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Evaluating Credit VIX (CDS IV) Prediction Methods with Incremental Batch Learning

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  • Robert Taylor

Abstract

This paper presents the experimental process and results of SVM, Gradient Boosting, and an Attention-GRU Hybrid model in predicting the Implied Volatility of rolled-over five-year spread contracts of credit default swaps (CDS) on European corporate debt during the quarter following mid-May '24, as represented by the iTraxx/Cboe Europe Main 1-Month Volatility Index (BP Volatility). The analysis employs a feature matrix inspired by Merton's determinants of default probability. Our comparative assessment aims to identify strengths in SOTA and classical machine learning methods for financial risk prediction

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  • Robert Taylor, 2024. "Evaluating Credit VIX (CDS IV) Prediction Methods with Incremental Batch Learning," Papers 2408.15404, arXiv.org.
    • Handle: RePEc:arx:papers:2408.15404
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    6. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
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