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We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models … unobservable volatility state, to an approximate likelihood procedure where the volatility state is replaced by the implied … volatility of a short dated at-the-money option. We find that the approximation results in a negligible loss of accuracy. We …
Persistent link: https://www.econbiz.de/10012767654
We present an econometric method for estimating the parameters of a diffusion model from discretely sampled data. The estimator is transparent, adaptive, and inherits the asymptotic properties of the generally unattainable maximum likelihood estimator. We use this method to estimate a new...
Persistent link: https://www.econbiz.de/10013235636
stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it … cross-section of yields well but not volatility while unspanned models fit volatility at the expense of fitting the cross-section …
Persistent link: https://www.econbiz.de/10013053780
We develop and implement a technique for closed-form maximum likelihood estimation (MLE) of multifactor affine yield models. We derive closed-form approximations to likelihoods for nine Dai and Singleton (2000) affine models. Simulations show our technique very accurately approximates true (but...
Persistent link: https://www.econbiz.de/10012762894
When a continuous-time diffusion is observed only at discrete dates, not necessarily close together, the likelihood function of the observations is in most cases not explicitly computable. Researchers have relied on simulations of sample paths in between the observations points, or numerical...
Persistent link: https://www.econbiz.de/10013216521
A solution method and an estimation method for nonlinear rational expectations models are presented in this paper. The solution method can be used in forecasting and policy applications and can handle models with serial correlation and multiple viewpoint dates. When applied to linear models, the...
Persistent link: https://www.econbiz.de/10013220429
A well known result is that the Gaussian log-likelihood can be expressed as the sum over different frequency components. This implies that the likelihood ratio statistic has a similar linear decomposition. We exploit these observations to devise diagnostic methods that are useful for...
Persistent link: https://www.econbiz.de/10013240316
In this paper, we consider the parametric estimation problem for continuous time stochastic processes described by general first-order nonlinear stochastic differential equations of the Ito type. We characterize the likelihood function of a discretely-sampled set of observations as the solution...
Persistent link: https://www.econbiz.de/10013244771
This working paper provides some preliminary results on the computational feasibility of nonlinear full information maximum likelihood (NECML) estimation. Severa1 of the test cases presented were also subjected to nonlinear three stage least square (NLBSLS) estimation in order to illustrate the...
Persistent link: https://www.econbiz.de/10013313666
The possibility of exact maximum likelihood estimation of many observation-driven models remains an open question. Often only approximate maximum likelihood estimation is attempted, because the unconditional density needed for exact estimation is not known in closed form. Using simulation and...
Persistent link: https://www.econbiz.de/10013308639