how to calculate the standard deviation of a portfolio?
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The standard deviation of a two-asset portfolio is calculated by squaring the weight of the first asset and multiplying it by the variance of the first asset, added to the square of the weight of the second asset, multiplied by the variance of the second asset.
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['Calculate the mean (simple average of the numbers).', 'For each number: subtract the mean. Square the result.', 'Add up all of the squared results.', 'Divide this sum by one less than the number of data points (N - 1). ... ', 'Take the square root of this value to obtain the sample standard deviation.']
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['Compute the square of the difference between each value and the sample mean.', 'Add those values up.', 'Divide the sum by n-1. This is called the variance.', 'Take the square root to obtain the Standard Deviation.']
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To calculate the standard deviation, you would begin with calculating the quantity (xi − ), which is the deviation of each data point from the average. You would square square each one, then add them up and divide by one less than the number of data points.
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The standard deviation is given by the square root of the variance. To find the variance, we first calculate the mean of the set of data. Next, we subtract the mean from each number in the data set and square the results. Then, we take the average of the squared differences.
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Calculating Standard Error of the Mean First, take the square of the difference between each data point and the sample mean, finding the sum of those values. Then, divide that sum by the sample size minus one, which is the variance.
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['Covariance measures the total variation of two random variables from their expected values. ... ', 'Obtain the data.', 'Calculate the mean (average) prices for each asset.', 'For each security, find the difference between each value and mean price.', 'Multiply the results obtained in the previous step.']
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['Find the mean of the data set. Add all data values and divide by the sample size n.', 'Find the squared difference from the mean for each data value. Subtract the mean from each data value and square the result.', 'Find the sum of all the squared differences. ... ', 'Calculate the variance.']
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['Estimating the standard deviation, σ, of the sample data.', 'Multiplying that number by three.', 'Adding (3 x σ to the average) for the UCL and subtracting (3 x σ from the average) for the LCL.']
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To find the standard deviation, press SHIFT, 1, 4 (Var), 3 for standard deviation then you must press p to bring up the value. The mean is 5.9 and the standard deviation is 2.8792 to 4 decimal places. Turn the calculator off to clear then memories. Turn it on then press MODE, select 2 for statistics and 1 for 1-VAR.
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To calculate the portfolio variance of securities in a portfolio, multiply the squared weight of each security by the corresponding variance of the security and add two multiplied by the weighted average of the securities multiplied by the covariance between the securities.
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['Step 1: Enter your data into the calculator. This will be the first step for any calculations on data using your calculator. ... ', 'Step 2: Calculate 1-Variable Statistics. ... ', 'Step 3: Select the correct standard deviation.']
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Sum all of the squared deviations. Divide that sum by one less than the sample size (N–1) Last, take the square root of that result. That final number equals the standard deviation of your data set.
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All you need to do to calculate the standard deviation is select an empty cell on your spreadsheet, type =stdev(a1:a20) and you'll get your answer instantly. This assumes that your data is numerical values in cells A1 to A20.
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['Calculate the mean, x.', 'Write a table that subtracts the mean from each observed value.', 'Square each of the differences.', 'Add this column.', 'Divide by n -1 where n is the number of items in the sample This is the variance.']
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So the more spread out the group of numbers are, the higher the standard deviation. To calculate standard deviation, add up all the data points and divide by the number of data points, calculate the variance for each data point and then find the square root of the variance.
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['Calculate the mean.', 'Subtract the mean from each observation.', 'Square each of the resulting observations.', 'Add these squared results together.', 'Divide this total by the number of observations (variance, S2).', 'Use the positive square root (standard deviation, S).']