Sentiment Predictability for Stocks
arXiv:1712.05785v215 citations
Originality Synthesis-oriented
AI Analysis
This work addresses stock-market forecasting for investors, but it appears incremental as it uses existing methods without clear novelty.
The paper tackles stock-market prediction by applying textual sentiment analysis tools and prediction models like LSTMs and convolutional architectures, but no concrete results or numbers are provided in the abstract.
In this work, we present our findings and experiments for stock-market prediction using various textual sentiment analysis tools, such as mood analysis and event extraction, as well as prediction models, such as LSTMs and specific convolutional architectures.