1. Submission deadline: The assessment links will be accessible on Moodle from 10:00 AM,
18th January to 23:55 PM, 29 th January, Sydney Time.
2. Submission format:
• Please submit BOTH questionnaire and Excel work. If you only submit one of
them, you will not be able to receive any marks for this assessment. Both of these
links can be found in the Moodle section "Assessment - iLab: Data Exercise"
• Questionnaire: To submit your solutions for each question, please use the "Data
exercise Questionnaire" link. For successful submissions:
i. Please report your solutions as decimals (not percentages) exactly
following the example provided in the questionnaire.
ii. Only ONE attempt is allowed. So please prepare your solutions ready
before you start the questionnaire to avoid any technical issues.
iii. Your attempt will be submitted if and only if you click "Submit
questionnaire" . Please note that you cannot make any further changes and
resubmit the questionnaire after you click the submission button.
iv. All the questions should be attempted (i.e., no questions left blank).
• Excel: Please submit your Excel spreadsheet via the "Data exercise Excel
submission" link.
i. Your marks will be determined by your answers in the questionnaire rather
than the Excel file. However, the Excel file may be used/investigated by
grader if any clarification or checking of your solutions is required. The
Excel file does not require a specific format, as long as it is clear and easily
understandable. For clarity, you might consider creating separate sheets for
different questions and labeling them appropriately.
3. About enquiries: If you have questions regarding this assessment, please raise them on Moodle
discussion forum. However, please keep in mind that this assessment is one of the
individual assessments for this course (i.e., please treat it as a takehome exam) . Therefore,
only clarification-type questions (e.g., the ambiguity of the question) will be answered.
4. The total mark of this assessment is 54 . It accounts for 20% of the final mark for this course.
Gift mark for assigned group number.
Q1: what is your assigned group number which can be found on the first page of your
instruction file? (2 marks)
For Q1 to Q46: using the monthly data from 2014 Jan to 2018 Dec for the portfolio construction.
Please calculate the annualised average return and annualised variance of your assigned stocks and
S&P 500 index over the sample period (i.e., 2014 Jan to 2018 Dec), and check your basic summary
statistics with the solutions provided in the excel “Data pool” before you start solving the
questions. Your calculation of the basic summary statistics will not be marked but the
purpose of this step is to make sure you do not make naive mistakes (e.g., copy and paste
errors) at the very beginning of this assessment.
1. Markowitz optimization
• For the group of stocks assigned to you, form the minimum variance frontier. What is
the minimum attainable annualised standard deviation of the portfolio:
Q2: at an annualised average return level of 0% (1 mark)
Q3: at an annualised average return level of 15% (1 mark)
Q4: at an annualised average return level of 30% (1 mark)
• Calculate the portfolio weight for Global Minimum Variance Portfolio (GMVP). What is
GMVP portfolio weight? What is the annualised expected return and annualised standard
deviation of GMVP?
Q5: GMVP portfolio weight in STOCK 1 (1 mark)
Q6: GMVP portfolio weight in STOCK 2 (1 mark)
Q7: GMVP portfolio weight in STOCK 3 (1 mark)
Q8: GMVP portfolio weight in STOCK 4 (1 mark)
Q9: GMVP portfolio weight in STOCK 5 (1 mark)
Q10: GMVP annualised average return (1 mark)
Q11: GMVP annualised standard deviation (1 mark)
• Calculate the portfolio weight for the Optimal Risky Portfolio (P*). What is the P* portfolio
weight? What is the annualised expected return and annualised standard deviation of P*?
Q12: P* portfolio weight in STOCK 1 (1 mark)
Q13: P* portfolio weight in STOCK 2 (1 mark)
Q14: P* portfolio weight in STOCK 3 (1 mark)
Q15: P* portfolio weight in STOCK 4 (1 mark)
Q16: P* portfolio weight in STOCK 5 (1 mark)
Q17: P* annualised expected return (1 mark)
Q18: P* annualised standard deviation (1 mark)
• Suppose your utility function is 𝑼𝑼 = 𝑬𝑬(𝒓𝒓) − 𝟑𝟑𝝈𝝈 𝟐𝟐 . Form an optimal complete portfolio by
combining P* with the risk-free asset. What is the portfolio weight on each of individual asset
in this optimal complete portfolio? What is the max utility score that you can achieve?
Q19: complete portfolio weight in STOCK 1 (1 mark)
Q20: complete portfolio weight in STOCK 2 (1 mark)
Q21: complete portfolio weight in STOCK 3 (1 mark)
Q22: complete portfolio weight in STOCK 4 (1 mark)
Q23: complete portfolio weight in STOCK 5 (1 mark)
Q24: complete portfolio weight in Risk-free asset (1 mark)
Q25: Utility score is? (1 mark)
2. Short Selling Constraint
• Construct the GMVP and P* with the short selling constraint:
Q26: GMVP(with short selling constraint) annualised average return (1 mark)
Q27: GMVP(with short selling constraint) annualised standard deviation (1 mark)
Q28: P*(with short selling constraint) annualised average return (1 mark)
Q29: P*(with short selling constraint) annualised standard deviation (1 mark)
Q30: Compare the GMVP that you construct without and with short-selling constraints. Make
comments on their performance and explain why short selling constraints may affect the
optimization procedure (3 marks)
Q31: Compare the P* that you construct without and with short-selling constraints. Make
comments on their performance and explain why short selling constraints may affect the
optimization procedure (3 marks)
