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Implied volatility modeling and forecasting: evidence from China

Yuhan Jiao (School of Finance, Tianjin University of Finance and Economics, Tianjin, China)
Shuxin Guo (School of Economics and Management, Southwest Jiaotong University, Chengdu, China)
Qiang Liu (Institute of Chinese Financial Studies, Southwestern University of Finance and Economics, Chengdu, China)

China Finance Review International

ISSN: 2044-1398

Article publication date: 29 October 2024

38

Abstract

Purpose

Testing several approaches for implied volatility modeling and forecasting.

Design/methodology/approach

Comparative empirical study with four traded options.

Findings

Non-parametric higher-order spline is better than parametric stochastic volatility inspired (SVI) in China.

Research limitations/implications

Our results imply that even though popular on Wall Street, SVI seems not to be utilized by traders and market-makers in China.

Practical implications

Traders may consider higher-order spline as a better method for implied volatility modeling and forecasting.

Originality/value

Propose to model and forecast implied volatility via the fifth-order spline interpolation as a first; initiates studies of the empirical performance of SVI and the fifth-order spline models in implied volatility modeling and forecasting.

Keywords

Acknowledgements

We thank Ye Du for bringing SVI to our attention. All three authors contributed equally to this paper; their last names are in random order. This work was supported by the National Natural Science Foundation of China under Grant numbers 72371208, 71701171, 72073109, and 72071162, and by the Liberal Arts and Social Sciences Foundation of the Chinese Ministry of Education under Grant number 21XJC790003.

Citation

Jiao, Y., Guo, S. and Liu, Q. (2024), "Implied volatility modeling and forecasting: evidence from China", China Finance Review International, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/CFRI-03-2024-0126

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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