Course Description
"Deep Learning in Quantitative Finance" is an innovative and comprehensive course that bridges the gap between cutting-edge machine learning techniques and their practical applications in the financial sector. This course, developed by IVADO and Fin-ML, offers a unique opportunity to explore how deep learning and advanced analytics are revolutionizing financial, banking, and insurance industries.
What Students Will Learn
- Recognize appropriate use cases for machine learning models in financial contexts
- Apply best practices of machine learning and deep learning in finance
- Identify and understand specialized deep network architectures for solving financial problems, including:
- Graph neural networks in financial markets
- Reinforcement learning for portfolio optimization
- Information extraction techniques for ESG metrics
Prerequisites
- Intermediate knowledge of mathematics
- Programming skills (preferably in Python)
- Basic understanding of machine learning concepts (helpful but not required)
Course Content
- Review of machine learning and deep learning applications in finance
- Neural network architectures on graphs for financial markets and bitcoin transactions
- Portfolio design using reinforcement learning
- Natural Language Processing for information extraction from financial disclosures
- ESG and sustainable finance applications
- Real-world examples and case studies from industry experts
Target Audience
- Industry professionals in finance, banking, and insurance
- Academics interested in applied machine learning
- Graduate students in data science and quantitative finance
- Anyone interested in AI applications in the financial sector
Real-World Applications
- Enhance financial market analysis using graph neural networks
- Optimize investment portfolios with reinforcement learning techniques
- Extract valuable information from financial disclosures for ESG evaluation
- Implement advanced machine learning models in various financial applications
- Stay competitive in the rapidly evolving field of quantitative finance
Syllabus
Module 1 - Introduction and Background
Module 2 - Reminder Machine Learning and Deep Learning
Module 3 - GNN in Finance
Module 4 - ESG Evaluation
Module 5 - Portfolio Design using Reinforcement Learning
Module 6 - Conclusion
This course offers a unique blend of theoretical knowledge and practical applications, taught by six international experts from both academia and industry. By enrolling, you'll gain invaluable insights into the cutting-edge technologies shaping the future of finance, positioning yourself at the forefront of this rapidly evolving field.