BUS-F 579 Topics in Finance: Financial Data Analytics I
- 7 weeks
- 1.5 credits
- Prerequisite(s): MBA CORE
This course is the first of a two-course sequence in Financial Data Analytics. It introduces programming in Python, an excellent programming language that is used widely and relatively easy to learn. Students who are already familiar with programming in Python may skip this first course and take the second course with permission of the instructor.
BUS-F 579 Topics in Finance: Financial Data Analytics II: Scraping, Cleaning, Organizing, and Analyzing Data in Python
- 7 weeks
- 1.5 credits
- Prerequisite(s): MBA CORE
This course is the second of a two-course sequence in Financial Data Analytics. It introduces students to the analysis of real-world financial data in a variety of settings. Students will learn to apply textual analysis to large documents, identify “sentiment” in Google search data, conduct financial analysis of corporate filings and disclosures, and back-test trading strategies, to name just a few applications.
BUS-F 579 Topics in Finance: Fintech Applications in Machine Learning
- 7 weeks
- 1.5 credits
- Prerequisite(s): BUS Grad Students Only
This class shows students how to apply machine learning concepts to better understand financial markets. The course begins by discussing the value of information in financial markets. Students will then learn how to predict a range of financial outcomes, especially home prices and loan defaults, by applying common machine learning techniques such as: K-means, (ii) principal components, (iii) linear regressions, (iv) logistic regressions, (v) regularization, (vi) k-nearest neighbors, and (vii) decision trees. The class concludes with an overview of the role of management in the fintech sector. Students will learn to apply their knowledge through data analysis projects.
BUS-F 579 Topics in Finance: Fintech for Managers
- 7 week
- 1.5 credits
- Prerequisite(s): BUS Grad Students Only
Technology is changing finance. Fintech tools like blockchain, machine learning, big data, artificial intelligence are revolutionizing the finance landscape and creating new challenges for both new and existing firms. To succeed in this environment, startups must build, fund, and grow an innovative operation that can outperform larger companies, while incumbent firms must rethink their offerings and digital capabilities to safeguard against disruption. In this class, we will evaluate the best practices for managing these issues, consider the latest breakthroughs in fintech, and establish a game plan for your company—whether you're driving or defending against disruption. Students will develop a deeper understanding of the frictions that fintech aims to address, discover ways to overcome adoption barriers and quickly scale your business, and learn how to manage disruptive threats posed by agile, data-driven. Students will also gain a critical lens for distinguishing between innovations that offer sustainable value and those with fleeting benefits.