{"id":580,"date":"2015-09-15T16:03:13","date_gmt":"2015-09-15T06:03:13","guid":{"rendered":"http:\/\/casestudyhelp.com\/sample-questions\/?p=580"},"modified":"2018-01-29T17:58:39","modified_gmt":"2018-01-29T06:58:39","slug":"investment-analysis-assignment-help","status":"publish","type":"post","link":"https:\/\/casestudyhelp.com\/sample-questions\/investment-analysis-assignment-help\/","title":{"rendered":"Investment Analysis Assignment Help"},"content":{"rendered":"

25503 Investment Analysis<\/strong><\/p>\n

In this assignment you will implement an investment strategy (along with other tasks) based
\non mean-variance portfolio theory. In order to help you do this you will \fnd an Excel
\nworkbook called AssignmentData.xlsx on UTS Online. It contains weekly index data for
\nve asset classes and one individual asset (Gold).
\n1
\nDue to the reputation of UTS for producing work-ready graduates, you are head-hunted by
\na small asset management company to work part-time as a portfolio manager whilst you
\ncomplete your degree. After learning all about mean-variance analysis and e\u000ecient asset
\nallocation in 25503 Investment Analysis you are hoping to employ some of the tools you
\nhave learned in constructing your very \frst portfolio.
\nIt is your \frst day on the job and your boss is keen to see how much you really know.
\nShe provides you with a list of six asset classes and tasks you to investigate the e\u000ecient as-
\nset allocation between these asset classes. Moreover, you are asked to maximise the expected
\nutility of a client, which is measured by \u0016p 1
\n2a\u001b2
\np, where the level of risk aversion a = 5.
\nTo get started you decide to collect historical performance data for the last \fve years in
\norder to estimate the expected return and variance-covariance structure of the asset classes
\n(the data in the Excel \fle).
\nTo perform the asset allocation you decide to use the mean-variance portfolio theory you
\nlearnt in in 25503 Investment Analysis. After all, what can go wrong? Harry Markowitz won
\na Nobel prize for this stu\u000b! However, it has been a whole year since you completed the sub-
\nject, so naturally you feel a bit rusty. You recall the lecturer mentioning about e\u000ecient and
\nine\u000ecient assets, and that rational investors should never choose to invest in any ine\u000ecient
\nassets. So, \frst you decide to \fnd out which of the six assets are e\u000ecient and which are
\nine\u000ecient, then construct a portfolio of the e\u000ecient assets. In order to do that, you should
\ncopy the assignment data into an Excel workbook and perform the following tasks:
\n1. (a) Transform the index values into continuously-compounded weekly returns (you do
\nnot need to report these in your submission).
\n(b) Using the resulting returns data, estimate (and report) the vector of expected
\nreturns for the six assets, as well as the variance-covariance matrix of these returns.
\nThese expected returns etc. should be annualized (i.e. in annual units).
\n(c) Report which of the assets are e\u000ecient and which are ine\u000ecient. For each of the
\nine\u000ecient assets, \fnd another asset that dominate it. If the client was to invest
\n100% of her wealth into one of the e\u000ecient assets, which one should she choose?
\n(d) Choose two of the e\u000ecient assets, construct and plot the combination line between
\nthem (with short sales allowed) for expected (annual) returns ranging between 0%
\nand 20%. Your \fgure should also indicate the positions of the six assets.
\n(e) Identify the minimum variance portfolio (MVP), i.e. report the portfolio weights
\n(in the two e\u000ecient assets), expected return, and standard deviation of the MVP.
\n(f) Based on the client’s utility function, what is her optimal portfolio? i.e. report the
\nportfolio weights, expected return and standard deviation of her optimal portfolio.
\nYou are eager to impress so you send the results to your new boss just before you leave for
\nyour lunch break. Upon your return, the boss has looked at your report and notes that the
\n2
\nrisk of the portfolio is a little higher than she expected and wondered if adding additional
\nassets would help reduce the risk. Of course! You suddenly remember that the ine\u000ecient
\nassets can still be useful if we include them in a portfolio, that is what mean-variance portfolio
\ntheory and diversi\fcation is all about! You quickly run back to your desk and perform the
\nfollowing tasks:
\n2. (a) Using the vector of expected returns and variance-covariance matrix computed in
\nQuestion 1(a), compute and report the A, B, C and \u0001 parameters.
\n(b) Identify the global minimum variance portfolio (GMVP), i.e. report the portfolio
\nweights (in the six assets), expected return, and standard deviation of the GMVP.
\nCompared to the MVP in Question 1(e), are there any improvements?
\n(c) Determine and report the portfolio weights and standard deviations for two min-
\nimum variance portfolios (MVPs), P1 and P2, which have the same expected
\nreturns as the two e\u000ecient assets in Question 1(d). What are reductions in stan-
\ndard deviations?
\n(d) Construct and plot the combination line between P1 and P2 (with short sales
\nallowed) for expected (annual) returns ranging between 0% and 20% (note that
\nthis is also the MVS with short sales allowed). You should also plot the combina-
\ntion line between the two e\u000ecient assets from Question 1(d) for comparison, also
\nindicate the positions of the six assets and the two MVPs.
\n(e) Now based on the client’s utility function, what is her optimal portfolio (i.e.
\nportfolio weights in the two MVPs, expected return and standard deviation)?
\nCompare to the answer in Question 1(f), is she now better o\u000b? Report the
\nincrease in her expected utility.
\nYou inform your boss of these \fndings and she is happy with the reduction in risks and
\nthe improvement in the client’s expected utility. However, she informs you that the 10%
\nreturning portfolio you have constructed is not as `e\u000ecient’ as it might be as you have
\nforgotten all about the risk-free asset… oops! You quickly do some research and determine
\nthat the appropriate risk-free rate to use is 3% per annum. Perform the following tasks to
\nadjust your portfolio weights:
\n3. (a) Using the A, B, C and \u0001 parameters in Question 2(a), compute the expected
\nreturn and standard deviation of the tang ency portfolio.
\n(b) Using the Two Fund Theorem, determine the proportions that need to invested
\nin P1 and P2 to form the tangency portfolio.
\n(c) Construct and plot the MVS (with short sales allowed) for the six assets the risk-
\nfree bond paying 3%. Furthermore, plot the combination line between P1 and P2
\nfrom Question 2(c) on the same set of axes, also indicate the positions of the six
\nassets, two MVPs and the tangency portfolio.<\/p>\n

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3
\n(d) Determine and report the new optimal portfolio for the client, i.e. the portfolio
\nweights in the risk-free bond and the tang ency portfolio, expected return and stan-
\ndard deviation. Compare to Question 2(e), what is the increase in her expected
\nutility?
\nA little embarrassed from your mistake of not including the risk-free asset, you send the new
\nupdated results to your boss at 4:50pm. She is impressed with your e\u000eciency as well as the
\ne\u000eciency of the portfolio. However, she informs you that due to company’s credit worthiness,
\nany leverage (i.e. borrowing at the risk-free rate) and short-selling are not allowed. But you
\njust did all that work…oh well. Your boss wants you to investigate the e\u000bect a no short sales
\nconstraint will have on the MVS without a risk-free asset and any subsequent investment
\ndecisions. To do this you are asked to perform the following tasks:
\n4. (a) Construct and plot the risky asset only MVS with no short sales allowed for the
\nsix assets. (Recall you will need Solver to do this.)
\n(b) Plot the combination line between P1 and P2 in Question 2(c)|on the same set
\nof axes. Also, indicate the positions of the six assets.
\n(c) List the portfolio weights for all the data points used in constructing your no short
\nsales allowed graph.
\n(d) Identify and report the range of expected returns for which the short sales con-
\nstraint is not binding.
\n(e) Discuss the compositions of the portfolios at the end-points of the MVS with no
\nshort sales.
\n(f) Now with no short sales allowed, what is the optimal portfolio for the client?
\nReport the portfolio weights in the six assets, expected return and standard de-
\nviation of her optimal portfolio. Also, compare to Question 2(f), what is the
\nreduction in client’s expected utility?
\nAt 7:15pm, with a grumbling stomach, you send the results to your boss who is still working
\nhard in her o\u000ece. As you gather your things to leave, your email pings and it is a lengthly<\/p>\n

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