Article2001

Testing for Autocorrelation Using a Modified Box‐Pierce Q Test

Ignacio N. Lobato · John C. Nankervis · N. E. Savin

104 citations0/0 files storedInternational Economic Review

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

Abstract

This article investigates the finite‐sample performance of a modified Box‐Pierce Q statistic (Q*) for testing that financial time series are uncorrelated without assuming statistical independence. The finite‐sample rejection probabilities of the Q* test under the null and its power are examined in experiments using time series generated by an MA (1) process where the errors are generated by a GARCH (1, 1) model and by a long memory stochastic volatility model. The tests are applied to daily currency returns.

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References

1986Generalized autoregressive conditional heteroskedasticity 1992Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances 1992Simple Technical Trading Rules and the Stochastic Properties of Stock Returns 1996Fractionally integrated generalized autoregressive conditional heteroskedasticity 19965 Stochastic volatility 1990Stationarity and Persistence in the GARCH(1,1) Model 1975Weak convergence to fractional brownian motion and to the rosenblatt process 1993ARCH MODELS: PROPERTIES, ESTIMATION AND TESTING

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