What is Covariance?

What's covariance ?

The direct relationship between two asset classes' returns is called covariance. Statistics can be used to help you understand and assess stocks. Covariance, a well-known statistical concept, can be applied anywhere. However, when trading it's variables are two stocks. The formula to determine the covariance of two stocks can be used to predict their performance relative to each other. Covariance can be a useful statistical measure in portfolio management.

It can be used for determining which assets should be included in a portfolio. Covariance measures returns by measuring covariance. If two stocks move in the exact same direction, covariance will be positive. Covariance is negative when two stocks move in opposite directions. A manager should choose stocks that are compatible with each other, which will ensure they don't covary. When building a portfolio, it is important to choose stocks with negative covariation.

Covariance calculation:

A list of all the stock's previous returns is required to calculate covariance. These historical returns are what most quote pages refer to. To calculate the historical returns for a stock, one uses its closing price each day. This must be done for each stock one wishes to compare the covariance. Let's say that Stock X has a dairy return of 1.1%, 1.7% 2, 2.1%, 1.4%, 1.4%, 0.5%. Stock Z also showed returns of 3.0%, 4.2% and 4.9% respectively.

1. To calculate covariance, the first step is to average the performance of these stocks over the past five days. Stock X's average is 1.30%, while Stock Z's is 3.74%.

2. Each stock's five values must be subtracted from the averages, and the difference should be charted.

3. Multiply the difference between X and its average return, and the difference between Z and its return and its mean return.

4. There will still be five multiples that need to be added.

5. The summation must be divided by the total size of the sample, minus one. In the above example, the sample size was five (days). The summation is then divided by 5-1 = 4. The following formula will give you the covariance for the numbers above: 0.665

6. This positive number means that stocks are positively correlated. They are moving in the exact same direction, to a fairly strong degree. Stock X would likely have a high return if Stock Z had a high return.

Interpreting covariance

We now know how to identify covariance between stocks. Let's discuss how to interpret covariance so you don't misunderstand it. As you can see, the covariance between the two stocks is reasonable. It's also fair to assume that they move in the same direction. If the result was negative, one stock would have a positive response and the other would perform poorly.

Without looking at correlation, it is impossible to interpret covariance. Correlation is an important tool for determining the strength of a relationship between two stocks. Although they may have different levels of covariance, it is essential to look at correlation. Covariance is also used to determine correlation. Correlation values can range from -1 to 1. A negative correlation is the strongest possible, meaning the stocks have no relationship with each other. Positive correlation is the strongest positive correlation, meaning that the stocks always correspond with one another.

Conclusion

The covariance tool is a simple way to see if one stock's movements can be used as a predictor for others. Investors seek to reduce risk by including stocks that are negatively covariant. This means that if one stock is performing well, it is likely that the other will be underperforming. It is difficult to calculate covariance manually without a calculator or tool. Although stocks can be covariant, knowing the strength of their relationship (correlation), can help predict how consistent their covariance over time.