An Assessment of Alternative Models of Interest Rate Volatility in the Bond Market in Kenya
Abstract
This research project focuses on estimating volatility in interest rates in the bond market
in Kenya. It assesses the linear and non linear models of estimating volatility. Data comprising
of redemption yields for all bonds issued since January 1995 was obtained from
NSE. In the analysis six different models were assessed in estimating volatility. These six
models were the random walk, moving average (MA), autoregressive (AR), autoregressive
moving average (ARMA), autoregressive integrated moving average (ARIMA), autoregressive
conditional heteroskedasticity (ARCH) and generalised autoregressive conditional
heteroskedasticity (GARCH). The Akaike Information Criterion (AIC) were used
to rank the models. This study found out that the bond market in Kenya mainly comprised
of treasury bonds and twelve listed corporate bonds. It was also observed from the
data that the number of participants and trading frequency still remain low as compared
to other developed bond markets. The non-linear models ie ARCH and GARCH models
scored the lowest AIC values. From the findings of this study it was concluded that nonlinear
models better estimate volatility as compared to linear models.
Citation
MBA Thesis 2012Sponsorhip
University of NairobiPublisher
school of Business
Description
Master Thesis