In the field of Portfolio Optimization, Enhanced Indexation is the problem of selecting a portfolio that generates excess return with respect to a benchmark index. In this work, we propose a linear programming model for Enhanced Indexation that selects an optimal portfolio according to a generalization of strong stochastic dominance. Since our model has an exponential number of constraints, we solve it through a constraint generation procedure. Some experimental results are presented for well-known financial data sets showing good out-of-sample performance of our model.
R., B., Cesarone, F., A., S., F., T. (2012). A Linear Programming Model for Enhanced Indexation based on Strong Stochastic Dominance. In Proceedings of 25th European Conference on Operational Research.
A Linear Programming Model for Enhanced Indexation based on Strong Stochastic Dominance
CESARONE, FRANCESCO;
2012-01-01
Abstract
In the field of Portfolio Optimization, Enhanced Indexation is the problem of selecting a portfolio that generates excess return with respect to a benchmark index. In this work, we propose a linear programming model for Enhanced Indexation that selects an optimal portfolio according to a generalization of strong stochastic dominance. Since our model has an exponential number of constraints, we solve it through a constraint generation procedure. Some experimental results are presented for well-known financial data sets showing good out-of-sample performance of our model.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
