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Knowledge and Information Systems
Published in: Knowledge and Information Systems 1/2021

24-09-2020 | Regular Paper

Transferring trading strategy knowledge to deep learning models

Authors: Avraam Tsantekidis, Anastasios Tefas

Published in: Knowledge and Information Systems | Issue 1/2021

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Abstract

Trading strategies are constantly being employed in the financial markets in order to increase consistency, reduce human errors of judgment and boost the probability of taking profitable market positions. In this work, we attempt to transfer the knowledge of several different types of trading strategies to deep learning models. The trading strategies are applied on price data of foreign exchange trading pairs and are actual strategies used in production trading environments. Along with our approach to transfer the strategy knowledge, we introduce a preprocessing method of the original price candles making it suitable for use with Neural Networks. Our results suggest that the deep models that are tested perform better than simpler models and they can accurately learn a variety of trading strategies.
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Metadata
Title
Transferring trading strategy knowledge to deep learning models
Authors
Avraam Tsantekidis
Anastasios Tefas
Publication date
24-09-2020
Publisher
Springer London
Published in
Knowledge and Information Systems / Issue 1/2021
Print ISSN: 0219-1377
Electronic ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-020-01510-y

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