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Traditional methods of modeling and estimating the term structure of interest rates assume that bonds are fre- quently traded and have a complete data set. In this paper, we use the Kalman filter approach to estimate and compare the term structure of assets with complete and sparse data set in the same country. Brazil offers a unique case study because the stock of government bonds is one of the largest in the world. We test for two types of financial assets: government bonds (which are characterized by infrequent trading) and One-Day Interbank Deposit Futures (which are the most liquid interest rate derivative in the Brazilian market). Our results indicate that the model performs well in fitting observed yields of both government bonds and interest rates futures contracts. Most importantly, out-of-sample errors for government bonds are very close to those of interest rates futures contracts, which suggests that the model can be successfully used for forecasting yield curves of sporadically traded assets.

Estimating and Comparing the Term Structure of Interest Rates for Assets with Frequent and Infrequent Trading