HMM based scenario generation for an investment optimisation problem (original) (raw)

Annals of Operations Research, 2012

Abstract

The Geometric Brownian motion (GBM) is a standard method for modelling financial time series. An important criticism of this method is that the parameters of the GBM are assumed to be constants; due to this fact, important features of the time series, like extreme behaviour or volatility clustering cannot be captured. We propose an approach by which the parameters of

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