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Unit information: Quantitative Methods for Finance 1 in 2021/22

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Quantitative Methods for Finance 1
Unit code EFIM20041
Credit points 20
Level of study I/5
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Pedio
Open unit status Not open
Pre-requisites

Mathematics for Economics

Probability, Statistics and Econometrics

Co-requisites

None

School/department School of Accounting and Finance - Business School
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

This unit provides exposure to some of the theory and practice of empirical research in Finance.

The syllabus will feature mostly standard techniques in Econometrics but make extensive use of examples and applications that are specific to Finance. It will also introduce some techniques that are specific to Finance.

Topics include:

  • Review of estimation, properties of estimators (unbiasedness, efficiency, sampling distribution, consistency) and hypothesis testing.
  • Simple and multiple regression analysis; omitted variable bias; functional form; heteroskedasticity and weighted least squares; endogeneity (measurement error, simultaneity); instrumental variables and two-stage least squares;
  • Introduction to stationary and non-stationary time series analysis.

Students will work with software packages to perform and interpret estimations from finance data sets.

Intended Learning Outcomes

Students will be able to:

  1. Demonstrate an understanding of the relationship between financial theory and empirical testing
  2. Recognize the limitations and evolution of empirical tests and theory
  3. Demonstrate an ability to interpret financial data arising in the context of the firm and in financial markets
  4. Demonstrate the skills necessary to manipulate financial data and carry out statistical and econometric tests
  5. Demonstrate problem-solving skills and ability to think analytically.

Teaching Information

The following delivery methods are considered relevant to the mix of numerical and computer-based material required:

18 hours of lectures

9 hours of exercise lectures

4 hours of large group computer lab sessions

6 hours of small group classes

Formative assessment will consist of conceptual, problem-solving and data analysis questions, marked by the class tutor and returned with feedback.

Assessment Information

Summative assessment

2.5 hour closed book exam. This assesses all learning outcomes.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. EFIM20041).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.

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