How Robust are Limit Order Book Representations under Data Perturbation?
2021-10-10Code Available1· sign in to hype
Yufei Wu, Mahmoud Mahfouz, Daniele Magazzeni, Manuela Veloso
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Abstract
The success of machine learning models in the financial domain is highly reliant on the quality of the data representation. In this paper, we focus on the representation of limit order book data and discuss the opportunities and challenges for learning representations of such data. We also experimentally analyse the issues associated with existing representations and present a guideline for future research in this area.