• Corpus ID: 52942746

Deep calibration of rough stochastic volatility models

@article{Bayer2018DeepCO,
  title={Deep calibration of rough stochastic volatility models},
  author={Christian Bayer and Benjamin Stemper},
  journal={ArXiv},
  year={2018},
  volume={abs/1810.03399}
}
Techniques from deep learning play a more and more important role for the important task of calibration of financial models. The pioneering paper by Hernandez [Risk, 2017] was a catalyst for resurfacing interest in research in this area. In this paper we advocate an alternative (two-step) approach using deep learning techniques solely to learn the pricing map -- from model parameters to prices or implied volatilities -- rather than directly the calibrated model parameters as a function of… 

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