---
title: Neural Tangent Kernel for Nonlinear Implied Volatility Forecasting
url: https://www.ml-quant.com/papers/ssrn/4602820/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4602820
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4602820
featured: 2023-10-18
citations: unknown
topic: Derivatives & Volatility
---


# Neural Tangent Kernel for Nonlinear Implied Volatility Forecasting

The study proposes a Nonlinear Functional Autoregression framework for forecasting implied volatility in financial markets, proving its effectiveness in predicting the S&P 500 Index from 2009 to 2021.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4602820
- Identifier: SSRN 4602820
- Released: 2023-08-28
- First featured: Quant Letter No. 22 (2023-10-18): https://www.ml-quant.com/issues/2023-10-18/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

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