P1.T2.304. Covariance (Miller)
AIM: Define, calculate, and interpret the covariance and correlation between two random variables.
Questions:
304.1. Two assets, X and Y, produce only three simply joint outcomes: Prob[X = -3.0%, Y = -2.0%] = 30%, Prob[X = +1.0%, Y = +2.0%] = 50%, and Prob[X = +5.0%, Y = +3.0%] = 20%:![[IMG]](http://www.bionicturtle.com/images/2013/dailypq/T2.304.1_xyreturns.png)
What is the correlation between X & Y? (bonus question: if we removed the probabilities and instead simply treated the three sets of returns as a small historical sample, would the sample correlation be different?)
- 0.6330
- 0.7044
- 0.8175
- 0.9286
304.2. Each of random variable X and Y can have two outcomes. The following probability matrix gives their joint probabilities:![[IMG]](http://www.bionicturtle.com/images/2013/dailypq/T2.304.2_matrix_cov.png)
For example, the joint Prob[X = 4.0, Y = 3.0] = 30%. What is the covariance between X and Y?
- -0.9727
- 0.3150
- 1.4842
- 4.9224
304.3. Let X be a discrete uniform random integer in the set {1, 2, 3, 4, 5} with equal probability of each outcome and let Y = (X+1)^2:![[IMG]](http://www.bionicturtle.com/images/2013/dailypq/T2.304.3_formula.png)
What is the covariance between X & Y?
- 5.5
- 9.0
- 16.0
- 25.0
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