کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5097539 | 1376595 | 2007 | 41 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An efficient nonparametric estimator for models with nonlinear dependence
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: An efficient nonparametric estimator for models with nonlinear dependence An efficient nonparametric estimator for models with nonlinear dependence](/preview/png/5097539.png)
چکیده انگلیسی
We provide a convenient econometric framework for the analysis of nonlinear dependence in financial applications. We introduce models with constrained nonparametric dependence, which specify the conditional distribution or the copula in terms of a one-dimensional functional parameter. Our approach is intermediate between standard parametric specifications (which are in general too restrictive) and the fully unrestricted approach (which suffers from the curse of dimensionality). We introduce a nonparametric estimator defined by minimizing a chi-square distance between the constrained densities in the family and an unconstrained kernel estimator of the density. We derive the nonparametric efficiency bound for linear forms and show that the minimum chi-square estimator is nonparametrically efficient for linear forms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 137, Issue 1, March 2007, Pages 189-229
Journal: Journal of Econometrics - Volume 137, Issue 1, March 2007, Pages 189-229
نویسندگان
Patrick Gagliardini, Christian Gouriéroux,