Andreas S. Weigend, Fei Chen, Stephen Figlewski, Steven R. Waterhouse
This study uncovers trading styles in the transaction records of US Treasury bond futures. We use statistical clustering techniques to group together trades that are similar. Trade profit was held back in the clustering process. Results show that clusters differ significantly in their profit and risk characteristics. Some clusters uncover "technical" trading rules. Using the information about the individual accounts, we describe the assignments of accounts to clusters by entropy, and model the transitions of a given account through clusters by a first order Markov model.