Optimising liquidity with modified particle swarm optimization application: Case of Casablanca stock exchange

Drawing upon the main theories that frame investment management styles and liquidity of financial assets, this paper is about getting more insight into Optimization of liquidity of the stock market. The liquidity is very important to determinate investment decisions made by institutional investors [8]. We consider the RL variable, representing the liquidity ratio of the Moroccan stock market, as the function to be optimized. Then, we used a panel of 15 institutional investors (three pension funds, eleven insurance companies and aggregated Moroccan Mutual Funds-OPCVM-) to estimate the proportion of their portfolios which is allocated to equity pockets. The results indicate that the liquidity ratio is impacted in the short and long term by both macroeconomic and microstructure variables and by structural factors. The optimization method used is a modified particle swarm optimization (MPSO). It's known as an efficient approach with a high performance of solving optimization problems in many research fields. It is a population intelligence algorithm inspired by social behavior simulations of bird flocking. Considerable research work on classical method PSO (Particle Swarm Optimization) has been done to improve the performance of this method. This method has the advantage to provide best results comparing with all heuristics methods. The results of this paper allow us to conclude that equities are under weighted in the portfolios of Moroccan institutional investors. The consequences of this structure impede the development of capital market which includes the Casablanca stock exchange.