Decomposing the Sri Lanka Yield Curve Using Principal Component Analysis to Examine the Term Structure of the Interest Rate - K P N Sanjeewa Dayarathne; Uthayasanker Thayasivam (Engineering Proceedings)
In this study, we delve into the dynamics of the Sri Lankan government bond market, building upon prior research that focused on the application of principal component analysis (PCA) in modelling sovereign yield curves. Our analysis encompasses data spanning from January 2010 to August 2022. The study applied several PCA variants such as multivariate PCA, Randomized PCA, Incremental PCA, Sparse PCA, Functional PCA, and Kernel PCA on smoothed data. Kernel PCA was found to explain the majority of the variation associated with the data. Findings reveal that the first principal component accounted for a substantial 97.69% of the variations in yield curve movements, 2nd PCA accounted for 1.88%, and 3rd for 0.42%. These results align with previous research, which generally posits that the initial three principal components tend to elucidate around 95% of the fluctuations within the term structure of yields. Our results question the empirical findings, which state that the 1st PCA represents the longer tenor of the yield curve. In Sri Lanka, instead, the 1st PCA represents the 3-year bond yields. It may be because of the liquidity constraints in underdeveloped frontier markets, where longer tenor yields do not react fast enough to reflect the movement of the yield curve. The 2nd PCA represents the slope of the yield curve which is the yield difference of a 10-year T-Bond and 3 months T-Bill. The 3rd PCA which represents the curvature of the yield curve attributed to 2 × 3 years T-Bond yield—3 months T-bill10-year T-Bond.