Variance And Standard deviation in Python
Variance
Measurement of spread of between numbers in a data set. That is,it measures how far each number in the data set from mean and therefore from other numbers in the set
Key Takeaways
- In investing, variance is used to compare the relative performance of each asset in a portfolio.
- Because the results can be difficult to analyze, standard deviation is often used instead of variance.
- In either case, the goal for the investor is to improve asset allocation.
How to Use Variance
Variance measures variability from the average or mean. To investors, variability is volatility, and volatility is a measure of risk. Therefore, the variance statistic can help determine the risk an investor assumes when purchasing a specific security.
A large variance indicates that numbers in the set are far from the mean and from each other, while a small variance indicates the opposite.
Variance and Standard deviation in Python
Standard Deviation
The standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance.
Key Takeaways
- Standard deviation measures the dispersion of a dataset relative to its mean.
- A volatile stock has a high standard deviation, while the deviation of a stable blue-chip stock is usually rather low.
- As a downside, it calculates all uncertainty as risk, even when it’s in the investor’s favor — such as above average returns.