Risk factor models are now widely used by fund managers to construct portfolios and assess both return and risk based on the behaviour of common risk factors to which the portfolios are exposed. However, fund managers often have subjective views on these risk factors that they may wish to incorporate into their asset allocation strategies.
This study introduces an extension of the Black-Litterman model that allows views to be applied to risk factors rather than individual assets, greatly simplifying the process since the number of factors is typically much smaller than the number of assets in a portfolio.
The concept of risk premia is central to portfolio allocation, but is typically assessed at the asset level. In our framework, risk premia are formulated and analyzed at the factor level. This theoretical advance allows the manager to calculate factor risk premia, formulate views based on these premia, and incorporate them into the portfolio optimization process to create an adjusted portfolio that is consistent with the manager’s expectations.
This new framework has many applications. It allows fund managers to analyze the market’s implied risk premia and identify the key drivers of market returns. In addition, the model facilitates comparisons between an actively managed portfolio and its benchmark by calculating how both are priced and identifying the factors that differentiate them.
You can now read the full whitepaper at the link below
