2025/2026
Empirical Asset Pricing
Type:
Mago-Lego
Delivered by:
School of Finance
Where:
Faculty of Economic Sciences
When:
1 module
Open to:
students of one campus
Instructors:
Aleksandr Tomtosov
Language:
English
ECTS credits:
3
Contact hours:
32
Course Syllabus
Abstract
This course introduces students to state-of-the-art tools for identifying relationships between companies' financial, behavioral, and stock market factors and their future stock price performance. It examines and tests current academic and industry theories while gradually introducing the real-world constraints investors face when implementing investment strategies.
Learning Objectives
- To understand fundamental empirical asset pricing models and their specific applications. To develop technical skills for testing these models using Python. To evaluate model performance and comprehend the limitations and assumptions of different methodological approaches.
Expected Learning Outcomes
- Students should know the basic empirical asset pricing models and the specifics of their application. Students should have the technical skills to test models in Python. Students should be able to evaluate models' performance and understand the methods' limitations and assumptions.
Course Contents
- 1. An introduction to empirical asset pricing and model testing methods
- 2. Construction of single-factor strategies based on stock exchange and financial data
- 3. Behavioral factors in empirical pricing
- 4. Multifactor asset pricing models
- Alternative methods of constructing portfolios and testing hypotheses
- 6. Models performance evaluation
- 7. Multiple hypothesis testing and the problem of the “zoo” of explanatory pricing factors
