Create embedded formulae which generate statistical properties of the portfolio upon insertion of the weights. Observe the mean, the standard deviation, and the CV of the annual rate of return of the portfolio. Amazon Historical Annual Stock Price Data Year Average Stock Price Year Open Year High Year Low Year Close Annual % Change 2021 3315.9774 3186.6300 3731.4100 2951.9500 3444.1500 5.75% 2020 2680.8551 1898.0100 3531.4500 1676.6100 3256.9300 76.26% 2019 1789.1929 1539.1300 2020.9900 1500.2800 1847.8400 23.03% 2018 1641.7262 1189.0100 2039.5100 1189.0100 1501.9700 28.43% 2017 968.1670 753.6700 1195.8300 753.6700 1169.4700 55.96% 2016 699.5231 636.9900 844.3600 482.0700 749.8700 10.95% 2015 478.1373 308.5200 693.9700 286.9500 675.8900 117.78% 2014 332.5510 397.9700 407.0500 287.0600 310.3500 -22.18% 2013 298.0322 257.3100 404.3900 248.2300 398.7900 58.96% 2012 220.3037 179.0300 261.6800 175.9300 250.8700 44.93% 2011 196.6720 184.2200 246.7100 160.9700 173.1000 -3.83% 2010 139.1404 133.9000 184.7600 108.6100 180.0000 33.81% 2009 87.2811 54.3600 142.2500 48.4400 134.5200 162.32% 2008 69.8800 96.2500 96.2500 35.0300 51.2800 -44.65% 2007 67.2261 38.7000 100.8200 36.4300 92.6400 134.77% 2006 35.9104 47.5800 47.8700 26.0700 39.4600 -16.31% 2005 39.8969 44.5200 49.5000 31.7200 47.1500 6.46% 2004 43.5652 51.9000 57.1800 33.8300 44.2900 -15.83% 2003 37.7364 19.5700 59.9100 19.5700 52.6200 178.56% 2002 16.4817 10.9600 24.2500 9.1300 18.8900 74.58% 2001 12.2008 13.8800 21.8800 5.9700 10.8200 -30.46%

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Create embedded formulae which generate statistical properties of the portfolio upon insertion of the weights. Observe the mean, the standard deviation, and the CV of the annual rate of return of the portfolio.

Amazon Historical Annual Stock Price Data
Year	Average Stock Price	Year Open	Year High	Year Low	Year Close	Annual % Change
2021	3315.9774	3186.6300	3731.4100	2951.9500	3444.1500	5.75%
2020	2680.8551	1898.0100	3531.4500	1676.6100	3256.9300	76.26%
2019	1789.1929	1539.1300	2020.9900	1500.2800	1847.8400	23.03%
2018	1641.7262	1189.0100	2039.5100	1189.0100	1501.9700	28.43%
2017	968.1670	753.6700	1195.8300	753.6700	1169.4700	55.96%
2016	699.5231	636.9900	844.3600	482.0700	749.8700	10.95%
2015	478.1373	308.5200	693.9700	286.9500	675.8900	117.78%
2014	332.5510	397.9700	407.0500	287.0600	310.3500	-22.18%
2013	298.0322	257.3100	404.3900	248.2300	398.7900	58.96%
2012	220.3037	179.0300	261.6800	175.9300	250.8700	44.93%
2011	196.6720	184.2200	246.7100	160.9700	173.1000	-3.83%
2010	139.1404	133.9000	184.7600	108.6100	180.0000	33.81%
2009	87.2811	54.3600	142.2500	48.4400	134.5200	162.32%
2008	69.8800	96.2500	96.2500	35.0300	51.2800	-44.65%
2007	67.2261	38.7000	100.8200	36.4300	92.6400	134.77%
2006	35.9104	47.5800	47.8700	26.0700	39.4600	-16.31%
2005	39.8969	44.5200	49.5000	31.7200	47.1500	6.46%
2004	43.5652	51.9000	57.1800	33.8300	44.2900	-15.83%
2003	37.7364	19.5700	59.9100	19.5700	52.6200	178.56%
2002	16.4817	10.9600	24.2500	9.1300	18.8900	74.58%
2001	12.2008	13.8800	21.8800	5.9700	10.8200	-30.46%

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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