Deep learning calibration of option pricing models: some pitfalls and solutions

Addressing model calibration and the issue of no-arbitrage in a deep learning approach


Andrey Itkin considers a classical problem of mathematical finance: the calibration of option pricing models to market data. He highlights some pitfalls in the existing approaches and proposes resolutions that improve both performance and the accuracy of calibration. Itkin also addresses the problem of no-arbitrage pricing when using a trained neural net, which is currently ignored in the literature

Recently, a classical problem of mathematical finance – the

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