Leveraging Deep Learning and Online Source Sentiment for Financial Portfolio Management. (arXiv:2309.16679v1 [q-fin.PM])

Financial portfolio management describes the task of distributing funds and
conducting trading operations on a set of financial assets, such as stocks,
index funds, foreign exchange or cryptocurrencies, aiming to maximize the
profit while minimizing the loss incurred by said operations. Deep Learning
(DL) methods have been consistently excelling at various tasks and automated
financial trading is one of the most complex one of those. This paper aims to
provide insight into various DL methods for financial trading, under both the
supervised and reinforcement learning schemes. At the same time, taking into
consideration sentiment information regarding the traded assets, we discuss and
demonstrate their usefulness through corresponding research studies. Finally,
we discuss commonly found problems in training such financial agents and equip
the reader with the necessary knowledge to avoid these problems and apply the
discussed methods in practice.