References
- Ahn, D. and Gao, B. (1999). A parametric nonlinear model of term structure dynamics, The Review of Financial Studies, 12, 721-762. https://doi.org/10.1093/rfs/12.4.721
- Ait-Sahalia, Y. (1999). Transition densities for interest rate and other nonlinear diffusions, Journal of Finance, 54, 1361-1395. https://doi.org/10.1111/0022-1082.00149
- Ait-Sahalia, Y. (2002). Maximum-likelihood estimation of discretely-sampled diffusions: A closed-form approximation approach, Econometrica, 70, 223-262. https://doi.org/10.1111/1468-0262.00274
- Ait-Sahalia, Y. (2006). Likelihood inference for diffusions: A survey, Frontiers in Statistics: In Honor of Peter J. Bickel's 65th Birthday, Imperial College Press.
- Ait-Sahalia, Y. and Yu, J. (2006). Saddlepoint approximations for continuous-Time Markov processes, Journal of Econometrics, 134, 507-551. https://doi.org/10.1016/j.jeconom.2005.07.004
- Beskos, A., Papaspiliopoulos, O., Robert, G. O. and Fearnhead, P. (2006). Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes, The Journal of the Royal Statistical Society, Series B, 68, 333-383. https://doi.org/10.1111/j.1467-9868.2006.00552.x
- Brandt, M. and Santa-Clara, P. (2001). Simulated Likelihood Estimation of Diffusions with an Application to Exchange Rate Dynamics in Incomplete markets, Technical Report.
- Chan, K. C., Karolyi, G. A., Longstaff, F. A. and Sanders, A. B. (1992). An empirical comparison of alternative models of the short-term interest rate, Journal of Finance, 47, 1209-1227. https://doi.org/10.2307/2328983
- Cox, J. (1975). Notes on option pricing I: Constant elasticity of variance diffusions, Working paper, Stanford University (reprinted in Journal of Portfolio Management, 1996, 22, 15-17).
- Cox, J., Ingersoll, J. and Ross, S. (1985). A theory of the term structure of interest rates, Econometrica, 53, 385-407. https://doi.org/10.2307/1911242
- Dacunha-Castelle, D. and Florens-Zmirou, D. (1986). Estimation of the coefficients of a diffusion from discrete observations, Stochastics, 19, 263-284. https://doi.org/10.1080/17442508608833428
- Durham, G. and Gallant, R. (2001). Numerical Techniques for Maximum Likelihood Estimation of Continuous-Time Diffusion Processes, Technical report.
- Elerian, O., Chib, S. and Shephard, N. (2001). Likelihood inference for discretely observed nonlinear diffusions, Econometrika, 69, 959-993. https://doi.org/10.1111/1468-0262.00226
- Eraker, B. (2001). MCMC analysis of diffusion models with application to finance, Journal of Business & Economic Statistics, 19, 177-191. https://doi.org/10.1198/073500101316970403
- Hurn, A., Jeisman, J. and Lindsay, K. (2007). Seeing the wood for the trees: A critical evaluation of methods to estimate the parameters of stochastic differential equations, Journal of Financial Econometrics, 5, 390-455. https://doi.org/10.1093/jjfinec/nbm009
- Kloeden, P. and Platen, E. (1999). Numerical Solution of Stochastic Differential Equations, Springer.
- Nicolau, J. (2002). A new technique for simulating the likelihood of stochastic differential equations, Econometrics Journal, 5, 91-102. https://doi.org/10.1111/1368-423X.t01-1-00075
- Oksendall, B. (2003). Stochastic Differential Equations: An Introduction with Applications, Springer.
- Pederson, A. R. (1995). A new approach to maximum likelihood estimation for stochastic differential equations based on discrete observations, Scandinavian Journal of Statistics, 22, 55-71.
- Rogers, L. (1985). Smooth transitional densities for one-dimensional diffusions, Bulletin of the London Mathematical Society, 17, 157-161. https://doi.org/10.1112/blms/17.2.157
- Vasicek, O. (1977). An equilibrium characterization of the term structure, Journal of Financial Economics, 5, 177-188. https://doi.org/10.1016/0304-405X(77)90016-2
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