document: Estimating long-range dependence : finite sample properties and confidence intervals A major issue in financial economics is the behavior of asset returns over long horizons . Various estimators of long-range dependence have been proposed . Even though some have known asymptotic properties , it is important to test their accuracy by using simulated series of different lengths . We test R/S analysis , detrended fluctuation analysis and periodogram regression methods on samples drawn from Gaussian white noise . The DFA statistics turns out to be the unanimous winner . Unfortunately , no asymptotic distribution theory has been derived for this statistics so far . We were able , however , to construct empirical -LRB- i.e. approximate -RRB- confidence intervals for all three methods . The obtained values differ largely from heuristic values proposed by some authors for the R/S statistics and are very close to asymptotic values for the periodogram regression method
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