The Hurst exponent indicates whether a time series behaves randomly, trending, or mean-reverting. In this case, the autocorrelation increases with lag, resulting in a decreasing speed of autocorrelation. Therefore, it is an excellent trading tool.
The Hurst exponent is a measure of the memory in a time series and is used to classify the series as mean-reverting, trending, or a random walk. depending on the choice of the maximum lag parameter (i.e., whether we are looking for short or long term), the results can differ significantly.
A brief history of Hurst Phenomenon...
The Hurst exponent is used as a measure of long-term memory of time series. It relates to the autocorrelations of the time series, and the rate at which these decrease as the lag between pairs of values increases. Studies involving the Hurst exponent were originally developed in hydrology for the practical matter of determining optimum dam sizing for the Nile river's volatile rain and drought conditions that had been observed over a long period of time. The name "Hurst exponent", or "Hurst coefficient", derives from Harold Edwin Hurst (1880–1978), who was the lead researcher in these studies; the use of the standard notation H for the coefficient also relates to his name.
