A5086588103- Banking stability, regulation, efficiency
- Monetary Policy and Economic Impact
- Market Dynamics and Volatility
- Global Financial Crisis and Policies
- Credit Risk and Financial Regulations
- Financial Distress and Bankruptcy Prediction
- Financial Markets and Investment Strategies
- Housing Market and Economics
- Energy, Environment, Economic Growth
- Insurance and Financial Risk Management
- Corporate Finance and Governance
- Islamic Finance and Banking Studies
- Taxation and Compliance Studies
- Stock Market Forecasting Methods
- Risk Management in Financial Firms
- Climate Change Policy and Economics
- FinTech, Crowdfunding, Digital Finance
- Corporate Taxation and Avoidance
- Fiscal Policy and Economic Growth
- Brain Tumor Detection and Classification
- Innovation Policy and R&D
- Transport and Economic Policies
- Anomaly Detection Techniques and Applications
- Entrepreneurship Studies and Influences
- Spatial and Panel Data Analysis
Central University of Finance and Economics
2014-2024
University of Groningen
2013-2015
University of Chinese Academy of Sciences
2014
Abstract We examine the relationship between economic policy uncertainty (EPU) and stock price crash risk via corporate investment in Chinese listed firms. Results show that higher EPU is associated with lower risk. Firms increase financial asset holdings reduce overinvestment when rises, leading to future State‐owned enterprises (SOEs) firms management incentives tend overinvestment, whereas non‐SOEs holdings. Thus, be cautious their investments high, which reduces Our study provides new...
Abstract Predicting bank failures is important as it enables regulators to take timely actions prevent or reduce the cost of rescuing banks. This paper compares logit model and data mining models in prediction USA between 2002 2010 using levels rates change 16 financial ratios based on a cross‐section sample. The are estimated for in‐sample period 2002–2009, while year used out‐of‐sample tests. results suggest that predicts less precisely than models, but produces fewer missed false alarms...
Abstract Highly interconnected production network exists in one economy, and it is crucial to investigate how why supply-side shocks spread across industries via the cause systemic risks real sector. Based on input-output framework, this paper designed a model simulate propagation of risk spillovers along given shocks. This defined systemically important (SIIs) vulnerable (SVIs) according degree direction spillovers. Simulation results show that among network, leading also classified...
With the development of financial technology (referred to as fintech), risks faced by fintech companies have received increasing attention. This paper uses Sentence Latent Dirichlet Allocation (Sent-LDA) topic model comprehensively identify risk factors in industry based on textual disclosed Form 10-K. Furthermore, this analyzes importance and similarities for whole different sub-sectors from perspectives factor types contents. In empirical analysis, 53,452 headings 34 included KBW Nasdaq...
Abstract With the recurrence of infectious diseases caused by coronaviruses, which pose a significant threat to human health, there is an unprecedented urgency devise effective method identify and assess who most at risk contracting these diseases. China has successfully controlled spread COVID‐19 through disclosure track data belonging diagnosed patients. This paper proposes novel textual track‐data‐based approach for individual infection measurement. The proposed divided into three steps....
The stock price of a firm is dynamically influenced by its own factors as well those peers. In this study, we introduce Graph Attention Network (GAT) integrated with WaveNet architecture—termed the GAT-WaveNet model—to capture both time-series and spatial dependencies for forecasting crash risk Chinese listed firms from 2012 to 2021. Utilizing node-rolling techniques prevent overfitting, our results show that model significantly outperforms traditional machine learning models in prediction...
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