The Random Walk Of Stock Prices: Implications Of Recent Nonpara-Metric Tests
This paper applies six recently developed nonparametric tests of serial independence to monthly US stock returns. Findings of previous studies based on the BDS test are sup-ported since most of the new tests also reject the random walk hypothesis. Furthermore, power properties of the new tests are compared with those of the BDS test. The latter has much power against ARCH and GARCH alternatives whereas some of the more recent tests are superior against other alternatives. Finally, the power study of this paper shows, contrary to common belief, that ARCH and GARCH effects do not seem to explain rejec-tion of the random walk.
|Date of creation:||04 Aug 2001|
|Date of revision:|
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- Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-37, July.
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Cambridge University Press, number 9780521355643, September.
- Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
- Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
- Ahmad, Ibrahim A. & Li, Qi, 1997. "Testing independence by nonparametric kernel method," Statistics & Probability Letters, Elsevier, vol. 34(2), pages 201-210, June.
- Yongmiao Hong & Halbert White, 2005. "Asymptotic Distribution Theory for Nonparametric Entropy Measures of Serial Dependence," Econometrica, Econometric Society, vol. 73(3), pages 837-901, 05.
- P. M. Robinson, 1991. "Consistent Nonparametric Entropy-Based Testing," Review of Economic Studies, Oxford University Press, vol. 58(3), pages 437-453.
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