Instructions on Assessment
This assignment accounts for 80% of the overall mark for the module. You must attempt all the parts to meet the learning outcomes.
• Length maximum of 3000 words (with a tolerance level of 10%), which must be stated at the cover page of the assignment.
• Quotations of more than 2 lines must be indented and in italics with the reference and page number stated. Shorter quotations should be in italics but do not need to be indented.
• Tables and diagrams should be inserted at an appropriate point in the text and should be easily readable.
• All the results, their interpretation and discussion should be provided in a single MS Word document.
Programme: BA (Hons) Finance and Investment Management
BA (Hons) International Banking and Finance (Top-up)
BA (Hons) Business and Finance (Top-up)
Module Code: AF6003 and LD6008
Module Title: Banking Risk 1
Submission Time and Date: 10th January 2023
Word Limit: 3,000 words
Weighting This assignment accounts for 80% of the total mark for this module
Submission of Assessment Electronic Management of Assessment (EMA): Please note that your assignment is submitted electronically online via Turnitin by the given deadline. You will find a Turnitin link on the module’s ELP site.
It is your responsibility to ensure that your assignment arrives before the submission deadline stated above. See the University policy on late submission of work.
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A. Market Risk
In this section of your report, you are required to explain your understanding of VaR techniques and their application to banking risk management. You are therefore required to critically discuss market risk measurement using Value at Risk techniques and discuss the new developments, displaying your awareness of the methods and limitations by presenting clearly how you derived your results. Your portfolio should consist of at least five real-world assets, and the length of your sample period should be no longer than five years and must end before 31st December 2022. Please note that your answer should not just be an illustration of the methods, you should aim to provide interpretations and comparisons capturing your data and the latest published research.
(1,200 words, 40 Marks)
B. Credit Risk You are required to analyse a portfolio of loans consisting of companies of your choice with characteristics shown in the table below. For example, if you choose company 1 to be Microsoft, it will have a maturity of 10 years, a repayment value of 20 million and an annual interest rate of 7%. All computations must be carried out according to such characteristics.
Loan Company Name Maturity Repayment Value at Maturity $m
Annual Interest
1 Company 1 10 20 7%
2 Company 2 5 15 3%
In your report, you should clearly state the composition of your portfolio (i.e., fill in the table above with the names of two real-world companies).
Assume that both loans are senior unsecured debt denominated in US dollars and that the analysis was conducted on 30th October 2022. The loan will be repaid at the maturity date. Clearly state any assumptions you make in your estimations. Provide clear illustrations of how you have derived your results, supported by a clear explanation of each step.
1. Derive loan value distribution using CreditMetrics (full implementation) and compute relative VaR and Expected Shortfall with Monte-Carlo simulation for the loan portfolio above at time horizons of 1-year and 2-year periods and the confidence interval of 99%. Interpret the output from a risk management and regulatory point of view, supporting your claims with relevant literature.
(1200 words, 40 marks)
2. Calculate the Expected Default Frequency (EDF) for both loans using KMV. Compute the future prices of loans and portfolio risk in the default and no-default scenarios at time horizons of 1-year and 2-year periods. Interpret the output and compare results with those obtained using CreditMetrics in part 1. Explain any differences observed supporting your discussion with relevant literature.
(600 words, 20 Marks)
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Mapping to Programme Goals and Objectives Programme (Level) Learning Outcomes that this module contributes to: Knowledge & Understanding:
• Assess knowledge of contemporary professional practice in business and management informed by theory and research. [LO1.1]
• Appraise knowledge of business and management to complex problems in professional practice in order to identify justifiable, sustainable and responsible solutions [LO 1.2]
Intellectual / Professional skills & abilities:
• Critique creative and critical thinking skills that involve independence, understanding, justification and the ability to challenge the thinking of self and others [LO 2.2.]
Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
• Critique their personal skills and attitudes for progression to post-graduate contexts, including professional work, entrepreneurship and higher-level study [LO 3.2]
Module Specific Assessment Criteria Knowledge & Understanding:
• Develop knowledge and understanding of international banking regulation, credit, and market risks. [MLO1]
• Critically evaluate the measurement models and the management issues in the context of the regulatory requirements within the banking and finance sector. [MLO2]
Intellectual / Professional skills & abilities:
• You will develop quantitative as well as qualitative skills while measuring and managing the credit and market risks. [MLO3]
Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
• You will be made aware of the risk facing international financial markets and how you can equip management with the knowledge and expertise to implement stronger organisational controls to address these risks. [MLO4]
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Module Specific Marking Criteria
0 – 29% 30 – 39% 40 – 49% 50 – 59% 60 – 69% 70 – 79% 80 – 90% 90 – 100%
Part A:
Market Risk
Very weak, research and understanding of the VaR analysis and little attempt to provide an example.
Insufficient research and understanding of the VaR analysis. The use of real- world asset class is incorrect or incomplete.
Reasonable research and understanding of the VaR analysis with an attempt to illustrate real-world numerical examples. A reasonable understanding of new developments
Good research and understanding of the VaR analysis by using real-world asset class. Good knowledge of new developments and good related examples. Good understanding of new developments
Very Good research and understanding of the VaR analysis by using real-world asset class. Very good knowledge of new developments and very good, related examples. Very Good understanding of new developments
Excellent research and understanding of the VaR analysis by using real-world asset class. Excellent knowledge of new developments and excellent related examples. Excellent understanding of new developments
Outstanding research and understanding of the VaR analysis by using real-world asset class. Outstanding knowledge of new developments and Outstanding related examples. Outstanding understanding of new developments
Exemplary, sophisticated, and highly detailed research and understanding of the VaR analysis by using real-world asset class. Exemplary knowledge of new developments and Outstanding related examples. Outstanding understanding of new developments
Part B:
Credit Risk
Very poor research and understanding of the CreditMetrics and KMV risk measurement approach, evidence of calculations, and understanding of results. Very poor interpretation of output from risk management and regulatory perspective.
Insufficient research and understanding of the CreditMetrics and KMV risk measurement approach, evidence of calculations, and understanding of results. Insufficient interpretation of output from risk management and regulatory perspective.
Reasonable research and understanding of the CreditMetrics and KMV risk measurement approach, evidence of calculations, and understanding of results. A reasonable interpretation of output from a risk management and regulatory perspective.
Good research and understanding of the CreditMetrics and KMV risk measurement approach, evidence of calculations, and understanding of results. Good interpretation of output from risk management and regulatory perspective.
Very Good research and understanding of the CreditMetrics and KMV risk measurement approach, evidence of calculations, and understanding of results. Very good interpretation of output from risk management and regulatory perspective.
Excellent research and understanding the CreditMetrics and KMV risk measurement approach, evidence of calculations, and understanding of results. Excellent interpretation of output from risk management and regulatory perspective.
Outstanding research and understanding of the CreditMetrics and KMV risk measurement approach, evidence of calculations, and understanding of results. An outstanding interpretation of output from a risk management and regulatory perspective.
Exemplary, sophisticated and highly detailed research and understanding of the CreditMetrics and KMV risk measurement approach, evidence of calculations, and understanding of results. Exemplary interpretation of output from risk management and regulatory perspective.
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Assessment Regulations Please read the guidance for students regarding assessment policies. They are available online here. Late submission of work After the published hand-in deadline, the following penalties will apply where coursework is submitted without approval. For presentations submitted up to 1 working day (24 hours) after the published hand-
in deadline without approval, 10% of the total marks available for the assessment
(i.e.100%) shall be deducted from the assessment mark.
Presentation slides submitted more than one working day (24 hours) after the published hand-in deadline without approval will be regarded as not having been completed. A zero mark will be awarded for the assessment. These provisions apply to all assessments, including those assessed on a Pass/Fail basis. The full policy can be found here. Word limits and penalties No penalty will apply if the assignment is within +10% of the stated word limit. The word count should be declared on your assignment’s front page and cover sheet. The word count does not include appendices, glossaries, footnotes, tables, figures, and charts. Please note that in-text citations [e.g. (Smith, 2011)] and direct secondary quotations [e.g., “dib-dab nonsense analysis” (Smith, 2011 p.123)] are INCLUDED in the word count. The full policy is available here. Academic Misconduct The Assessment Regulations for Taught Awards (ARTA) contain the Regulations and procedures for cheating, plagiarism, and other forms of academic misconduct. The full policy is available here. You are reminded that plagiarism, collusion, and other forms of academic misconduct,
as referred to in the Academic Misconduct procedure of the assessment regulations,
are taken very seriously. Assignments in which evidence of plagiarism or other forms
of academic misconduct is found may receive a mark of zero.