Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?

被引：5

作者：

Hoogerheide, Lennart F. ^{[1
]}

Ardia, David ^{[1
]}

Corre, Nienke ^{[1
]}

机构：

[1] Vrije Univ Amsterdam, Dept Econometr, Amsterdam, Netherlands

来源：

ECONOMICS LETTERS | 2012年 / 116卷 / 03期

关键词：

GARCH; Bayesian; KLIC; Censored likelihood; CONDITIONAL HETEROSKEDASTICITY; FORECASTS;

D O I：

10.1016/j.econlet.2012.03.026

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Using GARCH models for density prediction of stock index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between qualities of whole density forecasts, whereas the Bayesian approach exhibits significantly better left-tail forecast accuracy. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：322 / 325

页数：4

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