Nonlinear, non-Gaussian state space models have found wide applications in many areas. Since such models usually do not allow for an analytical representation of their likelihood function, sequential Monte Carlo or particle filter methods are mostly applied to estimate their parameters. Since...

This paper generalizes the popular stochastic volatility in mean model of Koopman and Hol Uspensky (2002) to allow for time-varying parameters in the conditional mean. The estimation of this extension is nontrival since the volatility appears in both the conditional mean and the conditional...

Chapter 1 Introduction -- Chapter 2 Efficient markets -- Chapter 3 Equity premium -- Chapter 4 The dividend ratio model -- Chapter 5 Bond valuation -- Chapter 6 Yield curves -- Chapter 7 Term structure models -- Chapter 8 Real estate market -- Chapter 9 Derivative securities -- Chapter 10...