Clustering, Long Memory and Stocks’ Performance

In this chapter, we investigate the existence of a relationship between long memory, considering Hurst exponents, and financial performances, taking the Sharpe ratio. To this aim, we collect a sample of more than one thousand stocks in the U.S. financial market. Moreover, we identify clusters of stocks characterized by different relationships using clusterwise mixture regression modelling. We find that a large Hurst exponent is associated with a low financial performance. However, we also show that this relationship obeys a clustered structure and that the relationship is not the same across the identified clusters.