I’m working on a risk management writing question and need an explanation to help me understand better.Please note that ANSWER HAS BEEN FINISHED, what I need is some supplement of chart or diagram of the data to QUESTION 3 ONLY, I will provide the answers and you need to provide chart or diagram of the data to explain the data.FIN41360: Portfolio and Risk Management

Assignment 1

(Please read all instructions and notes very carefully)

Portfolio Choice and Performance Attribution

January 21, 2021

Required tasks:

1. Familiarize yourself with the content of the data library on Professor Kenneth French’s

webpage by reading the online legends and help. The web address of the data library is the

following:

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html

2. Then, select data from January 1963 to December 2020 on the 17 industry portfolios and

carry out the following analysis:

a. Sketch the monthly MV efficient frontier of these portfolios using first the sample

estimates of the required means and variance-covariance matrix and subsequently

their Bayes-Stein counterparts, first by shrinking only the mean and then shrinking

both the mean and the variance-covariance matrix.

b. On the frontiers you constructed, highlight the points corresponding to the global

minimum variance portfolio and to the tangency portfolio, assuming a risk-free rate

equal to its average over the sample period. For these portfolios, also compute and

report the mean excess-return, volatility and Sharpe ratio.

c. Compare and contrast the three frontiers you constructed (the frontier based on

sample estimates and the two based on their Bayes-Stein counterparts). How would

you explain their differences?

3. Next, choose one stock from each of the 17 industries and repeat the analysis above.

Compare and contrast the two pairs of MV efficient frontiers you constructed, first when

using sample estimates and then when using their Bayes-Stein counterparts. How would

you explain their differences?

4. Select data for the appropriate sample period on the risk-free rate (included among the socalled “Fama and French factors”, and available for download from the same data library)

and sketch the monthly MV efficient frontier for the 17 industry portfolios and the riskfree asset, using sample estimates of the required means and variance-covariance matrix.

Page 1 of 5

Compare and contrast this frontier to the ones previously constructed, after having

explained the sample period for which you obtained data on the risk-free rate.

5. Repeat the analysis required in the item just above (i.e., in question 4) using the Fama and

French factor-mimicking portfolios, also available from the webpage of Prof Kenneth

French, in place of the industry portfolios. Do so first using the so called “Fama/French 3

Factors” and then the “Fama/French 5 Factors (2×3)” mimicking portfolios (See Fama and

French, 1993, ”Common Risk Factors in the Returns on Stocks and Bonds,” Journal of

Financial Economics, and Fama and French, 2014, “A Five-Factor Asset Pricing Model”

for a complete description of the factor returns). Compare the resulting efficient frontiers

to the ones previously obtained. How would you explain their differences?

6. Repeat the above analysis (as specified in the item just above, namely question 5) using

suitable “practical proxies” for the Fama and French factor-mimicking portfolios in place

of the Fama and French factor-mimicking portfolios themselves. These practical proxies

should be highly investable, keeping transaction and execution costs in mind. That is, they

should be investable by the average portfolio manager, not necessarily the highly

sophisticated portfolio manager capable of replicating the actual factor-mimicking

portfolios. You may look for such proxy portfolios by checking out the websites of the

main futures exchanges (e.g., look for futures on small caps, such as the Russell 2000 Index

mini futures, and value/growth stocks) or even look for suitably focused ETFs (exchange

traded funds).1 In particular, try and find ways to work around the difficulty of short-selling

or minimize the associated costs. For ideas, check out this web-article:

http://money.usnews.com/investing/articles/2016-06-07/why-investors-should-considersmall-cap-stocks

Do so at least for “practical proxies” for the “Fama/French 3 Factors” and, ideally, also for

the “Fama/French 5 Factors (2×3)” mimicking portfolios, for as long a sample period for

which you can find data, making sure that the last observation is for December 2019 or

later (i.e., do not work with ‘dead’ series). To work around the lack of long time series on

suitable “practical proxies” (e.g., the Russell 2000 Index mini futures), you may use the

time series on a closely correlated asset or portfolio (e.g., the stock index underlying the

Russell 2000 Index mini futures, available since 1978), possibly after showing some

evidence on the strength of the correlation.

Compare and contrast the resulting efficient frontiers for the “practical proxies” to the ones

for the corresponding factor mimicking portfolios (make sure both frontiers are estimated

using the same sample period), explaining and/or commenting as appropriate.

7. Re-estimate the monthly frontiers for the 17 industry portfolios and for the “Fama/French

3 Factors (2×3)” mimicking portfolios over two contiguous time periods of equal length,

one ending in December 1991 and the other one ending in December 2020,

including the risk-free asset in the investment opportunity set. Pick at least one portfolio

See, for example, the approach adopted by Faff (2003) [Faff, R.W., 2003, “Creating Fama and French Factors with

Style”. Financial Review 38(2), 311-322].

1

Page 2 of 5

from each of the frontiers estimated in the first period and, for the portfolios thus selected,

compare the performance during this period to the performance during the second period.

Do these portfolios remain on the efficient frontier out-of-sample? Conduct the comparison

using the ‘all-time classic’ Jobson and Korkie (1981) test for the equality of the Sharpe

ratios (the test statistic is defined in footnote 20, page 271 of the Jorion (1985) article) as

well as the more modern test that does not require either the i.i.d. assumption or normality

(check out the article by Ledoit and Wolf (2008) and the accompanying Matlab code

available in the Brightspace page of the course).

8. Then, for at least some of the assets previously considered, repeat the above analysis

subject to any constraint and/or by applying any method, approach or technique (e.g.,

adding assets to better exploit the benefits of diversification, relying on the global

minimum variance portfolio, resampling, etc.) that you believe might be of interest and

might offer valuable insight from an investment management point of view.

9. Use the market portfolio, the practical proxies and the tangency portfolios (as appropriate)

on the various efficient frontiers you constructed above to assess the performance of tree

mutual funds of your choice, commenting on the results. A good source of data on mutual

funds is Yahoo Finance. Please see the Appendix for help on how to access data on Yahoo

Finance.

Provide a soft copy report containing your findings, which should be appropriately tabulated so

as to maximize their legibility, any required evaluation and discussion of your findings and,

when appropriate, a description of the methodology adopted. The report should be submitted

via the submission folder on Brightspace by 22nd February 2021 (midnight). The submitted

report should be attached to the appropriate submission form, which should closely

adhere to the template provided in Brightspace and clearly provide all information

required therein, including the assignment number, the team number, the name and student

number of each team member and details on their individual contribution.2

The maximum length of the report should be 3000 words, including tables and figures (and

everything else). Do not neglect to cite references as appropriate (of course, the bibliography

is included in the word count). To stay within the word count, it will be important to organize

your report appropriately (e.g., making appropriate use of tables, avoiding repetitions, etc.).

Workings by way of MS Excel spreadsheets or Matlab code and data should be e-mailed to

my e-mail address: emmanuel.eyiah-donkor@ucd.ie. Although grades are solely based on

your report, the workings are required to verify all calculations. In the email title, you should

indicate FIN41360: Assignment 1, followed by the team number in brackets.3

The due date and weighting on the overall module grade of this assignment are as specified in

the course outline.

2

Please note that this is a requirement and, if not fulfilled, I will not accept the submission, applying any relevant late

submission penalty until a proper submission is made.

3

Please note that this is a requirement and, if not fulfilled, I will not accept the submission, applying any relevant late

submission penalty until a proper submission is made.

Page 3 of 5

Notes:

•

The required tasks in the above list are, to a large extent, in a sequential order, in the sense that

the initial ones are necessary for the subsequent ones. Hence, if you run out of time, it is better

to carry out the earlier ones to the best of your ability rather than trying to do everything to a

lesser standard.

•

Clarity is of paramount importance and lack thereof will be penalized heavily. Essentially, as

in real world endeavors, unclear answers and discussion will amount to not having provided

the required answer/discussion. Hence, try and privilege clarity and quality over quantity. For

example, if you are running out if time, it is better to address well a few questions than to

attempt to address them all in a poor and, hence, necessarily obscure manner.

•

All the relevant information for the assignment is provided in this document and the course

outline. If an aspect of the analysis is not specified in either document, it means that it is left

for students to make a choice on it, in light of the theory covered in the course.

•

Students are required to make and motivate any such choice relying on the insight offered by

the theory covered in the course and relevant references. The soundness of such choices,

evaluated in the light of available theory and empirical evidence, will be assessed and

contribute to the overall mark. The more advanced aspects of the assignment also require a

certain amount of autonomous research, which will play an especially important role in the

assignment of higher marks.

•

Submissions should contain, as appropriate, a literature review. The latter should strive to offer

a comprehensive and systematic, yet succinct, review and discussion of academic and

practitioners contributions to the body of knowledge on issues and topics examined during the

course that are relevant to address the issues at hand, with the aim to expand and offer

additional substantial insight compared to the insight and level of knowledge developed by the

course material (including lectures).

•

In this regard, keep in mind that the assignment is designed so that only a small fraction of the

teams will be able to address all questions well, because marking practice in serious

Universities (such as UCD, which has this enshrined in official marking rules) dictate that the

highest marks be awarded with parsimony.

•

In preparing the report, try and replicate as closely as possible the layout and structure (though

subject to the applicable maximum length restriction) of academic papers that evaluate the

performance of alternative portfolio construction methodologies. A good yet nice and readable

example is the article by Stevenson (2002) titled “Ex-Ante and Ex-Post Performance of

Optimal REIT Portfolios” (among the readings in Brightspace). You might also take heed from

industry reports that do something similar, which often have nice and witty ways of making

insightful points, though strive to aim at a level of clarity and rigor comparable to the academic

papers. The paper by Rob Arnott of Research Affiliates (titled “How Can Smart Beta Go

Horribly Wrong”) is a good example of clear and compelling industry report:

https://www.researchaffiliates.com/en_us/publications/articles/442_how_can_smart_beta_go_horribl

y_wrong.html

Page 4 of 5

Please keep in mind however that, if you lack the insight of an industry maverick (that comes

with many years of first-hand experience), the academic format might be a safer option as it is

designed to facilitate making a point in an effective way relying only on research, without

needing any special experience of the subject matter. An academic researcher gains insight

from research, not necessarily experience, so it is a situation closer to the one of a typical

student.

•

Appropriate use of tables and figures, as in academic papers and rigorous industry reports, is

of crucial importance to attain the required clarity. They should be thoughtfully designed to

maximize clarity and impact. For example, annotate your tables and figures to help the reader

gain an immediate understanding of the findings reported therein. Also, try and condense your

findings in as few tables and figures as possible, to help the reader see the overall picture

emerging from your study.

•

Mutatis mutandis (i.e., with the appropriate adaptation) and unless otherwise specified, all the

above notes apply to subsequent assignments too.

•

Teams are strongly encouraged to appoint an “editor” whose job should be to coordinate the

efforts of the team and make sure that the final report is coherent and well organized.

Appendix – Accessing data in Yahoo Finance

On Yahoo Finance, find two ETFs (Exchange Traded Funds) that have been listed for at least a year and

download the time series of closing prices for the last 251 trading days (if any one of the ETFs does not

trade on a given trading day, assume that the closing price is the same as for the previous trading day).

To get this data, you need to go to https://finance.yahoo.com. Then, under the “My Screeners” tab, select

the “Mutual Fund Screener” tab and, when the “Mutual Fund Screener” dialog box opens, add or remove

filters according to your own preference. When you are done, press “Find Mutual Funds”. A selection of

Mutual Funds will be shown. Choose the ones you want by clicking on the symbol of each. In the screen

that opens when you click each Mutual Fund symbol, select the “Historical Data” tab and, in the screen that

opens next, select the “Daily” frequency (from the dedicated drop-down menu) and then click “Download

Data”.

Page 5 of 5

Portfolio and Risk Management

Student’s Name:

Institutional affiliations:

Date:

Question 3:

An efficient Frontier is a set of optimal portfolios that provides the best returns in a given

level of risks or have the lowest chances in a defined group of expected returns. In industry 17,

the weighted average returns of clothes and mines are used to discuss the efficient frontiers for

sector 21.

Average weighted returns

Clothes

Mines

17.21

11.74

The variance level is directly proportional to the risk level, where high variance indicates a high

level of risks and low friction shows a low-risk group.

Portfolio variance = W12Q12+W22Q22+ 2w1w2Cov1, 2

The correlation of Clothes Is 0.17, and the correlation of mines is 0.12

= (17.212 *0.172) + (11.742 *0.122) + (0.17*0.12 17.21*11.24)

= (296.18* 0.0289) =0.8559602

= (137.83* 0.0144) = 1.984752

= (0.17*0.12) = 0.0204

= (17.21*11.24) = 193.4404

(0.0204 193.4404) = 1.055

0.8559602+ 1.984752+1.055= 3.8957122

Average weighted returns

Durable

Cnstr

11.49

10.52

Portfolio variance = W12Q12+W22Q22+ 2w1w2Cov1, 2

(11.492 *0.112) + (10.522 *0.112) + (0.11*0.11 11.49*10.52)

= (132.0202* 0.0121) =1.59744

= 110.6704* 0.0121= 1.33911184

0.0121 120.8748 =1.001

=1.59744+ 1.33911184+1.001= 3.93755184

The two pairs are different where the first was 3.8957122, and the second one was

3.93755184. The second pair has higher efficient frontiers showing that the first has lower

chances of risks. The second production mix has a higher level of risk and lower returns.

According to Kalygin (2020), the producer may consider the first pair due to the lower risk rate.

Risk management is an important aspect to determine the product mix with lower rates of risks.

The difference in the results is also due to the differences in the average value-weighted returns.

The first pair has a higher average value-weighted return than the second one and thus the

differences in efficient frontiers.

Question 4:

The two frontiers are different due to the differences in the various aspects of the

production mix. The risk-free rate is where the investor can operate and runs the project risk-free

over a specified period. In this period, the risk management strategies are of no need, and thus

the operation runs smoothly. Kalygin (2020) affirmed that the investor expects to earn on

investments with zero risks during this period. The return rate where the returns of a

hypothetical investment meet a fixed period’s payments and all payment obligations are covered.

The free, risk-free rate results impact the optimal portfolio in the real aspects, not only the

assumption. The theory of risk-free is unrealistic, and thus it is criticized as compared to the

efficient frontier, which is considered more realistic. Risk-free trade eliminates unsystematic or

specific risk, unlike the effective frontier, which does not stop these risks (Bauder, 2019). The

disadvantage of risk-free trade is that it leads to vitality, unlike the latter and thus not considered.

It also negatively impacts the return on the market. It may also lead to the backward presentation

of the returns and, therefore, may not be preventable in the future market returns.

Question 5:

Factor mimicking portfolio is a list of assets designed to stand in place of the background

factors. It is the replication of the stock to produce the same in an equal period. It is an important

aspect used as an exchange-traded fund that serves as proxies for global factors. The firm’s size

is also a cause of the disparity between the two variables (Bauder, 2019). The other aspect is the

value premium and excess returns on the market. Profitability and investment is also a

mimicking tool. The profitability of a project and a successful investment can be used to decide

what investment to replicate. Large firms’ portfolios have a high average return than the small

firms and thus the difference in the different aspects. The significant size factor is also defined

as small minus big. The difference in size influences portfolio returns since the amount of risk is

relative to the market (Das, 2011). The differences are in a stock’s total return, the risk-free

return rate of the two projects, absolute market portfolio differences, and size and value

premium. Coefficient factors, momentum, and quality are also other differences in the two

aspects.

Question 6:

Useful proxies are the art of statistical and portfolio modeling. It is a comparison of the

performance of the stock in the market and that of the market. Also, the theoretical perceptive

and presentation of the price movements of all market sectors. The larger market size and

complexity influences the practical proxies of the portfolio modeling. The pricing model strategy

ensures that the investment provides more returns and increases the project; pricing restriction is

excellent, primarily with an observable risk-free rate (Das, 2011). This mode holds all security

returns, including the proxy returns and the structural relationship between the security and

proxy returns. The model also confirms the number of replication a stock can take to make a

profit and ensure the profitability of the organization’s investment. These techniques save cost

and provide even though the project’s organization is small; it matches their target indices ad thus

a practical method to compare the index returns accounting effort the transaction costs as

affirmed by Kalygin (2020). This proxy matches the dimensions of the relevant risk, and with

accuracy, the analysis results are of perfection and thus profitability of the organization. It also

ensures systemic reduction of risks and therefore sufficiently matches the industry’s dynamics

providing credit qualities and prevents domination of non-systemic risks.

References

Kalygin, V. A., & Slashchinin, S. V. (2020, May). Uncertainty of Efficient Frontier in Portfolio

Optimization. In International Conference on Learning and Intelligent Optimization (pp.

371-376). Springer, Cham.

Bauder, D., Bodnar, R., Bodnar, T., & Schmid, W. (2019). Bayesian estimation of the efficient

frontier. Scandinavian Journal of Statistics, 46(3), 802-830.

Das, S., Markowitz, H., Scheid, J., & Statman, M. (2011). Portfolios for Investors Who Want to

Reach TheirGoals While Staying on the Mean-Variance Efficient Frontier. The Journal

of Wealth Management, 14(2), 25-31.

Portfolio and Risk Management Outline

1.1 Question 3

1.2 Question 4

1.3 Question 5

1.4 Question 6

1.5 References

Purchase answer to see full

attachment

#### Why Choose Us

- 100% non-plagiarized Papers
- 24/7 /365 Service Available
- Affordable Prices
- Any Paper, Urgency, and Subject
- Will complete your papers in 6 hours
- On-time Delivery
- Money-back and Privacy guarantees
- Unlimited Amendments upon request
- Satisfaction guarantee

#### How it Works

- Click on the “Place Order” tab at the top menu or “Order Now” icon at the bottom and a new page will appear with an order form to be filled.
- Fill in your paper’s requirements in the "
**PAPER DETAILS**" section. - Fill in your paper’s academic level, deadline, and the required number of pages from the drop-down menus.
- Click “
**CREATE ACCOUNT & SIGN IN**” to enter your registration details and get an account with us for record-keeping and then, click on “PROCEED TO CHECKOUT” at the bottom of the page. - From there, the payment sections will show, follow the guided payment process and your order will be available for our writing team to work on it.