Goldman Sachs’ Beta Calculation by Means of Regression
By Jonathan Marville, B.S.
What is beta? Beta is a measure of volatility of a security relative to the rest of the market (for this example we will use the S & P 500 Index). Beta represents the systematic risk of a company given current market conditions. It is the part of risk that cannot be diversified away through efficient portfolio management. Financial analysts use a couple different methods of achieving beta. The method I chose to use is through the use of statistical regression analysis. I believe this to be the most accurate since it is a highly mathematical approach. Beta is nothing more than the slope of a line that runs through the mean of returns of the stock and the market. To find this slope I gathered four years of historical stock prices for both the S&P 500 Index and Goldman Sachs. The data was entered into an Excel spreadsheet where I calculated the individual returns for each month dating back to April 2000. Next, I calculated the average annual returns for all months, calculated the standard deviations for both. I calculated the correlation between the S&P 500 Index and Goldman Sachs. As shown on the following pages I have included all the statistics and attached a graph of the regression line. Finally, beta was calculated by taking the slope of the regression line. Beta was found to be 1.513.>
Goldman Sachs’ Beta Calculation by Means of Regression
By Jonathan Marville, B.S.
What is beta? Beta is a measure of volatility of a security relative to the rest of the market (for this example we will use the S & P 500 Index). Beta represents the systematic risk of a company given current market conditions. It is the part of risk that cannot be diversified away through efficient portfolio management. Financial analysts use a couple different methods of achieving beta. The method I chose to use is through the use of statistical regression analysis. I believe this to be the most accurate since it is a highly mathematical approach. Beta is nothing more than the slope of a line that runs through the mean of returns of the stock and the market. To find this slope I gathered four years of historical stock prices for both the S&P 500 Index and Goldman Sachs. The data was entered into an Excel spreadsheet where I calculated the individual returns for each month dating back to April 2000. Next, I calculated the average annual returns for all months, calculated the standard deviations for both. I calculated the correlation between the S&P 500 Index and Goldman Sachs. As shown on the following pages I have included all the statistics and attached a graph of the regression line. Finally, beta was calculated by taking the slope of the regression line. Beta was found to be 1.513.>