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Learning parameter dependence for Fourier-based option pricing with tensor networks
In this study, we propose a pricing method, where, by a tensor learning algorithm, we build tensor trains that approximate functions appearing in FT-based option pricing with their parameter dependence and efficiently calculate the option price for the varying input parameters.
Time series generation for option pricing on quantum computers using tensor network
To validate our approach, taking the Heston model as a target, we conduct numerical experiments to generate time series in the model.
The cross-sectional stock return predictions via quantum neural network and tensor network
In this paper, we investigate the application of quantum and quantum-inspired machine learning algorithms to stock return predictions.
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