Journal of Finance and Economics

Journal of Finance and Economics

ISSN: 2291-4951 (Print)    ISSN: 2291-496X (Online)

Volume 3 (2015), No. 2, Pages 1-10

DOI: 10.12735/jfe.v3i2p01

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Investigating Robust Estimation and Forecasting of Volatilities of Futures with Interquartile Range Models

Lianqian Yin1 

1Finance Department of International Bussiness School, Jinan University, Zhuhai, Guangdong Province, China

URL: https://doi.org/10.12735/jfe.v3i2p01

To Cite this Article     Article Views: 634     Downloads: 354  Since deposited on 2015-07-15

Abstract

A robust proxy of volatility, interquartile range is investigated with the estimation and forecasting of volatility of five American futures using GARCH-type models. With utilizing realized volatility as the yardstick of true underlying volatility, the Mincer-Zarnowitz (MZ) regression and four loss functions in Hansen and Lunde (2005) are employed as criterions for assessing the forecasting ability of competitive volatility models, both in sample and out of sample. It is found that, in samples of NY Light Crude (CL) and NY Natural Gas (NG) which are more volatile and have more extreme outliers than the other three, interquartile range models outperforms those standard models. But in samples of Dow Futures (DJ), Nasdaq 100 Futures (ND) and S&P 500 Futures (SP) which are relatively stable, the results are, however, opposite.

JEL Classifications: F3, G1, C5

Keywords: GARCH model, interquartile range, realized volatility, Mincer-Zarnowitz regression, loss function

To Cite this Article: Yin, L. (2015). Investigating robust estimation and forecasting of volatilities of futures with interquartile range models. Journal of Finance and Economics, 3(2), 1-10. https://doi.org/10.12735/jfe.v3i2p01

Copyright © Lianqian Yin

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This article is published under license to Science and Education Centre of North America. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License.

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Investigating Robust Estimation and Forecasting of Volatilities of Futures with Interquartile Range Models
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