Find attached required data into excel and answers with the help of excel formulas.
Date | Open | High | Low | Close | Adj Close | Volume | |||
01-12-2014 | 47.88 | 49.06 | 44.9 | 46.45 | 41.700874 | 626771200 | Average return | 81.23 | |
01-01-2015 | 46.66 | 47.91 | 40.35 | 40.4 | 36.269444 | 918966800 | Geometric return | 75.19392 | |
01-02-2015 | 40.59 | 44.3 | 40.23 | 43.85 | 39.366711 | 656509700 | Standard deviation | 32.54891 | |
01-03-2015 | 43.67 | 44.19 | 40.54 | 40.66 | 36.762642 | 824335300 | Variance | 1042.064 | |
01-04-2015 | 40.6 | 49.54 | 40.12 | 48.64 | 43.977737 | 874535300 | |||
01-05-2015 | 48.58 | 48.91 | 46.02 | 46.86 | 42.368355 | 633072800 | |||
01-06-2015 | 47.06 | 47.77 | 43.94 | 44.15 | 40.177536 | 664853400 | |||
01-07-2015 | 44.46 | 47.4 | 43.32 | 46.7 | 42.498096 | 725458100 | |||
01-08-2015 | 46.98 | 48.41 | 39.72 | 43.52 | 39.604225 | 776480300 | |||
01-09-2015 | 42.17 | 45 | 41.66 | 44.26 | 40.543247 | 673079900 | |||
01-10-2015 | 44.75 | 54.37 | 43.75 | 52.64 | 48.219536 | 856716800 | |||
01-11-2015 | 52.85 | 54.98 | 52.53 | 54.35 | 49.785923 | 662626600 | |||
01-12-2015 | 54.41 | 56.85 | 53.68 | 55.48 | 51.163593 | 792820900 | |||
01-01-2016 | 54.32 | 55.39 | 49.1 | 55.09 | 50.803936 | 927914700 | |||
01-02-2016 | 54.88 | 55.09 | 48.19 | 50.88 | 46.921478 | 814770900 | |||
01-03-2016 | 50.97 | 55.64 | 50.58 | 55.23 | 51.29874 | 641110900 | |||
01-04-2016 | 55.05 | 56.77 | 49.35 | 49.87 | 46.320259 | 699025700 | |||
01-05-2016 | 50 | 53 | 49.46 | 53 | 49.227463 | 530704800 | |||
01-06-2016 | 52.44 | 52.95 | 48.04 | 51.17 | 47.860149 | 823627000 | |||
01-07-2016 | 51.13 | 57.29 | 50.39 | 56.68 | 53.013744 | 647587800 | |||
01-08-2016 | 56.6 | 58.7 | 56.14 | 57.46 | 53.743298 | 467078900 | |||
01-09-2016 | 57.01 | 58.19 | 55.61 | 57.6 | 54.210018 | 526427800 | |||
01-10-2016 | 57.41 | 61.37 | 56.32 | 59.92 | 56.393475 | 614841800 | |||
01-11-2016 | 59.97 | 61.41 | 57.28 | 60.26 | 56.713467 | 613056800 | |||
01-12-2016 | 60.11 | 64.1 | 58.8 | 62.14 | 58.877903 | 513579700 | |||
01-01-2017 | 62.79 | 65.91 | 61.95 | 64.65 | 61.256142 | 493453500 | |||
01-02-2017 | 64.36 | 65.24 | 62.75 | 63.98 | 60.621319 | 440744000 | |||
01-03-2017 | 64.13 | 66.19 | 63.62 | 65.86 | 62.780933 | 489169700 | |||
01-04-2017 | 65.81 | 69.14 | 64.85 | 68.46 | 65.259361 | 433191200 | |||
01-05-2017 | 68.68 | 70.74 | 67.14 | 69.84 | 66.574867 | 517218500 | |||
01-06-2017 | 70.24 | 72.89 | 68.09 | 68.93 | 66.084045 | 629716800 | |||
01-07-2017 | 69.33 | 74.42 | 68.02 | 72.7 | 69.698387 | 469851200 | |||
01-08-2017 | 73.1 | 74.96 | 71.28 | 74.77 | 71.682907 | 444070500 | |||
01-09-2017 | 74.71 | 75.97 | 72.92 | 74.49 | 71.794968 | 375983900 | |||
01-10-2017 | 74.71 | 86.2 | 73.71 | 83.18 | 80.170578 | 449950000 | |||
01-11-2017 | 83.68 | 85.06 | 82.24 | 84.17 | 81.124741 | 421926000 | |||
01-12-2017 | 83.6 | 87.5 | 80.7 | 85.54 | 82.85923 | 466203300 | |||
01-01-2018 | 86.13 | 95.45 | 85.5 | 95.01 | 92.032455 | 574258400 | |||
01-02-2018 | 94.79 | 96.07 | 83.83 | 93.77 | 90.831299 | 725663300 | |||
01-03-2018 | 93.99 | 97.24 | 87.08 | 91.27 | 88.824951 | 750754800 | |||
01-04-2018 | 90.47 | 97.9 | 87.51 | 93.52 | 91.014671 | 668130700 | |||
01-05-2018 | 93.21 | 99.99 | 92.45 | 98.84 | 96.192154 | 509417900 | |||
01-06-2018 | 99.28 | 102.69 | 97.26 | 98.61 | 96.384285 | 602585200 | |||
01-07-2018 | 98.1 | 111.15 | 98 | 106.08 | 103.685684 | 569352300 | |||
01-08-2018 | 106.03 | 112.78 | 104.84 | 112.33 | 109.794617 | 456628100 | |||
01-09-2018 | 110.85 | 115.29 | 107.23 | 114.37 | 112.218773 | 480255500 | |||
01-10-2018 | 114.75 | 116.18 | 100.11 | 106.81 | 104.800964 | 927548000 | |||
01-11-2018 | 107.05 | 112.24 | 99.35 | 110.89 | 108.804222 | 720228600 | |||
01-12-2018 | 113 | 113.42 | 93.96 | 101.57 | 100.090057 | 944314600 | |||
01-01-2019 | 99.55 | 107.9 | 97.2 | 104.43 | 102.908394 | 714212800 | |||
01-02-2019 | 103.78 | 113.24 | 102.35 | 112.03 | 110.397652 | 469095900 | |||
01-03-2019 | 112.89 | 120.82 | 108.8 | 117.94 | 116.717896 | 589095800 | |||
01-04-2019 | 118.95 | 131.37 | 118.1 | 130.6 | 129.246719 | 433157700 | |||
01-05-2019 | 130.53 | 130.65 | 123.04 | 123.68 | 122.398415 | 547218800 | |||
01-06-2019 | 123.85 | 138.4 | 119.01 | 133.96 | 133.062622 | 508324300 | |||
01-07-2019 | 136.63 | 141.68 | 134.67 | 136.27 | 135.357162 | 484079900 | |||
01-08-2019 | 137 | 140.94 | 130.78 | 137.86 | 136.936493 | 584482000 | |||
01-09-2019 | 136.61 | 142.37 | 134.51 | 139.03 | 138.558517 | 472544800 | |||
01-10-2019 | 139.66 | 145.67 | 133.22 | 143.37 | 142.883804 | 549523400 | |||
01-11-2019 | 144.26 | 151.33 | 142.97 | 149.48 | 148.973083 | 302260100 | |||
21-11-2019 | 149.4 | 149.8 | 148.51 | 149.48 | 149.479996 | 18576083 |
2. Go to Yahoo Finance, and search for Microsoft (MSFT). Click on historical data tab, and...
Go to Yahoo Finance, and search for MSFT (MSFT). Click on the historical Data tab, and pull the last 5 years of dividend (not stock price) data into excel. Calculate the yearly dividend payout using the trailing 12-months (does not have to correspond to calendar year). If you use the most recent annual growth rate (not the average calculated in part a), what is the required rate that yields a price closest to the current trading price? If MSFT decides...
Go to Yahoo Finance and find historical stock price information for Microsoft. Export the daily data from 1/1/2012 to 10/1/2012 into Excel. To download the historical prices, go to Yahoo Finance and type "Microsoft" into the search bar. Select the result with the ticker symbol "MSFT," click on "Historical Prices" in the left menu bar and set a date range from 1/3/2012 to 10/1/2012. Leave the "Daily" option checked and click on "Get prices." At the bottom of the table,...
At the beginning of 2020 you invest $3,000 in Microsoft (MSFT) stock and $5,000 in Proctor and Gamble (PG) stock. Suppose you expect the monthly return to be 1.2% for MSTF and 0.5% for PG and the standard deviation of monthly returns to be 11.6% for MSTF and 6.5% for PG, and that the correlation of the returns on the two stock is 0.18. - What are the expected monthly return on your portfolio and its stand dard deviation? -...
Regression Analysis Estimate the beta of Amazon. 1. Use Yahoo Finance, download Amazon's historical monthly stock prices for the "time period" (1/1/2009- 12/31/2018) and calculate monthly holding period returns. Holding period return (Ending price-Beginning Price)/ Beginning price. 2. Use Yahoo Finance, download S&P 500 historical monthly prices for the "time period" (1/1/2009 -12/31/2018) and calculate monthly holding period returns. Holding period return (Ending price - Beginning Price) / Beginning price. 3. Use 1% as Risk-free rate during these periods. 4....
Returns earned over a given time period are called realized returns. Historical data on realized returns is often used to estimate future resu Analysts across companiess use realized stock returns to estimate the risk of a stock. Consider the case of Falcon Freight Inc. (FF): Five years of realized returns for FF are given in the following table. Remember: 1. While FF was started 40 years ago, its common stock has been publicly traded for the past 25 years. 2....
The purpose of this analysis is to find an intrinsic value for Microsoft (MSFT) using the both the Constant Dividend Discount Model (DDM) and the Non-constant DDM. You will need to (1) estimate Beta in order to calculate the required return for MSFT; (2) estimate dividend growth rate; and (3) estimate future dividends. Submit your Excel spreadsheet with all data and formulas so that your answers can be replicated. You may answer the questions on the spreadsheet. HOWEVER, WRAP YOUR...
2. Measuring standalone risk using realized (historical) data Aa Aa Returns earned over a given time period are called realized returns. Historical data on realized returns is often used to estimate future results. Analysts across companies use realized stock returns to estimate the risk of a stock. Consider the case of Falcon Freight Inc. (FF): Five years of realized returns for FF are given in the following table. Remember: 1. While FF was started 40 years ago, its common stock...
2. Measuring standalone risk using realized (historical) data Aa Aa Returns earned over a given time period are called realized returns. Historical data on realized returns is often used to estimate future results. Analysts across companies use realized stock returns to estimate the risk of a stock. Consider the case of Falcon Freight Inc. (FF): Five years of realized returns for FF are given in the following table. Remember: 1. While FF was started 40 years ago, its common stock...
Returns earned over a given time period are called realized returns. Historical data on realized returns is often used to estimate future results. Analysts across companies use realized stock returns to estimate the risk of a stock. Consider the case of Blue Ulama Mining Inc. (BLM): Five years of realized returns for BLM are given in the following table. Remember: 1. While BLM was started 40 years ago, its common stock has been publicly traded for the past 25 years....
1. Measuring stand-alone risk using realized (historical) data Returns earned over a given time Analysts across companies alled returns. Historical data on realized returns is often used to estimate future results. estimate the risk of a stock. Consider the case of Celestial Five years of realized returns llowing table. Remember: has been publicly traded for the past 25 years. 3. The 2014 17.50% Stock return Given the preceding data, the average CCC's stocks of CCC's historical returns. Based on this...