The conjugate gradient (CG) method is an optimization method which is commonly applied for solving unconstrained optimization problems due to its simplicity, properties of simplicity for low memory requirements and it is Hessian free. The CG method has been developed and improved in terms of efficiency by undergoing numerous modifications from time to time. An efficient investment portfolio is important for all investors to keep track of the best investment following the current situation. A hybrid CG method is used in optimizing the investment portfolio selection. Numerical comparison associated with unconstrained test functions as benchmark between six hybrid CG methods is done to investigate the efficiency of the methods by using exact line search. As a result, the hybrid-Syarafina-Mustafa-Rivaie (HSMR) method is considered as the most efficient method. Thus, the HSMR method is being applied as optimization method in obtaining the optimal investment portfolio selection.