Portfolio selection model using teaching learning-based optimization approach

<p>Portfolio selection is among the most challenging processes that have recently increased interest of professionals in area. The goal mean-variance portfolio to maximize expected return with minimizing risk. Markowitz model was employed solve linear problem. However, due numerous constraints and complexities, problem so critical traditional models are insufficient provide efficient solutions. Teaching learning-based optimization (TLBO) a powerful population-based nature-inspired approach problems. This article presents using TLBO portfolio's Sharpe Ratio. ratio combines both algorithm natural teaching process classroom two main phases, viz., learning. Performance analysis has been undertaken investigate suitability based solution by comparing it genetic (GA) particle swarm (PSO) on real datasets, Deutscher Aktienindex (DAX) 100, Hang Seng 31, Standard Poor’s (S&P) financial times stock exchange (FTSE) Nikkei 225. empirical results verify superiority over GA PSO.</p>