Goals
The team explores financial markets with machine learning tools. Machine learning (ML) techniques are heavily employed in quantitative trading strategies to predict or price stocks and other asset markets such as bonds, options and other derivatives, commodities, etc. Students will not only do research in these areas, but they will also learn how to use ML tools to better understand and predict financial motives in household finances, corporate finance, FinTech, or banking. Consumer or firm choices are recorded at an individual level allowing us to discover new patterns in behavior.
Issues Involved or Addressed
With special emphasis on ML techniques used in quantitative trading, investment, corporate finance, FinTech, households' financial decisions, and banking. Employing supervised machine learning tools such as regularized regression, tree-based methods, neural networks, deep learning and other recent advances in machine learning to predict certain events or uncovering the causal effect of a policy or regulatory change. Students first will learn how to approach finance problems with advanced statistical tools in prediction and in the potential outcome framework for causality.
Methods and Technologies
Academic Majors of Interest
- Business›Finance
- Business›Global Development
- Business›IT Management
- Business›Leadership and Organizational Change
- Business›Marketing
- Business›Operations and Supply Chain Management
- Business›Strategy and Innovation
- Computing›Algorithms, Combinatorics and Optimization
- Computing›Analytics
- Computing›Computational Science and Engineering
- Computing›Human-Centered Computing
- Sciences›Mathematics
Preferred Interests and Preparation
Motivated and interested in learning novel approaches in finance and machine learning. Strong motivation and passion to learn or work in Finance Effective communication skills Have a basic understanding of machine learning tools and finance. Have solid ground in programming in python and/or R Familiar with Git and GitHub (if not, you will be required to attend workshop offered by PACE) Driven and committed, self-motivation and eagerness to become familiar with new concepts. Ability to work well with others across teams with varied strengths.
Meeting Schedule & Location
Team Advisors
- Scheller College of Business
- Scheller College of Business