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The management of deep learning algorithms to enhance momentum trading strategies during the time frame to quick detect market of smart money
Published in Noura Metawa, Mohamed Elhoseny, Aboul Ella Hassanien, M. Kabir Hassan, Expert Systems in Finance, 2019
Khalid Abouloula, Ali Ou-Yassine, Salah-ddine Krit
Generally, algorithmic trading is the use of a computer program to create automation in one or several steps of the trading process, depending on the technology used, the objective or where in the trader pipeline the automation occurs. Algorithmic trading includes the following sub-categories [3]: systematic trading (ST), or systems that use trading strategies based on a set of predefined rules received as human input; and high-frequency trading (HTF), which is usually used in systems characterized with fast execution speed (on the order of milliseconds) and holding stock for a short time span. Usually an HFT algorithm proceeds without the intervention of a human; there is an infinite number of trading algorithms, but there are not too many winning solutions, because it brings a lot of money to hedge funds, consulting companies, brokers, traders and so forth.
A High-Frequency Algorithmic Trading Strategy for Cryptocurrency
Published in Journal of Computer Information Systems, 2020
HFT has its start as early as 1998, when the Security Exchange Commission allowed electronic exchanges to be able to trade securities legally.7 HFT is the use of computerized trading algorithms to buy and sell assets quickly and frequently, with a short holding period to earn miniscule margins on each trade. HFT have been used on various asset markets such as foreign exchanges, fixed income, equity, and derivatives. Interested readers should peruse ref.7–10 for an in-depth background on HFT.