The article discusses how to calculate, model, and predict stock market volatility using high-frequency data. The researchers found that the decay of high-frequency returns follows a specific pattern, helping to choose the best sampling frequency for volatility calculations. They also discovered that volatility can be modeled as a specific type of process, which performs better than traditional models but is more complex and data-intensive.