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Optimal Stochastic Decensoring and Applications to Calibration of Market Models

Computational Finance 2017-12-20 v2 Probability
Authors: Anastasis Kratsios
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Abstract

Typically flat filling, linear or polynomial interpolation methods to generate missing historical data. We introduce a novel optimal method for recreating data generated by a diffusion process. The results are then applied to recreate historical data for stocks.

Keywords

optimal decensoring diffusion process missing data stock historical data market model calibration

Cite

@article{arxiv.1712.04844,
  title  = {Optimal Stochastic Decensoring and Applications to Calibration of Market Models},
  author = {Anastasis Kratsios},
  journal= {arXiv preprint arXiv:1712.04844},
  year   = {2017}
}

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