ARCH Test Explained

In this week’s issue of Tips & Tricks, we use the NumXL package to explain a common – and commonly misunderstood – diagnostic in econometric and time series analysis: the Auto-Regressive Conditional Heteroskedacity test or ARCH test for short.

As we will show, the ARCH test is essentially a tool for detecting non-linear autocorrelation in the time series. To illustrate this, we will use the time series of the IBM stock prices in the period between May 17, 1961, and November 2nd, 1962. We will then use the ARCH test to detect a time-varying phenomenon in the conditional volatility, and, in effect, help us to select different models to capture these dynamics. The exercise highlights the ARCH test’s utility as a tool for examining the time dynamics of the second moment and will serve as a useful introduction to the ARCH Test function in NumXL.

You can find more details and a step-by-step tutorial, along with a downloadable spreadsheet and PDF, at the following link: ARCH Test Explained

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