module specification

FE5001 - Econometrics and Financial Modelling (2018/19)

Module specification Module approved to run in 2018/19
Module title Econometrics and Financial Modelling
Module level Intermediate (05)
Credit rating for module 30
School Guildhall School of Business and Law
Total study hours 300
9 hours Assessment Preparation / Delivery
210 hours Guided independent study
81 hours Scheduled learning & teaching activities
Assessment components
Type Weighting Qualifying mark Description
In-Course Test 25%   60 minutes In-class tests
Coursework 25%   1500 words individual coursework
Coursework 10%   2,000 words group coursework
Unseen Examination 40%   Two hours unseen and closed examination
Running in 2018/19
Period Campus Day Time Module Leader
Year City Thursday Morning

Module summary

The first half of this module focuses on Econometrics, and deals with the theory and application of the Classical Linear Regression Model (CLRM), providing a firm grounding in the theory of Ordinary Least Squares (OLS) and an appreciation of its limitations. It provides a theoretical understanding of the causes, consequences and detection of, and remedies for, the violation of the assumptions of the classical linear regression model.  It develops knowledge and skills to use standard statistical/econometric software package (e.g. EViews) and apply techniques to economics, finance and banking problems and models.

The second half of this module focuses on Financial Modelling, and involves the use of EViews and Excel and other relevant software to construct financial models including valuation and portfolio models.

The module provides students with the knowledge and skills to design, undertake, and evaluate empirical work within economics, finance and banking.

Students are encouraged to reflect and draw on their diverse socio-cultural
backgrounds and experiences.

Equality is promoted by treating everyone with equal dignity and worth, while also raising aspirations and supporting achievement for people with diverse requirements, entitlements and backgrounds

A range of transferable and subject specific skills are developed, in particular: self- assessment and reflection; peer assessment; written; IT; applied analysis; subject research; problem solving; data and quantitative; analytical and critical thinking.


Review of statistics:  probability distributions, sampling theory, estimation, confidence intervals, hypothesis testing and applications to economic, finance and banking.
Correlation and regression analysis: applications to economics and finance.
Introduction to Econometrics: economic theory versus empirics.
The Classical Linear Regression Model: assumptions, specification, estimation and hypothesis-testing.
Functional form and non-linearity and dummy variables All LO1

Violations of the assumptions of the classical linear regression model: causes, consequences, tests and solutions for multicollinearity, autocorrelation, heteroscedasticity, specification errors. LO2

Use IT to access sources of relevant economic and financial information, and transform into usable information relevant to the analysis of economics, finance and banking.
Development of intermediate knowledge of spreadsheets, using workbooks and solving problems by analysing data. Using and interpreting the output of dedicated econometric software (e.g. EViews), conducting appropriate econometric tests, and writing reports analysing econometric problems. All LO2

Financial Modelling involving the implementation of financial models in Excel. Basic and advanced models in the areas of corporate finance such as valuation models for securities, Optimal vale of investment portfolios, pricing options, and measurement of value at risk (VAR) in Excel spreadsheets. All LO3

Examination of the technical aspects of EViews and Excel as tools of Financial Modelling for data analysis and measuring value of financial assets at risk exposure. LO4

Balance of independent study and scheduled teaching activity

Learning consists of ‘formal’ class room learning directed by the teaching team, and reflective independent learning. The formal learning involves lectures, seminars and computer-workshops while the independent learning consists of reading of the course material, working on weekly exercises including computing assignments using software (for example EViews) and coursework that involves undertaking econometric analysis and writing a report, and preparing for the final written exam.

The module is delivered in a three-hour session each week which comprises a two-hour lecture, and a one-hour seminar or a one-hour computer workshop. In the seminar students present their solution(s) to the problems set and raise questions on the lecture material. In the computer workshop students undertake empirical analysis using IT software. The seminar and the workshop provide opportunities for active and reflective learning, and also formative feedback. A virtual learning environment (WebLearn) supports blended learning by providing module handbook, lecture notes, seminar materials, IT workshop exercises, past test and exam papers with guideline answers, coursework brief with assessment and grading criteria, EViews videos and other learning material.

All activities provide students with knowledge and understanding of econometrics, statistics and financial modelling. The weekly exercises and the coursework give students such diverse skills as working independently, problem solving, writing concisely and clearly, retrieving secondary data from various online sources and describing and exploring them using econometric software and spreadsheets.

Professional and transferable skills are developed in lectures and seminars, and through independent directed learning and assessment. Skills development is enhanced through working cooperatively solving economic problems.

Initiative and independence is developed progressively through the module such that students are required to take greater responsibility of their work.

Learning outcomes

On successful completion of this module students will be able to:

1.  Demonstrate a broad knowledge and a systematic understanding of statistics;
correlation and linear regression analysis; hypothesis testing and application to
economics, finance and banking.

2. Produce evidence, collect, analyse and interpret data and explain regression results; test hypotheses; evaluate regression models and use dedicated statistical and econometric software such as Excel and EViews.

3. Employ financial Models including security valuation, portfolio selection and pricing options using EViews, Excel and other relevant software.

4. Apply theoretical and practical knowledge for the analysis of financial data and risk management.

Assessment strategy

The formative and summative assessments and feedback practices are informed by reflection, consideration of professional practice, and subject-specific knowledge and educational scholarship.

There is a formative peer assessment in week 4 which supports students in developing for summative assessment, in-class test later in the term. It allows students to reflect on their own learning and provide peer feedback.

There are four summative assessments consisting of one In-class test in week 10
assessing learning outcome 1, an individual coursework (1500 words econometric report) in week 14 assessing learning outcome 2, a group coursework (2,000 words) assessing learning outcome 3, and a two-hours unseen exam assessing learning outcome 4 in relation to financial modelling.

Through the summative assessments, students are provided with opportunities to develop an understanding of, and the necessary skills to demonstrate, good academic practice.

The in-class test examines students’ understanding of key principles and concepts developed in the module. The test gives students helpful feedback on their strengths and weaknesses in this technical subject. Before the in-class test, revision activities are carried out to support students’ learning to improve performance.

The first coursework is an independent piece of work requiring the application of knowledge gained on the module. The coursework is based on a computing assignment that applies econometric and other quantitative methods to a particular economic/ finance/ banking model using dedicated econometric software. Students write a report and are assessed on their knowledge and skills in designing, executing and evaluating empirical work within a range of economic and financial contexts.

A feed-forward strategy is used to provide early feedback to students to improve their final submission. Use of the feedforward strategy and class discussion of a detailed grading and assessment criteria create an opportunity for dialogue between students and staff and promote shared understanding of the basis on which academic judgements are made.

The second coursework develops students’ ability to work in a team and share knowledge and skills to promote work commitment and leadership for problems solving. Detailed information on requirements and guidance will be delivered within the teaching progress. This coursework is due in week 24. Students will receive timely, constructive and developmental feedback.

The coursework and exam assess the student’s: knowledge and understanding of quantitative analysis and methods applied to economics, finance and banking. Subject research, written communication; data and quantitative analysis; critical thinking; problem solving and IT skills and ability to apply specialist econometric software package, Excel and SPSS are developed and assessed.

The examination will primarily provide a thorough assessment of students' theoretical knowledge and ability to produce, interpret, evaluate and explain quantitative results and solve problems in relation to financial modelling,

During seminars students receive formative feedback on their knowledge and understanding of quantitative techniques and analysis by working though exercises and problems which they prepare before the session. This preparation and feedback provides support for students when they later tackle problems set in summative assessment such as In-class tests and final exam.

Through the summative assessments, students are provided with opportunities to develop an understanding of, and the necessary skills to demonstrate, good academic practice. Written communication, analytical, critical thinking, problem solving, quantitative and interpreting skills are assessed.

Towards the end of the module, revision activities and sessions are designed to provide support for students in preparing for examinations. This should boost students’ confidence as they approach the examination period and thereby improve their performance.

All the information about processes of marking and moderating marks, timing of assessments and deadlines for feedback provision are clearly articulated in the module booklet and communicated to students through Weblearn as well.


Core Textbook:

1.  Asteriou, D and Hall S G (2016). Applied econometrics, 3rd ed., Palgrave Macmillan
     This is an E-BOOK. Hard copies are available at Aldgate 330.015195 AST
2.  Benninga, S. (2014) Financial Modelling 4th Edition, MIT Press, London.
     Aldgate 332.015118 BEN
3.  Brooks, C. (2014) Introductory Econometrics for Finance, 3rd Edition, Cambridge
    University Press, Cambridge. Earlier editions are available as E-BOOK and hard
    copies at Aldgate 332.015118 BRO

Additional Textbooks:

4.  Barrow, M. (2013) Statistics for economics, accounting and business studies, 6th
     ed., FT Prentice Hall. This is an E-BOOK. Hard copies available at Holloway Rd and
     Aldgate 519.502433 BAR
5. Bradley, T. (2007). Essential statistics for economics, business and management, John Wiley & Sons Ltd. Aldgate 519.5 BRA
6. Dougherty, C. (2016). Introduction to econometrics, 5th edition, Oxford.
    Aldgate 330.015195 DOU    
7.  Gujarati, D. N. (2015). Econometrics by example, 2nd ed., Palgrave MacMillan
     This is an E-BOOK. Hard copies of earlier editions are available at Aldgate
     330.015195 GUJ
8.  Gujarati, D.N. and Porter D. (2010). Essentials of econometrics, 4th ed., McGraw
     Hill. Aldgate 330.015195 GUJ
9.  Gujarati, D.N. and Porter D. (2014). Basic econometrics, 6th ed., McGraw Hill
     Earlier editions are available at Aldgate 330.015195 GUJ
10. Keller, G. (2012). Managerial statistics, 9th ed., South Western Cengage learning
11. Oakshott, Les (2016). Essential quantitative methods for business, management
      and finance, 6th ed. Palgrave Macmillan. This is also available as an E-Book. Hard
       copies are available at   658.0015195 OAK Holloway Rd and Aldgate
12. Waters, Donald (2011) Quantitative methods for business, 5th ed., FT Prentice Hall,
      This book is available as E-BOOK.
13. Wooldridge, J. M. (2016). Introduction to econometrics, 4th ed., South Western
     College Publishing. This is an E-BOOK. Earlier editions are available as hard copies
     at Aldgate 330.015195 WOO