However, within the last few decades, practitioners and academics have become aware of its drawbacks. Modern Portfolio Theory (MPT) has served as the foundation and industry standard for portfolio optimization, being capable of demonstrating the concepts of diversification and risk-return efficiency based on a mean-variance framework. The problem of portfolio optimization is one of the most important issues in asset management. Specifically, portfolios set for profitability goals create excess return in a general/upward trending market portfolios targeted for operating fitness perform better in a downward trending market, and can be considered as a defensive strategy in the event of a crisis.

We find that Fundamental Networks efficient portfolios are in general more mean-variance efficient in out-of-sample performance than Markwotiz’s efficient portfolios. Two empirical models are provided in this paper as applications of Fundamental Networks. As a proxy for a portfolio, a fundamental network is defined as a set of “interconnected” stocks, among which linkages are a measure of similarity of fundamental information and are referred to asset allocation directly. FN is an effective and robust network-based fundamental-incorporated method, and can be served as an alternative to classical mean-variance framework models. This article proposes the use of a novel approach to portfolio optimization, referred to as “Fundamental Networks” (FN).

2School of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, United States.

1Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, China.Xiangzhen Yan 1, Hanchao Yang 1*, Zhongyuan Yu 2 and Shuguang Zhang 1

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