MCMC Based Estimation of Term Structure Models
We develop a state space framework for estimating term structure models, where latent Markovian state variables are mapped non-linearly into observable market data. The measurement equation of our framework is explicitly constructed such that it takes raw market prices and rates as direct inputs. We thus avoid entirely, the need for data preprocessing, such as the use of ad hoc interpolation and data smoothing techniques. As our general estimation approach, we demonstrate how Markov chain Monte Carlo techniques are well suited for handling complex functional relations between state vari-ables and data, parameter restrictions and other features of popular term structure mod-els, which have proved hard to handle for alternative econometric techniques. Our estimation framework therefore handles popular multi-factor model specifications such as exponential affine and quadratic models, but facilitates richer Markovian HJM model specifications as well. Efficient Markov chain Monte Carlo implementations are highly model dependent. Therefore, having developed the general estimation principles of our framework, we demonstrate how one could approach sampler specification for a particular model example which we fit to a panel data set of swap and money market rates.
|Date of creation:||21 May 2001|
|Contact details of provider:|| Postal: The Aarhus School of Business, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark|
Fax: + 45 86 15 19 43
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- J. Durbin & S. J. Koopman, 2000.
"Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives,"
Journal of the Royal Statistical Society Series B,
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- Durbin, J. & Koopman, S.J.M., 1998. "Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives," Discussion Paper 1998-142, Tilburg University, Center for Economic Research.
- Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
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- Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
- Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 371-389, October.
- Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
- Donald W.K. Andrews, 1988. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Cowles Foundation Discussion Papers 877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
- Tomas Björk & Bent Jesper Christensen, 1999. "Interest Rate Dynamics and Consistent Forward Rate Curves," Mathematical Finance, Wiley Blackwell, vol. 9(4), pages 323-348.
- Björk, Tomas & Christensen, Bent Jesper, 1997. "Interest Rate Dynamics and Consistent Forward Rate Curves," SSE/EFI Working Paper Series in Economics and Finance 209, Stockholm School of Economics.
- Duffie, Darrell & Singleton, Kenneth J, 1997. " An Econometric Model of the Term Structure of Interest-Rate Swap Yields," Journal of Finance, American Finance Association, vol. 52(4), pages 1287-1321, September.
- Chan, K C, et al, 1992. " An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-1227, July.
- Tom Doan, "undated". "RATS programs to replicate CKLS(1992) estimation of interest rate models," Statistical Software Components RTZ00035, Boston College Department of Economics.
- Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
- repec:bla:restud:v:65:y:1998:i:3:p:361-93 is not listed on IDEAS
- repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
- Sandmann, Gleb & Koopman, Siem Jan, 1998. "Estimation of stochastic volatility models via Monte Carlo maximum likelihood," Journal of Econometrics, Elsevier, vol. 87(2), pages 271-301, September. Full references (including those not matched with items on IDEAS)
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