LONG-TERM MEMORY EFFECT IN STOCK PRICES ANALYSIS

Abstract

The Hurst exponent is widely applied for time series analysis. The Hurst exponent is a statistical measure used to classify time series. Using the Hurst parameter processes are classified into long range dependence, antipersistence and white noise processes.

R/S analysis method is one of the few methods that evaluate the Hurst exponent. This method uses the rescaled range statistic (R/S statistic). The R/S statistic is the range of partial sums of deviations of a time series from its mean, rescaled by its standard deviation. A log-log plot of the R/S statistic versus the number of points of the aggregated series should be a straight line with the slope being an estimation of the Hurst exponent.

However, there are many methods of evaluating the Hurst exponent such as ratio variance of residuals, the periodogram method, the Whittle method, the Abri-Veitch method, etc.

Investigation object – the Baltic sector indices. The latter represent tendencies of different sector activity indices in the stock market.

The work concentrates on calculating the Hurst parameter, evaluated Hurst parameters of the Baltic sector indices are given for different periods of time.