An evolutionary programming methodology for portfolio selection

We present an approach to compute the efficient frontier for portfolio optimization based on evolutionary programming (EP) technique. Our approach relies on multiple EP runs within a search to create the frontier. Results from simulation, which runs on a personal computer platform, are shown for data set consisting of 24 types of securities. The algorithm converges quickly with consistent performance, making it suitable for creating an efficient frontier for a much larger number of assets. The versatility of the approach makes it viable to accommodate constraints or scenarios, which we perceive as either investors or market imposed conditions. Our technique opens up an avenue to conveniently overcome the symptomatic “unrealizable or unreasonable portfolios” syndrome that plagued methodology that relies on identifying corner portfolios as a basis for creating the frontier