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股票与权证的交易网络结构和市场变量

文章 arXiv papers · 作者: Ming-Xia Li et al.
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总结

本研究考察交易网络中的交易者关系如何对应股票及其权证的市场行为。作者使用宝钢及其权证在所述研究期间的逐笔交易审计轨迹数据，将每个交易日划分为五分钟窗口，并为每个窗口构建一个网络。由此得到的序列包含超过 1,100 个网络。网络指标包括中心化程度、同配性和平均路径长度，旨在描述订单执行模式。

论文报告称，对于这两种证券，网络指标与包括收益率、波动率、交易间隔和交易量在内的金融变量之间存在较强的同期相关性。这表明观测数据中的网络结构与市场状况相关，但所报告的关系是相关性的，且为同期关系。摘要并未证实因果效应或预测价值，也未说明这些模式能否推广到所研究股票、权证和期间之外。

核心观点

  • 作者根据交易记录中的成对买卖关系构建交易者网络。
  • 每个交易日被划分为五分钟窗口，以生成网络时间序列。
  • 研究将网络中心化程度、同配性和平均路径长度与市场变量进行比较。
  • 研究报告称，这些指标与收益率、波动率、交易间隔和交易量存在同期相关性。
  • 证据属于观察性研究，且仅限于一只股票、其权证和所述样本期。

标签

股票市场微观结构统计学波动率
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# 1308.0925


# Unveiling correlations between financial variables and topological metrics of trading networks: Evidence from a stock and its warrant









Traders adopt different trading strategies to maximize their returns in financial markets. These trading strategies not only results in specific topological structures in trading networks, which connect the traders with the pairwise buy-sell relationships, but also have potential impacts on market dynamics. Here, we present a detailed analysis on how the market behaviors are correlated with the structures of traders in trading networks based on audit trail data for the Baosteel stock and its warrant at the transaction level from 22 August 2005 to 23 August 2006. In our investigation, we divide each trade day into 48 time windows with a length of five minutes, construct a trading network within each window, and obtain a time series of over 1,100 trading networks. We find that there are strongly simultaneous correlations between the topological metrics (including network centralization, assortative index, and average path length) of trading networks that characterize the patterns of order execution and the financial variables (including return, volatility, intertrade duration, and trading volume) for the stock and its warrant. Our analysis may shed new lights on how the microscopic interactions between elements within complex system affect the system's performance.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。