Modelling and asset allocation for financial markets based on a stochastic volatility microstructure model
On the basis of the market microstructure theory, a continuous time microstructure model is proposed for describing the dynamics of financial markets with stochastic volatility property. From the microstructure model, one may obtain the estimates of two state variables, which represent the market excess demand and liquidity respectively but cannot be directly observed. Based on the indirectly obtained excess demand information instead of the prediction of price, a simple asset dynamic allocation approach is investigated. The local linearization method, nonlinear Kalman filter and maximum likelihood method-based estimation approach for the microstructure model proposed is presented. Case studies on the financial markets modelling and the estimated model-based asset dynamic allocation control for the JPY/ USD ( Japanese Yen/US Dollar) exchange rate and Japan TOPIX ( Tokyo stock Price IndeX) show a satisfactory modelling precision and dynamic allocation performance.
market microstructure asset dynamic allocation kalman filter maximum likelihood financial dynamics stochastic difference equations stochastic volatility model parameter estimation