Enhanced Index Investing Based on Goal Programming

Abstract

Enhanced index investing involves tracking a benchmark index closely and using risk-controlled strategies to add modest value to the index. The typical approaches to construction of such portfolios involve subjective management judgments. A new approach to enhanced indexing instead formulates the problem as a dual-criteria goal programming problem. Unlike the traditional approaches, which require a fund manager to buy and sell stocks actively in order to improve returns, the proposed approach is based on the passive management of a small number of stocks. Empirical results from tests in the Taiwan stock market suggest the new approach incurs lower transaction costs and produces sustainable risk-controlled enhanced returns.