Financial Econometrics

FIN538 Financial Econometrics

Autumn 2019

  • Topics

    The goal of the course is to cover econometrics methods widely used in asset pricing and corporate finance with a particular emphasis on intuition and empirical applications.

    Topics covered:

    • Introduction to R
    • Basic Econometrics
      • Ordinary Least Squares
      • Maximum Likelihood
      • Generalized Method of Moments
    • Cross-section of stock returns (CAPM, multifactor models, Arbitrage Pricing Theory (APT))
      • Black, Jensen and Scholes (1972) approach
      • Fama MacBeth (1973) approach
      • Principal Component Analysis
    • Time series of stock returns (Efficient Market Hypothesis, volatility and correlation modelling, high-frequency data)
      • Event studies
      • Vector-autoregressions
      • ARCH/GARCH/DCC models
      • High-frequency time-series
    • Risk management
      • Value-at-Risk
      • Expected Shortfall
      • Extreme Value Theory
    • Causality
      • Panel data
      • Instrumental variables
      • Natural experiments

  • Learning outcome

    After completion of the course, the student's will be able to:

    Knowledge

    • Assess the common empirical research methods in finance
    • Understand methods for testing asset pricing models
    • Understand methods used corporate finance, time series analysis and choice theory.

    Skills

    • Implement the common empirical methods in finance using R.
    • Replicate analysis in state-of-the art empirical finance papers.

    Competence

    • Will be able to conduct, interpret and critically deal with empirical studies in finance.
    • Has the tools and knowledge necessary to define, design and deliver the results of empirical investigations as done in academic articles.

  • Teaching

    The course will consist of the combination of lectures and class student presentations.

  • Recommended prerequisites

    Advanced master-level courses such as asset pricing, investment, corporate finance, and econometrics.

  • Credit reduction due to overlap

    The course cannot be combined with ECS503 Advanced Econometrics.

  • Assessment

    Class participation (20%)

    Individual presentation(s) of academic paper(s) (20%)

    Four individual assignments (60%)

  • Grading Scale

    Grading scale A - F.

  • Computer tools

    R/ RStudio

  • Literature

    No textbook. The course is based on lecture slides and academic papers.

Overview

ECTS Credits
7.5
Teaching language
English
Semester

Autumn, offered autumn 2019.

Course responsible

Assistant Professor Darya Yuferova, Department of Finance, NHH