【PAC-BASIN FINANC J】Individual defense and joint defense: A new defensive portfolio selection method based on stock network structure 个体防御与联合防御：基于股票网络结构的一种新型防御型投资组合选择方法——李本初分享

科研基地组织前沿文献研读交流会，李本初围绕2026年发表于Elsevier旗下SSCI Q1金融期刊Pacific-Basin Finance Journal的论文Individual defense and joint defense: A new defensive portfolio selection method based on stock network structure进行主题分享。

文章基于收益序列的相关性构建股票网络，引入网络层面两类拓扑指标来构建投资组合权重优化模型，从而提出一种基于股票网络的投资组合选择方法。在个股节点维度，采用中心性特征来刻画单只股票在网络中的重要程度，反映个股的系统性风险（贝塔值）；在关联边维度，利用结构差异特征衡量网络中两只股票的位置差异，反映不同股票的本质差异。本文从网络结构优化思路出发，设计了三类投资组合构建策略：首先，尽可能选取网络边缘节点个股，即最小化组合整体中心性；其次，最大化网络内个股分布离散度，也就是最大化投资组合的结构差异性；第三，同步对中心性、结构相似度两类指标进行优化。对2002年至2022年中国市场的实证分析表明，就风险（风险价值）和收益（累计收益率）而言，文章建立的投资组合表现优于马科维茨的经典方法和朴素方法。值得注意的是，在牛市期间，该投资组合倾向于选择顺周期股票（尤其是金融板块的股票）；而在熊市期间，则倾向于选择逆周期股票（尤其是IT板块的股票），这体现了投资组合对市场风险的防御能力。

ABSTRACT

We establish a stock network using the correlation of return sequences and model the optimization problem of portfolio weights using two types of topological metrics within the network to construct a method for selecting investment portfolios based on stock networks. At the individual level, centrality features are utilized to describe the importance of a stock within the network, reflecting the systemic risk (beta value) of the individual stock; at the connection level, structural dissimilarity features are used to describe the positional differences between two stocks within the network, reflecting the nature differences of different stocks. Regarding network structure, we propose several approaches for constructing investment portfolios: firstly, selecting stocks located at the periphery of the network as much as possible, which implies minimizing the centrality features of the portfolio. Secondly, maximizing the dispersion of stocks within the network, which implies maximizing the structural dissimilarity of the portfolio. Thirdly, simultaneously optimizing centrality features and structural similarity features. Empirical analysis on the Chinese market from 2002 to 2022 demonstrates that our investment portfolios outperform Markowitz's classic method and the Naive method in terms of risk (value-at-risk) and return (cumulative return rate). Interestingly, our portfolios select pro-cyclical stocks, particularly those from the financial sector, during bull markets and counter-cyclical stocks, particularly from the IT sector, during bear markets, reflecting the defensive capability of the portfolios against market risk.