In this paper it is shown that the space of stochastic integrals w.r. to a special semimartingal is closed and hence every square integrable random variable admits a best approximation in this space. In terms of financial economics this means that for every contingent claim there exists a...

We consider the simultaneous linear minimax estimation problem in linear models with ellipsoidal constraints imposed on the unknown parameter. Using convex analysis we derive necessary and sufficient optimality conditions for a matrix to define the best linear minimax estimator. For certain...

In this paper we consider regression models with forecast feedback. Agents' expectations are formed via the recursive estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic approximation algorithms whose gain sequence is...