Choose your favorite company or brand and search finance.yahoo.com with that com

Question

Choose your favorite company or brand and search finance.yahoo.com with that company name and “historical stock prices.” Download the stock history for this company for the past 6 weeks by selecting the appropriate dates and clicking on “Download to Spreadsheet” at the bottom of page. Calculate the daily change in the closing stock prices by taking the difference between the closing and opening price for the day. This is the daily stock change. Calculate the mean and standard deviation of the daily stock changes by running the Descriptive Statistics in Excel Data Analysis. Share the summary table. Consider the mean, median and mode (if it exists). Is your daily stock change distribution right skewed (median < mean), left skewed (mean < median), or symmetric (mean median)? What other considerations would you look at to determine whether or not this distribution is approximately normally distributed?

Explanation / Answer

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1) example 1

2) example 2

Date Open High Low Close Volume Adj Close Daily stock change 4/7/2017 899.65 900.09 889.31 894.88 3695900 894.88 -4.77 Descriptive Statistics output 4/6/2017 913.8 917.19 894.49 898.28 6331800 898.28 -15.52 4/5/2017 910.82 923.72 905.62 909.28 7489400 909.28 -1.54 Mean 0.8140015 4/4/2017 891.5 908.54 890.28 906.83 4967700 906.83 15.33 Standard Error 1.285649503 4/3/2017 888 893.49 885.42 891.51 3418300 891.51 3.51 Median 0.9600225 3/31/2017 877 890.35 876.65 886.54 3910700 886.54 9.54 Mode #N/A 3/30/2017 874.95 877.06 871.66 876.34 2745800 876.34 1.39 Standard Deviation 7.041792336 3/29/2017 859.05 876.44 859.02 874.32 4464400 874.32 15.27 Sample Variance 49.5868393 3/28/2017 851.75 858.46 850.1 856 3033000 856 4.25 Kurtosis 1.037194319 3/27/2017 838.07 850.3 833.5 846.82 2754200 846.82 8.75 Skewness -0.224844955 3/24/2017 851.68 851.8 843.53 845.61 2118300 845.61 -6.07 Range 30.970032 3/23/2017 848.2 850.89 844.8 847.38 1945700 847.38 -0.82 Minimum -15.640015 3/22/2017 840.43 849.37 839.05 848.06 2636200 848.06 7.63 Maximum 15.330017 3/21/2017 858.84 862.8 841.31 843.2 4349100 843.2 -15.64 Sum 24.420045 3/20/2017 851.51 857.8 851.01 856.97 2223300 856.97 5.46 Count 30 3/17/2017 853.49 853.83 850.64 852.31 3380700 852.31 -1.18 3/16/2017 855.3 855.5 850.51 853.42 1832600 853.42 -1.88 3/15/2017 854.33 854.45 847.11 852.97 2556700 852.97 -1.36 3/14/2017 853.55 853.75 847.55 852.53 2128700 852.53 -1.02 Answers 3/13/2017 851.77 855.69 851.71 854.59 1906100 854.59 2.82 Since mean < median, the distribution is skewed to the left 3/10/2017 857 857.35 851.72 852.46 2422000 852.46 -4.54 Following considerations are taken to check whether or not this distribution is approximately normally distributed: 3/9/2017 851 856.4 850.31 853 2040600 853 2.00 1. Whether mean = median 3/8/2017 848 853.07 846.79 850.5 2286500 850.5 2.50 2. 68% of the data should be within one standard deviation of the mean, 95% should be within two standard deviations, and 99% should be within three standard deviations 3/7/2017 845.48 848.46 843.75 846.02 2217800 846.02 0.54 3. There must be an equal likelihood of positive and negative deviations from the mean. 3/6/2017 845.23 848.49 841.12 846.61 2598400 846.61 1.38 4. The frequency of the deviations must fall off rapidly while moving away from the central value 3/3/2017 847.2 851.99 846.27 849.88 1941100 849.88 2.68 3/2/2017 853.08 854.82 847.28 848.91 2129200 848.91 -4.17 3/1/2017 853.05 854.83 849.01 853.08 2752000 853.08 0.03 2/28/2017 851.45 854.09 842.05 845.04 2777700 845.04 -6.41 2/27/2017 842.38 852.5 839.67 848.64 2702300 848.64 6.26

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