What can we see from Investment Simulation based on Generalized (m,2)-Zipf law?

The paper revisits the investment simulation based on strategies exhibited by Generalized (m, 2)-Zipf law to present an interesting characterization of the wildness in financial time series. The investigations of dominant strategies on each specific time series shows that longer words dominant in larger time scale exhibit shorter dominant ones in smaller time scale and vice versa. Moreover, denoting the term wildness based on persistence over short term trend and memory represented by particular length of words, we can see how wild historical fluctuations over time series data coped with the Zipf strategies.