We present a new difference of convex functions algorithm (DCA) for solving linear and nonlinear mixed complementarity problems (MCPs). The approach is based on the reformulation of bilinear complementarity constraints as difference of convex (DC) functions, more specifically, the difference of scalar, convex quadratic terms. This reformulation gives rise to a DC program, which is … Read more
We focus on multi-agent, multi-objective problems, particularly on those where the objectives admit a potential structure. We show that the solution to the potential multi-objective problem is always a noncooperative optimum for the multi-agent setting. Furthermore, we identify a class of problems for which every noncooperative solution can be computed via the potential problem. We … Read more
One of the biggest challenges in quantitative finance is the efficient allocation of capital. Thus, in this study, a two-step methodology was proposed, in which a combination of logistic regression and Markowitz model was performed to determine optimized portfolios. In this context, in the first step, fundamentalist indicators were used as inputs to the logistic … Read more