Use Correlation Validation in Financial Generative AI

Contributed by: Sofien Kaabar

Difficulty level: Intermediate

Correlation is a statistical measure that quantifies the degree to which two variables are related or associated with each other. It is a way to assess whether changes in one variable are associated with changes in another variable. Correlation does not imply causation; it simply indicates that there is a statistical relationship between the two variables.

The most commonly used correlation measure is the Pearson correlation coefficient, which measures the linear relationship between two variables. The Pearson correlation coefficient ranges from –1 to 1, where:

• A correlation coefficient of 1 indicates a perfect positive correlation, meaning that as one variable increases, the other also increases proportionally.
• A correlation coefficient of –1 indicates a perfect negative correlation, meaning that as one variable increases, the other decreases proportionally.
• A correlation coefficient of 0 indicates no linear correlation, meaning that there is no consistent linear relationship between the two variables.

There are certain financial time series known to have a high degree of correlation (whether positive or negative) due to statistical and economic reasons. This Shortcut shows you how to generate synthetic data on two different, but related, time series and then calculate the correlation between the two generated time series. This may serve as a way to validate ...