Description: This presentation illustrates a calibration model against 60 years of historical data using a pragmatic mixture of filtering, maximum likelihood and method of moments techniques, and compare the resulting model with interest rates in contemporary economic scenario generators.

Description: Prior work indicates that a regime-switching stochastic model with randomized regime parameters creates a more plausible set of extreme paths than do the usual stochastic interest rate models. Generalizing the Black-Karasinski model by randomizing the mean reversion target provides an example. Better to understand such models, as well as to calibrate their parameters without trial and error runs of a stochastic model, this paper uses an asymptotic expansion to estimate the moments of the integrated stochastic process over time. Mention is made of a family of related asymptotic expansions that could be of wider interest.