00:01
Okay, so if returns of a stock are perfectly correlated, then the stocks return up and down further.
00:05
Prorella would be exactly as risks as an individual stocks.
00:07
So kind of demonstrate this.
00:09
So we talk about a correlation between two stocks, we'll call them a and b, is one.
00:14
So what that means is if we're going to look at the combining two perfect...
00:20
Okay, so if we look at the risk of an individual stock is typically measured by its standard deviation or variance.
00:25
So when we look at that, so we can kind of reference this mathematically.
00:28
So for two stocks with a and b, the rate will call it ra for return of a and r of b, is return of b.
00:36
If they're poorly correlated, the correlation coefficient looks like this.
00:40
The variance, we'll call it, the variance overall will be sigma squared here, is going to equal to, based on the weights of everything, it's going to be the weight of a squared.
01:00
Weight of a squared times sigma a squared.
01:06
Okay, so it plus the weight of b squared times the sigma b squared.
01:13
Okay.
01:16
Plus two times the weight of a times the weight of b times the correlation coefficient between a and b...