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Interpretable Latent Variables in Deep State Space Models
We introduce a new version of deep state-space models (DSSMs) that combines a recurrent neural network with a state-space framework to forecast time series data.
A News-based Machine Learning Model for Adaptive Asset Pricing
The paper proposes a new asset pricing model -- the News Embedding UMAP Selection (NEUS) model, to explain and predict the stock returns based on the financial news.
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