We consider an homogeneous class of assets, whose returns are driven by an unobservablefactor. We derive approximated prediction and pricing formulas for the future factorvalues and their proxies, when the size n of the class is large. Up to order 1=n, these approximationsinvolve solely...

The recursive prediction and filtering formulas of the Kalman filter are difficult to implementin nonlinear state space models. For Gaussian linear state space models, or for models with qualitativestate variables, the recursive formulas of the filter require the updating of a finite number...