What is Standard Deviation compared to Beta Score, and How is it Used in Picking Stocks (Simply Explained)?
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Standard Deviation helps us assess Risk and Return for a Stock. The higher the standard deviation, the riskier the investment in terms of expected return also reflected in Beta Score and Volatility Percentage.
So before we get into why you clicked on this article you have to understand Mean.
What is the Mean? The average of Data Points
There are 2 types of Means
- Actual mean method (The mathematical formula to get the actual mean)
- Assumed mean method (A guess of what the mean would be)
Mean is very important in Normal Distribution.
What is Normal Distribution?
- Data that is Normally Distributed
- This tell us most values are near the mean
- When data is normally distributed this means the Mean and Median are equal
- When data is not normally distributed that means a bias to the left or right exists
- Median is simply the middle number
- 1,2,3,4,5 (Median is 3)
- 1,2,3,4,5,6 (Median is 3+4 divided by 2 = 3.5)
- Represented by a Standard Bell Curve’
Example of when a Skewed Data Set when Distribution will occur:
Lets say 11 unemployed women are in a survey about their net worth. Two of these people doing the Survey are Michelle Obama and Hilary Clinton.
The mean net worth of the 11 women would be highly skewed and represent a Skewed Distribution!
What is a Standard Deviation?
- A number that represents how one group differs from the mean value of entire group or data set.
How is Standard Deviation Calculated?
What is 68–95–99.7 Rule?
- The Percentages or Standard Deviation from the mean
- 68% of values are within 1 Standard Deviations
- 95% of values are within 2 Standard Deviations
- 99.7% of values are within 3 Standard Deviations
σ Stands for Standard Deviation
μ Stands for Mean
Examples of IQ scores (If Mean = 100, Standard Deviation = 15)
Someone scored = 131
- 1 Standard Deviation = 85 and 115 = 68% (score falls within 68% of data)
- 2 Standard Deviations = 70–85 and 115–130 = 95% (score falls within 95% of data)
- 3 Standard Deviations = 55–70 and 130–145 = 99.7% (score falls within 95% of data)
This means 131 is 3 Standard Deviations from our mean which means this person has a score that is 99.7% better than the other scores.
One of the most popular Use Cases for Standard Deviation is in Finance.
A stock with a mean price of $35 and a standard deviation of $5, means that the price majority of the time will be between $30 and $40.
This helps us gauge the future of our Stock Price.
The larger the Standard Deviation the lower the probability of expected return. This isn’t necessarily a bad thing but it just makes the stock or investment less predictable.
Standard deviation measures the volatility or predictability of the investment’s average return over a period of time.
Beta could be calculated by dividing the Standard Deviation by the S&P 500 of returns. This tells us how volatile our stock is in comparison to the overall market.
As long term investors we typically look for Beta Scores from 0 to 1.
A Beta score of 2, can be interpreted as this Stock changes value twice as much as the S & P 500.
We tend to look for Standard Deviations relative to the mean. The more disparity from the mean the more volatile that stock is predicted to be.
A High or Large Standard Deviation tells us that the probability of a predictable return is low.
When using Standard Deviation you must always understand that Finance, Probability, and Data Science all have a strong basis in Predictive Analytics!
Hopefully you understand Standard Deviation!
