Answer: 0.1865

## Explanation The correlation coefficient is calculated using the formula: $$\text{Corr}(R_x, R_y) = \frac{\text{Cov}(R_x, R_y)}{\sigma(R_x) \cdot \sigma(R_y)}$$ Given: - Covariance: Cov(Rₓ, Rᵧ) = 0.093 - Variance of Rₓ = 0.69 - Variance of Rᵧ = 0.36 First, we need to calculate the standard deviations: - σ(Rₓ) = √(Variance of Rₓ) = √0.69 = 0.8306 - σ(Rᵧ) = √(Variance of Rᵧ) = √0.36 = 0.6 Now, plug into the correlation formula: $$\text{Corr}(R_x, R_y) = \frac{0.093}{0.8306 \times 0.6} = \frac{0.093}{0.49836} = 0.1865$$ Therefore, the correlation coefficient is 0.1865, which corresponds to option B. **Key points:** 1. Correlation is the standardized version of covariance 2. Standard deviation is the square root of variance 3. The correlation coefficient ranges from -1 to +1 4. This positive correlation (0.1865) indicates that when Stock X's returns increase, Stock Y's returns tend to increase slightly as well, though the relationship is relatively weak.

Author: Nikitesh Somanthe