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Autocorrelation, definition, estimation, and the returns puzzle

Define the autocorrelation function of a stationary time series and its sample estimate. How would you test whether a return series is serially correlated? And what does it mean that stock returns show near-zero autocorrelation while their absolute values show strong, slowly decaying autocorrelation?

Show a hint

Under the null of white noise, sample autocorrelations at each lag are approximately N(0,1/n)\mathcal{N}(0, 1/n). For the puzzle: does zero correlation imply independence?

Your answer

This one is open-ended. Work it through, then check your reasoning against the full solution.

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