In this course, students will learn to apply the tools introduced in Business Analytics I in the context of Finance. In order to acquire the skills necessary to make complex data-based financial decisions, all lecture units consist of a theoretical Finance part followed by practical applications. In particular, the following topics will be covered:
- Basic Data Handling and Summary Statistics
- Students will learn how to handle a firm-level dataset of financial characteristics and time-series of prices
- Data Visualization and Summary Statistics
- Students will learn how to compute measures of financial performance and risk and how to adequately present them
- Hypothesis Testing
- Students will compare firm performance in the cross-section based on standard firm-level and/or stock characteristics
- The Simple Linear Regression Model
- Students will learn how to evaluate the exposure of a single firm’s stock price to the market’s risk
- The Multiple Linear Regression Model
- Students will explore exposures of single firms’ stock prices to other risk factors
- Explanatory Factor Analysis
- Students will learn how to distill information from multiple financial time-series into a single explanatory factor
- Optimization
- Students will form minimum variance portfolios