Bridging the divide in financial market forecasting: machine learners vs. financial economists
- Submitting institution
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University of Edinburgh
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 58898677
- Type
- D - Journal article
- DOI
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10.1016/j.eswa.2016.05.033
- Title of journal
- Expert Systems with Applications
- Article number
- -
- First page
- 215
- Volume
- 61
- Issue
- -
- ISSN
- 0957-4174
- Open access status
- Technical exception
- Month of publication
- May
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
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B - Data Science and Artificial Intelligence
- Citation count
- 39
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the first paper providing significant new insight to resolve different opinions of financial market prediction proposed by computer science and finance communities. The paper’s results, over 40 markets globally, shed light on the sources of model prediction biases, and attracted significant industry funding over £800k on unbiased risk management. This project funded by Innovate UK/ESRC has been awarded Certificate of Excellence, the highest award for knowledge transfer and awarded as one of the winners of Lenovo/Supercomputing Conference AI Innovation Challenge 2017 on Financial Risk Management. The work has an invited presentation on SuperComputing17 with more than 15000 attendees.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -