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BOUNDED UNCERTAINTY MODELS IN FINANCE: PARAMETER ESTIMATION AND FORECASTING
Laurent El Ghaoui* and Giuseppe Calafiore**
* Department of Electrical Engineering and Computer
Science, UC Berkeley, CA. e-mail:
elghaoui@eecs.berkeley.edu
** Dipartimento di Automatica e Informatica, Politecnico
di Torino, Italy. e-mail: calafiore@polito.it
In this paper we consider the problem of modelling observed data using a class of multivariate models with unknown-but-bounded (ubb) noise and uncertainty. Standard ARX models with additive and multiplicative bounded noise belong to the considered class, as well as the deterministic counterpart of ARCH models extensively used in econometrics. We outline a method to fit these models based on historical data, and discuss the issues of set-valued forecasting.
Keywords: Identification, Bounded uncertainty, Semidefinite programming, Financial modelling
Session slot T-We-A02: Set-membership estimation for uncertain dynamics and control/Area code 3a : Modelling, Identification and Signal Processing
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