大流行与德国市场动态的马尔可夫状态转换分析

2021 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2021-12-01 DOI:10.1109/CSCI54926.2021.00162

Kangrong Tan, S. Tokinaga

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引用次数: 0

摘要

本文研究了新冠肺炎疫情对股票市场的影响。我们重点关注感染病例与德国股市变化之间的联系。我们采用马尔科夫状态转换分析(MRSA)来揭示COVID-19大流行的情况，以及大流行与市场之间的共同运动。通过我们的实证分析，我们发现MRSA可以很好地将整个时间范围划分为具有不同统计属性或不同制度状态的几个区间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Markov Regime Switching Analysis for the Pandemic and the Dynamics of German Market

This paper deals with the impact of COVID-19 pandemic on the stock market. We focus on the link between the infected cases and the change of the stock market in Germany. We employ the Markov Regime Switching Analysis (MRSA) to expose the situations of COVID-19 pandemic, and the co-movement between the pandemic and the market. Through our empirical analysis, we find that MRSA works well to divide the whole time horizon into several intervals with different statistical properties, or different regime states.

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2021 International Conference on Computational Science and Computational Intelligence (CSCI)

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