Variance Covariance
About the Lecture
The lecture Variance Covariance by Edu Pristine is from the course Archiv - Quantitative Analysis. It contains the following chapters:
- Variance & Standard deviation
- Covariance and correlation
- Question
- Some Properties of Variance
- Skewness
- Kurtosis
- Coskewness and Cokurtosis
- BLUE
- Question
- Question - FRM Exam 2009
Author of lecture Variance Covariance
Edu Pristine
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Excerpts from the accompanying material
... Square root of the Variance is more convenient to use, as it has the same units as the original variable X ...
... EduPristine For Quantitative Analysis-I (Confidential) Correlation coefficient always lies in the range of +1 to -1. A correlation of 1 means that the two variables always move in the same direction A correlation of -1 ...
... what is the Variance of X given Variance[Y] = 100, Variance [4X ...
... 9*Var[Y] + 2*4*(-3)*Var[X]^(1/2)* Var[Y]^(1/2)*correlation[X,Y] -Solve for Var[X] = ...
... that the distribution has a long left tail, which indicates a high probability of observing large negative values.If this represents the distribution of ...
... observations in the tail will have a large weight and hence create large kurtosis. Such a distribution is called leptokurtic, or fat tailed. ...
... for these two variables at different point of time most risk models ignore the effects of coskewness and cokurtosis. The main reason for this is that as the number of variables increases, the number of coskewness ...
... to the parameter you are trying to estimate. An unbiased parameter is also efficient if its sampling distribution has minimum variance. ...
... deviations from the mean. -2 = [(12-5.67) 2 + (5-5.67) 2 + (-7-5.67) 2 + (11-5.67) 2 + (2-5.67) 2 + ...
... 0.5. The variance of 2X + 3Y is: A.13 B.29 ...
... - Y) = Var(X) + Var(Y) -2*Cov(x,y) -Var(cX) = c^2 * Var(X) -Cov (ax,by) = abCov(x,y) ...
... 4 million in stock P. You are considering a strategy of shifting USD 1 million into stock Q and keeping USD 3 million in stock P. What percentage of risk, as measured ...
... a variable to exceed a specified extreme value ‘X’ which is greater than the mean assuming the distributions all. ...
... Therefore, the probability of exceeding a specified extreme value will be higher. -B. Incorrect. Since answer A. has a lower kurtosis, a distribution with a kurtosis of 8 will necessarily produce a larger probability in the tails. © EduPristine For Quantitative ...
