Financial Engineering and the Japanese Markets

, Volume 2, Issue 3, pp 197–218 | Cite as

A new approach for testing the randomness of heteroskedastic time series data

  • Kazuo Kishimoto


Proposed is a conditional approach for testing the randomness of heteroskedastic time series data as well as for checking the validity of this testing. It is shown that the ordinary serial correlation test works correctly neither for daily sequence of the TOPIX index in Tokyo Stock Exchange nor for heteroskedastic models, while our approach works well for them. It is also shown that our approach is enough powerful for detecting the departure from the randomness.

An advantage of this approach is that it allows us to use any quantity for testing. Its application to the TOPIX index detected statistically significant long term correlation which causes both the mean reversion and the outperformance of the Alexander's filter rule over the buy-and-hold strategy.


Transaction Cost Serial Correlation Stable Distribution Filter Size Short Selling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Kazuo Kishimoto
    • 1
  1. 1.Institute of Socio-Economic Planning University of TsukubaTsukuba IbarakiJapan

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