The article discusses a new method for testing cointegration in economic and financial data that does not rely on the assumption of normality. By using Independent Component Analysis, the researchers developed a framework that can handle non-normal distributions and their independence. Their simulations show that this new test is as effective as traditional methods when there are many observations, and even better when observations are limited. This method is also practical for real-world research due to its manageable computational requirements.