Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news
By Tomer Geva, Jacob Zahavi. 2014
133 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
In Finance
In Management Science and Operations Research
- Mathias Kraus
- Vadlamani Ravi
- Stefan Feuerriegel
- Longbing Cao
- Dogu Araci
- M. Ugur Gudelek
- Omer Berat Sezer
- A. Ozbayoglu
Citations in the corpus
- Decision support from financial disclosures with deep neural networks and transfer learning (2017, methodology): “The components are adapted from the systems described in [12, 8, 9, 10, 11].”
- A survey on opinion mining and sentiment analysis: Tasks, approaches and applications (2015, background): “Geva and Zahavi [53] performed a systematic evaluation of the effectiveness of augmenting market-data with textual news-based data for intraday stock recommendation decisions.”
- Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook (2018, unknown): “(2012); Ghose et al. (2012); Geva and Zahavi (2013)).”
- Financial Time-Series Data Analysis Using Deep Convolutional Neural Networks (2016, unknown): “[13] confirmed that the nonlinear neural network has a significant effect on the processing of textual data, and can be used to predict the market.”