Papers with 8K-powered deep learning model

    1 papers
    Forecasting Firm Material Events from 8-K Reports (D19-51)

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    Challenge: In this paper, we show deep learning models can be used to forecast firm material event sequences based on the contents of the company’s 8-K Current Reports.
    Approach: They exploit state-of-the-art neural architectures, including sequence-to-sequence architecture and attention mechanisms, to build a deep learning model that can forecast firm material event sequences based on company 8-K Current Reports.
    Outcome: The proposed model can forecast firm material event sequences based on the contents of the firm's 8-K Current Reports.

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