FE4003 - Quantitative Methods for Banking, Finance and Economics (2019/20)
|Module specification||Module approved to run in 2019/20|
|Module title||Quantitative Methods for Banking, Finance and Economics|
|Module level||Certificate (04)|
|Credit rating for module||30|
|School||Guildhall School of Business and Law|
|Total study hours||300|
|Running in 2019/20||
This module enables students to acquire quantitative skills and a foundation in mathematical and statistical concepts and techniques so they can analyse and solve economic, banking and finance problems. It develops students’ ability to understand and apply mathematical and statistical methods to economic and finance theories. It provides an opportunity for students to collect, present, analyse and interpret real data using appropriate computer software.
Students are encouraged to reflect and draw on their diverse socio-cultural
backgrounds and experiences. A student centred coaching system is used where second / third year degree students who have performed well in the subject, are trained to support weaker students in small groups or on a one to one basis. This has worked effectively in the past and raised engagement and performance.
Equality is promoted by treating everyone with equal dignity and worth, while also raising aspirations and supporting achievement for those students with diverse requirements, entitlements and backgrounds
A range of transferrable and subject specific skills are developed, in particular: self- assessment and reflection; peer assessment; written and oral communication; research; problem solving; data collection and quantitative; IT; interpreting and analytical skills.
A. Mathematical Foundations
Introduction to algebra
Linear equations and applications to economics, finance and banking
Non-linear functions and applications to banking, economic and finance problems
Logarithmic and exponential function and their applications
The time value of money, present and future values, simple and compound interest, arithmetic and geometric progressions, depreciation, payment of interest,
Using IT software to analyse and present mathematical concepts and relations.
Discounting and present value, annuities and mortgages, investment appraisal techniques including Payback, ARR, NPV and IRR.
Portfolio Analysis, return, variance, covariance, portfolio markets and beta
Return on Investment (AMROI & GMROI) All LO1
Differentiation, risk and diversification.
Integration, dividend payments, expected option values, annuities and growing annuities All LO3
Optimisation with one variable and applications to economics and finance: Identifying maximum, minimum, and inflection points. Applications such as marginal cost, marginal revenue and elasticity.
Maximising profit, total revenue and minimising average cost
Optimisation with more than one variable and economic applications:
Non- constrained and constrained optimisation
Integration and application to economics and finance: Consumer and producer surplus All LO4
B. Statistical Foundations
Data issues: collection, selection and sources.
Use IT and appropriate software such as Excel and or SPSS to access sources of relevant economic and financial information; transform; present; analyse and interpret information relevant to banking, economics and finance.
Graphical data presentation using different techniques such as frequency distributions, pie and bar charts, and histograms
Summarising data using measures of average, dispersion and skewness
Probability theory - classical, empirical and subjective approaches
Discrete probability distribution: Binomial & Poisson probability distributions
Expected values and uncertainty
Decision making under uncertainty, expected monetary value, decision tree with application in economics, banking & finance. All LO3
Continuous probability distribution: Normal probability distribution
Sampling probability distribution
Point and interval estimation, small and large samples
Hypothesis testing, significance levels, errors
Measuring relationships between variables in the context of banking, economics and finance - scatter diagrams, correlation, covariance, simple linear regression, strength of evidence & statistical testing, predictions: Basic principles, use of Excel/SPSS, and their interpretation, forecasting: extrapolation, interpolation; All LO2
Balance of independent study and scheduled teaching activity
Students’ learning is organised around formal direct contact time with the teaching team, and reflective independent learning. Student formal contact time is normally 3 hours per week. Lectures are around 2 hours and deliver core subject knowledge and materials in an interactive way allowing periods of reflection by students. During seminars students go through previously set problem sheets. The emphasis is on student learning through problem solving, participation, and formative feedback. A PASS coaching programme supports weaker students to improve their engagement and performance. Seminars are also used to develop IT skills and support students’ learning.
Students are expected to complement the 'formal' learning activity with reading of the material suggested in the teaching sessions; solving mathematical and statistical problems as applied to banking, economics and finance problems; collecting, analysing and interpreting data; writing, planning and preparing for group presentation and report; and preparing for the in-class tests and final exam.
The module makes extensive use of blended learning through use of virtual learning environment platforms (WebLearn) where module handbook; lecture slides; seminar questions; coursework brief; assessment and grading criteria; past in-class tests and exam papers; guideline answers to seminar questions; past in-class test and exam papers; and other relevant learning materials are provided. Links to other online resources, government data bases and videos are also available on Weblearn.
On successful completion of this module students will be able to:
1. Understand and apply fundamental principles of mathematics to solve banking, economics and financial problems.
This is assessed by a one hour long in-class test 1.
Self-assessment and reflection; peer assessment; problem solving; and quantitative skills are developed and assessed.
2. Understand and apply fundamental principles of statistics to solve banking, economics and financial problems.
This is assessed by a one hour long in-class test 2.
Self-assessment and reflection; peer assessment; problem solving, and quantitative skills are developed and assessed.
3. Collect, collate and analyse quantitative data in a subject context and appropriately interpret and report results from an empirical exercise using IT software such as excel and/or SPSS. Understand and apply a range of statistical techniques to solve banking, economics and financial problems.
This is assessed by a 1500 words group project.
Written and oral communication; research; problem solving; data collection and quantitative; IT; interpreting and analytical skills are developed and assessed.
4. Understand and apply a range of mathematical techniques to solve economic, banking and financial related problems.
This is assessed by a two-hours unseen exam.
Written; problem solving; quantitative and analytical skills are developed and
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. It allows students to reflect on their own learning and provide peer feedback.
During seminars students receive formative feedback on their knowledge and understanding of mathematical and statistical methods and their application to problems 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.
There are four summative assessments consisting of two In-class test in weeks 11, and 23 covering learning outcomes 1 and 2, group presentation and submission of slides in week 14 assessing learning outcome 3, and a two-hours unseen final exam assessing learning outcome 4.
Assessment components are designed to test students’ knowledge and understanding of mathematical and statistical concepts and theories and applications to economics, finance and banking. The group presentation is designed to test students’ ability to apply statistical techniques and IT software to real data. Students are required to collect, present, analyse and interpret data and make a power point presentation and submit slides.
Students team work and presentation skills are developed and assessed.
Revision activities and sessions are delivered before each in-class test and final exam to provide support for students. This should boost students’ confidence and 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.
1. Swift, L. (2014). Quantitative methods for business, management and finance, 4th
ed., Palgrave-Macmillan. This is an E-BOOK. Hard copies available at
Aldgate 519.5 SWI
2. Jacques, I. (2015). Mathematics for economics and business, 8th ed., FT Prentice
Hall. This is an E-BOOK. Earlier editions are available as hard copies at Aldgate
and Holloway Road 510.2433 JAC
3. Renshaw, G. (2016). Mathematics for economics, 4th ed., Oxford University Press
Aldgate 510.2433 REN
4. Bradley, T. (2013). Essential mathematics for economics and business, 3rd ed.,
John Wiley & Sons Ltd. Aldgate 330.0150 BRA
5. Bradley, T (2007). Essential statistics for economics, business and management,
John Wiley & Sons Ltd. Aldgate 519.5 BRA
6. Chiang, A. C. and Wainwright, K. (2005). Fundamental methods of mathematical
economics, 4th ed., McGraw-Hill. Aldgate 330.0151 CHI
7. Oakshott, Les (2016). Essential quantitative methods for business, management
and finance, 6th ed., Palgrave Macmillan. This is an E-Book. Earlier editions are
available as hard copies at Aldgate 658.0015195 OAK
8. Sydsaeter, K. and Hammond, P. (2016). Essential mathematics for economic
analysis, 4th ed., FT Prentice Hall. This is an E-Book. Earlier editions are available
as hard copies at Aldgate 330.0151 SYD
9. Waters, Donald (2011). Quantitative methods for business, 5th ed., FT Prentice Hall,
This is an E-BOOK. Earlier editions are available as hard copies at Aldgate