FINC3017-无代写-Assignment 1
时间:2023-08-22
Discipline of Finance
FINC3017 Investments and Portfolio Management S2-2023
Assignment 1
Due date: Monday 11th September 2023 before 11:59:59 pm
You are an investment analyst working for a large institutional fund manager. Your manager is interested
in studying low risk portfolios as they believe that, due to inefficiencies in financial markets, low risk invest-
ments can offer improved performance relative to the market portfolio. You have been tasked with studying
whether your managers position is accurate. To this end, you have been provided data related to a set
of 20 stocks as well as the level of the S&P 500 index and the risk-free return. You are to use this data
to construct and analyse the performance of several low risk portfolios. This will require two components
- a completed Excel template to store your numerical results and a written report that discusses your findings.
Data Description
You have been emailed four files containing the data on 20 US stocks, the S&P 500 index and risk-free rate.
You will need all this data for your analysis. The files with a title followed by your 8-digit SID (xxxxxxxxx)
are unique to each student and must be used by the corresponding student to complete this assignment. The
files you have are:
1. Price Data xxxxxxxx.csv: Prices for your assigned stocks.
2. Share Data xxxxxxxx.csv: Number of shares outstanding (in thousands) for your assigned stocks.
3. AdjFac Data xxxxxxxx.csv: Adjustment factor to account for corporate actions such a stock splits.
All values of the factor at 30-12-2022 are equal to 1. They may have changed in the past due to
corporate actions such as stock splits (or reverse splits). For example, Apple did a 4:1 split on 31-
8-2020. This means that if you owned 1 share in Apple prior to 31-8-2020, on 31-8-2020 it would
convert into 4 shares. The price would also fall by a factor of 4. This adjustment factor must be used
to compute the returns on your stocks to ensure that you do not attribute significant returns to a
corporate action that doesn’t affect shareholder value.
4. Mkt Data.csv: Index level of the S&P 500 index and the yield on a 1-month US Treasury Bill, converted
into a daily rate, that you will use as a proxy for the risk free rate. Note that the risk-free rate is
expressed in percentages so 5% would be 5, not 0.05.
The data provided covers a period from 3rd January 2017 to 30th December 2022 and is at the daily fre-
quency. You are to split this data into two sets. The first, covering the period from 3-1-2017 to 31-12-2021
will be used to compute portfolio weights while the remaining data, from 3-1-2022 to 30-12-2022, will be
used to examine the performance of your portfolios.
Template Requirements
On Canvas you will find an Excel file titled “FINC3017 Asmnt1 Template.xlsx” which is where you will
provide your numerical solutions. Your solutions must be provided as numerical values only (no formulas)
with a minimum of 8 decimal places of precision (more is fine). Compute solutions to the following questions
and place your answers in the template using the provided cell references provided as Sheet Name-[Top
Left Cell:Bottom Right Cell].
1. Compute the simple daily returns, expressed as decimals, for all 20 stocks in your portfolio and the
S&P 500 index for the period 3-1-2017 to 31-12-2021. These will be the returns used to generate your
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portfolio weights. Q1-[C2:W1259]
Hint: Do not use market capitalizations to correct for corporate actions. Market caps can change due
to share buybacks which we do not want to adjust for. You should use the price adjustment factors
provided to compute returns.
2. Using the returns computed in question 1, compute the average excess returns Q2,3,4,5,6,7,8-[B2:V2]
and the standard deviation of returns Q2,3,4,5,6,7,8,9-[B3:V3] for each of your 20 stocks and the
S&P 500 . Express your answers as annualized figures. Use these values to also compute annualized
Sharpe ratios for each stock and the S&P 500 Q2,3,4,5,6,7,8,9-[B4:V5].
3. Using the returns computed in question 1, compute the annualized sample covariance matrix for the
20 stocks under analysis. Q2,3,4,5,6,7,8-[B8:U27]
4. Using the returns computed in question 1 and the risk-free rates provided, compute the CAPM betas
for your 20 stocks. Q2,3,4,5,6,7,8-[B31:U31].
5. Using your answer to question 2, compute the allocation vector for the global minimum variance
portfolio assuming short sales are allowed. Call this portfolio P1. Q2,3,4,5,6,7,8,9-[B35:U35].
6. Using your answer to questions 2, compute the allocation vector for the global minimum variance
portfolio with the constraint that each asset must have at least 2% of the investors wealth allocated to
it. Call this portfolio P2. Q2,3,4,5,6,7,8,9-[B39:U39].
7. Using you answer to question 4, compute the portfolio with weights given by the inverse of their betas
and assuming short sales are allowed. Call this portfolio P3. Q2,3,4,5,6,7,8,9-[B43:U43].
8. Compute the market capitalization weighted portfolio of your 20 stocks using the market caps observed
on 31-12-2021. Call this portfolio P4. Q2,3,4,5,6,7,8,9-[B47:U47].
9. Assume that average returns computed in question 2 and covariance matrix computed in question 3 rep-
resent future expected excess returns and covariances. Compute the annualized expected excess return
and expected annualized standard deviation for P1, P2, P3 and P4. Q2,3,4,5,6,7,8,9-[B51:E52]
10. Assume now that you construct each of the portfolios, P1, P2, P3 and P4 at the market open on
3-1-2022. Each portfolio is constructed using the weights computed in questions 5, 6, 7 and 8 at
initiation and no further changes are made. Compute the series of realized returns on each of these
portfolios and the S&P 500 index. You may assume that you can purchase fractional units of each
stock. Q10-[C2:G251].
11. Using your answers to question 10, compute the annualized average excess return Q11-[B2:E2] and
annualized standard deviation of returns Q11-[B3:E3] for each portfolio that you expected to achieve
at initiation. Use these results to compute annualized Sharpe ratios for portfolios P1, P2, P3, P4 and
the S&P 500 index Q11-[B4:E4].
Report Requirements
With reference to your numerical results computed in the section above, you are to write a report of no more
than 2 pages and formatted with 1 inch margins, 11 point font and single spacing (tables and plots can use
smaller fonts if necessary) that addresses the following points.
1. Explain why it goes against standard economic principles to think that low risk portfolios generate
higher risk adjusted performance.
2. Provide an overview of the literature regarding the performance of low risk portfolios. This discussion
should proceed along several dimensions outlined in Chopra and Ziemba (1993), Frazzini and Pedersen
(2014) and Clarke et al. (2006). You may also cite other sources that provide evidence for/against low
risk portfolios.
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3. Discuss the broad industries that your allocated firms operate in and comment on how your allocation
may affect the ability to create low risk portfolios. Be sure to include a table that lists your allocated
stocks and their industry. You may wish to explore the Standard Industrial Classification (SIC) Codes
and the associated 10 major divisions.
4. Compare the performance of your portfolios to the expectations you had when constructing them. Do
the outcomes match the expectations? Why/why not?
5. Provide a comparison of the performance of your portfolios (P1, P2, P3, P4 and the S&P 500) to argue
whether you believe the evidence suggests improved performance can be obtained through lower risk.
You may use plots and tables to illustrate your discussion.
6. Provide a conclusion stating whether your results support your managers assertion regarding the per-
formance of low risk portfolios. Also outline any shortcomings associated with your research and future
directions that could address these concerns.
You are to write your report in a professional manner with a short executive summary and conclusion that
is based on your findings. You should not assume that your report is being read with your template and
hence should include any required figures you use to support arguments made in your report.
References
Chopra, V. K. and Ziemba, W. T. (1993). The effect of errors in means, variances, and covariances on
optimal portfolio choice. Journal of Portfolio Management, 19(2):6.
Clarke, R., de Silva, H., and Thorley, S. (2006). Minimum-variance portfolios in the U.S. equity market.
Journal of Portfolio Management, 33(1):10–24,4.
Frazzini, A. and Pedersen, L. H. (2014). Betting against beta. Journal of Financial Economics, 111(1):1–25.