Abstract
This paper uses a statistical model developed by Beran and Feng (2001) to analyze the daily turnover of the stocks that made up the Dow Jones industrial index from June 1962 to December 2002. Using this model, I find that the historical daily stock turnover can be decomposed into two parts: a nonlinear deterministic trend term and a random term. The long memory process of the random term dominates its dynamics while the short memory process is surprisingly insignificant. The innovation process of the random term has heavy tails which may be due to the temporal dependence of the conditional variance.
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