NONLINEAR DYNAMICS AND THE DISTRIBUTION OF DAILY STOCK INDEX RETURNS

B. Wade Brorsen; Seung‐Ryong ‐R Yang

doi:10.1111/j.1475-6803.1994.tb00185.x

NONLINEAR DYNAMICS AND THE DISTRIBUTION OF DAILY STOCK INDEX RETURNS

B. Wade Brorsen^*, Seung‐Ryong ‐R Yang

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

Three alternative models of daily stock index returns are considered: (1) a diffusion‐jump process; (2) an extended generalized autoregressive conditional heteroskedasticity (GARCH) process; and (3) a combination of the GARCH and jump processes. Non‐nested tests between the diffusion‐jump process and a GARCH(1.1) process with t‐distributed errors reject the diffusion‐jump process, but do not always reject the GARCH process. Kolmogorov‐Smirnov tests of fit, however, reject the GARCH(1,1)‐t process for all cases. Nonlinear dependence is not removed for the value‐weighted index and the S&P 500 stock index; therefore, deterministic chaos cannot be dismissed.

Original language	English
Pages (from-to)	187-203
Number of pages	17
Journal	Journal of Financial Research
Volume	17
Issue number	2
DOIs	https://doi.org/10.1111/j.1475-6803.1994.tb00185.x
Publication status	Published - 1994
Externally published	Yes

ASJC Scopus subject areas

Accounting
Finance

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abstract = "Three alternative models of daily stock index returns are considered: (1) a diffusion‐jump process; (2) an extended generalized autoregressive conditional heteroskedasticity (GARCH) process; and (3) a combination of the GARCH and jump processes. Non‐nested tests between the diffusion‐jump process and a GARCH(1.1) process with t‐distributed errors reject the diffusion‐jump process, but do not always reject the GARCH process. Kolmogorov‐Smirnov tests of fit, however, reject the GARCH(1,1)‐t process for all cases. Nonlinear dependence is not removed for the value‐weighted index and the S\&P 500 stock index; therefore, deterministic chaos cannot be dismissed.",

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AB - Three alternative models of daily stock index returns are considered: (1) a diffusion‐jump process; (2) an extended generalized autoregressive conditional heteroskedasticity (GARCH) process; and (3) a combination of the GARCH and jump processes. Non‐nested tests between the diffusion‐jump process and a GARCH(1.1) process with t‐distributed errors reject the diffusion‐jump process, but do not always reject the GARCH process. Kolmogorov‐Smirnov tests of fit, however, reject the GARCH(1,1)‐t process for all cases. Nonlinear dependence is not removed for the value‐weighted index and the S&P 500 stock index; therefore, deterministic chaos cannot be dismissed.

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ER -

NONLINEAR DYNAMICS AND THE DISTRIBUTION OF DAILY STOCK INDEX RETURNS

Abstract

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