Asset Management with Programming Applications (not offered)

FIE451 Asset Management with Programming Applications (not offered)

Autumn 2021

  • Topics

    This course develops and examines models for portfolio decisions by investors and the pricing of securities in capital markets. We will develop portfolio theory along the way, and study the extensive empirical work that characterizes movements in security prices, evaluates alternative asset pricing models, and attempts to test whether markets are efficient.


    • Portfolio Theory and the CAPM
    • Cross-Sectional Asset Pricing Tests
    • Time-Series Asset Pricing Tests
    • Multifactor Models
    • Market Efficiency and Inefficiency
    • Momentum
    • The Value Premium
    • Robustness of Anomalies
    • Trading Costs, Liquidity, and Liquidity Risk
    • Other Asset Classes and Factors

  • Learning outcome

    • In terms of knowledge, students shall:
      • Realize that expected returns do vary across time, and across assets, in ways that the static CAPM and random-walk view does not recognize.
      • Understand how stock and bond returns can be predicted over time.
    • In terms of skills, students shall:
      • Assess the volatility of stock and bond returns.
      • Be able to use multi-factor models to comprehend the cross-sectional pattern of average returns, such as value, growth and momentum effects.
      • Possess the necessary skills to test advanced trading strategies used by trading desks and hedge funds.
      • Understand performance evaluation and benchmarks for funds.
    • In terms of general competence, students shall:
      • Be up-to-date on asset pricing theory and corresponding empirical work.
      • Be used to work with data and manage a large work load in a short period of time.

  • Teaching

    This course covers a multitude of papers on asset pricing. While the readings are extensive, the emphasis of the course is on the analysis and understanding of both the economics and the empirics.

    The course relies on two main elements: lectures and supporting material. Lectures will be used mainly to discuss the paper(s) covered in each topic. While the empirics are discussed in class, details on how to implement and replicate parts of the analysis will be covered by supporting material, e.g. short video clips uploaded on the course website.

    Students have a responsibility to come well prepared and participate actively in the classroom discussion. I encourage voluntary participation, but may call on any student.

  • Required prerequisites

    Students are required to have taken a master-level course in investments, such as FIE400E(N) or equivalent.

  • Requirements for course approval


  • Assessment

    Assessment for this course will not be changed spring 2020.

    The final course grade has two components: class participation (40%) and a term paper (60%). All classroom discussion and the term paper should be in English. Grading scale A-F.

    Class participation - 40%

    Dialogue and debate are an important part of this course. For each topic, at least one of the following elements will be used to measure class participation:

    • In-class quiz;
    • Problem set related to the paper(s);
    • Presentation of the paper(s).

    In-class quizzes are individual effort. Problem sets and paper presentation are group effort. The final class participation is the sum of all session scores over the whole term.

    Term project - 60%

    Students are required to do a term project in a group, resulting in a paper. The assignment consists of one of the following:

    • Replication of a paper (or parts of a paper) from a list of papers provided;
    • Replication of a paper (or parts of a paper) proposed by the students and approved by the lecturer;
    • Development of a new paper after discussion and approval by the lecturer.


    Due to risk of plagiarism, it is only possible to take the course one time. Retake is only possible if the course is failed.

  • Grading Scale

    Grading scale A-F.

  • Computer tools

    SAS (recommended), Stata, R or Excel. Students are not required to be familiar with any of this software, but should expect by the end of the course to use them for empirical work.

  • Literature

    Course package, containing academic articles and supporting material.


ECTS Credits
Teaching language

Spring. Not offered Spring 2021.

Course responsible

Associate Professor Francisco Santos, Department of Finance, NHH