符号编码方法与基于的应用对金融时间序列分析的符号编码方法.
Joanna Olbryś1, Natalia Komar1
1Faculty of Computer Science, Bialystok University of Technology, Wiejska 45a, 15-351 Białystok, Poland.
Entropy (Basel, Switzerland)
|July 29, 2023
概括
这项研究表明,使用量子值值的符号编码有效地分析了股票市场的效率. 在COVID-19流行病和乌克兰战争等极端事件期间,市场信息效率下降.
科学领域:
- 量化金融 量化金融
- 信息理论 信息理论
- 金融计量经济学 金融计量经济学
背景情况:
- 符号编码是信息理论的基础,与资本市场效率有关.
- 评估股票市场参与者的信息处理对于理解市场动态至关重要.
- 金融时间序列分析通常需要对极端市场事件有稳定的方法.
研究的目的:
- 为了比较符号编码方法与修改的香农,用于股票市场效率分析.
- 在动荡时期调查市场效率,特别是COVID-19大流行和乌克兰战争.
- 确定用于金融时间序列分析的最有效的符号编码方法.
主要方法:
- 使用值 (5%和95%量子) 的符号编码.
- 修改的香农值计算用于信息效率评估.
- 在极端事件期间分析欧洲股票市场指数.
主要成果:
- 5%/95%的量子值编码方法被证明是识别动态模式的最有效方法.
- 使用这种方法的Shannon Entropy分析在各个市场产生了同质的结果.
- 在极端事件期间,指数收益率的度衡量的市场信息效率下降.
结论:
- 符号值编码方法是金融时间序列分析的精确工具.
- 农断证实了危机期间市场信息效率降低.
- 在极端事件期间,建议使用STSA (象征值象征总量) 方法进行财务时间序列分析.
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