Stock Market, Time Series Analysis, Time Series Forecasting, Python, Monte Carlo.
“absolute” joint variability so another way to visualize the relationship between the variables is to use a correlation matrix which is a “normalized” version of the covariance matrix where each value is between -1(completely negatively correlated) to 0 (no correlation) to +1 (perfectly positively