MTH305 Risk Management
Coursework instructions
6 November 2023
1 General Information
1. The coursework contributes 15% towards your final module grade.
2. The lab in weeks 4 and 7 is related to the coursework. Please study the labsolution
files, and the BBB recordings are available on Learning Mall.
3. In the coursework, you will work with a stock portfolio and assess its market risk.
(a) Suppose you were the manager of a portfolio of 30 stocks.
(b) It is now at the end of today 20231027.
(c) You are currently holding CNY100 in each stock.
(d) The aim is to assess the market risk of the stock portfolio for the next trading day by calculating the 99% one-day VaR of the portfolio.
(e) For all calculations, assume that the mean of stock returns is zero over a one-day horizon.
2 The data
1. The stock data is the daily closing price of stocks traded on Shanghai and Shenzhen
Stock Exchanges in the sample period from 20211027 to 20231027.
2. The data source is CSMAR. Imposing the constraint that there is stock price data
on each trading day we have obtained 4090 out of a total of 5475 stocks.
3. Each student is randomly assigned 30 stocks for the analysis.
4. The bond yield data is ChinaBond Government bond yields for maturities 3-month, 6-month, 1-year, 3-year, 5-year, 7-year, 10-year and 30-year in the same sample
period from 20211027 to 20231027, downloaded from the People’s Bank of China.
3 Data analysis
For the coursework, you should use MATLAB only, and please use the provided data file only. Open the template MATLAB file “MTH305 CW2.m” and follow the instructions
therein. Please do not change the name of variables. For how to install Matlab on your
own computer, see page 3 of week 1 lecture slides.
1. Import data and calculate stock and portfolio returns. [10 marks]
(a) Please do not change the order of the 30 stocks.
2. Calculate 5 measures of VaRs:
(a) historical simulation, equal weight [15 marks]
(b) historical simulation, exponential weight [10 marks]
(c) historical simulation, volatility scaling [20 marks]
. Let the module leader know if there is a warning when calling function
’EstMdl=estimate(Mdl,return portfolio);’
.
(d) variance-covariance approach, equal weight [10 marks]
(e) variance-covariance approach, EWMA [15 marks].
3. Calculate VaR via principal component analysis [20 marks].
Suppose you are following the research of Dr. Feeble, who finds that the value of stocks is sensitive to interest rate changes. Using his/her method, you have calculated that the change in your portfolio value (in CNY) due to 1 basis point change in 3-month, 6-month, 1-year, 3-year, 5-year, 7-year, 10-year and 30-year yields is 5, 10, 15, 20, 25, 30, 35, 40, respectively. Calculate the VaR of the portfolio
using the first two principal components of bond yields.
4 Submission
1. The submission deadline is Monday, 27 November, 9am.
2. Submit the following files (do not rename or zip files):
(a) MTH305 CW2.m that contains your work
(b) results.mat: the mat file that saves all the variables
(c) any other function files you have used (not MATLAB built-in functions).
3. Submit one PDF file of MATLAB code in Submission 2 (a) and (c) at Turnitin.
4. You can edit your submissions by clicking the button ”Edit submission”. Editing
submission after the deadline will be viewed as late submission.
5. Late submission will have a penalty of 5 marks per working day, up to a maximum
of five working days.
. Less than one working day will be counted as one working day.
. Work received more than five working days after the submission deadline will
receive a mark of zero.
6. Abnormal similarity of MATLAB code will be subjected to investigation as per the academic integrity policies, and in the worst case, resulting in zero mark and the disciplinary process.
7. Your marks are solely from answering the questions.
. Marking takes into account rounding errors.
. Error Carried Forward is employed in marking. For example, you will have the full mark for correctly calling the function ’VaR count’ even if your calculation
of input ’loss’ is wrong in previous steps.
. The quality of the code will not be marked.
8. Students who believe that their performance may have been impaired by illness or other exceptional circumstances should follow the procedures set out in the Univer-
sity’s ’Mitigating Circumstances Policy’ .
. Fill in the form ’Request for Extension of Coursework Submission Deadline’
(available on e-Bridge).
. The request must be made with documentary evidence to the Examinations
Officer as soon as possible, but no later than the original submission deadline.
. Also inform the module leader.