Decomposition of Japanese Yen Interest Rate Data Through Local Regression

Seven different Japanese Yen interest rates recorded on a daily basis for the period from 1986 to 1992 are simultaneously analyzed. By introducing a new concept of ‘short term trend’, we decompose each interest rate series into three components, ‘long termtrend’, ‘short term trend’ and ‘irregular’. It is obtained by a two step lowess smoothing technique. After that, a multivariate autoregressive model (MAR) is fitted to the vector valued time series obtained by combining those seven irregular components. The decomposition and MAR model fitting were quite satisfactory. It enables us to understand well various aspects of interest rate series from the trends, the MAR (2) coefficients and its residuals. The result is compared with the decomposition through sabl and the advantages of our procedure will be demonstrated in relations to other parametric model fitting like ARCH or GARCH. Based on the decomposition we can have better daily prediction and more stable long term forecasting. Copyright Kluwer Academic Publishers 1997