Many problems in quantitative finance involve both predictive forecasting and decision-based optimization. Traditionally, models are optimized with unique prediction-based objectives constraints, therefore unaware of how those predictions will ultimately be used the context their final We present a stochastic optimization framework for integrating regression based mean-variance portfolio settin...

The aim of optimization methods is to identify the best results in search area. In this research, we focused on a mixture interior point method, opposite gradient and mean-variance mapping optimization, named IPOG-MVMO, where solutions can be obtained from field cost function constraint manifold. process was divided into three main phases. first phase, method applied for local searching. Second...