Anas Abdelhakmi – Mathematics and Decision

$\begin{quote} \begin{center} \textbf{A Multi-Period Black-Litterman Model with Desynchronized Expert Views } \end{center} \medskip The Black-Litterman model is a framework for incorporating forward-looking expert views in a portfolio optimization problem. Existing work focuses almost exclusively on single-period problems where the horizon of expert forecasts matches that of the investor. We consider a multi-period generalization of the Black- Litterman model where the investor trades dynamically, and the horizon of expert views may differ from that of the investor. By exploiting an underlying graphical structure relating the asset price process and the forward-looking expert views, we derive the conditional distribution of asset returns when the price process is assumed to be geometric Brownian motion. The new price process is an affine factor model where an adjustment of the unconditional log-price process is a factor, and is closely related to the smoothed estimates of future asset prices. We derive an explicit expression for the optimal dynamic investment policy and analyze the hedging demand associated with the new covariate. More generally, this application shows that smoothed estimates of underlying random processes appear naturally as state variables when there are forward looking forecasts. \end{quote}$