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Term-structure estimation in markets with infrequent trading

Author

Listed:
  • Gonzalo Cortazar

    (Pontificia Universidad Católica de Chile, Chile)

  • Eduardo S. Schwartz

    (University of California at Los Angeles, USA)

  • Lorenzo F. Naranjo

    (New York University, USA)

Abstract

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 © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Gonzalo Cortazar & Eduardo S. Schwartz & Lorenzo F. Naranjo, 2007. "Term-structure estimation in markets with infrequent trading," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(4), pages 353-369.
    • Handle: RePEc:ijf:ijfiec:v:12:y:2007:i:4:p:353-369
    DOI: 10.1002/ijfe.317
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    Cited by:

    1. Fernando A. Broner & Guido Lorenzoni & Sergio L. Schmukler, 2013. "Why Do Emerging Economies Borrow Short Term?," Journal of the European Economic Association, European Economic Association, vol. 11, pages 67-100, January.
    2. Gonzalo Cortazar & Cristobal Millard & Hector Ortega & Eduardo S. Schwartz, 2019. "Commodity Price Forecasts, Futures Prices, and Pricing Models," Management Science, INFORMS, vol. 65(9), pages 4141-4155, September.
    3. Cifuentes, Sebastián & Cortazar, Gonzalo & Ortega, Hector & Schwartz, Eduardo S., 2020. "Expected prices, futures prices and time-varying risk premiums: The case of copper," Resources Policy, Elsevier, vol. 69(C).
    4. Cortazar, Gonzalo & Kovacevic, Ivo & Schwartz, Eduardo S., 2015. "Expected commodity returns and pricing models," Energy Economics, Elsevier, vol. 49(C), pages 60-71.
    5. Gonzalo Cortazar & Cristobal Millard & Hector Ortega & Eduardo S. Schwartz, 2016. "Commodity Price Forecasts, Futures Prices and Pricing Models," NBER Working Papers 22991, National Bureau of Economic Research, Inc.
    6. Alfaro, Rodrigo & Becerra, Juan Sebastian & Sagner, Andres, 2010. "Estimación de la estructura de tasas utilizando el modelo Dinámico Nelson Siegel: resultados para Chile y EEUU [The Dynamic Nelson-Siegel model: empirical results for Chile and US]," MPRA Paper 25912, University Library of Munich, Germany, revised 23 Jun 2010.
    7. Juan Andrés Espinosa Torres & Luis Fernando Melo Velandia & José Fernando Moreno Gutiérrez, 2014. "Estimación de la prima por vencimiento de los TES en pesos del gobierno colombiano," Borradores de Economia 854, Banco de la Republica de Colombia.
    8. Rodrigo Alfaro & Juan Sebastián Becerra, 2011. "Uso de la Aproximación TIR/Duración en la Estructura de Tasas: Resultados Cuantitativos Bajo Nelson - Siegel," Working Papers Central Bank of Chile 616, Central Bank of Chile.
    9. Gonzalo Cortazar & Simon Gutierrez & Hector Ortega, 2016. "Empirical Performance of Commodity Pricing Models: When is it Worthwhile to Use a Stochastic Volatility Specification?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 457-487, May.
    10. Cortazar, Gonzalo & Eterovic, Francisco, 2010. "Can oil prices help estimate commodity futures prices? The cases of copper and silver," Resources Policy, Elsevier, vol. 35(4), pages 283-291, December.
    11. Shigeyuki Hamori & Naoko Hamori, 2009. "International term structure of interest rates in the Euro area," Applied Economics Letters, Taylor & Francis Journals, vol. 16(11), pages 1113-1116.
    12. Juan Andrés Espinosa Torres & Luis Fernando Melo Velandia & José Fernando Moreno Gutiérrez, 2014. "Estimación de la prima por vencimiento de los TES en pesos del gobierno colombiano," Borradores de Economia 12333, Banco de la Republica.
    13. Cortazar, Gonzalo & Beuermann, Diether & Bernales, Alejandro, 2013. "Risk Management with Thinly Traded Securities: Methodology and Implementation," IDB Publications (Working Papers) 4647, Inter-American Development Bank.
    14. Sabit Khakimzhanov & Yerulan Mustafin & Olzhas Kubenbayev & Dulat Atabek, 2019. "Constructing a Yield Curve in a Market with Low Liquidity," Russian Journal of Money and Finance, Bank of Russia, vol. 78(4), pages 71-98, December.

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