A growing number of investment managers today regard the function of the enterprise risk management system as moving above and beyond simple compliance into the heart of the investment process. Risk models are no longer simply used to monitor risk, but to actually drive portfolio performance.
They are used for risk forecasting (as forward-looking tools to predict future volatility), risk analysis (as tools to understand current risk exposures), and risk attribution (as guides to past performance, evaluating actual returns in relation to risk exposures of the portfolio).
In this paper, we discuss the structure of the FactSet Multi-Asset Class (MAC) factor risk framework and the types of factors used in its models and describe estimation techniques used to compute risk factors and the corresponding security returns.
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