Detecting Arch Effects in Non-Gaussian Time Series

Posted: 10 Jul 2008

See all articles by Burkhard Raunig

Burkhard Raunig

Austrian National Bank - Economic Studies Division

Date Written: Spring 2008


Engles ARCH test has become the standard test for ARCH effects in applied work. Under non-normality the true rejection probability of this test can differ substantially from the nominal level, however. Bootstrap and Monte Carlo versions of the test may then be used instead. This paper proposes an alternative test procedure. The new test exploits the empirical distribution of the data and an extended probability integral transformation. The test is compared with the former tests in Monte Carlo experiments. Under normality, the new test works as well as the conventional Monte Carlo test and the bootstrap. Under non-normality, the test tends to be more accurate and more powerful than the bootstrapped ARCH test. The procedure is then used to test for ARCH effects in S&P 500 returns sampled at different frequencies. In contrast to the standard and the bootstrapped ARCH tests, the new test detects ARCH effects in the transformed low-frequency returns.

Keywords: C12, C14, C22, C52, ARCH, GARCH, bootstrap, Monte Carlo tests, distributional assumptions

Suggested Citation

Raunig, Burkhard, Detecting Arch Effects in Non-Gaussian Time Series (Spring 2008). Journal of Financial Econometrics, Vol. 6, Issue 2, pp. 271-289, 2008. Available at SSRN: or

Burkhard Raunig (Contact Author)

Austrian National Bank - Economic Studies Division ( email )

POB 61
Vienna, A-1011
+43 1 404 20 7219 (Phone)
+43 1 404 20 7299 (Fax)

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