The article explores a new way to estimate volatility in financial data by looking at the changes in log-prices over time. This method focuses on the quadratic variation of second order log-price differences, unlike the traditional approach which looks at first order differences. The new estimator is efficient and provides valuable insights into asset pricing. The researchers compared this new method to the usual volatility estimators and found promising results. Simulation experiments were conducted to demonstrate the effectiveness of the new approach.