Abstract:
In this study, I evaluate two versions of the Nelson and Siegel (1987) model, namely
the Nelson-Siegel model using the methodology presented in Diebold and Li (2006)
and Nelson-Siegel-Svensson model (1994), with the purpose of fitting the current yield
curve and forecasting the yield curve for the Sri Lankan government securities market.
The study finds that using the Svensson model which has an additional curvature factor
compared to the Nelson -Siegel (Diebold and Li model) leads to a better in-sample fit
of the term structure, and thus a better fit of the yield curve is observed. The superior
in-sample fit of the Svensson model is clearly visible in the graphical outputs obtained
and is further supported by the higher 𝑅
2
and lower RMSE associated with the
Svensson model.
The results obtained are robust for recent events such as the COVID -19 pandemic that
affected the country.
Forecasting performance of the two models, indicated opposite results compared to
results obtained in the estimation of yield curves. Yield curves from Nelson-Siegel
(Diebold and Li) model are predicted better compared to the Svensson model under
both the short forecast horizon of one month and longer forecast horizon of six months.
This is clearly exhibited in the lower RMSE associated with the Nelson -Siegel
(Diebold and Li) model under the rolling window forecasting design that was applied
using an AR(1) forecasting model.
Citation:
Yapa, L.T.S. (2022). Estimating and forecasting the yield curve : Sri Lankan government securities market [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21211