Modelling and forecasting international interest rate spreads: UK, Germany, Japan and the US

The interest rate spread is of importance to policy-makers and finance professionals in asset allocation and is a common measure of financial market stress. In this paper, we model and forecast the interest rate spreads for a number of countries using two well-known continuous time models and discrete time ARMA and ARFIMA models. We use monthly and weekly data which cover the recent global financial market crisis of 2007-2009 for Germany, Japan, UK and the USA. We find that the Merton's continuous-time model outperforms all other model specifications in terms of the mean of the forecast errors, MAPE and RMSE

US and Canadian term structures of interest rates: A forecasting comparison

This paper provides empirical evidence for the US and Canadian yield curves using a one- and two-factor Generalised Vasicek model, using a data set comprised of daily panel data over the period between 2003 and 2011, which includes the recent global financial crisis. The two-factor model is found to have a good fit for both the US and Canadian yield curves. We also compare the forecasting performance of the term structure model with those from ARIMA, ARFIMA and Nelson-Siegel models. We find that for Canada the Nelson-Siegel model dominates, while for the US the ARFIMA model has a satisfactory performance

Empirical analysis of the US swap curve

This paper provides an empirical analysis of the US swap rate curve using principal components analysis (PCA) to identify the factors which explain the variation in the data. We also investigate the forecasting performance of different econometric models for individual maturities across the curve using daily data over the period 1998 to 2011. The PCA analysis indicates that the first two factors explain approximately 99.76% of the cumulative variation in the sample. We also find that a continuous time modelling approach has a satisfactory performance across the curve based on the RMSE

Maximum likelihood and Gaussian estimation of continuous time models in finance

Ministry of Education, Singapore under its Academic Research Funding Tier

Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance

Published in Handbook of financial time series, 2008, https://doi.org/10.1007/978-3-540-71297-8_22</p

Modelling the UK and Euro yield curves using the Generalized Vasicek model: Empirical results from panel data for one and two factor models

In this paper we estimate the Generalized Vasicek term structure model using United Kingdom and Euro panel data. The model is presented in a state space form and the Kalman filter is used to estimate the unobserved state variables and the parameters of the model. One and two factor versions are estimated and the empirical results provide evidence that the two factor model provides a good description of the UK and Euro yield curves

Rex Bergstrom's contributions to continuous time macroeconometric modelling

This paper reviews the contributions of Rex Bergstrom to the development of continuous time dynamic disequilibrium macroeconomic modeling since the early 1960s. The models provide an elegant integration of economic theory with analysis of steady state and stability properties. The subsequent contributions of his Ph.D. students, spawned by Bergstrom’s work over the years, is also reviewed. It was Bergstrom’s early pioneering vision 40 years ago of formulating and estimating continuous time models that underlies much of the research in that area of econometrics and finance today

Gaussian estimation of continuous time diffusions of UK interest rates

This paper estimates stochastic differential equation models for the interest rate dynamics of the United Kingdom bond market using Gaussian estimation econometric methods and monthly data over the period 1970–2010 using a range of maturities. Gaussian estimates of single and two equation models indicate that there is a relationship between the level of rates and the volatility of rates across the maturities. In addition, there is some evidence of feedback effects