Extension and Industrialisation of Generative Neural Networks for Financial Time Series Modelling and Forecasting

In this work, we built up on our previous work in generative modelling, extending our GAN model designed for the conditional generation of financial time series. In particular, the contribution of this research activity was twofold: (i) we modified the generator so as to obtain a recurrent sequence-to-sequence architecture, and (ii) we added a self-attention mechanism, bringing improved performance and interpretability.

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