Sig-SDEs model for quantitative finance

@article{Arribas2020SigSDEsMF,
  title={Sig-SDEs model for quantitative finance},
  author={Imanol Perez Arribas and Cristopher Salvi and Lukasz Szpruch},
  journal={Proceedings of the First ACM International Conference on AI in Finance},
  year={2020}
}
Mathematical models, calibrated to data, have become ubiquitous to make key decision processes in modern quantitative finance. In this work, we propose a novel framework for data-driven model selection by integrating a classical quantitative setup with a generative modelling approach. Leveraging the properties of the signature, a well-known path-transform from stochastic analysis that recently emerged as leading machine learning technology for learning time-series data, we develop the Sig-SDE… 

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