Suppose that there are some data collected in the form of time series from 3 subjects:
$X_1 = (x_{11}, x_{12}, ..., x_{1n})$
$X_2 = (x_{21}, x_{22}, ..., x_{2n})$
$X_3 = (x_{31}, x_{32}, ..., x_{3n})$
To simplify the situation, assume that the components in each time series are independent from each other and follow $N(0, \sigma_1^2)$, $N(0, \sigma_2^2)$, and $N(0, \sigma_3^2)$ respectively. The Pearson correlation coefficients among the three subjects are,
$r_{12} = E(X_1 X_2)/(\sigma_1 \sigma_2)$
$r_{13} = E(X_1 X_3)/(\sigma_1 \sigma_3)$
$r_{23} = E(X_2 X_3)/(\sigma_2 \sigma_3)$
My question is, are the 3 correlation coefficients (as random variables) independent from each other? If not, how to demonstrate the situation?