Choosing News Topics to Explain Stock Market Returns

We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment of the topic model... (read more)

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METHOD TYPE
LDA
Dimensionality Reduction
Random Search
Hyperparameter Search