Postgraduate Course: Quantitative Techniques for Finance I (CMSE11674)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course will provide you with the statistical concepts needed for financial applications. The goal is to apply statistical tools to analyse data, solve problems and make business decisions. This introductory course will provide you with the essential background for subsequent courses. |
| Course description |
This course covers foundation knowledge in probability and statistical inference. Although there is a strong emphasis on theory, you will get an introduction to an econometric software for conducting basic empirical research. The material is presented to help students understand, rather than memorise, statistical concepts. The course shall be accessible for both, students with strong quantitative background, and those who are ready to put effort into the class material. This course also introduces students to the three prongs of ethics in quantitative analysis: data transparency, production transparency, and analytical transparency.
Outline content
Data: Plots and Summaries; Introduction to Probability; Statistical Inference: Confidence Intervals, Hypothesis Tests, and p-values; The Simple & Multiple Linear Regression Models.
Student learning experience
This course is taught via a combination of weekly lectures and tutorials. Students will be introduced to an econometrics software during computer-based tutorials. Tutorials are intended to help students go over exercises they found difficult rather than to solve all the weekly tutorial questions. Therefore, students should attempt solving tutorial questions in advance of tutorial sessions.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | This course is for students enrolled in MSc Finance & Investment and MSc Accounting & Financial Management |
Course Delivery Information
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| Academic year 2025/26, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 10,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
166 )
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| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
60% Written exam (Individual) - Assesses all course Learning Outcomes
40% Class test (Individual) - Assesses course Learning Outcomes 1,2 |
| Feedback |
Formative: Students are encouraged to ask questions in lectures and tutorials. Students can get early feedback on their performance by engaging with tutorial questions. Students can also use their performance in the mid-term exam to assess their understanding.
Summative: Feedback will be provided on the assessments within agreed deadlines. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Define, explain and illustrate the concepts of probability, random variables, point estimation, interval estimation, hypothesis testing and inference.
- Critically discuss the link of theory with empirical applications.
- Understand and critically evaluate the importance of assumptions in statistics/econometrics.
- Carry out basic data analysis in a statistical software package.
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Reading List
Douglas A. Lind, William G Marchal, Samuel A. Wathen (2012), Statistical Techniques in Business and Economics, 15th Edition, McGraw-Hill ISBN: 9780073401805.
Wooldridge, J. (2015), Introductory Econometrics: A Modern Approach, 6th edition, Thomson.
McClave, J. T., Benson, P. G., & Sincich, T. (2021). Statistics for Business and Economics (14th ed.). Pearson.
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2021). Basic Statistics for Business and Economics (10th ed.). McGraw-Hill Education.
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Additional Information
| Graduate Attributes and Skills |
Communication, ICT, and Numeracy Skills
After completing this course, students should be able to:
Convey meaning and message through a wide range of communication tools, including digital technology and social media; to understand how to use these tools to communicate in ways that sustain positive and responsible relationships.
Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts. |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Angelica Gonzalez
Tel: (0131 6)51 3027
Email: angelica.gonzalez@ed.ac.uk |
Course secretary | |
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