分析全球金融指数中的危机,使用基于循环神经网络的自动编码器
Mimusa Azim Mim1, Md Kamrul Hasan Tuhin1,2, Ashadun Nobi1
1Department of Computer Science and Telecommunication Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh.
PloS one
|July 14, 2025
概括
本研究介绍了一种新型的重复神经网络自编码器 (RNN-AE),用于分析金融危机期间的全球股票市场动态. 该模型揭示了主要经济事件期间市场之间相互连接的独特模式.
科学领域:
- 量化金融 量化金融
- 网络科学 网络科学
- 机器学习 机器学习
背景情况:
- 全球股票市场表现出复杂的相互依存关系,在金融危机期间演变.
- 了解这些动态对于投资者和政策制定者来说至关重要,以应对经济波动.
研究的目的:
- 开发和应用一种新的循环神经网络自编码器 (RNN-AE) 模型来分析全球股票市场的互连.
- 在2007-2024年重大金融危机期间识别和描述网络结构和拓指标.
主要方法:
- 利用来自24个全球股票市场的时间序列数据 (2007-2024年).
- 采用修改后的RNN-AE来从正常化股票回报中推导相关性.
- 使用中间层权重和分析的拓指标 (,聚类系数,最短路径长度) 构建值网络.
主要成果:
- 该RNN-AE模型成功捕捉了主要的金融危机,包括全球金融危机 (GFC),欧洲主权债务危机 (ESD) 和COVID-19大流行.
- 在GFC和COVID-19期间,美国指数和俄罗斯-乌克兰冲突期间的欧洲指数之间的相互作用增加.
- 揭示了不同的洲际交互模式:欧洲-美国在GFC/ESD期间,美国-亚洲在COVID-19期间.
结论:
- 基于RNN-AE的网络构建方法为市场动态和金融危机检测提供了宝贵的见解.
- 结构有效监测市场状况,为投资者和政策制定者提供一种工具.
- 该研究强调了危机期间全球股票市场互连的不断变化的性质.
相关概念视频
01:37Neural Regulation
40.2K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
40.2K
01:11Regression Analysis
6.1K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
6.1K
01:30Classification of Signals
903
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
903
01:25Neural Circuits
1.6K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.6K