PFA
The Purpose This is an individual assignment designed to enhance students’ knowledge in the following areas: an understanding of and ability to identify the financial risks faced by individuals and corporations; an ability to undertake statistical analysis, including calculation of alternative risk measures and statistics in Excel; familiarity with the construction of tables and graphics and their integration into written reports; and high-level written communication skills. Information: You have been asked to provide analysis for and advice to an Australian-based, high net worth client, who is considering the purchase of a structured financial product (SFP) issued by a US-based large-cap firm. Your client wishes to be advised on the financial risks to which they would be exposed in association with investment in this SFP. You have the following information on this SFP, as well as other information on key financial variables: · The face value of the SFP is USD25,000 · The payoff is due in one year · Payoff at maturity is min{USD25,000, [(SP500T/SP5000 )x USD25,000]} · SP500T represents the value of the S&P 500 Index at maturity of the investment product and SP5000 the value of the S&P 500 Index at inception of the SFP (i.e., the end of June 2021) · USD/AUD represents the US dollar/Australian dollar exchange rate (price of AUD 1 in USD) · The yield/discount rate of this SFP is the yield on the comparable U.S. government bond plus 200 basis points · You have been provided with time series data (as of the end of June 2021, the date you will assume as ‘now/today’ for undertaking your calculations) in the form of the yield on U.S. government bonds (% p.a.), the USD/AUD exchange rate, and the value of the S&P 500 Index (see the spreadsheet provided with the Assignment BANK 3003 Risk Management Case Data.xlsx). The Task Prepare a brief (i.e., no more than 3 pages) report in which you address the following: a) Identifies the financial risks to which your client would have exposure if invested in this SFP. You should tabulate the different financial risks to which an investor would be exposed if they bought the SFP and the sources of each financial risk. (10 marks) b) Your client is concerned about the default risk of the issuer. How would you assess the credit risk of this SFP? (Hint 1: You should discuss in detail, without calculations, the credit risk assessment process. Describe what method(s) might be employed using which dataset(s) and, if available, how you would go about collecting those data.) (30 marks) c) Your client is especially concerned about extreme adverse movements associated with the payoff of this SFP. Provide estimates on the potential loss(es) associated with the payoff at maturity of the SFP given the underlying risk factor(s). Estimate the current price/value of the SFP given the potential loss(es) scenarios. (Hint 2: the potential loss(es) must relate to any amount less than USD25,000 in AUD that the investor may be receive at maturity and should consider both likely payoffs and the probabilities of these payoffs.) (Hint 3: you should consider measures such as value-at-risk (VaR) to assist you in determining the loss(es). Any proper attempts to further assess the extreme risk will be rewarded.) (40 marks) d) Provide a brief, but critical, evaluation of the limitations and model risks of each of the methods that you have used to develop the estimates in part b) and c). (Hint 4: discuss only one or two limitations/model risks associated with each method using your own words.) (20 marks) What to Submit and When? Each student should submit one copy of the following via learnonline: 1. A WORD file (of no more than 3 pages) by 5pm, 12 Nov 2021. Supporting materials such as tables, figures, references, and appendices do not count towards the page limit. There is no word limit. The word limit shown in the course outline is the ‘word-equivalent’ limit. It does not strictly apply to word count because we have quantitative elements. 2. An Excel file for calculation references by 5pm, 12 Nov 2021. Note that this file is not graded. The grader may reference the Excel file if the main report is unclear or ambiguous. Therefore, there is minimum expectation in terms of formatting and explanation. HB, April 2011 [Type text] FRA Assignment Data S&P500 Share Price Index Exchange Rate (USD/AUD)US Government Liabilities Spot Rates (% p.a.) 1-Jul-061276.660.76593.6660 1-Aug-061303.820.76333.9490 1-Sep-061335.850.74653.9510 1-Oct-061377.940.77504.1270 1-Nov-061400.630.78864.3860 1-Dec-061418.300.78884.3940 1-Jan-071438.240.77574.3670 1-Feb-071406.820.78714.5110 1-Mar-071420.860.80894.7330 1-Apr-071482.370.82994.8360 1-May-071530.620.82844.9040 1-Jun-071503.350.84824.9750 1-Jul-071455.270.85205.1920 1-Aug-071473.990.81654.9790 1-Sep-071526.750.88814.8250 1-Oct-071549.380.93184.6620 1-Nov-071481.140.88554.7590 1-Dec-071468.360.87434.6870 1-Jan-081378.550.89544.8000 1-Feb-081330.630.92974.9660 1-Mar-081322.700.91384.6380 1-Apr-081385.590.94384.5870 1-May-081400.380.95564.6660 1-Jun-081280.000.95804.8790 1-Jul-081267.380.94064.9540 1-Aug-081282.830.85724.5630 1-Sep-081166.360.79264.1820 1-Oct-08968.750.66903.9590 1-Nov-08896.240.65183.8090 1-Dec-08903.250.70553.0840 1-Jan-09825.880.63853.2500 1-Feb-09735.090.64252.1650 1-Mar-09797.870.69181.7630 1-Apr-09872.810.72671.6420 1-May-09919.140.80102.3420 1-Jun-09919.320.80622.6570 1-Jul-09987.480.83562.3700 1-Aug-091020.620.84292.3630 1-Sep-091057.080.88382.2050 1-Oct-091036.190.90101.5900 1-Nov-091095.630.91761.4340 1-Dec-091115.100.89830.9240 1-Jan-101073.870.88630.3400 1-Feb-101104.490.89880.4880 1-Mar-101169.430.91560.7240 1-Apr-101186.690.92480.5750 1-May-101089.410.84660.5040 1-Jun-101030.710.84130.4630 1-Jul-101101.600.90520.4580 1-Aug-101049.330.89180.2590 1-Sep-101141.200.96940.2440 1-Oct-101183.260.97280.1880 1-Nov-101180.550.96070.1780 1-Dec-101257.641.01580.2410 1-Jan-111286.120.98740.4190 1-Feb-111327.221.01450.2900 1-Mar-111325.831.03190.2970 1-Apr-111363.611.09390.3860 1-May-111345.201.07030.3840 1-Jun-111320.641.06930.3460 1-Jul-111292.281.10000.3200 1-Aug-111218.891.06760.2950 1-Sep-111131.420.97650.2490 1-Oct-111253.301.06740.2560 1-Nov-111246.961.00180.2210 1-Dec-111257.601.01410.2740 1-Jan-121312.411.05860.2770 1-Feb-121365.681.08000.2360 1-Mar-121408.471.03510.2440 1-Apr-121397.911.04560.2720 1-May-121310.330.97050.2010 1-Jun-121362.161.02410.1600 1-Jul-121379.321.04990.1910 1-Aug-121406.581.02810.2060 1-Sep-121440.671.03570.0920 1-Oct-121412.161.03660.1040 1-Nov-121416.181.04290.1170 1-Dec-121426.191.03920.1140 1-Jan-131498.111.04190.1070 1-Feb-131514.681.02320.1170 1-Mar-131569.191.04090.1629 1-Apr-131597.571.03440.1700 1-May-131630.740.96690.1750 1-Jun-131606.280.91280.1900 1-Jul-131685.730.90730.2080 1-Aug-131632.970.89020.1730 1-Sep-131681.550.93010.1730 1-Oct-131756.540.94700.1600 1-Nov-131805.810.91130.1750 1-Dec-131848.360.89200.1700 1-Jan-141782.590.87960.1450 1-Feb-141859.450.89620.1370 1-Mar-141872.340.92600.1520 1-Apr-141883.950.92750.1268 1-May-141923.570.93090.1090 1-Jun-141960.230.94170.1320 1-Jul-141930.670.93260.1520 1-Aug-142003.370.93340.1120 1-Sep-141972.290.87170.1200 1-Oct-142018.050.88250.0940 1-Nov-142067.560.84430.0990 1-Dec-142058.900.81840.1220 1-Jan-151994.990.77890.1190 1-Feb-152104.500.78190.1010 1-Mar-152067.890.76580.1040 1-Apr-152085.510.79950.1167 1-May-152107.390.76580.1090 1-Jun-152063.110.76730.0960 1-Jul-152103.840.72940.1015 1-Aug-151972.180.71410.1140 1-Sep-151920.030.70040.0964 1-Oct-152079.360.70900.0964 1-Nov-152080.410.71840.1015 1-Dec-152043.940.72850.1269 1-Jan-161940.240.70690.1929 1-Feb-161932.230.71280.1522 1-Mar-162059.740.76610.2031 1-Apr-162065.300.76070.2495 1-May-162096.950.71960.2342 1-Jun-162098.860.74700.2546 1-Jul-162173.600.75880.2648 1-Aug-162170.950.75240.3465 1-Sep-162168.270.76280.3721 1-Oct-162126.150.75980.3210 1-Nov-162198.810.74840.3057 1-Dec-162238.830.72090.4795 1-Jan-172278.870.75650.6075 1-Feb-172363.640.76760.4487 1-Mar-172362.720.76550.5716 1-Apr-172384.200.74830.6162 1-May-172411.800.74590.5549 1-Jun-172423.410.76850.6776 1-Jul-172470.300.79860.4527 1-Aug-172471.650.79070.5139 1-Sep-172519.360.78460.5957 1-Oct-172575.260.76980.5803 1-Nov-172647.580.75670.6468 1-Dec-172673.610.78080.7697 1-Jan-182823.810.81010.8125 1-Feb-182713.830.77940.7798 1-Mar-182640.870.76780.7798 1-Apr-182648.050.75751.0319 1-May-182705.270.75711.0628 1-Jun-182718.370.73461.1554 1-Jul-182816.290.74071.2224 1-Aug-182901.520.72621.2172 1-Sep-182913.980.72251.2274 1-Oct-182711.740.70991.2997 1-Nov-182760.170.73221.4184 1-Dec-182506.850.70451.6047 1-Jan-192704.100.72551.7396 1-Feb-192784.490.71481.8816 1-Mar-192834.400.70872.0747 1-Apr-192945.830.70552.0901 1-May-192752.060.69062.2366 1-Jun-192941.760.70042.2101 1-Jul-192980.380.68752.3148 1-Aug-192926.460.67362.4140 1-Sep-192976.740.67612.4504 1-Oct-193037.560.68982.5765 1-Nov-193140.980.67652.6442 1-Dec-193230.780.70012.6808 1-Jan-203225.520.67082.5857 1-Feb-202954.220.65802.5838 1-Mar-202584.590.61692.5469 1-Apr-202912.430.65552.3956 1-May-203044.310.66342.4109 1-Jun-203100.290.68722.3054 1-Jul-203271.120.72041.9489 1-Aug-203500.310.73731.9851 1-Sep-203363.000.71441.7656 1-Oct-203269.960.70381.7730 1-Nov-203621.630.74001.5935 1-Dec-203756.070.76891.5935 1-Jan-213714.240.76441.5840 1-Feb-213811.150.78701.4801 1-Mar-213972.890.76091.1743 1-Apr-214181.170.77780.1421 1-May-214204.110.77100.1675 1-Jun-214297.500.75140.1777 Souce: Thomson Reuters Datascope Select