Prediction of Realized Volatility Based on Realized-GARCH-Kernel Model: The Comparison of CHINA and US

42 Pages Posted: 28 Mar 2019 Last revised: 2 Sep 2021

See all articles by Jiazhen Wang

Jiazhen Wang

Zhejiang University - College of Economics

Yuexiang Jiang

Zhejiang University - College of Economics

Yanjian Zhu

Zhejiang University

Jing Yu

The University of Sydney; Financial Research Network (FIRN)

Date Written: January 15, 2019

Abstract

We propose a Realized-GARCH-Kernel model to predict realized volatilities of 50 ETF in China and S&P500 index in U.S..The Kernel density fitting on disturbance term and semi-parametric method make our model perform well both statistically and economically. First, our model has the lowest in- and out-of-sample prediction errors among five comparable prediction models. The result is robust in eight measures of realized volatility. Second, in both China and U.S. markets, straddle option trading strategies with volatilities predicted with our model generate larger monthly profit and greater Sharpe ratio. Our model is useful in practical investment.

Keywords: Realized-GARCH-Kernel model; Kernel density; realized volatility; straddle

JEL Classification: G17, C14

Suggested Citation

Wang, Jiazhen and Jiang, Yuexiang and Zhu, Yanjian and Yu, Jing, Prediction of Realized Volatility Based on Realized-GARCH-Kernel Model: The Comparison of CHINA and US (January 15, 2019). 2019 Financial Markets & Corporate Governance Conference, Available at SSRN: https://ssrn.com/abstract=3316068 or http://dx.doi.org/10.2139/ssrn.3316068

Jiazhen Wang

Zhejiang University - College of Economics ( email )

Yuquan Campus 38 Zheda Road
Hangzhou, Zhejiang 310027
China

Yuexiang Jiang

Zhejiang University - College of Economics ( email )

Yuquan Campus 38 Zheda Road
Hangzhou, Zhejiang 310027
China

Yanjian Zhu (Contact Author)

Zhejiang University ( email )

38 Zheda Road
Hangzhou, Zhejiang 310027
China
(86)87951610 (Phone)
(86)87951610 (Fax)

Jing Yu

The University of Sydney ( email )

University of Sydney
Sydney, NSW 2006
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

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