Produktdetaljer
Biografisk notat
Huijian Dong received his doctorate education from Columbia University and University of Delaware. He joined Dickinson State University as provost and chief academic officer in early 2023 from New Jersey City University. He is a professor of finance and a CFA and CAIA charterholder. He served as director of Merrill Lynch Wealth Management Center at University of South Florida where he managed the Student Investment Fund. He published more than 40 research articles in renowned journals on topics ranging across the field of asset pricing and portfolio management. He was also invited to serve on the editorial board for American Business Review and other finance and education journals.
Data Analytics in Finance covers the methods and application of data analytics in all major areas of finance, including buy-side investments, sell-side investment banking, corporate finance, consumer finance, financial services, real estate, insurance, and commercial banking. It explains statistical inference of big data, financial modeling, machine learning, database querying, data engineering, data visualization, and risk analysis. Emphasizing financial data analytics practices with a solution- oriented purpose, it is a “one-stop-shop” of all the major data analytics aspects for each major finance area.
The book paints a comprehensive picture of the data analytics process including:
- Statistical inference of big data
- Financial modeling
- Machine learning and AI
- Database querying
- Data engineering
- Data visualization
- Risk analysis
Each chapter is crafted to provide complete guidance for many subject areas including investments, fraud detection, and consumption finance. Avoiding data analytics methods widely available elsewhere, the book focuses on providing data analytics methods specifically applied to key areas of finance. Written as a roadmap for researchers, practitioners, and students to master data analytics instruments in finance, the book also provides a collection of indispensable resources for the readers’ reference. Offering the knowledge and tools necessary to thrive in a data-driven financial landscape, this book enables readers to deepen their understanding of investments, develop new approaches to risk management, and apply data analytics to finance.
The book covers the methods and application of data analytics in all major areas of finance. It introduces statistical inference of big data, financial modeling, machine learning, database querying, data engineering, data visualization, and risk analysis.
1. Data Analytics in Finance: Introductory Case Studies 2. Data Analytics in Finance: Tools and Platforms 3. Data Analytics in Investments 4. Data Analytics in Consumption Finance 5. Data Analytics in Corporate Finance 6. Data Analytics in Financial Services and Banking 7. Data Analytics in Insurance 8. Data Analytics in Auditing 9. Data Analytics in Policy and Government 10. Data Analytics in Real Estate 11. Data Analytics in Risk Management 12. Data Analytics in Fraud Detection
Produktdetaljer
Biografisk notat
Huijian Dong received his doctorate education from Columbia University and University of Delaware. He joined Dickinson State University as provost and chief academic officer in early 2023 from New Jersey City University. He is a professor of finance and a CFA and CAIA charterholder. He served as director of Merrill Lynch Wealth Management Center at University of South Florida where he managed the Student Investment Fund. He published more than 40 research articles in renowned journals on topics ranging across the field of asset pricing and portfolio management. He was also invited to serve on the editorial board for American Business Review and other finance and education journals.