Feature Engineering for Mid-Price Prediction With Deep Learning

Feature Engineering for Mid-Price Prediction With Deep Learning

Mid-price movement prediction based on the limit order book data is a challenging task due to the complexity and dynamics of the limit order book. So far, there have been very limited attempts for extracting relevant features based on the limit order book data. In this paper, we address this problem...

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Bibliographic Details
Main Authors: Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Deep learning
econometrics
high-frequency trading
limit order book
mid-price
U.S. data
Online Access:https://ieeexplore.ieee.org/document/8743410/

Internet

https://ieeexplore.ieee.org/document/8743410/

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