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Neural Networks in Trading: State Space Models

Neural Networks in Trading: State Space Models

In recent times, the paradigm of adapting large models to new tasks has become increasingly widespread. These models are pre-trained on extensive datasets containing arbitrary raw data from a broad spectrum of domains, including text, images, audio, time series, and more.

Neural Networks in Trading: State Space Models
Neural Networks in Trading: State Space Models
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A large number of the models we have reviewed so far are based on the Transformer architecture. However, they may be inefficient when dealing with long sequences. And in this article, we will get acquainted with an alternative direction of time series forecasting based on state space models.
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