PDF(Pubmed)
Abstract：
Transactions in financial markets are not evenly spaced but can be concentrated within a short period of time. In this study, we investigated the factors that determine the transaction frequency in financial markets. Specifically, we employed the Hawkes process model to identify exogenous and endogenous forces governing transactions of individual stocks in the Tokyo Stock Exchange during the COVID-19 pandemic. To enhance the accuracy of our analysis, we introduced a novel EM algorithm for the estimation of exogenous and endogenous factors that specifically addresses the interdependence of the values of these factors over time. We detected a substantial change in the transaction frequency in response to policy change announcements. Moreover, there is significant heterogeneity in the transaction frequency among individual stocks. We also found a tendency where stocks with high market capitalization tend to significantly respond to external news, while their excitation relationship between transactions is weak. This suggests the capability of quantifying the market state from the viewpoint of the exogenous and endogenous factors generating transactions for various stocks.
摘要：
金融市场上的交易不是均匀分布的，而是可以在短时间内集中。在这项研究中,我们调查了决定金融市场交易频率的因素。具体来说,我们使用Hawkes过程模型来确定在COVID-19大流行期间控制东京证券交易所个股交易的外生和内生力量。为了提高我们分析的准确性，我们引入了一种新的EM算法，用于估计外生因素和内生因素，该算法专门解决了这些因素的值随时间的相互依赖性。我们检测到交易频率发生了重大变化，以响应政策变更公告。此外，个股之间的交易频率存在显著的异质性。我们还发现了一种趋势，即高市值的股票倾向于对外部消息做出显著反应，而它们之间的交易激励关系较弱。这表明，从产生各种股票交易的外生和内生因素的角度来量化市场状态的能力。
