Testing for Covariance Stationarity in Stock Market Data
Adrian R. Pagan
Australian National University
G. William Schwert
University of Rochester, Rochester, NY 14627
and National Bureau of Economic Research
Economics Letters, 33 (1990) 165-170
This paper proposes several non-parametric tests for covariance stationarity and applies them to common stock return data from 1834-1987. Recursive variance plots, post-sample prediction tests, Cumulative Sum (henceforth CUSUM) tests, and modified scaled range tests all show strong non-stationarity in stock returns, primarily due to the large increase in volatility during the Great Depression. These tests should be useful as diagnostics for data where the assumptions underlying the desired statistical procedure require stationarity.
Key words: Volatility, Heteroskedasticity, Stock Market, Non-parametric, CUSUM, Stationarity
JEL Classifications: G14, C22
Cited 59 times in the SSCI and SCOPUS through 2020
© Copyright 1990, Elsevier
The following file contains the reprint of this paper in Acrobat's portable data format (.pdf).
Click here to download
this paper in PDF format.
Return to Publications Page
© Copyright 1998-2021, G. William
Schwert
Last Updated on 9/17/2021