The article introduces a new way to measure risk in financial markets with heavy-tailed distributions. By using extreme value theory, the researchers developed a more accurate method called Value at Risk (VaR) that considers the risks of individual assets in a portfolio. This VaR measure is less affected by changes in location and is found to be more precise in predicting potential losses in stock markets. By addressing the limitations of traditional risk management tools like VaR, this new approach offers a better way to manage risks in volatile financial markets.