搜索结果: 1-6 共查到“经济学 Maximum likelihood”相关记录6条 . 查询时间(0.078 秒)
Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models
Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models
2015/8/5
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 hand...
上海财经大学经济学院高级计量经济学I课件Lecture 3 Maximum Likelihood Estimation
上海财经大学经济学院 高级计量经济学I 课件 Lecture 3 Maximum Likelihood Estimation
2012/7/16
上海财经大学经济学院高级计量经济学I课件Lecture 3 Maximum Likelihood Estimation.
Maximum likelihood approach for several stochastic volatility models
Maximum likelihood approach several stochastic volatility models Computational Finance
2012/4/28
Volatility measures the amplitude of price fluctuations. Despite it is one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method...
Finite-sample Properties of Maximum Likelihood and Whittle Estimators in EGARCH and FIEGARCH Models
EGARCH fractionally integrated EGARCH maximum likelihood estimator
2010/9/7
EGARCH models for conditionally heteroscedastic time series have attracted a steadily increasing degree of attention in financial econometrics and related fields. These models are able to represent so...
Maximum likelihood estimation of stochastic volatility models
Closed-form likelihood expansions Volatility proxies Heston model GARCH model CEV model
2014/3/13
We develop and implement a method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure,where an optio...
Maximum-Likelihood Estimation of Discretely-Sampled Diffusions: A Closed-Form Approximation Approach
Maximum-Likelihood Estimation Discretely-Sampled Diffusions A Closed-Form Approximation Approach
2014/3/13
Maximum-Likelihood Estimation of Discretely-Sampled Diffusions: A Closed-Form Approximation Approach.