The ability to attribute portfolio risk and performance to key factors, such as overall market exposure, rates, sectors, and quality, is an essential tool for helping portfolio managers to understand their risk and interpret their results. A parsimonious factor risk model can also support advanced portfolio construction goals, such as minimizing benchmark tracking error or realizing factor exposure tilts.
Risk model providers often commonly report the average R2 value of the asset returns model. Some models, such as statistical models, will consistently have greater R2 values than others. However, strong explanatory power from a returns model does not necessarily translate into an accurate risk model.