Nonparametric Time Series Analysis of the Conditional Mean and Volatility Functions for the COP/USD Exchange Rate Returns

被引：0

作者：

Gallon, Santiago ^{[1
,3
]}

Gomez, Karoll ^{[2
,3
]}

机构：

[1] Univ Antioquia, Dept Econ, Fac Ciencias Econ, Dept Estadist & Matemat, Medellin, Colombia

[2] Univ Nacl Colombia, Fac Ciencias Humanas & Econ, Dept Econ, Medellin, Colombia

[3] Univ Antioquia, Grp Econometria Aplicada, Fac Ciencias Econ, Medellin, Colombia

来源：

REVISTA COLOMBIANA DE ESTADISTICA | 2010年 / 33卷 / 01期

关键词：

Nonparametric regression; Local polynomial regression; Nonlinear time series; Variance function estimation; Autoregressive conditional heteroscedasticity; Time series analysis; MODELS; HETEROSCEDASTICITY; REGRESSION; VARIANCE;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The modeling and estimation of the conditional volatility associated with a stochastic process usually have been based on parametric ARCH-type and stochastic volatility models. These time series models are very powerful in representing the dynamic stochastic properties of the data generating process only in the parametric functions are correctly specified. The nonparametric approach acquires importance as a complementary and flexible method to explore these properties without imposing particular functional forms on the conditional moments of process. This paper presents an application of non-parametric time series methods to estimate the conditional volatility function of the COP/USD exchange rate returns. Additionally, we estimate the conditional mean function under this approach.

引用

页码：25 / 41

页数：17