Data augmentation and mixup techniques for stock returns prediction

Data augmentation and mixup techniques for stock returns prediction

In financial forecasting, the caliber of data underpinning models is critical for precision in predicting market trends. This research investigates the efficacy of data aug- mentation, a technique widely used in domains such as image processing, applied to financial time series. We assess how method...

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Bibliographic Details
Main Author: Tan, Regan Yik Rong
Other Authors: Bo An
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Computer and Information Science
Mathematical Sciences
Other
Quantitative finance
Stocks
Data science
Machine learning
Online Access:https://hdl.handle.net/10356/175462

Internet

https://hdl.handle.net/10356/175462

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