Article1998

Nonlinearities and Nonstationarities in Stock Returns

55 citations0/0 files storedJournal of Business and Economic Statistics

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Financial Markets and Investment Strategies Financial Risk and Volatility Modeling Complex Systems and Time Series Analysis

Abstract

This article addresses the question of whether recent findings of nonlinearities in high-frequency financial time series have been contaminated by possible shifts in the distribution of the data. It applies a recursive version of the Brock–Dechert–Scheinkman statistic to daily data on two stock-market indexes between January 1980 and December 1990. It is shown that October 1987 is highly influential in the characterization of the stock-market dynamics and appears to correspond to a shift in the distribution of stock returns. Sampling experiments show that simple linear processes with shifts in variance can replicate the behavior of the tests, but autoregressive conditional heteroscedastic filters are unable to do so.

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References

1995Journal of the American Statistical Association 1996A test for independence based on the correlation dimension 1994Autoregressive conditional heteroskedasticity and changes in regime 1990Persistence in Variance, Structural Change, and the GARCH Model 1994Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance 1991Chaos and Nonlinear Dynamics: Application to Financial Markets 1996The econometrics of financial markets 1994Chapter 49 Arch models

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