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. Disney Historical Annual Stock Price Data Year Average Stock Price Year Open Year High Year Low Year Close Annual % Change 2021 180.3683 177.6800 201.9100 163.0300 171.1800 -5.52% 2020 126.4019 148.2000 181.1800 85.7600 181.1800 25.27% 2019 130.7728 108.9700 151.6400 106.3300 144.6300 31.90% 2018 108.3752 111.8000 118.9000 98.5400 109.6500 1.99% 2017 106.3582 106.0800 115.8400 96.9300 107.5100 3.16% 2016 97.4618 102.9800 106.6000 88.8500 104.2200 -0.82% 2015 107.8355 93.7500 121.6900 90.9600 105.0800 11.56% 2014 84.4812 76.2700 95.5000 69.9900 94.1900 23.29% 2013 62.8879 51.1000 76.4000 50.5800 76.4000 53.44% 2012 46.4359 38.3100 52.9700 38.3100 49.7900 32.77% 2011 37.9914 37.8200 44.0700 29.0000 37.5000 -0.03% 2010 34.1449 32.0700 37.9500 29.3200 37.5100 16.31% 2009 24.5009 23.9200 32.4300 15.5900 32.2500 42.13% 2008 29.6764 31.8400 34.9900 18.7300 22.6900 -29.71% 2007 34.2773 34.2000 36.5500 31.2400 32.2800 -5.81% 2006 29.5654 24.4000 34.8500 23.9900 34.2700 42.97% 2005 26.3047 27.8500 29.8800 22.9600 23.9700 -13.78% 2004 24.7151 23.6700 28.0000 20.8900 27.8000 19.16% 2003 19.9203 17.2600 23.4800 15.0200 23.3300 43.04% 2002 19.7296 21.4500 25.0000 13.7700 16.3100 -21.28% 2001 26.4359 27.9400 34.5000 16.9800 20.7200 -28.40%

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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Question

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.

Disney Historical Annual Stock Price Data
Year	Average Stock Price	Year Open	Year High	Year Low	Year Close	Annual % Change
2021	180.3683	177.6800	201.9100	163.0300	171.1800	-5.52%
2020	126.4019	148.2000	181.1800	85.7600	181.1800	25.27%
2019	130.7728	108.9700	151.6400	106.3300	144.6300	31.90%
2018	108.3752	111.8000	118.9000	98.5400	109.6500	1.99%
2017	106.3582	106.0800	115.8400	96.9300	107.5100	3.16%
2016	97.4618	102.9800	106.6000	88.8500	104.2200	-0.82%
2015	107.8355	93.7500	121.6900	90.9600	105.0800	11.56%
2014	84.4812	76.2700	95.5000	69.9900	94.1900	23.29%
2013	62.8879	51.1000	76.4000	50.5800	76.4000	53.44%
2012	46.4359	38.3100	52.9700	38.3100	49.7900	32.77%
2011	37.9914	37.8200	44.0700	29.0000	37.5000	-0.03%
2010	34.1449	32.0700	37.9500	29.3200	37.5100	16.31%
2009	24.5009	23.9200	32.4300	15.5900	32.2500	42.13%
2008	29.6764	31.8400	34.9900	18.7300	22.6900	-29.71%
2007	34.2773	34.2000	36.5500	31.2400	32.2800	-5.81%
2006	29.5654	24.4000	34.8500	23.9900	34.2700	42.97%
2005	26.3047	27.8500	29.8800	22.9600	23.9700	-13.78%
2004	24.7151	23.6700	28.0000	20.8900	27.8000	19.16%
2003	19.9203	17.2600	23.4800	15.0200	23.3300	43.04%
2002	19.7296	21.4500	25.0000	13.7700	16.3100	-21.28%
2001	26.4359	27.9400	34.5000	16.9800	20.7200	-28.40%

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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