From Volatility to Variance: A Skew-Enhanced SABR Model and Its Empirical Study in the Chinese Financial Options Market
Wenxuan Zhang, Zhouchi Lin, Benzhuo Lu

TL;DR
This paper introduces a skew-enhanced SABR model that better captures implied volatility asymmetries, demonstrating superior empirical performance in the Chinese options market compared to existing models.
Contribution
The paper develops a novel skew-SABR model with explicit skew parameterization, improving flexibility and accuracy in fitting complex volatility smile patterns.
Findings
Skew-SABR outperforms classical SABR, SVI, polynomial, and spline models in fitting accuracy.
The model maintains simplicity while capturing volatility asymmetries.
Empirical tests show high stability across different market regimes.
Abstract
Accurately characterizing the implied volatility curves is a central challenge in option pricing and risk management. The classical SABR model by Hagan et al. has been widely adopted in practice due to its well-defined stochastic volatility structure and its tractable closed-form approximation for Black implied volatility. However, under complex market conditions, its fitting accuracy for implied volatility curves remains limited. To address this issue, this paper proposes an extended model within the SABR framework, referred to as skew-SABR. Specifically, the proposed approach introduces an extension to the stochastic dynamics of the underlying asset price and its variance process, under which a corresponding Black implied volatility expression is derived. By further simplifying and reorganizing the resulting formula, the implied volatility can be expressed in a form that explicitly…
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