英文标题：
《Multilayer Aggregation with Statistical Validation: Application to
  Investor Networks》
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作者：
K\\k{e}stutis Baltakys, Juho Kanniainen, Frank Emmert-Streib
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最新提交年份：
2018
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英文摘要：
  Multilayer networks are attracting growing attention in many fields, including finance. In this paper, we develop a new tractable procedure for multilayer aggregation based on statistical validation, which we apply to investor networks. Moreover, we propose two other improvements to their analysis: transaction bootstrapping and investor categorization. The aggregation procedure can be used to integrate security-wise and time-wise information about investor trading networks, but it is not limited to finance. In fact, it can be used for different applications, such as gene, transportation, and social networks, were they inferred or observable. Additionally, in the investor network inference, we use transaction bootstrapping for better statistical validation. Investor categorization allows for constant size networks and having more observations for each node, which is important in the inference especially for less liquid securities. Furthermore, we observe that the window size used for averaging has a substantial effect on the number of inferred relationships. We apply this procedure by analyzing a unique data set of Finnish shareholders during the period 2004-2009. We find that households in the capital have high centrality in investor networks, which, under the theory of information channels in investor networks suggests that they are well-informed investors.
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中文摘要：
多层网络在包括金融在内的许多领域吸引着越来越多的关注。在本文中，我们开发了一种基于统计验证的多层聚合新的可处理程序，并将其应用于投资者网络。此外，我们对他们的分析提出了另外两个改进：交易引导和投资者分类。聚合过程可用于集成投资者交易网络的安全信息和时间信息，但不限于财务信息。事实上，它可以用于不同的应用，如基因、运输和社交网络，只要它们是推断的或可观察的。此外，在投资者网络推断中，我们使用交易引导进行更好的统计验证。投资者分类允许固定大小的网络，并对每个节点进行更多观察，这在推断中非常重要，尤其是对于流动性较低的证券。此外，我们观察到，用于平均的窗口大小对推断关系的数量有很大影响。我们通过分析2004-2009年期间芬兰股东的独特数据集来应用这一程序。我们发现，首都的家庭在投资者网络中具有高度的中心性，根据投资者网络中的信息渠道理论，这表明他们是消息灵通的投资者。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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