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Module ASB-1117:
Fin Techniques and Analysis

Module Facts

Run by Bangor Business School

20 Credits or 10 ECTS Credits

Semester 2

Organiser: Dr Danial Hemmings

Overall aims and purpose

Note: The module comprises a trading simulation component running alongside weekly lectures on core financial mathematics and analytical techniques.

The module aims to develop mathematical and analytical skills to a level that allows the use of quantitative techniques in a wide variety of Financial and Economic applications, including but not limited to securities trading and investment. The core part of the module introduces financial mathematics and techniques that are applicable to decision-making in a wide range of contexts. The purpose of the trading simulation part is to develop the application of analytical and valuation techniques in the specific context of stock market investment, using spreadsheet modelling and simulated securities trading within a virtual dealing environment.

Course content

The module covers quantitative techniques that are applicable in a wide variety of Financial and Economic contexts: the time-value of money, including future values of capital sums and savings plans, present values of capital sums and annuities, and compound interest; investment appraisal, including Net Present Value (NPV) and Internal Rate of Return (IRR); investment risk and return; gradients and introduction to differentiation; price elasticity and firm production functions; second derivatives and optimization problems. In addition, the module provides an overview of exchange traded securities (including equities, or ‘stocks’), and the trading simulation component will introduce the application of key financial techniques in the context of securities trading. This will involve real-time trading of securities in a virtual portfolio using the Stocktrak simulation software.

Assessment Criteria


D- to D+ (40-49%): No major omissions or inaccuracies in the deployment of information/skills. Some grasp of theoretical/conceptual/practical elements. Integration of theory/practice/information present intermittently in pursuit of the assessed work's objectives.


B- to B+ (60-69%): Very good performance Most of the relevant information accurately deployed. Good grasp of theoretical/conceptual/practical elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Evidence of the use of creative and reflective skills.


A- to A+ (70%+): Outstanding performance. The relevant information accurately deployed. Excellent grasp of theoretical/conceptual/practice elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Strong evidence of the use of creative and reflective skills.

C- to C+

C- to C+ (50-59%): Much of the relevant information and skills mostly accurately deployed. Adequate grasp of theoretical/conceptual/practical elements. Fair integration of theory/practice/information in the pursuit of the assessed work's objectives. Some evidence of the use of creative and reflective skills.

Learning outcomes

  1. Understand the application of financial mathematics techniques to value cash flows that take place over time.

  2. Understand and be able to implement techniques for investing in exchange-traded securities.

  3. Derive and manipulate algebraic equations, differentiate and solve optimization problems.

  4. Apply all techniques to business, economics and finance problems involving cash flows such as revenues, costs, profit and interest.

Assessment Methods

Type Name Description Weight
CLASS TEST Class test

1 hour closed-book class test under examination conditions.

EXAM Formal Examination

Two hour closed-book exam at the end of semester 2.

COMPREHENSION TEST Practical skills assessment

Practical skills assessment based on the trading simulation component of the module.


Teaching and Learning Strategy


2-hour lecture per week

Private study

Private study will include time reviewing lecture materials and recommended reading, completing exercises, and revising for assessments.

Practical classes and workshops

1-hour 'trading simulation' workshop per week


1-hour drop-in workshop per week


Transferable skills

  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Information retrieval - Able to access different and multiple sources of information
  • Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Subject specific skills

  • knowledge of theories and empirical evidence concerning financial management, risk and the operation of capital markets (in cases of degrees with significant finance content).
  • Analysis, deduction and induction. Economic reasoning is highly deductive, and logical analysis is applied to assumption-based models. However, inductive reasoning is also important. The development of such analytical skills enhances students' problem-solving and decision-making ability.
  • Quantification and design. Data, and their effective organisation, presentation and analysis, are important in economics. The typical student will have some familiarity with the principal sources of economic information and data relevant to industry, commerce, society and government, and have had practice in organising it and presenting it informatively. This skill is important at all stages in the decision-making process.
  • Framing. Through the study of economics, a student should learn how to decide what should be taken as given or fixed for the purposes of setting up and solving a problem, i.e. what the important 'parameters' are in constraining the solution to the problem. Learning to think about how and why these parameters might change encourages a student to place the economic problem in its broader social and political context. This 'framing' skill is important in determining the decision-maker's ability to implement the solutions to problems.
  • A knowledge of the major theoretical tools and theories of finance, and their relevance and application to theoretical and practical problems (e.g. concept of arbitrage and examples of its use; financial mathematics and capital budgeting criteria; informational efficiency; optimal risk sharing; portfolio theory; asset pricing models and the valuation of securities; cost of capital; derivative pricing; risk management; information asymmetry; principal agency relationships; signalling; Fisher separation and capital budgeting criteria; behavioural finance; term structure and the movement of interest rates; determination of exchange rates and financial intermediation).
  • An ability to interpret financial data including that arising in the context of the firm or household from accounting statements and data generated in financial markets. The interpretation may involve analysis using statistical and financial functions and procedures such as are routinely available in spreadsheets (eg Microsoft Excel) and statistical packages. It may assume the skills necessary to manipulate financial data and carry out statistical and econometric tests (e.g. estimation and interpretation of asset pricing models; financial modelling and projections; event studies and residuals analysis; elements of time series analysis, such as serial correlation mean reversion, and stochastic volatility).
  • Numeracy: the use of quantitative skills to manipulate data, evaluate, estimate and model business problems, functions and phenomena.


Reading list

Jacques, I. (2018). Mathematics for economics and business, 9th ed. Pearson.

Curwin, J., Slater, R., and Eadson, D. (2013). Quantitative Methods for Business Decisions, 7th Ed. Cengage.

Reilly, F., and Brown, K. (2012). Investment Analysis and Portfolio Management, 10th Ed. Cengage.

Pring, M. (2014). Technical Analysis Explained, 5th ed. McGraw-Hill.

Courses including this module

Compulsory in courses:

Optional in courses: