Implied volatility modeling and forecasting: evidence from China
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
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