Realized volatility risk in stock and index returns is significant, leading to uncertainty in predicting future returns. A new model called dually asymmetric realized volatility (DARV) captures the varying volatility, skewness, and kurtosis of returns, especially in high volatility periods. This model has shown empirical advantages when applied to data from the S&P 500 index and other stocks and indexes.