Calculate stock beta

A Comprehensive Look At How To Calculate A Stocks Beta

The second letter of the greek alphabet ‘Beta’ has an important context in Financial Markets.  A stocks beta refers to its volatility or risk factor when compared to the market as a whole.

In this post I will provide step by step instructions on how to calculate a Stocks Beta.

A Stocks Beta is a form of regression analysis, and is considered one of the few data points that can be beneficial for the technical and fundamental analysis of a stock.

A Beta of 1

The whole of all the stocks together in the S&P Index is considered to have a Beta of 1.  This is the benchmark where individual stocks are measured against.  So, if a stock has a beta of 1, then it’s assumed that stock will mimic the fluctuations of the S&P Index.

Beta is expressed in percentage, so if a stock has a Beta of 1, then it’s no more or no less volatile than the overall market.

Beta greater than 1. 

When a stocks Beta is greater than 1, it usually moves more erratically than the broader market and would be considered more volatile.  Beta is measured in percentages, so a stock with a beta of 1.10, is generally assumed to be 10% more volatile than the total market.  

Five stocks in the S&P Index with a beta greater than 1

Carrier global Corporation-1.08

Celanese Corpoation-1.18

Honeywell International Inc.-1.08

LyondellBasell Industries N.V.-1.29

ONEOK, Inc..- 1.70

Beta less than 1

When a stock or fund has a Beta less than 1, also referred to as a Negative Beta, it generally moves less than the broader market and considered less volatile.  A stock with a negative beta of .89, is considered 11% less volatile than the broader market.  

Here are five stocks in the S&P 500 with beta less than 1.



Procter and Gamble-.39


Lockheed Martin-.76

Should investors focus on Negative Beta Stocks to avoid getting recked?

Warren Buffett doesn’t think so, here is what he said at the Annual Shareholders Meeting back in 1994:

“It became very fashionable in the academic world, and then that spilled over into the financial markets, to define risk in terms of volatility, of which beta became a measure, but that is no measure of risk to us,”

It appears that Buffett doesn’t put much ‘importance’ in A Stocks Beta, and seems to advocate that long-term investors should have a good understanding of the economics of the business they invest in, rather than focus on Beta.

His company; Berkshire Hathaway has a range of positions in companies with Negative Beta, but the the great portion of the companies have a beta between 1-1.5.

In fact, there are only 3 stocks in Berkshire Hathaway’s Top-Ten holdings which currently have a Negative Beta:


Negative Beta Stocks


Buffett also says:

The nice thing about Beta, which is a measure of volatility, is that it’s nice and mathematical…But, it’s wrong in terms of measuring Risk.  Risk comes from the nature of certain kinds of businesses.

So, perhaps Beta Investing should be left to Traders?

Long term holders of a stock shouldn’t put much emphasis on Beta, simply because a stock may be volatile in the short term, but stable over a longer term.

Think about the oil and gas industry today, where the price of a barrel of crude oil is historically high.  This has an adverse effect on the Beta of stocks in that sector over the short term.  Once crude oil prices come down, and the storm is weathered, beta will revert back toward the sectors mean.

According to Beta works best in the short term where volatility, especially downside volatility, often times passes for risk.  Because traders are in and out of positions rather quickly, Beta Investing may be an advantageous tool.

How do I calculate the Beta of my portfolio.

Calculating the beta of your portfolio will take some number crunching and manipulation, and best if you’re armed with a spreadsheet.  But, if you’re anything like me, using a spreadsheet is the fun part.

To calculate the Beta of your portfolio against that of the S&P.

Go to Yahoo Finance:  Enter in ‘GSPC’ as the symbol for the S&P, and click on ‘Historical Data’.

A Stocks Beta

Unfortunately, Yahoo Finance does not allow you to download this data into an CSV for the S&P, but it does for individual stocks.  So, unless you can copy and paste this into Excel, you will have to hand-key it into a spreadsheet.

A Stocks Beta

Then, search for the stock you want to compare beta’s against the S&P with, and go to ‘Historical Prices’.  Enter in the date range, whether that be; last month, quarter, year, or custom:  Hit apply, then download.

In this example, I’m using Groupon (GRPN).

A Stocks Beta

For “Time Period” I chose 3 Months

A Stocks Beta

For the individual Stock, A CSV sheet will be created.  Take the CSV and open it up in Excel.

The only information you need from this CSV is the ‘Date’ and the ‘Closing Price’, you can delete all the other columns.

Create a new column to the right of the ‘Close” price, and call it ‘Price Change’.  Use this column to calculate the daily price change, by subtracting todays price close, from that of yesterdays ‘Close’.

A Stocks Beta

Once you have all the ‘Price Changes’ calculated for your selected date range, you must calculate the mean of all these prices.

At the bottom of the ‘Price Change’ Column write the formula =Average(D4:D64). Keep in mind, Your letters and numbers will vary depending on which column you used for your ‘Price Change’ Calculation, and also how many prices you have in your sample.  

In the case of my (GRPN) Stock the Mean is -0.0116

And the S&P is -0.00313.

Next we must calculate the Deviation from the Mean in order to find the Beta

To do this, we take the daily price change minus the Mean of (GRPN) -0.0116.

Next find the Deviation from the Mean of the S&P Index’s prices.

Follow the same steps above to calculate the daily ‘Price Change” of the S&P, then calculate the Mean, just like you did for your chosen stock.

Calculating Beta of a stock

Below are the daily Deviations from the Mean for the three months I selected for GRPN.

Deviation from stock mean

And the Daily Deviation from the Mean for the S&P at the time.

Deviation from Stock Mean


Next we multiply the daily Deviations from the mean by each other.

For instance; the first Deviation from the mean for (GRPN) was 0.0273, and the S&P was -0.0096, multiplied together gives us -0.0003.  This becomes the ‘Product of the Deviation’.

Now, repeat this calculation for each day of the “Price Change”.

Once we calculate all the ‘products of the deviations’, we add them together to find the Sum total.  In the case of (GRPN) verses the S&P, the sum total of the ‘product of the deviations’ is 0.0310.

Now that we have the product of the deviations, we take this and multiply it by 1/N-1N= the number of observations, in this case I had 61 observations over the three month trading period.  It looks like this:

(.0310*1/n-1)  or .0310*1/60 since N=61, then 61-1=60.  The product of this is .00051667, which becomes our Co-Variance.

We are not done yet.  To find the beta of a stock you need to divide the Co-Variance by the Variance.

Now that we know the Co-Variance, we have to calculate the Variance of the S&P, and in order to do that we need to square the deviations from the mean for the S&P, see here:

A Stocks Beta


We are almost finished.  The sum of this is .019869.  We then take this number and divided it by N-1.  We’ve determined that N=61, so N-1 again is 60.  So, we divide .019869 by 60 or .00033115, which becomes the Variance.

Now, we simply divide the Co-Variance, (.00051667) by the Variance  (.00033115) and this will give us our Beta of 1.56022.

GRPN is considered a High Beta Stock.

With a Beta of 1.56022, it is generally assumed the stock will move nearly 1.5 times as much as the S&P, which is rather volatile.  This is likely not a stock Warren Buffett would ever invest in, but it’s a great stock for a day-trader to ‘swing trade’.  Either way, depending on what side of the trade you are on, either long or short, it could be very lucrative or very un-profitable.

So, choose your position wisely and go out and make some money!




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