Discrete Volatility Models Using Deep Learning. Improving the approach of Horvath, Blanka and Muguruza, Aitor and Tomas, Mehdi, Deep Learning Volatility (January 24, 2019). Available at SSRN: https://ssrn.com/abstract=3322085 or http://dx.doi.org/10.2139/ssrn.3322085
The goal of this thesis is to show that it is possible to use NNs for efficient and accurat pricing, as well as calibration, of discrete volatility models (mainly HNG as first reference) NN-visualisation tool: http://alexlenail.me/NN-SVG/LeNet.html Master Thesis: https://www.overleaf.com/project/5e349d09b88ae3000144bbd2
Discrete Volatility Models Using Deep Learning. Improving the approach of Horvath, Blanka and Muguruza, Aitor and Tomas, Mehdi, Deep Learning Volatility (January 24, 2019). Available at SSRN: https://ssrn.com/abstract=3322085 or http://dx.doi.org/10.2139/ssrn.3322085