Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
special section
Discriminant analyses of stock prices by using multifractality of time series generated via multi-agent systems and interpolation based on wavelet transforms
Shozo TokinagaYoshikazu Ikeda
Author information
JOURNALS FREE ACCESS

2010 Volume 1 Issue 1 Pages 133-145

Details
Abstract

In investments, it is not easy to identify traders'behavior from stock prices, and agent systems may help us. This paper deals with discriminant analyses of stock prices using multifractality of time series generated via multi-agent systems and interpolation based on Wavelet Transforms. We assume five types of agents where a part of agents prefer forecast equations or production rules. Then, it is shown that the time series of artificial stock price reveals as a multifractal time series whose features are defined by the Hausedorff dimension D(h). As a result, we see the relationship between the reliability (reproducibility) of multifractality and D(h) under sufficient number of time series data. However, generally we need sufficient samples to estimate D(h), then we use interpolations of multifractal times series based on the Wavelet Transform.

Information related to the author
© 2010 The Institute of Electronics, Information and Communication Engineers
Previous article Next article
feedback
Top