Long-Term Memory in Stock Market Prices
提出一种对短期依赖稳健的长期记忆检验方法，并应用于多频率股票回报指数，发现考虑短期自相关后不存在长期依赖证据。
A test for long-run memory that is robust to short-range dependence is developed. It is a simple extension of Mandelbrot's range over standard deviation or R/S statistic, for which the relevant asymptotic sampling theory is derived via functional central limit theory. This test is applied to daily, weekly, monthly, and annual stock returns indexes over several different time periods. Contrary to previous findings, there is no evidence of long-range dependence in any of the indexes over any sample period or sub-period once short-term autocorrelations are taken into account. Illustrative Monte Carlo experiments indicate that the modified R/S test has power against at least two specific models of long-run memory, suggesting that stochastic models of short-range dependence may adequately capture the time series behavior of stock returns.