Quantitative Methods - BUSN8022

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2023 to 2024
Canterbury
 Autumn Term 7 15 (7.5) Nikolaos Voukelatos checkmark-circle

Overview

This module provides a general introduction to the quantitative methods used in financial applications and topics may include:

Statistical concepts
Probability distributions
Statistical inference, estimation and hypothesis testing
Correlation, spurious correlation and general dependence measures
Linear regression
Multiple linear regression
Logistic regression
Monte Carlo simulation
Modelling in Excel

Details

Contact hours

Total contact hours: 37
Private study hours: 113
Total study hours: 150

Method of assessment

Main assessment methods:
Individual Empirical Report (3000 words) (40%)
Examination, 2 hour (60%).

Reassessment method:
100% Exam

Indicative reading

Required Reading:

Brooks, C. (2008) Introductory Econometrics for Finance, 2nd edition, Cambridge University Press

Gujarati, D.N. (2009) Basic Econometrics, 5th Edition, McGraw-Hill, New York and London


Supplementary Reading:

Anderson, D.R., Sweeney, D.J., Williams, T.A., Freeman, J. and Shoesmith, E. (2010), Statistics for Business and Economics (2nd edition), London: Cengage

Green, W.H. (2011) Econometric Analysis (7th edition), Harlow: Pearson

Watsham, T. and Parramore, K. (2007), Quantitative Methods in Finance, London: Thomson Learning

See the library reading list for this module (Canterbury)

Learning outcomes

The intended specific learning outcomes:
On successfully completing the module students will be able to:
- Demonstrate knowledge and understanding of the use of quantitative techniques for application to problems in a finance context.
- Demonstrate an ability to undertake statistical investigation of financial data.
- Identify and select appropriate statistical techniques to apply to issues within a finance context.
- Apply quantitative techniques for solving problems within a finance context.
- Analyse and interpret results derived from statistical models.
- Demonstrate proficiency band competency in numeracy skills.

The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Analyse compare, discuss, and critically evaluate various statistical methods.
- Plan work, use relevant sources and study independently.
- Work in groups, listen, respond to different points of view and negotiate outcomes. Ability to receive and use criticism and advice.
- Select appropriate formats for presentation of work, which includes the acknowledgement and reference of sources.
- Analyse structured and unstructured problems.

Notes

  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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