy distribution is found to fit the data quite well. Since this is not a stable distribution, the sealing behavior observed for short times should brake down for longer times. We demonstrate that the characteristic time where this cross-over starts is of the order of one day. (C) 1999 Elsevier Science B.V. All rights reserved.
In this study we analyze the Standard and Poor's 500 index data of the New York Stock Exchange far more than 32 years. Using a simple random walk model we demonstrate that the proper variable to look at is the logarithmic return. In the statistical analysis we have done fittings to the Livy distribution using either the index data as such or pre-processing it with ARCH, GARCH or IGARCH methods, which tend to remove the time-dependent variance. For short times the truncated Levy distribution is found to fit the data quite well. Since this is not a stable distribution, the sealing behavior observed for short times should brake down for longer times. We demonstrate that the characteristic time where this cross-over starts is of the order of one day. (C) 1999 Elsevier Science B.V. All rights reserved.
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