Class Topper Optimization for the Problem of Portfolio Optimization with a Restricted Set of Assets

Abstract

Portfolio inflexibility is one of the most explored topics in FIES (financial investment expert system). Conventional ways to resolving the non-linear limited portfolio optimization issue with multi-objective functions are inefficient. In this work, Class Topper Optimization (CTO) technique is used to provide a meta-heuristic strategy for portfolio optimization. The mean-variance portfolio selection is the subject of the research. The goal is to manage an asset portfolio that reduces risk while adhering to the constraint of ensuring a certain level of return. In this work, Indian stock exchange share market value is examined to maximize the sharp ratio and expected returns with minimizing the risk of portfolio. A comparative study with CTO algorithm is undertaken when the model is put to the test on a number of hazardous stock holdings, both restricted and unconstrained. The CTO model has a great processing efficiency when it comes to build optimal risky portfolios. According to preliminary studies of PSO and excel solver, the method looks to be quite promising, with results that are comparable to some state-of-the-art solvers.