Corporate finance is concerned mainly with shareholder value maximization, and refers to the financial operations essential to operating a company. The concept is centered on the investment, financing, and dividend philosophies, while the capital budgeting, capital structure, working capital management, and dividend policy are the main functional areas. Any decision involving the distribution of funds is a corporate financial decision, and every business decision has associated financial ramifications. Every investment strategy involves some degree of risk, which needs to be carefully monitored. The objective of risk management is to ensure that a company has the resources needed to invest in assets that will yield in revenue. Nevertheless, a variety of unpredictable and unstable situations are faced by corporations, including constantly soaring inflation, geopolitical conflict, supply chain disruptions, workforce deficiencies, technological innovations, and other challenges such as pandemics. Several corporations employ risk management methods and approaches that were designed for times of stability and that depend on straightforward statistical risk measures. However, corporate risk management strategies are necessary in these current turbulent times, when significant threats appear more frequently, and the financial markets go through cycles of boom and bust.
Quantitative methods are a powerful instrument in the corporate financial sector and, when implemented properly, give corporations a strategic advantage since the digital age is data-driven in every aspect. Quantitative analysis can be used to explore the past, present, and expected upcoming events that affect the financial markets. Applying investment strategies that take historical quantitative data into consideration is acknowledged as quantitative or systematic investing. Along with adjusting portfolios to suit the requirements of investors, quantitative techniques also aid in risk management and asset allocation. The application of quantitative strategies to outperform the market is regarded as quantitative investing.
The scope of this Research Topic encompasses, but is not restricted to, research on quantitative enterprise risk management, artificial intelligence in credit risk supervision, predicting firm performance with machine learning, volatility modeling and forecasting, blockchain, and cryptocurrency and fintech.
Topics of interest include, but are not limited to, the application of quantitative methods to:
- Drivers of time-varying optimal capital structure
- Machine learning models for corporate valuation
- FinTech acquisition and corporate financial performance
- Waste management and firm performance
- The effect of R&D expenditures on stock returns
- Integration and risk contagion in financial crises
- Investor sentiment and asset prices
- Abnormal returns in stock markets
- Connectedness between Bitcoin and conventional financial markets
- Oil price shocks and economic policy uncertainty
Corporate finance is concerned mainly with shareholder value maximization, and refers to the financial operations essential to operating a company. The concept is centered on the investment, financing, and dividend philosophies, while the capital budgeting, capital structure, working capital management, and dividend policy are the main functional areas. Any decision involving the distribution of funds is a corporate financial decision, and every business decision has associated financial ramifications. Every investment strategy involves some degree of risk, which needs to be carefully monitored. The objective of risk management is to ensure that a company has the resources needed to invest in assets that will yield in revenue. Nevertheless, a variety of unpredictable and unstable situations are faced by corporations, including constantly soaring inflation, geopolitical conflict, supply chain disruptions, workforce deficiencies, technological innovations, and other challenges such as pandemics. Several corporations employ risk management methods and approaches that were designed for times of stability and that depend on straightforward statistical risk measures. However, corporate risk management strategies are necessary in these current turbulent times, when significant threats appear more frequently, and the financial markets go through cycles of boom and bust.
Quantitative methods are a powerful instrument in the corporate financial sector and, when implemented properly, give corporations a strategic advantage since the digital age is data-driven in every aspect. Quantitative analysis can be used to explore the past, present, and expected upcoming events that affect the financial markets. Applying investment strategies that take historical quantitative data into consideration is acknowledged as quantitative or systematic investing. Along with adjusting portfolios to suit the requirements of investors, quantitative techniques also aid in risk management and asset allocation. The application of quantitative strategies to outperform the market is regarded as quantitative investing.
The scope of this Research Topic encompasses, but is not restricted to, research on quantitative enterprise risk management, artificial intelligence in credit risk supervision, predicting firm performance with machine learning, volatility modeling and forecasting, blockchain, and cryptocurrency and fintech.
Topics of interest include, but are not limited to, the application of quantitative methods to:
- Drivers of time-varying optimal capital structure
- Machine learning models for corporate valuation
- FinTech acquisition and corporate financial performance
- Waste management and firm performance
- The effect of R&D expenditures on stock returns
- Integration and risk contagion in financial crises
- Investor sentiment and asset prices
- Abnormal returns in stock markets
- Connectedness between Bitcoin and conventional financial markets
- Oil price shocks and economic policy uncertainty
