HyperIV: Real-time Implied Volatility Smoothing

We propose HyperIV, a novel approach for real-time implied volatility smoothing that eliminates the need for traditional calibration procedures. Our method employs a hypernetwork to generate parameters for a compact neural network that constructs complete volatility surfaces within 2 milliseconds, using only 9 market observations. Moreover, the generated surfaces are guaranteed to be free of static arbitrage. Extensive experiments across 8 index options demonstrate that HyperIV achieves superior accuracy compared to existing methods while maintaining computational efficiency. The model also exhibits strong cross-asset generalization capabilities, indicating broader applicability across different market instruments. These key features – rapid adaptation to market conditions, guaranteed absence of arbitrage, and minimal data requirements – make HyperIV particularly valuable for real-time trading applications. We make code available at https: //github. com/qmfin/hyperiv.

Authors

• Yongxin Yang
• Wenqi Chen
• Chao Shu
• Timothy M. Hospedales

Keywords

• Implied volatility surface
• quantitative finance
• hypernetworks