The article presents a new method for accurately estimating how much a stock price will change over time, even when the data is noisy. The researchers used a multi-scale approach to analyze the data at different levels of detail, allowing them to better capture the underlying patterns of volatility. Their findings show that this method can provide more efficient and reliable estimates of stock price movements, even in the presence of uncertainty.