Scenario generation by selection from historical data

Abstract In this paper, we present and compare several methods for generating scenarios stochastic-programming models by direct selection from historical data. The range standard sampling k -means, through iterative sampling-based methods, to a new moment-based optimization approach. We the on simple portfolio-optimization model show how use them in situation when are selecting whole sequences data, instead of single data points.