In this thesis, we investigate the optimal mean-variance portfolio selection models in continuous-time and their extensions with Markov-modulation, also known as regime-switching. These models combine the Markowitz’s idea of the meanvariance portfolio selection with Black-Scholes framework in continuous time and can be converted into linear quadratic stochastic optimal control problems. With the help of the developed stochastic control theories, the explicit expressions of the efficient portfolios and efficient frontiers are derived. With Markov-modulation, the market parameters are allowed to switch between different states defined by a Markov chain, leading to more realistic models. Simulations of these models with fourteen selected asset classes are conducted as well.     «

In this thesis, we investigate the optimal mean-variance portfolio selection models in continuous-time and their extensions with Markov-modulation, also known as regime-switching. These models combine the Markowitz’s idea of the meanvariance portfolio selection with Black-Scholes framework in continuous time and can be converted into linear quadratic stochastic optimal control problems. With the help of the developed stochastic control theories, the explicit expressions of the efficient portfoli...     »