Applications of tensor neural networks to financial forecasting in incomplete markets

pre-agreed price. The problem of what an option is worth is usually solved using costly numerical simulation methods.
We will apply Deep Learning methods to solve the Option Pricing Problem. This cutting edge technique has the advantage that, once trained, the model can simulate many scenarios at a low computational cost. Unfortunately, training is costly and can be unstable.
Our original contribution is to use Tensor Networks to improve this Deep Learning model.