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Mutual information based stock networks and portfolio selection for intraday traders using high frequency data: An Indian market case study

机译:使用高频数据的交易商的相互信息基于股票网络和投资组合选择:印度市场案例研究

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摘要

In this paper, we explore the problem of establishing a network among the stocks of a market at high frequency level and give an application to program trading. Our work uses high frequency data from the National Stock Exchange, India, for the year 2014. To begin, we analyse the spectrum of the correlation matrix to establish the presence of linear relations amongst the stock returns. A comparison of correlations with pairwise mutual information shows the further existence of non-linear relations which are not captured by correlation. We also see that the non-linear relations are more pronounced at the high frequency level in comparison to the daily returns used in earlier work. We provide two applications of this approach. First, we construct minimal spanning trees for the stock network based on mutual information and study their topology. The year 2014 saw the conduct of general elections in India and the data allows us to explore their impact on aspects of the network, such as the scale-free property and sectorial clusters. Second, having established the presence of non-linear relations, we would like to be able to exploit them. Previous authors have suggested that peripheral stocks in the network would make good proxies for the Markowitz portfolio but with a much smaller number of stocks. We show that peripheral stocks selected using mutual information perform significantly better than ones selected using correlation.
机译:在本文中,我们探讨了在高频级别的市场股票中建立网络的问题,并申请了编程交易。我们的工作使用来自印度国家证券交易所的高频数据,2014年。首先,我们分析相关矩阵的频谱,以建立股票回报之间的线性关系的存在。与成对互信息的相关性的比较显示了不通过相关性捕获的非线性关系的进一步存在。我们还看到,与早期工作中使用的每日回报相比,在高频关系中,非线性关系更加明显。我们提供了这种方法的两个应用。首先,我们基于互信息构建股票网络的最小跨越树,并研究其拓扑。 2014年的行为在印度进行了大选,数据允许我们探讨其对网络方面的影响,例如无宇宙的财产和镇集群。其次,已经建立了非线性关系的存在,我们希望能够利用它们。以前的作者提出了网络中的外围库存将为Markowitz产品组合提供良好的代理,但股票数量较少。我们展示使用互信息选择的外围库存比使用相关性选择的更好地表现得明显更好。

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  • 作者

    Charu Sharma; Amber Habib;

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  • 年度 2019
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  • 原文格式 PDF
  • 正文语种 eng
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