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
Article

Abstract

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.

Keywords

Transaction Cost Serial Correlation Stable Distribution Filter Size Short Selling 

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References

  1. Alexander, S.S. (1961), ‘Price movements in speculative markets: trends or random walks’,Industrial Management Review of MIT,2, 7–26.Google Scholar
  2. Bird, P.J.W.N. (1985), ‘The weak form efficiency of the London Metal Exchange’,Applied Economics,17, 571–587.Google Scholar
  3. Dryden, M.M. (1969), ‘A source of bias in filter test of share prices’,Journal of Business,42, 321–325.CrossRefGoogle Scholar
  4. Engle, R.T. (1982), ‘Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation’,Econometrica,50, 987–1007.CrossRefGoogle Scholar
  5. Fama, E.F. and Blume, M.E. (1966), ‘Filter rules and stock-market trading’,Journal of Business.39, 226–241.CrossRefGoogle Scholar
  6. Fama, E.F. and French, K.R. (1988), ‘Dividend yields and expected stock returns’,Journal of Financial Economics,22, 3–25.CrossRefGoogle Scholar
  7. Fushimi, M. (1986), ‘The test of randomness of 800 million M-series random numbers (in Japanese)’,Japanese Journal of Applied Statistics,15, 157–162.Google Scholar
  8. Ikeda, M. (1988) ‘The day of the week effect and the mixture of normal distribution hypothesis (in Japanese)’,Japan Financial Review,8, 27–53.Google Scholar
  9. Kariya, T., Tsukuda, Y. and Maru, J. (1989),Stock Price Changes in Japan (in Japanese), Toyokeizaishinposha: Tokyo.Google Scholar
  10. Kishimoto, K. (1989), ‘A new approach for testing the weak form of efficiency, Institute of Socio-Economic Planning’,Discussion Paper Series, 415.Google Scholar
  11. Lo, A.E. and MacKinlay, A.C. (1988), ‘Stock market prices do not follow random walks: evidence from a simple specification test’,The Review of Economics Studies,1, 41–66.Google Scholar
  12. Mandelbrot, B. (1963), ‘The variation of certain speculative prices’,Journal of Business,36, 394–419.CrossRefGoogle Scholar
  13. Poterba, J.M. and Summers, L.H. (1988), ‘Mean reversion in stock prices: evidence and implications’,Journal of Financial Economics,22, 27–59.CrossRefGoogle Scholar
  14. Praetz, P.D. (1976), ‘On the methodology of testing for independence in future prices: comment’,Journal of Finance,31, 977–979.CrossRefGoogle Scholar
  15. Praetz, P.D. (1979), ‘A general test of a filter effect, Journal of Financial and Quantitative Analysis’,Journal of Financial and Quantitative Analysis,14, 385–394.CrossRefGoogle Scholar
  16. Summers, L.H. (1986), ‘Does the stock market rationally reflect fundamental values?’Journal of Finance,41, 591–602.CrossRefGoogle Scholar
  17. Sweeney, R.J. (1986), ‘Beating the foreign exchange market’,Journal of Finance,41, 163–182.CrossRefGoogle Scholar
  18. Sweeney, R.J. (1988), ‘Some new filter rule tests’,Journal of Quantitative Analysis,23, 285–300.CrossRefGoogle Scholar
  19. Taylor, S. (1980), ‘Conjectured models for trends in financial prices, tests and forecasts’.Journal of Royal Statistical Society, Ser. A,143, 338–362.Google Scholar
  20. Taylor, S. (1982), ‘Tests of the random walk hypothesis against a price-trend hypothesis’,Journal of Financial and Quantitative Analysis,17, 37–61.CrossRefGoogle Scholar
  21. Taylor, S. (1984), ‘Estimating the Variances of autocorrelations calculated from financial time series’,Applied Statistics,33, 300–308.CrossRefGoogle Scholar
  22. Taylor, S. (1986)Modelling Financial Time Series, John Wiley & Sons: New York.Google Scholar
  23. Ziemba, W.T. (preprint)Japanese security market regularities: monthly, turn of the month and year, holiday and golden week effects.Google Scholar

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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