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We study nonparametric estimation of the volatility function of a diffusion process from discrete data, when the data are blurred by additional noise. This noise can be white or correlated, and serves as a model for microstructure effects in financial modeling, when the data are given on an...
Persistent link: https://www.econbiz.de/10013139169
We develop a minimum distance estimator for dynamic games of incomplete information. We take a two-step approach, following Hotz and Miller (1993), based on the pseudo-model that does not solve the dynamic equilibrium so as to circumvent the potential indeterminacy issues associated with...
Persistent link: https://www.econbiz.de/10011757102
A Bayesian analysis is presented of a time series which is the sum of a stationary component with a smooth spectral density and a deterministic component consisting of a linear combination of a trend and periodic terms. The periodic terms may have known or unknown frequencies. The advantage of...
Persistent link: https://www.econbiz.de/10014029563
estimation approach, e.g., for agent based microsimulation models or complex multifractal models, simulation based estimators …
Persistent link: https://www.econbiz.de/10003548061
We develop a test of equality between two dependence structures estimated through empirical copulas. We provide inference for independent or paired samples. The multiplier central limit theorem is used for calculating p-values of the Crameacute;r-von Mises test statistic. Finite sample properties...
Persistent link: https://www.econbiz.de/10003550857
accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of …
Persistent link: https://www.econbiz.de/10013154330
We propose a simulated maximum likelihood estimator for dynamic models based on non-parametric kernel methods. Our method is designed for models without latent dynamics from which one can simulate observations but cannot obtain a closed-form representation of the likelihood function. Using the...
Persistent link: https://www.econbiz.de/10012722610
We propose a simulated maximum likelihood estimator (SMLE) for general stochastic dynamic models based on nonparametric kernel methods. The method requires that, while the actual likelihood function cannot be written down, we can still simulate observations from the model. From the simulated...
Persistent link: https://www.econbiz.de/10012734210
No, not really, since spectral estimators suffer from small sample and misspecification biases just as VARs do. Spectral estimators are no panacea for implementing long-run restrictions. In addition, when combining VAR coefficients with non-parametric estimates of the spectral density, care...
Persistent link: https://www.econbiz.de/10013128713
This paper proposes computational framework for empirical estimation of Financial Agent-Based Models (FABMs) that does not rely upon restrictive theoretical assumptions. We customise a recent methodology of the Non-Parametric Simulated Maximum Likelihood Estimator (NPSMLE) based on kernel...
Persistent link: https://www.econbiz.de/10011448663