Deep Learning in Quantitative Finance

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.