The article presents a simple model for predicting financial returns throughout the day. By analyzing three years of data, the researchers found that past returns and the time of day influence return distribution. This model can estimate volatility, asymmetry, and kurtosis without relying on specific mathematical properties. It also accurately forecasts intraday Value at Risk, outperforming other methods like GARCH. The findings reveal seasonal patterns and time dependencies beyond just volatility.