A0338
Title: Estimating the Hurst parameter via ordinal pattern distributions
Authors: Alexander Schnurr - University Siegen (Germany) [presenting]
Abstract: The ordinal structure of long-range dependent time series is analyzed. To this end, so-called ordinal patterns are used, which describe the relative position of consecutive data points. Two estimators are provided for the probabilities of ordinal patterns and prove limit theorems in different settings, namely stationarity and (less restrictive) stationary increments. In the second setting, a Rosenblatt distribution in the limit is encountered. More general limit theorems are proven for functions with Hermite rank 1 and 2. The limit distribution is derived for an estimation of the Hurst parameter H if it is higher than 3/4. Thus, the theorems complement results for lower values of H, which can be found in the literature.
