Forecasting the term structure of interest rates in Kenya using Bayesian models post 2007-2008 financial crisis

Abstract

Despite the growing significant advances in the modelling of the term structure of interest rates after the great recession of 2008, little attention has been paid to the problem of forecasting the term structure which has proven to be an important rate in several products and instruments offered by financial institutions. This dissertation makes use of a Dynamic Nelson-Siegel model with a Time-Varying Vector Auto- Regressive component to fit a model and forecast the h-step ahead expected yield. The model makes use of four parameters representing a decay factor, level, slope and curvature latent factors estimated with high efficiency. We propose to use our DNS-TV-VAR model to estimate our factors and demonstrate the model consistency to a range of stylized yield curve initial data. We apply the model in forecasting a term structure for short and long horizons and conclude that the forecasts appear more accurate for long horizons.