Course - Real Estate Finance - BMAC8104
BMAC8104 - Real Estate Finance
Lessons are not given in the academic year 2020/2021
This course introduces students to the theoretical foundations and modern research methodologies in real estate finance. Students gain fundamental insights into the research that has developed over more than a decade on current issues in residential and commercial real estate such as macroeconomic fundamentals of real estate markets, property valuation, mortgage securitization, and asset pricing. There will be tutorials in R to provide parctical experience.
- Real Estate and the Macroeconomy
- Structure and Pricing of Mortgages
- Hedonic Valuation and Spatial Regression Models
- Real Estate Asset Pricing
Knowledge: Students will become familiar with the properties of real estate data, the fundamental drivers and main indicators of real estate prices, as well as the pricing mechanism of mortgage backed securities. The course will prepare the students with various theoretical models and econometric techniques to study major topics in the field of real estate finance.
Skills: At the end of the course, students will have a profound knowledge of theoretical models in real estate finance. The course aims to provide students with a profound knowledge of econometric tools in micro- and macroeconometrics to analyze real estate markets. They will achieve programming skills in order to implement empirical models and to interpret their results.
Competence: Because the course covers the state-of-the-art techniques to analyze real estate markets, students will develop analytical and writing skills which allow them to conduct their own research.
Learning methods and activities
PhD workshops and lectures.
Students should bring their own laptops to class.
Further on evaluation
60% of the grading is related to a term paper which includes either a replication or extension of a published paper or the implementation of students' own research ideas. The latter could also serve as a starting point for a research project within their PhD thesis.
40% of the grading consists of two graded assignments.
Recommended previous knowledge
The course demands prior knowledge of economics, finance and econometrics at the master's level. Furthermore, students should be familiar with a software package which allows them to conduct empirical analyses (e.g. R, STATA, or MATLAB).
Required previous knowledge
Students should be interested in real estate finance and investments and are expected to demonstrate a command of micro- and macroeconomic theory, econometrics and statistics, as well as finance at master's level.
Credits: 3.0 SP
Study level: Doctoral degree level
Language of instruction: English
- Business Economics
- Financial Economics
- Economics and Administration
- Management Accounting and Control
Department with academic responsibility
NTNU Business School
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"