EXACT FAST SMOOTHING IN SWITCHING MODELS WITH APPLICATION TO STOCHASTIC VOLATILITY
Résumé
We consider the problem of statistical smoothing in nonlin-ear non-Gaussian systems. Our novel method relies on a Markov-switching model to operate recursively on series of noisy input data to produce an estimate of the underlying system state. We show through a set of experiments that our technique is efficient within the framework of the stochastic volatility model.
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