Forecasting Financial Risk using Quantum Neural Networks

There has been enormous attention in quantum algorithms for reinforcing machine learning (ML) algorithms. In the current paper, we present quantum neural networks (QNNs) and a method of training which is well in quantum system and is improved with momentum accession and parameter self adaptive algorithm, and we build a new financial risk forecasting model. We apply this model to the empirical research on the financial risk forecasting of some Moroccan companies. Then we will compare the findings with the standard artificial neural network (ANNs).