Adaptive filtering for stochastic risk premia in bond market

Abstract

We consider the adaptive filtering problem for estimating the randomly changing risk premium and its system parameters for zero-coupon bond models. The term structure model for a zero-coupon bond is formulated including the stochastic risk-premium factor. We specify our observation data from the yield curve and bond data which are used to hedge some option claims. For the xed system parameters, the Kalman filter for the risk-premium and the factor process is constructed first. Secondly, by using the parallel filtering technique and resampling technique commonly used in particle filters, the on-line estimation algorithm for model parameters is constructed. Some simulation studies are nally presented.