Application of the Maximum Score/Maximum Profit Bi-Objective Estimator to Stocks of the Banking Sector in the Athens Stock Exchange

We are familiar with the maximum score estimator of (Manski, C.F., 1975, Journal of Econometrics 3, 205-228). A generalization of the maximum score estimator is the maximum profit estimator of (Skouras, S., 2003, Computational Statistics and Data Analysis 42, 349-361). The general case is the maximum weighted score estimator (K. Florios, S. Skouras, 2008, Journal of Econometrics, 146, 86-91). First, we define the bi-objective estimator maximum score/maximum profit (MS-MP). In this paper, we study mainly the computational characteristics of MS-MP in a study of four stocks of the Banking Sector from the Athens Stock Exchange (ASE). The estimation techniques that are used are Non Dominated Sorting Genetic Algorithm II (NSGA-II) and the e-Constraint method of mathematical programming. The comparison of the two estimation techniques results in a tie and the choice of technique depends on the familiarity of the user with available methods and the availability of software. Further comparison to more sophisticated mathematical programming techniques can be organized