View Specification DocumentEconometric Methods for Accounting and Finance ACCFIN4079
- Academic Session: 2026-27
- School: Adam Smith Business School
- Credits: 20
- Level: Level 4 (SCQF level 10)
- Typically Offered: Semester 2
- Available to Visiting Students: Yes
- Collaborative Online International Learning: No
- Curriculum For Life: No
Short Description
This course will build on material covered in the Statistical Analysis (ACCFIN2018) course. It will extend knowledge on a set of important tools in modelling financial and accounting data and testing beliefs about how financial markets function. This course will also test theories on whether firms' decision makers are involved in value enhancing investments by relying on both econometric techniques and finance theory covered in Finance 1 and Finance 2. Among other important topics to be covered, students will be exposed to the multivariate case based on the Ordinary Least Squares (OLS) technique, Time Series Analysis methods, as well as Forecasting techniques.
Timetable
Lectures: 2 hours of lectures × 10 weeks.
Labs: 1 hour of lab × 8 weeks.
Requirements of Entry
Normally a D3 in ACCFIN2018 Statistical Analysis and Methods or equivalent.
Excluded Courses
Econometrics 1: Introduction to Econometrics (Exchange Students) ECON4083
Econometrics 1: Introduction to Econometrics ECON4003
Econometrics 2: Multiple Regression and Applications ECON4004 (must not be taken in the same Semester; preferably the ACCFIN4079 should be taken first and then the ECON4004)
Co-requisites
None
Assessment
1. Written assignment, including essay; Group; 2250 words; 25%; ILOs 2-5.
2. Degree exam: in-person; Individual; 90 minutes; 75%; ILOs 1-3.
Main Assessment In: April/May
Course Aims
The aim of the course is to provide students with an advanced understanding of some important concepts of econometrics. Specifically, building on some concepts that have been covered in earlier statistics course(s), this course will introduce the multivariate OLS method, as well as the properties of OLS estimators. The course will also introduce linear stochastic time series models and their applicability to financial data, the application of co-integration techniques to financial data, as well as the application of ARCH and GARCH techniques in modelling volatility (risk) in financial markets. After finishing this course, students are expected to have insights that are of academic interest and practical importance on crucial elements influencing financial decisions which will be derived from the analysis of financial or accounting data.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
1. Evaluate the properties of OLS estimators and adjust them to accommodate statistical irregularities.
2. Understand the testable channels, including the robustness checks, and the challenges involved in verifying a theoretical proposition or hypothesis.
3. Analyse financial and accounting data by applying appropriate econometric tools.
4. Critically assess corporate financing, investment and strategy decisions.
5. Critically refer to existing literature and empirically test research hypotheses.