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Fixed-point iterative algorithm for SVI model

Author

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  • Yang, Shuzhen
  • Zhang, Wenqing

Abstract

The stochastic volatility inspired (SVI) model is widely used to fit the implied variance smile. Currently, most optimization algorithms for SVI models are strongly dependent on the input starting point. In this study, we develop an efficient iterative algorithm for the SVI model based on a fixed-point least-squares optimizer, further presenting the convergence results for this novel iterative algorithm under certain condition. The experimental evaluation results of our approach using market data demonstrate the advantages of the proposed fixed-point iterative algorithm over the Quasi-explicit SVI method.

Suggested Citation

  • Yang, Shuzhen & Zhang, Wenqing, 2025. "Fixed-point iterative algorithm for SVI model," Finance Research Letters, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:finlet:v:80:y:2025:i:c:s1544612325006385
    DOI: 10.1016/j.frl.2025.107378
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    References listed on IDEAS

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