Module ASB-3001:
Market Risk Analytics

Module Facts

Run by Bangor Business School

10 Credits or 5 ECTS Credits

Semester 2

Organiser: Dr Gwion Williams

Overall aims and purpose

To provide an introduction to the key concepts of market risk analysis and financial engineering. This module examines derivatives such as options, swaps, and securitization.

The module will look at how derivatives can be used for speculative, hedging, and arbitrage strategies, how derivatives are priced, and how they can be used to manage risk.

Microsoft Excel is used for the testing and application of theories.

Course content

  • Topics may include but not be limited to: Introduction to financial derivatives, option strategies, structured products, option pricing (binomial model and Black-Scholes), greeks, volatility trading, swaps, and interest rate risk and management.

Assessment Criteria

threshold

D- to D+ Demonstration of the required knowledge and techniques but with significant mistakes and little development of the subject beyond lecture material.

good

B- to B+ Good understanding of the subject, together with evidence of investigation and understanding of theoretical and application, but with some minor errors.

excellent

A- to A* Excellent grasp of the concepts and techniques together with significant evidence of engagement and understanding of the theory and application in this area.

C- to C+

C- to C+ Clear understanding of the subject, together with some evidence of investigation and understanding of theoretical and application, but with errors.

Learning outcomes

  1. Demonstrate a broad understanding of the role of swaps in managing interest rate risks

  2. Evaluate the role of derivatives in market risk analytics and in strategic decision making

  3. Comprehend and analyse the role of stochastic modelling in derivative pricing

  4. Perform a detailed assessment of how to create hedging and speculating strategies depending on the risk preferences of the firm and economic climate

  5. Develop and evaluate option and swap strategies for specific market risk problems

Assessment Methods

Type Name Description Weight
EXAM Exam

1.5 hour end of semester examination worth 75% module weight

75
CLASS TEST Online test mid semester

1 hour online test worth 25% module weight

25

Teaching and Learning Strategy

Hours
Lecture

2-hour lecture per week, including some practical sessions within this time.

20
Private study

8-hours private study per week on average. This will involve revising lecture material, completing exercises, and textbook readings.

80

Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • 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.
  • Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
  • Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
  • Management - Able to utilise, coordinate and control resources (human, physical and/or financial)
  • 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

  • skills in recording and summarising transactions and other economic events; preparation of financial statements; analysis of the operations of business (for example, decision analysis, performance measurement and management control); financial analysis and projections (for example, analysis of financial ratios, discounted cash flow analysis, budgeting, financial risks)
  • knowledge of contemporary theories and empirical evidence concerning accounting in at least one of its contexts (for example, accounting and capital markets; accounting and the firm; accounting and the public sector; accounting and society; accounting and sustainability) and the ability to critically evaluate such theories and evidence age
  • knowledge of theories and empirical evidence concerning financial management, risk and the operation of capital markets (in cases of degrees with significant finance content).
  • Abstraction. From the study of economic principles and models, students see how one can abstract the essential features of complex systems and provide a useable framework for evaluation and assessment of the effects of policy or other exogenous events. Through this, the typical student will acquire proficiency in how to simplify while still retaining relevance. This is an approach that they can then apply in other contexts, thereby becoming more effective problem-solvers and decision-makers.
  • 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.
  • An appreciation of the nature of the contexts in which finance can be seen as operating, including knowledge of the institutional framework necessary for understanding the role, operation and function of markets and financial institutions (e.g. the economic, legal, regulatory and tax environment, both national and international; the firm; the capital markets and the public sector).
  • 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).
  • An understanding of the relationship between financial theory and empirical testing, and application of this knowledge to the appraisal of the empirical evidence in at least one major theoretical area. The appraisal should involve some recognition of the limitation and evolution of empirical tests and theory (eg the efficient markets hypothesis; anomalies; pricing of derivatives and other securities; bond portfolio management; exchange rates; raising capital and capital structure).
  • An understanding of the factors influencing the investment behaviour and opportunities of private individuals (bonds, equities, and derivatives; risk aversion; risk/return trade-offs; portfolio management and performance measurement; pensions and long term savings; the tax treatment of savings and investments; international diversification; forex risk; objectives of and constraints on institutional investors and advisors).
  • An understanding of financial service activity in the economy, and an appreciation of how finance theory and evidence can be employed to interpret these services (for example, information asymmetry, adverse selection and moral hazard could be employed to analyse the fundamental nature of services, such as insurance, pensions, bank lending and consumer credit, and also explore fundamental problems arising in such financial service provision. Efficient market hypothesis could be used to explore evidence for fund manager performance and the effectiveness of equity and bond saving services).
  • Problem solving and critical analysis: analysing facts and circumstances to determine the cause of a problem and identifying and selecting appropriate solutions.
  • Research: the ability to analyse and evaluate a range of business data, sources of information and appropriate methodologies, which includes the need for strong digital literacy, and to use that research for evidence-based decision-making.
  • Commercial acumen: based on an awareness of the key drivers for business success, causes of failure and the importance of providing customer satisfaction and building customer loyalty.
  • Innovation, creativity and enterprise: the ability to act entrepreneurially to generate, develop and communicate ideas, manage and exploit intellectual property, gain support, and deliver successful outcomes.
  • Numeracy: the use of quantitative skills to manipulate data, evaluate, estimate and model business problems, functions and phenomena.
  • Ability to work with people from a range of cultures.
  • Articulating and effectively explaining information.
  • Communication and listening including the ability to produce clear, structured business communications in a variety of media.
  • Conceptual and critical thinking, analysis, synthesis and evaluation.
  • Self-management: a readiness to accept responsibility and flexibility, to be resilient, self-starting and appropriately assertive, to plan, organise and manage time.
  • Self reflection: self-analysis and an awareness/sensitivity to diversity in terms of people and cultures. This includes a continuing appetite for development.

Resources

Talis Reading list

http://readinglists.bangor.ac.uk/modules/asb-3001.html

Reading list

Options, Futures, and Other Derivatives, John C. Hull. Ninth Edition, Global Edition, Pearson (2017).

Courses including this module