In this work, we focus on the cross-shareholding structure in financial markets. Specifically, we build ad hoc indices of concentration and control by employing a complex network approach with a weighted adjacency matrix. To describe their left and right tail dependence properties, we explore the theoretical dependence structure between such indices through copula functions. The theoretical framework has been tested over a high-quality dataset based on the Italian Stock Market. In doing so, we clearly illustrate how the methodological setting works and derive financial insights. In particular, we advance calibration exercises on parametric copulas under the minimization of both Euclidean distance and entropy measure.

在这项工作中，我们关注金融市场的交叉持股结构。具体来说，我们通过采用具有加权邻接矩阵的复杂网络方法来构建集中和控制的临时指数。为了描述它们的左右尾依赖特性，我们通过 copula 函数探索这些索引之间的理论依赖结构。该理论框架已经在基于意大利股票市场的高质量数据集上进行了测试。在这样做的过程中，我们清楚地说明了方法设置如何运作并获得财务见解。特别是，我们在欧几里得距离和熵测度的最小化下推进了参数连接的校准练习。