Does the Federal Open Market Committee cycle affect credit risk?

Huang, Duo; Li, Yubin; Wang, Xinjie; Zhong, Zhaodong

doi:10.1111/fima.12364

Cited by 21 publications

(9 citation statements)

References 40 publications

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“…Thus, higher information disclosure can effectively decrease the information asymmetry among stakeholders, enhance investors’ market attention and trading confidence, attract more investor participation, and thus foster the improvement of stock liquidity [ 48 , 49 ]. For enterprises with poor information disclosure, investors lack the basis for value judgment and cannot efficiently assess enterprise value, increasing the likelihood of internal transactions, agent conflicts, and other difficulties and reducing investors’ willingness to hold, which leads to diminished stock liquidity [ 50 , 51 ]. Enterprise digital transformation disrupts the "information island", extends the information search channel through digital technology, enhances the scope and quality of enterprise information disclosure, and alleviates the problem of stakeholder information bias and adverse selection.…”

Section: Theoretical Analysis and Research Hypothesesmentioning

confidence: 99%

Enterprise digital transformation’s impact on stock liquidity: A corporate governance perspective

Liu,

Zhu,

Cheng

2024

PLoS ONE

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The innovation in technology and economic growth, which are brought about by digital transformation in enterprises, will inevitably impact their performance in the capital market. Using a sample of Chinese A-share listed companies from 2012 to 2021, this study extensively examines the impact, mechanism, and economic consequences of enterprises digital transformation on stock liquidity. The research reveals that enterprises digital transformation can significantly improve stock liquidity. From the perspective of corporate governance, a further analysis indicates that the digital transformation of enterprises can improve stock liquidity by three mechanisms: easing financing constraints, improving the quality of internal control, and enhancing information disclosure. The results of the heterogeneity analysis indicate that the digital transformation of enterprises, combined with a high level of financial technology, developed financial markets, and policy guidance, has a significantly more significant effect on improving stock liquidity. The analysis of economic consequences reveals that the digital transformation of enterprises can lower the risk of a stock price crash and enhance the accuracy of analysts’ forecasts, primarily by improving stock liquidity. This study offers empirical evidence from a micro-mechanism perspective that elucidates the spillover effect of enterprise digital transformation on the capital market. It provides insight into the impact of enterprise digital transformation on stock liquidity and offers theoretical guidance to promote the adoption of enterprise digital transformation across different countries and enhance stock liquidity in the capital market.

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Section: Theoretical Analysis and Research Hypothesesmentioning

confidence: 99%

Enterprise digital transformation’s impact on stock liquidity: A corporate governance perspective

Liu,

Zhu,

Cheng

2024

PLoS ONE

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“…The level of economic development and innovation in the Yangtze River Delta, the Pearl River Delta and the Bohai Rim are significantly higher than those in the central and western regions. This paper refers to Huang et al (2021), uses the per capita GDP of cities to measure the level of regional economic development. According to the median of per capita GDP of cities, the sample is divided into enterprises with high economic development level and enterprises with low economic development level.…”

Section: From the Perspective Of Enterprise Characteristicsmentioning

confidence: 99%

Policy Uncertainty, Financialization and Enterprise Technological Innovation: A Way Forward Towards Economic Development

Zhang

Zhuo

Deng

2022

Front. Environ. Sci.

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Technological innovation is the core factor for enterprises to maintain competitiveness. This paper aims to investigate how policy uncertainty affect enterprises’ innovation. On the basis of theoretical analysis, this study selects data from 2008–2017- and a share of non-financial listed companies as the research sample. Using patent data of listed companies and China’s economic policy uncertainty (EPU) index, the study examines the impact of EPU on enterprise innovation. In addition, the regulatory effect of enterprise financialization has been investigated. The results show that the EPU can promote the quantity growth of enterprise innovation but inhibit the improvement of enterprise innovation quality. The impact of EPU on enterprise innovation will be affected by enterprise ownership, financing constraint level, life cycle, regional administrative level and regional economic level. Furthermore, enterprise financialization shows a negative regulatory effect in the process of EPU affecting enterprise innovation. This study provides policy enlightenment for reasonably formulating economic policies and promoting enterprise financialization, so as to effectively improve enterprise innovation ability and economic development.

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“…By analyzing risk factors, risk trends can be controlled and potential risks can be predicted. Huang et al [ 9 ] studied the return rate of the Credit Default Swap (CDS) index during the Federal Open Market Committee (FOMC) cycle in the United States. The results indicated that in even weeks of the Federal Open Market Committee cycle, the CDS return rate were significantly higher than in odd weeks.…”

Section: Introductionmentioning

confidence: 99%

The financial risk of real estate combined factor analysis with grey prediction in Liaoning Province

Yuan,

Jing

2024

PLoS ONE

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The importance of real estate development has been widely accepted by all countries. Through early warning and avoidance of real estate financial risks, it can effectively promote the healthy and healthy development of the real estate industry, avoiding the impact of accidental factors, such as the COVID-19 pandemic, and promoting the overall economic development. Based on multiple regression analysis and grey prediction methods, this article constructs a real estate financial risk estimation model, and the real estate financial risk is estimated using the relevant data of Liaoning Province from 2001 to 2020. Analyzing the research results of financial risks in Liaoning Province, we can find that the real estate financial risks reached the peak in 2013, and then the real estate financial risks gradually showed a slow decline trend. In general, the financial risks in Liaoning Province are controllable. The study of financial risks in Liaoning Province will help to judge the development of the real estate industry and promote the continuous improvement of the overall economy. The article, through the study of real estate financial risks in Liaoning Province, can promote the development of regional real estate in Liaoning Province and promote the overall economic development of Liaoning Province, which has strong practical significance. The study of real estate financial risks, relevant risk research theories can be enriched, the identification of financial risks can be improved, and the study of real estate financial risks can be strengthened. The article uses a combination of multivariate statistics and grey fuzzy theory to complete the study of real estate financial risks. Therefore, through the exploration of multivariate statistics and grey fuzzy theory, its application value can be elevated.

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Does the Federal Open Market Committee cycle affect credit risk?

Cited by 21 publications

References 40 publications

Enterprise digital transformation’s impact on stock liquidity: A corporate governance perspective

Enterprise digital transformation’s impact on stock liquidity: A corporate governance perspective

Policy Uncertainty, Financialization and Enterprise Technological Innovation: A Way Forward Towards Economic Development

The financial risk of real estate combined factor analysis with grey prediction in Liaoning Province

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