Linear combinations of Random Variables:
Let us consider a two random variable X and Y. let us define the linear combination of X and Y as follows.
"W = aX-bY"
Here, a and b are constants.
The mean or expected value of W is
"\u03bc_W = a \\times \u03bc_X -b \\times \u03bc_Y"
The variance for W is as follows.
"\u03c3_W^2 = a^2 \\times \u03c3_X^2 + b^2 \\times \u03c3_Y^2 -2 \\times a \\times b \\times \u03c1(X,Y) \\times \u03c3_X \\times \u03c3_Y"
We are working on an investor plans. Let us define two random variables X and Y. X represent the first investment and Y represents second investments
"X = N(\u03bc_X=0.1, \u03c3_X^2 = 0) \\\\\n\nY = N(\u03bc_Y=0.18, \u03c3_Y^2 = 0.06)"
We are interested in computing the mean and variance of the total profit.
"P = 100000X + 100000Y"
We compute the mean and standard deviation of P by using previous formula
"a = 100000 \\\\\n\nb = 100000 \\\\\n\n\u03bc_P = a \\times \u03bc_X + b \\times \u03bc_Y \\\\\n\n= 100000 \\times 0.1 + 100000 \\times 0.18 \\\\\n\n= 28000"
The mean of total profit is 28000.
"\u03c3_W^2 = a^2 \\times \u03c3_X^2 + b^2 \\times \u03c3_Y^2 -2 \\times a \\times b \\times \u03c1(X,Y) \\times \u03c3_X \\times \u03c3_Y \\\\\n\n\n\n= (100000)^2 \\times 0 + (100000)^2 \\times (0.06)^2 -2 \\times 100000 \\times 100000 \\times (0) \\times 0.06 \\\\\n\n\n\n= 36000000"
We know that the standard deviation is the positive square root of the variance, thus we have
"\u03c3 = \\sqrt{36000000} \\\\\n\n= 6000"
The standard deviation of total profit is 6000.
Comments
Leave a comment