Volatility forecasting using high frequency data: Evidence from stock markets

被引：35

作者：

Celik, Sibel ^{[1
]}

Ergin, Huseyin ^{[2
]}

机构：

[1] Dumlupinar Univ, Sch Appl Sci, Ankara, Turkey

[2] Dumlupinar Univ, Business Adm, Kutahya, Turkey

来源：

ECONOMIC MODELLING | 2014年 / 36卷

关键词：

Volatility; Realized volatility; High frequency data; Price jumps; RETURN; INDEX;

D O I：

10.1016/j.econmod.2013.09.038

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

The paper aims to suggest the best volatility forecasting model for stock markets in Turkey. The findings of this paper support the superiority of high frequency based volatility forecasting models over traditional GARCH models. MIDAS and HAR-RV-CJ models are found to be the best among high frequency based volatility forecasting models. Moreover, MIDAS model performs better in crisis period. The findings of paper are important for financial institutions, investors and policy makers. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：176 / 190

页数：15

共 27 条

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Alper C. Emre, 2009, MIDAS VOLATILI UNPUB

[2]

Andersen T. G., 1999, REALIZED VOLAT UNPUB

[3]

Andersen T. G., 2000, Multinational Finance Journal, V4, P159, DOI [10.17578/4-3/4-2, DOI 10.17578/4-3/4-2]

[4] The distribution of realized stock return volatility [J].