英文标题：
《Stock market as temporal network》
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作者：
Longfeng Zhao, Gang-Jin Wang, Mingang Wang, Weiqi Bao, Wei Li, H.
Eugene Stanley
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最新提交年份：
2017
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英文摘要：
Financial networks have become extremely useful in characterizing the structure of complex financial systems. Meanwhile, the time evolution property of the stock markets can be described by temporal networks. We utilize the temporal network framework to characterize the time-evolving correlation-based networks of stock markets. The market instability can be detected by the evolution of the topology structure of the financial networks. We employ the temporal centrality as a portfolio selection tool. Those portfolios, which are composed of peripheral stocks with low temporal centrality scores, have consistently better performance under different portfolio optimization schemes, suggesting that the temporal centrality measure can be used as new portfolio optimization and risk management tools. Our results reveal the importance of the temporal attributes of the stock markets, which should be taken serious consideration in real life applications.
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中文摘要：
金融网络在描述复杂金融系统的结构方面变得非常有用。同时，股票市场的时间演化特性可以用时间网络来描述。我们利用时间网络框架来描述基于时间演化相关性的股票市场网络。通过金融网络拓扑结构的演化可以发现市场的不稳定性。我们使用时间中心性作为投资组合选择工具。这些由时间中心性得分较低的外围股票组成的投资组合在不同的投资组合优化方案下表现一直较好，这表明时间中心性测度可以作为新的投资组合优化和风险管理工具。我们的结果揭示了股票市场时间属性的重要性，在实际应用中应予以认真考虑。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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