Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
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This paper proposes markovian models in portfolio theory and risk management. In a first analysis, we describe discrete time optimal allocation models. Then, we examine the investor’s optimal choices either when returns are uniquely determined by their mean and variance or when they are modeled by a Markov chain. Moreover we propose different models to compute VaR and CVaR when returns are modeled by a Markov chain.