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熵作为危机时期股票市场效率分析的工具。

Entropy as a Tool for the Analysis of Stock Market Efficiency During Periods of Crisis.

作者信息

Papla Daniel, Siedlecki Rafał

机构信息

Department of Insurance, Faculty of Economics and Finance, Wroclaw University of Economics and Business, 53-345 Wroclaw, Poland.

Department of Corporate Finance and Public Finance, Faculty of Economics and Finance, Wroclaw University of Economics and Business, 53-345 Wroclaw, Poland.

出版信息

Entropy (Basel). 2024 Dec 11;26(12):1079. doi: 10.3390/e26121079.

Abstract

In the article, we analyse the problem of the efficiency market hypothesis using entropy in moments of transition from a normal economic situation to crises or slowdowns in European, Asian and US stock markets and the economy in the years 2007-2023 (2008-2009, U.S. financial sector crises; 2020-2021, Pandemic period; and the 2022-2023 period of Russia's attack on Ukraine). The following hypothesis is put forward in the article: In periods of economic slowdown and economic crises, the entropy of prices and return rates decreases. According to the principles of physics, in an isolated system, entropy increases and decreases at the moment of external intervention, similar to finance, where during crises and economic slowdowns, there is interference from governments introducing new regulations and intervening in financial markets. The article uses the Shannon entropy method. This measure, as a statistical measure, does not require the assumption of stationarity of time series or a known probability distribution, unlike classical statistical methods. Our results confirm decreased entropy in stock markets during crisis.

摘要

在本文中,我们运用熵来分析效率市场假说的问题,研究时段为2007年至2023年期间欧洲、亚洲和美国股票市场及经济从正常经济状况过渡到危机或衰退阶段(2008 - 2009年,美国金融部门危机;2020 - 2021年,大流行时期;以及2022 - 2023年俄罗斯对乌克兰发动攻击的时期)。本文提出了以下假说:在经济放缓和经济危机时期,价格和回报率的熵会降低。根据物理学原理,在一个孤立系统中,熵在外部干预时会增加和减少,这类似于金融领域,在危机和经济放缓期间,政府会出台新法规并干预金融市场,从而产生干扰。本文使用了香农熵方法。与经典统计方法不同,作为一种统计量度,该方法不需要时间序列的平稳性假设或已知的概率分布。我们的结果证实了危机期间股票市场熵的降低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d889/11675851/f3ad90bfd4fd/entropy-26-01079-g0A1a.jpg

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