The article discusses how using high frequency data can help accurately estimate volatility in financial markets. By considering the noisy nature of price formation processes, researchers developed unbiased estimators to account for this incoherent effect. They tested these estimators using simulations that included realistic market dynamics and found them to be robust even with changes in data frequency. The best estimators were then applied to real-world data to demonstrate their effectiveness in estimating volatility.