BUS329 Applied Financial Econometrics

Credits (ECTS):10

Course responsible:Daumantas Bloznelis

Campus / Online:Taught campus Ås

Teaching language:Engelsk

Course frequency:Annually.

Nominal workload:250 hours.

Teaching and exam period:This course starts in Autumn parallel. This course has teaching/evaluation in Autumn parallel.

About this course

This course covers econometric analysis of financial and commodity markets. It links up financial theory with real data from major financial databases to facilitate forecasting, optimization and risk management. Combining econometric theory with extensive software applications, the hands-on approach provides a head start for a master’s thesis in finance - and a glimpse into the work of a quantitative analyst.

The econometric topics to be covered include (the list is indicative):

  • Time series properties, leads, lags, autocorrelation, stationarity, unit roots and structural breaks;
  • Autoregressive moving-average (ARMA) model;
  • Vector autoregression (VAR) and Granger causality;
  • Cointegration and vector error correction (VEC) model;
  • Volatility models such as GARCH;
  • Seemingly unrelated regressions; and
  • Generalized method of moments for systems of equations.

Learning outcome

Knowledge:

Students have advanced knowledge of

  • core ideas, principles and models in financial econometrics;
  • stylized facts of financial data;
  • selected sources of financial data;
  • the role of empirical analysis in the use, assessment and development of financial theory;
  • the relevance of econometrics in solving forecasting, optimization and risk management problems in finance.

Skills:

Students can

  • formulate, estimate, evaluate and interpret selected financial econometric models;
  • carry out selected analyses within financial forecasting, optimization and risk management;
  • present empirical findings and integrate financial econometric analysis into a research paper or a master’s thesis.

General Competence:

Students

  • appreciate the use of econometric analysis in developing and assessing financial theory;
  • can analyze and discuss forecasting, optimization and risk management problems in finance both conceptually and at the level of implementation;
  • can use R or other suitable software for retrieving, manipulating, analyzing and modelling financial data;
  • appreciate the limitations of empirical econometric analysis.
  • Learning activities
    The course will consist of on-campus and digital lectures and on-campus exercise sessions. Students should bring their own laptops to the exercise sessions and familiarize themselves with the use of available data and software for empirical analysis of financial and commodity markets.
  • Teaching support
    Office hours by appointment.
  • Prerequisites

    1. Basic regression analysis (STAT100 or equivalent)

    2. Basic programming and data management (e.g. BUS350 or INF120)

    3. Basic finance and investment (BUS220 or equivalent)

    4. Financial investments and risk management (BUS322 or equivalent)

  • Recommended prerequisites

    1. Statistics and econometrics on bachelor level (e.g. ECN201 or STAT200)

    2. Commodity markets and derivatives (BUS323)

    3. Corporate finance (BUS315 or equivalent)

    4. Advanced econometrics: Econometric methods (ECN301)

    5. Familiarity with major databases for finance such as Thomson Reuters Eikon / Refinitiv Datastream that is introduced in BUS322

  • Assessment method
    Portfolio assessment consisting of one term paper in groups and a 1.5-hour-long end-of-term exam in the teaching period. No re-sit examination will be arranged in this course.

  • Examiner scheme
    External examiner will control quality of the final examination task and principles for the assessment of the examination answers.
  • Mandatory activity

    Mandatory attendance of at least 70% of the exercise sessions. Four groupwise mandatory activities (approved/not approved) consisting of three written submissions and an oral presentation/discussion.

    Approved mandatory activity from previous years is valid when retaking the course.

  • Notes
    The course is taught in English.
  • Teaching hours

    6 hours of teaching per week, distributed as follows:

    2 hours of lectures (physically on campus);

    2 hours of exercises (physically on campus);

    2 hours of digital lectures.

  • Reduction of credits
    5 study points against BUS326
  • Admission requirements
    The course is intended for students enrolled in master programmes at NMBU. It is also open for other students with sufficient prior knowledge.