Investment Research Methods 1
This module provides students with a foundation in research methods used in finance. In particular, it introduces the fundamental quantitative techniques that are essential for a financial analyst, such as basic statistics, probability theory and regression analysis. Theory and techniques will be covered in the lectures, while in the tutorials students will work through numerical examples and financial applications.
Internationalisation: This is a technical module on statistical tools for international financial research, which are applicable across countries. This module also incorporates new research on investment from various countries, including the USA and the UK.
Sustainability: All of the lecture material and the basic text e-book are available on the ELE (Exeter Learning Environment).
External Engagement: This module follows the CFA curriculum.
Employability: Students learn the basic statistical tools that can be used in financial analysis, and will help students score well in the CFA examination. This module also helps develop numerical and creativity skills, which are valuable skills for financial analysts and traders.
Full module specification
|Module title:||Investment Research Methods 1|
|Duration of module:||
Duration (weeks) - term 1: |
The aim of this module is to introduce students to research methods commonly used in finance. In particular, it aims to develop students’ ability to select and critically evaluate the major tools of investment research, as they have been developed in current research.
ILO: Module-specific skills
- 1. discuss, calculate and interpret descriptive statistics;
- 2. use the basic probability tools needed to make investment decision;
- 3. discuss, use and interpret different probability distributions commonly used in finance;
- 4. demonstrate knowledge of basic concepts in estimation theory
- 5. construct and interpret point estimates and confidence intervals;
- 6. perform hypothesis tests and interpret the results;
- 7. use and critically evaluate tools such as correlation analysis and regression analysis
ILO: Discipline-specific skills
- 8. develop rigorous theoretical arguments based on mathematical and analytical economic reasoning
- 9. analyze quantitative problems in finance;
- 10. interpret financial data and problems in the light of established theories;
- 11. access a wide body of empirical research literature and critically appraise it.
ILO: Personal and key skills
- 12. plan and manage his/her own study;
- 13. make appropriate use of learning resources;
- 14. analyze critically problems arising in both academic and practical contexts
Learning activities and teaching methods (given in hours of study time)
|Scheduled Learning and Teaching Activities||Guided independent study||Placement / study abroad|
Details of learning activities and teaching methods
|Category||Hours of study time||Description|
|Form of assessment||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Mock exam||1 hour||1-14||In class|
Summative assessment (% of credit)
|Coursework||Written exams||Practical exams|
Details of summative assessment
|Form of assessment||% of credit||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Mid-term exam (multiple choice questions)||20||1 hour||1-7, 8-9, 12-14||In class & correct answers on ELE|
|Final exam (multiple choice questions and essay type questions)||80||2 hours||1-14||Correct answers on ELE|
Details of re-assessment (where required by referral or deferral)
|Original form of assessment||Form of re-assessment||ILOs re-assessed||Timescale for re-assessment|
|Mid-term exam and final exam||Exam (100%) 2 hours||1-14||Aug/Sep|
• Introduction to basic concepts: Descriptive statistics and market returns.
• Some basic probability concepts.
• Probability distributions commonly used in finance.
• Estimating population parameters and constructing confidence interval.
• Hypothesis testing.
• Regression analysis and applications in finance.
• Dummy variables regressions and event studies.
• Introduction to time series analysis.
Indicative learning resources - Basic reading
DeFusco, R.A., McLeavey, D.W., Pinto, J.E. and Runcle, D.E. (2007) Quantitative Investment Analysis, Second Edition, US: Association for Investment and Management Research.
Anderson, D.R., Sweeney, D.J., Williams, T.A., Freeman, J. and Shoesmith, E. (2010) Statistics for Business and Economics, Second Edition, Cengage.
Brooks, C. (2008) Introductory Econometrics for Finance, Second Edition, Cambridge University Press.
Campbell, J.Y., Lo, A.W. and MacKinlay, C.A. (1997) The Econometrics of Financial Markets, US: Princeton University Press.
Module has an active ELE page?
Last revision date