This paper applies the time varying parameter-vector autoregression model to explore the dynamic relationship between economic policy uncertainty, investor sentiment and financial stability in China in different periods and at different time points. The empirical results show that economic policy uncertainty has an obvious negative impact on investor sentiment before 2012 and financial stability in the short term, and the influence of economic policy uncertainty on investor sentiment is greater than that of economic policy uncertainty on financial stability. These influences were more significant during the period of the global financial crisis in 2008. Moreover, investor sentiment had a positive and gradually increasing effect on financial stability, while after 2010, the positive impact gradually weakened. Furthermore, economic policy uncertainty is negatively affected by financial stability, and the effect of financial stability on investor sentiment is positive. In terms of mediating effects, economic policy uncertainty has an indirect impact on financial stability through investor sentiment and vice versa. This paper provides a new solution to economic problems explored in behavioral finance research. Additionally, Chinese government agencies can achieve the goal of preventing financial crises and maintaining financial stability by monitoring investor sentiment and implementing targeted economic policies.
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http://dx.doi.org/10.1007/s11403-021-00342-5 | DOI Listing |
J Environ Manage
January 2025
School of Management, Lanzhou University, Gansu, China. Electronic address:
How do physical environment risks affect financial market systemic risk? We use remoting data to measure physical environment risks and select 26 banks across 12 EU countries. We extend the CoVaR framework with the quantile-mLSTM algorithm, obtaining time-varying CoVaRs. We then use time-varying partial derivatives to calculate the banks' tail risk spillover effects.
View Article and Find Full Text PDFRisk Anal
December 2024
College of Business, Alfaisal University, Riyadh, Saudi Arabia.
Increasing awareness of climate change and its potential consequences on financial markets has led to interest in the impact of climate risk on stock returns and portfolio composition, but few studies have focused on perceived climate risk pricing. This study is the first to introduce perceived climate risk as an additional factor in asset pricing models. The perceived climate risk is measured based on the climate change sentiment of the Twitter dataset with 16 million unique tweets in the years 2010-2019.
View Article and Find Full Text PDFHeliyon
October 2024
College of Economics and Management, Northwest A&F University, #3 Taicheng Lane, Shaanxi Pronvince, 712100, China.
Under the guidance of the United Nations SDGs target framework, enterprises' ESG practices of developed countries can effectively promote external investors' ESG investment, thus easing enterprises' financing constraints. Using the data of Chinese A-share listed companies in the Shanghai- and Shenzhen-stock exchange markets from 2013 to 2022, this study explores the causal relationship between enterprises' ESG practices and their financing constraints to provide Chinese experience, examines the mediating effect with corporate transparency and investor sentiment, and analyzes the heterogeneity with external auditor type and earnings management motivation. It is found that enterprise ESG practices can enhance their financing ability by improving corporate transparency and suppressing investor sentiment; for the non-Big 4 audit listed companies and the listed companies with the weak motivation of earnings management, the corporate ESG practice has a more significant effect on their financing ability.
View Article and Find Full Text PDFHeliyon
November 2024
Department of Information Systems and Technology, College of Computer Science and Engineering, University of Jeddah,Jeddah, 21959, Saudi Arabia.
This research delves into the obstacles and difficulties associated with predicting cryptocurrency movements in the volatile global financial market. This study develops and evaluates an advanced Deep Learning-Enhanced Temporal Fusion Transformer (ADE-TFT) model to estimate Bitcoin values more accurately. This research employs cutting-edge artificial intelligence (AI) and machine learning (ML) techniques to comprehensively examine various aspects of cryptocurrency forecasting, including geopolitical implications, market sentiment analysis, and pattern detection in transactional datasets.
View Article and Find Full Text PDFPLoS One
November 2024
Faculty of Finance and Banking, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
This study delves into the impact of reversals and investor attention on cryptocurrency returns before and during the COVID-19 pandemic. We employ the Two Stages Least Squares to analyze a sample of the top 20 cryptocurrencies from January 2016 to April 2021. Our results reveal that investor attention positively influences bitcoin returns in both periods, with a more pronounced effect during the pandemic.
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