Stock index return value at risk estimates are affected by asymmetries in how stocks respond to good and bad news. Researchers compared models assuming symmetric returns and volatility to those allowing for asymmetries. They found that asymmetry in the unconditional distribution of returns is more important for accurate estimates. Using semi-variance, which accounts for this feature, leads to more stable and reliable value at risk estimates compared to simpler models.