In order to explore the fractal characteristic in Dempster–Shafer evidence theory, a fractal
dimension of mass function is proposed recently, to reveal the invariance of scale of belief …

In this paper, we analyze 26 Chinese sectoral indices and evaluate the effects of the crisis
caused by COVID-19 on its efficiency. We calculated the degree of multifractality in the pre …

We investigate financial market dynamics by introducing a heterogeneous agent-based
opinion formation model. In this work, we organize individuals in a financial market …

The existing literature on corporate disclosures suggests that managerial sentiments are the
outcome of the firm's financial performance. We extend this line of research and examine …

股价预测一直是投资者在股票市场中关注的焦点. 近年来, 深度学习技术在这一领域得到广泛
应用. 在融合卷积神经网络(CNN) 和长短时记忆网络(LSTM), 构建CNN-LSTM 模型的基础上 …

Understanding cross-correlation and information flow between stocks is crucial for stock
market analysis. However, traditional methods often struggle to capture financial markets' …

The prediction of the stock price index is a challenge even with advanced deep-learning
technology. As a result, the analysis of volatility, which has been widely studied in traditional …

This paper combines the ensemble empirical mode decomposition (EEMD) method, the
transfer entropy (TE) method and complex network theory to analyze the causal …

Conventional logging interpretation methods qualitatively identify shale reservoirs using
shale attribute parameters and interpretation templates. However, improving the …

The efficiency of stock markets in different regions of the world has been investigated using
multifractal formalism, but little attention has been paid to developing markets like Nigeria. In …