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There are two issues that are of central importance in term structure analysis. One is the modeling and estimation of the current term structure of spot rates. The second is the modeling and estimation of the dynamics of the term structure. These two issues have been addressed independently in the literature. The methods that have been proposed assume a sufficiently complete price data set and are generally implemented separately. However, when the methods are applied to markets with sparse bond price, results are unsatisfactory. We develop a method for jointly estimating the current term structure and its dynamics for markets with low-frequency transactions. We propose solving both issues by using a dynamic term structure model estimated from incomplete panel data. To achieve this, we modify the standard Kalman filter approach to deal with the missing-observation problem. In this way, we can use historic price data in a dynamic model to estimate the current term structure. With this approach we are able to obtain an estimate of the current term structure even for days with an arbitrary low number of price observations. The proposed methodology can be applied to a broad class of continuous-time term-structure models with any number of stochastic factors. To show the implementation of the approach, we estimate a three-factor generalized-Vasicek model using Chilean government bond price data. The approach, however, may be used in any market with low-frequency transactions, a common characteristic of many emerging markets.

There are two issues that are of central importance in term-structure analysis. One is the modelling and estimation of the current term structure of spot rates. The second is the modelling and estimation of the dynamics of the term structure. These two issues have been addressed independently in the literature. The methods that have been proposed assume a sufficiently complete price data set and are generally implemented separately. However, there are serious problems when these methods are applied to markets with sparse bond prices. We develop a method for jointly estimating the current term-structure and its dynamics for markets with infrequent trading. We propose solving both issues by using a dynamic term-structure model estimated from incomplete panel-data. To achieve this, we modify the standard Kalman filter approach to deal with the missing-observation problem. In this way, we can use historic price data in a dynamic model to estimate the current term structure. With this approach we are able to obtain an estimate of the current term structure even for days with an arbitrary low number of price observations. The proposed methodology can be applied to a broad class of continuous-time term-structure models with any number of stochastic factors. To show the implementation of the approach, we estimate a three-factor generalized-Vasicek model using Chilean government bond price data. The approach, however, may be used in any market with infrequent trading, a common characteristic of many emerging markets. Copyright (c) 2007 John Wiley & Sons, Ltd.

A common European bond would yield a common European Monetary Union risk free rate. We present tentative estimates of this common risk free for the European Monetary Union countries from 2004 to 2009 using variables motivated by a theoretical portfolio selection model. First, we analyze the determinants of EMU sovereign yield spreads and find significant effects of the credit quality, macro, correlation, and liquidity variables. However, their effects are different before and after the current financial crisis, being stronger in the latter period. Robustness tests with different data frequencies, benchmarks, liquidity variables, cross section regressions and balanced panels confirm the initial results. We propose four different estimates of the common risk free rate and show that, in most cases, this common rate could imply savings in borrowing costs for all the countries involved.

A common European bond would yield a common European Monetary Union risk free rate. We present tentative estimates of this common risk free for the European Monetary Union countries from 2004 to 2009 using variables motivated by a theoretical portfolio selection model. First, we analyze the determinants of EMU sovereign yield spreads and find significant effects of the credit quality, macro, correlation, and liquidity variables. However, their effects are different before and after the current financial crisis, being stronger in the latter period. Robustness tests with different data frequencies, benchmarks, liquidity variables, cross section regressions and balanced panels confirm the initial results. We propose four different estimates of the common risk free rate and show that, in most cases, this common rate could imply savings in borrowing costs for all the countries involved.