Obtain the monthly returns for IBM (symbol: IBM), Verizon Communication (symbol: VZ), and S&P500 index (symbol: ^GSPC) from November 2000 through November 2020. Put these into a sp

INSTRUCTIONS ARE ATTACHED:
You need to collect input data for this project. Obtain the monthly returns for IBM (symbol: IBM), Verizon Communication (symbol: VZ), and S&P500 index (symbol: ^GSPC) from November 2000 through November 2020. Put these into a spreadsheet. You can easily obtain monthly prices (split- and dividend- adjusted) from http://quote.yahoo.com by choosing to view a table of monthly prices from October 1, 2000 through November 30, 2020 (you will see why we start from October in Project 1 Example). Then choose to ‘Download Spreadsheet Format’. Convert the prices to returns, then use a spreadsheet to do the tasks and answer the questions bellow. You will also need risk free interest data for this project. Go to Canvas course website, click on the Assignments link and then click on Rf in the Excel file, FF risk free.xlsx?. The rf rate is provided in percentage.
Refer to the PDF file, Project 1 Example? to see exactly what you have to do and how your work should be presented. This document is found on Assignments page. This document will be referred to at various points in the following discussion.
Use Microsoft Excel to perform the tasks described below. Once you have accomplished the tasks, answer the questions on pages 4-5 of this document. .
Things to submit: Answers to multiple choice questions on Canvas plus Excel spreadsheets with your work.
Requirements: AS SHOWN IN EXAMPLE DOC ATTACHED | .doc file
Page?1Monthly?returnsABCDEFGHIJ1CompanyTickerDateBAC?priceT?priceSP500?pricer?BACr?Tr?SP500period2Bank?of?AmericBAC1998?10?0113.5817.931098.673ATTT1998?11?0115.4018.651163.6313.3704.0235.913Nov?9841998?12?0114.2020.871229.23?7.76611.8645.638Dec?9851999?01?0116.0221.011279.6412.7870.6994.101Jan?9961999?02?0115.6420.671238.33?2.336?1.646?3.228Feb?9971999?03?0116.9118.441286.378.134?10.7563.879Mar?9981999?04?0117.3721.791335.182.69218.1463.794Apr?9991999?05?0115.7020.081301.84?9.607?7.852?2.497May?99101999?06?0117.7922.781372.7113.33313.4475.444Jun?99111999?07?0116.3422.441328.72?8.159?1.509?3.205Jul?99121999?08?0114.9018.961320.41?8.851?15.495?0.625Aug?99131999?09?0113.7120.141282.71?7.9556.242?2.855Sep?99141999?10?0116.1120.911362.9317.4603.8276.254Oct?99151999?11?0114.6520.871388.91?9.045?0.2071.906Nov?99161999?12?0112.5419.331469.25?14.369?7.3915.784Dec?99172000?01?0112.3217.001394.46?1.812?12.051?5.090Jan?00182000?02?0111.7015.051366.42?5.032?11.473?2.011Feb?00192000?03?0113.3316.791498.5813.99511.5899.672Mar?00202000?04?0112.7417.471452.43?4.4794.006?3.080Apr?00212000?05?0114.4117.511420.6013.1380.264?2.192May?00222000?06?0111.3817.641454.60?20.9970.7152.393Jun?00232000?07?0112.5417.061430.8310.174?3.267?1.634Jul?00242000?08?0114.1816.831517.6813.094?1.3256.070Aug?00252000?09?0114.1420.101436.51?0.28619.417?5.348Sep?00262000?10?0112.9823.251429.40?8.23415.664?0.495Oct?00272000?11?0110.7922.251314.95?16.905?4.298?8.007Nov?00282000?12?0112.7419.341320.2818.134?13.0830.405Dec?00292001?01?0114.9519.581366.0117.3191.2573.464Jan?01302001?02?0114.0819.421239.94?5.797?0.841?9.229Feb?01312001?03?0115.5418.171160.3310.392?6.436?6.420Mar?01322001?04?0115.9016.791249.462.283?7.5737.681Apr?01332001?05?0116.8217.631255.825.8034.9690.509May?01342001?06?0117.3716.401224.383.257?6.945?2.504Jun?01352001?07?0118.4118.441211.235.98012.406?1.074Jul?01362001?08?0117.8016.861133.58?3.332?8.582?6.411Aug?01372001?09?0116.9019.421040.94?5.04115.180?8.172Sep?01382001?10?0117.3815.701059.782.871?19.1211.810Oct?01392001?11?0118.0915.491139.454.051?1.3637.518Nov?01402001?12?0118.5516.231148.082.5584.7890.757Dec?01412002?01?0118.9415.521130.202.092?4.391?1.557Jan?02422002?02?0119.2115.781106.731.4601.694?2.077Feb?02432002?03?0120.8315.611147.398.408?1.0573.674Mar?02442002?04?0122.2012.951076.926.557?17.041?6.142Apr?02452002?05?0123.2214.401067.144.59411.203?0.908May?02462002?06?0121.5512.81989.82?7.189?11.053?7.246Jun?02472002?07?0120.7011.62911.62?3.937?9.311?7.900Jul?02482002?08?0121.8110.48916.075.383?9.7880.488Aug?02492002?09?0119.868.52815.28?8.961?18.755?11.002Sep?02502002?10?0122.1210.87885.7611.39627.6628.645Oct?02512002?11?0122.2112.23936.310.40112.5125.707Nov?02522002?12?0122.0511.64879.82?0.728?4.877?6.033Dec?02532003?01?0122.6210.49855.702.585?9.849?2.741Jan?03542003?02?0122.369.01841.15?1.156?14.128?1.700Feb?03552003?03?0121.588.69848.18?3.466?3.5580.836Mar?03562003?04?0124.3710.12916.9212.91116.4518.104Apr?03572003?05?0124.4211.17963.590.20310.4135.090May?03582003?06?0126.0111.21974.506.5090.3541.132Jun?03((F3?F2)/F2)*100
Risk?and?return?analysisPage?2ABCDEFGHIJL1Monthly?return1+monthly?returnBACT2periodBACTBACTT,?No.?of?months613Nov?1313.243?1.4301.1320.986T?1604Dec?13?1.580?0.1420.9840.999Arithmetic?Average,?%1.5370.3215Jan?147.648?5.2331.0760.948Geometric?Average,?%1.2760.2136Feb?14?1.313?2.8940.9870.971Standard?Dev,?%7.3454.6707Mar?144.0539.8341.0411.098Covariance?0.2948Apr?14?11.9241.7960.8811.018Correlation?0.00869May?140.0000.6601.0001.00710Jun?141.519?0.3101.0150.911Jul?14?0.7170.6500.9931.00712Aug?145.508?0.4991.0550.99513Sep?145.9660.8011.0601.00814Oct?140.955?1.1351.0100.98915Nov?14?0.6992.8900.9931.02916Dec?144.988?5.0591.0500.94917Jan?15?15.068?1.9950.8490.98018Feb?154.3566.4711.0441.06519Mar?15?2.657?5.5270.9730.94520Apr?153.8326.0951.0381.06121May?153.5781.1451.0361.01122Jun?153.1522.8371.0321.02823Jul?155.368?2.1961.0540.97824Aug?15?8.054?2.4600.9190.97525Sep?15?5.231?2.5720.9480.97426Oct?158.0492.8541.0801.02927Nov?153.8741.9151.0391.01928Dec?15?3.4422.1980.9661.02229Jan?16?15.7474.7950.8431.04830Feb?16?11.4573.9100.8851.03931Mar?167.9876.0081.0801.06032Apr?168.102?0.8941.0810.99133May?161.5802.1011.0161.02134Jun?16?10.27710.3700.8971.10435Jul?169.5640.1851.0961.00236Aug?1611.387?4.5101.1140.95537Sep?16?2.585?0.6600.9740.99338Oct?165.431?9.4071.0540.90639Nov?1628.0006.2801.2801.06340Dec?169.7334.5301.0971.04541Jan?17?1.9494.4080.9811.04442Feb?179.0110.2741.0901.00343Mar?17?4.417?0.5740.9560.99444Apr?17?0.758?4.6210.9920.95445May?17?3.985?1.6140.9600.98446Jun?178.611?2.0761.0860.97947Jul?17?0.5773.3660.9941.03448Aug?17?0.954?2.6980.9900.97349Sep?176.6124.5651.0661.04650Oct?178.090?14.0921.0810.85951Nov?172.8489.4711.0281.09552Dec?175.2396.8721.0521.06953Jan?188.401?3.6781.0840.96354Feb?180.312?1.7871.0030.98255Mar?18?6.573?1.7910.9340.98256Apr?180.141?8.2751.0010.91757May?18?2.9410.2450.9711.00258Jun?18?2.530?0.6500.9750.99459Jul?189.542?0.4361.0950.99660Aug?180.1621.4581.0021.01561Sep?18?4.7535.1350.9521.05162Oct?18?6.202?8.6360.9380.91463Nov?183.2733.3401.0331.03397COUNT(B3:B63)AVERAGE(C3:C63)(GEOMEAN(F3:F63)??1)*100STDEV(C3:C63)COVAR(B3:B63,C3:C63)*(I2/I3)CORREL(B3:B63,C3:C63)1+(C10/100)
Page?3Investent?Opportunity?SetABCDEFGH1Input?data2E(rBAC)E(rT)σBACσTcorrelation31.5370.3217.3454.670?0.0094wBACwTExpected?returnStandard5E(rP)?=?Col?A?x?A3?+?Col?B?x?B3Deviation?*61.000.001.5377.3470.900.101.4156.6280.800.201.2945.9490.700.301.1725.31100.600.401.0504.77110.500.500.9294.33120.400.600.8074.04130.300.700.6863.92140.200.800.5644.00150.100.900.4434.26160.001.000.3214.67170.2890.7110.6733.9218192021222324252627282930313233343536373839404142434445464748495051525354555657585327252620050.0000.2000.4000.6000.8001.0001.2001.4001.6001.8000.0001.0002.0003.0004.0005.0006.0007.0008.000Portfolio?return,?rpPortfolio?standard?deviation,?σpUse?arithmetic?average,?sample?variance?and?correlation?from?earlier?analysis?(Worksheet?”Risk?and?Return?Analysis”)Weights?of?stocks?in?minimum?variance?portfolioWeight?on?BAC,?wBAC?=?(D3^2??C3*D3*E3)/(C3^2?+?D3^2??2*C3*D3*E3)Weight?on?T,?wT?=?1??wBAC*Formula?for?portfolio?standard?deviation:SQRT((Col?A*$C$3)^2+(Col?B*$D$3)^2?+?2*Col?A*$C$3*Col?B*$D$3*$E$3)
rf,%199811300.310.0031199812310.380.0038199901290.350.0035199902260.350.0035199903310.430.0043199904300.370.0037199905280.340.0034199906300.40.004199907300.380.0038199908310.390.0039199909300.390.0039199910290.390.0039199911300.360.0036199912310.440.0044200001310.410.0041200002290.430.0043200003310.470.0047200004280.460.0046200005310.50.005200006300.40.004200007310.480.0048200008310.50.005200009290.510.0051200010310.560.0056200011300.510.0051200012290.50.005200101310.540.0054200102280.380.0038200103300.420.0042200104300.390.0039200105310.320.0032200106290.280.0028200107310.30.003200108310.310.0031200109280.280.0028200110310.220.0022200111300.170.0017200112310.150.0015200201310.140.0014200202280.130.0013200203280.130.0013200204300.150.0015200205310.140.0014200206280.130.0013200207310.150.0015200208300.140.0014
Inputs?for?regression?analysisPage?4ABCDEFGHI1Monthly?return,?%Monthly?excess?return,?%2periodBACSP500RfBAC?rfSP500?rf3Nov?9813.3705.9130.3113.0605.603C3-D34Dec?98?7.7665.6380.38?8.1465.2585Jan?9912.7874.1010.3512.4373.7516Feb?99?2.336?3.2280.35?2.686?3.5787Mar?998.1343.8790.437.7043.4498Apr?992.6923.7940.372.3223.4249May?99?9.607?2.4970.34?9.947?2.83710Jun?9913.3335.4440.4012.9335.04411Jul?99?8.159?3.2050.38?8.539?3.58512Aug?99?8.851?0.6250.39?9.241?1.01513Sep?99?7.955?2.8550.39?8.345?3.24514Oct?9917.4606.2540.3917.0705.86415Nov?99?9.0451.9060.36?9.4051.54616Dec?99?14.3695.7840.44?14.8095.34417Jan?00?1.812?5.0900.41?2.222?5.50018Feb?00?5.032?2.0110.43?5.462?2.44119Mar?0013.9959.6720.4713.5259.20220Apr?00?4.479?3.0800.46?4.939?3.54021May?0013.138?2.1920.5012.638?2.69222Jun?00?20.9972.3930.40?21.3971.99323Jul?0010.174?1.6340.489.694?2.11424Aug?0013.0946.0700.5012.5945.57025Sep?00?0.286?5.3480.51?0.796?5.85826Oct?00?8.234?0.4950.56?8.794?1.05527Nov?00?16.905?8.0070.51?17.415?8.51728Dec?0018.1340.4050.5017.634?0.09529Jan?0117.3193.4640.5416.7792.92430Feb?01?5.797?9.2290.38?6.177?9.60931Mar?0110.392?6.4200.429.972?6.84032Apr?012.2837.6810.391.8937.29133May?015.8030.5090.325.4830.18934Jun?013.257?2.5040.282.977?2.78435Jul?015.980?1.0740.305.680?1.37436Aug?01?3.332?6.4110.31?3.642?6.72137Sep?01?5.041?8.1720.28?5.321?8.45238Oct?012.8711.8100.222.6511.59039Nov?014.0517.5180.173.8817.34840Dec?012.5580.7570.152.4080.60741Jan?022.092?1.5570.141.952?1.69742Feb?021.460?2.0770.131.330?2.20743Mar?028.4083.6740.138.2783.54444Apr?026.557?6.1420.156.407?6.29245May?024.594?0.9080.144.454?1.04846Jun?02?7.189?7.2460.13?7.319?7.37647Jul?02?3.937?7.9000.15?4.087?8.05048Aug?025.3830.4880.145.2430.34849Sep?02?8.961?11.0020.14?9.101?11.14250Oct?0211.3968.6450.1411.2568.50551Nov?020.4015.7070.120.2815.58752Dec?02?0.728?6.0330.11?0.838?6.14353Jan?032.585?2.7410.102.485?2.84154Feb?03?1.156?1.7000.09?1.246?1.79055Mar?03?3.4660.8360.10?3.5660.73656Apr?0312.9118.1040.1012.8118.00457May?030.2035.0900.090.1135.00058Jun?036.5091.1320.106.4091.032
SUMMARY?OUTPUTRegression?StatisticsMultiple?R0.539645556R?Square0.291217326Adjusted?R?Square0.288251709Standard?Error9.727722006Observations241ANOVAdfSSMSFSignificance?FRegression19292.3235059292.32350598.197858981.29483E?19Residual23922616.2295394.62857542Total24031908.55303CoefficientsStandard?Errort?StatP?valueLower?95%Upper?95%Lower?95.0%Upper?95.0%Intercept0.3500752560.6285154120.5569875440.578057149?0.8880620221.588212534?0.8880620221.588212534SP500?rf1.4948481830.1508502659.9094832851.29483E?191.1976823011.7920140651.1976823011.792014065
FIN4504-100 Spring 2023 Project 1 Instructor: A. Agapova 1 General Instructions: 1. Due date: February 19, 2023, 11:59pm. 2. Any project that is submitted after the due date will not be accepted and a zero (0) will be assigned to the project. 3. This is individual work; it is NOT group work. Each student is individually responsible for completing the project. Each student is expected to do his/her own work without help from any other person, except, possibly, the instructor. 4. You need to collect input data for this project. Obtain the monthly returns for IBM (symbol: IBM), Verizon Communication (symbol: VZ), and S&P500 index (symbol: ^GSPC) from November 2000 through November 2020. Put these into a spreadsheet. You can easily obtain monthly prices (split- and dividend-adjusted) from http://quote.yahoo.com by choosing to view a table of monthly prices from October 1, 2000 through November 30, 2020 (you will see why we start from October in Project 1 Example). Then choose to ‘Download Spreadsheet Format’. Convert the prices to returns, then use a spreadsheet to do the tasks and answer the questions bellow. You will also need risk free interest data for this project. Go to Canvas course website, click on the Assignments link and then click on Rf in the Excel file, FF risk free.xlsx?. The rf rate is provided in percentage. 5. Refer to the PDF file, Project 1 Example? to see exactly what you have to do and how your work should be presented. This document is found on Assignments page. This document will be referred to at various points in the following discussion. 6. Use Microsoft Excel to perform the tasks described below. Once you have accomplished the tasks, answer the questions on pages 4-5 of this document. Record your answers on Canvas. 7. Things to submit: Answers to multiple choice questions on Canvas plus Excel spreadsheets with your work on Canvas. Primary objective: Financial modeling using spreadsheets is a standard tool in the investment analyst?s tool kit. The overall aim of the projects is to get students started on using spreadsheets for investment analysis. Specific learning objectives 1. Learn to embed formulas into Excel worksheets. 2. Compute the number of return observations using the COUNT function. 3. Compute the arithmetic average using the AVREAGE function. 4. Compute the geometric average using the GEOMEAN function. 5. Compute the sample standard deviation using the STDEV function. 6. Compute the sample covariance using the COVAR function. 7. Compute the sample correlation using the CORREL function. 8. Use Excel to create and draw the investment opportunity set. 9. Calculate the portfolio weights in the minimum variance portfolio. 10. Perform a simple regression analysis using Excel?s Data Analysis package. Task 1: Use the monthly returns of IBM and Verizon Communication between November 2015 and November 2020 to do the following: a) Calculate each stock?s arithmetic average using the AVERAGE function.
FIN4504-100 Spring 2023 Project 1 Instructor: A. Agapova 2 b) Calculate each stock?s geometric average using the GEOMEAN function. c) Calculate each stock?s sample standard deviation using the STDEV function. d) Calculate the sample covariance of IBM and Verizon Communication using the COVAR function. You also need the COUNT function. In general, the sample covariance of stock A and B is given by: ??=??????TtBtBAtArrrrT1,,))((11 where T is the number of periods, and Ar(Br) is the arithmetic average of stock A (B). Excel?s COVAR function gives you ??=????TtBtBAtArrrrT1,,))((1. So you have to multiply this result by 1??TT to get the sample covariance. To compute T, you use the COUNT function. e) Calculate the correlation coefficient of IBM and Verizon Communication. Presentation of your work: Provide a spreadsheet in an Excel file showing your work. Follow the format in Project 1 Example? pages 1 and 2. Task 2: Investment Opportunity Set To create the investment opportunity set, we need expected returns, standard deviation and the correlation coefficient. We let the expected return of IBM (E(rIBM)) be equal to its arithmetic average calculated in Task 1. Similarly, we let the standard deviation of IBM (σIBM) be equal to its sample standard deviation from Task 1. Do the same for Verizon Communication. Finally, for correlation coefficient (ρIBM,F), use the correlation coefficient calculated in Task 1. Let wIBM be IBM?s portfolio weight and let wF Verizon Communication?s portfolio weight. a) Compute the portfolio expected return and standard deviation using the following weights: WIBM WF 1.0 0.0 0.9 0.1 0.8 0.2 0.7 0.3 0.6 0.4 0.5 0.5 0.4 0.6 0.3 0.7 0.2 0.8 0.1 0.9 0.0 1.0 b) Compute the portfolio expected return and standard deviation of the minimum variance portfolio consisting of IBM and Verizon Communication. c) Draw the investment opportunity set obtained in Task 2a using Scatter diagram Excel tool.
FIN4504-100 Spring 2023 Project 1 Instructor: A. Agapova 3 Presentation of your work: Provide a spreadsheet in an Excel file showing your calculations of the various combinations of expected return and standard deviation. Follow the format in Project 1 Example? page 3. Task 3: Regression Analysis a) Use regression analysis to estimate the single index model for Verizon (VZ). For input data, use monthly excess returns from November 2000 through November 2020. The Y-variable is the monthly excess return of VZ and the X-variable is the monthly excess return of the S&P 500 stock index. Performing regression analysis using Excel 2013?s (or older version) Data Analysis package i) On the Tool menu, click Data Analysis. If Data Analysis is not available, load the Analysis ToolPak. How? On the Tools menu, click Add-Ins. In the Add-Ins available list, select the Analysis ToolPak box, and then click OK. If necessary, follow the instructions in the setup program. ii) In the Data Analysis dialog box click Regression and then click OK. iii) In the Regression dialog box, you must specify the inputs. For Input Y Range, highlight the monthly excess returns of VZ (including the column heading) as the Y-axis variable. For Input X Range, highlight the monthly excess returns of SP500 (including the column heading) as the X-axis variable. iv) Check the Labels box. v) In the Output option section, highlight an empty area in the worksheet. Make sure the highlighted area has at least 20 rows and 10 columns. vi) Click OK. If you have questions at any stage, you can use the Help button on the dialog box to get more information about the options. Presentation of your work: Provide a spreadsheet in an Excel file showing your work for the regression analysis results. Follow the format in Project 1 Example? page 5.
FIN4504-100 Spring 2023 Project 1 Instructor: A. Agapova 4 Multiple Choice Questions Instructions: 1. There are 10 questions. Choose the best answer to each question and select your answer choice (A, B, C, D or E) on the questionnaire on Canvas. Each question is worth 10 points. 2. The questions will be graded according to the Course Syllabus. Your Excel spreadsheets will serve as evidence of your work. 3. Submit the answer sheet together with your Excel spreadsheets. 4. Make sure you do your work in excel spreadsheets CLEARLY and NEATLY. Untidy work will result in a 1 point penalty per question. Questions 1 to 5 are directed at Task 1 1. What is IBM?s arithmetic average and geometric average between November 2015 and November 2020? A. Arithmetic average is 0.397% and Geometric average is 0.142% B. Arithmetic average is 0.397% and Geometric average is 0.804% C. Arithmetic average is 0.804% and Geometric average is 0.920% D. Arithmetic average is 0.920% and Geometric average is 0.804% E. Arithmetic average is 0.179% and Geometric average is 0.397% 2. What is Verizon Communication?s arithmetic average and geometric average between November 2015 and November 2020 A. Arithmetic average is 0.397% and Geometric average is 0.142% B. Arithmetic average is 0.397% and Geometric average is 0.804% C. Arithmetic average is 0.804% and Geometric average is 0.920% D. Arithmetic average is 0.920% and Geometric average is 0.804% E. Arithmetic average is 0.179% and Geometric average is 0.397% 3. What is IBM?s sample standard deviation between November 2015 and November 2020? A. 0.397% B. 0.142% C. 7.121% D. 4.853% E. 6.194% 4. What is Verizon Communication?s sample standard deviation between November 2015 and November 2020? A. 0.397% B. 0.142% C. 7.121% D. 4.853% E. 6.194%
FIN4504-100 Spring 2023 Project 1 Instructor: A. Agapova 5 5. What is the sample covariance of IBM and Verizon Communication between November 2015 and November 2020? A. 0.397 B. 0.142 C. 7.121 D. 4.853 E. 6.194 Questions 6 to 8 are directed at Task 2 6. If you form a portfolio with equal weights on IBM and Verizon Communication, what will be the expected return and standard deviation? A. Expected return = 0.397% and Standard deviation = 7.121% B. Expected return = 0.502% and Standard deviation = 5.948% C. Expected return = 0.659% and Standard deviation = 4.654% D. Expected return = 0.920% and Standard deviation = 4.853% E. Expected return = 0.774% and Standard deviation = 4.322% 7. What are the weights on IBM and Verizon Communication in the minimum variance portfolio? A. Weight on IBM = 0.84, weight on Verizon Communication = 0.16 B. Weight on IBM = 0.28, weight on Verizon Communication = 0.72 C. Weight on IBM = 0.5, weight on Verizon Communication = 0.5 D. Weight on IBM = 0.72, weight on Verizon Communication = 0.28 E. Weight on IBM = 0.16, weight on Verizon Communication = 0.84 8. What is the expected return and standard deviation of the minimum variance portfolio? A. Expected return = 0.397% and Standard deviation = 7.121% B. Expected return = 0.502% and Standard deviation = 5.948% C. Expected return = 0.659% and Standard deviation = 4.654% D. Expected return = 0.920% and Standard deviation = 4.853% E. Expected return = 0.774% and Standard deviation = 4.322% Questions 9 to 10 are directed at Task 3 9. What is VZ?s beta between November 2000 and November 2020? A. 0.633 B. 1.000 C. 0.343 D. 0.270 E. 0.078 10. What is the intercept of the single-index model? A. 0.633 B. 1.000 C. 0.270 D. 0.137 E. 0.078

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