Results 1 to 10 of about 6,258,655 (251)
ITM Web of Conferences, 2021 Algorithmic trading uses algorithms that follow a trend and defined set of instructions to perform a trade. The trade can generate revenue at an inhuman and enhanced speed and frequency.
Mathur Medha +3 more
doaj +4 more sources
Survey on the application of deep learning in algorithmic trading
Data Science in Finance and Economics, 2021 Algorithmic trading is one of the most concerned directions in financial applications. Compared with traditional trading strategies, algorithmic trading applications perform forecasting and arbitrage with higher efficiency and more stable performance ...
Yongfeng Wang, Guofeng Yan
doaj +3 more sources
Social signals and algorithmic trading of Bitcoin. [PDF]
R Soc Open Sci, 2015 The availability of data on digital traces is growing to unprecedented sizes, but inferring actionable knowledge from large-scale data is far from being trivial.
Garcia D, Schweitzer F.
europepmc +7 more sources
The Complexity of Cryptocurrencies Algorithmic Trading
Mathematics, 2022 In this research, we provided an answer to a very important trading question, what is the optimal number of technical tools in order to achieve the best trading results for both swing trade that uses daily bars and intraday trade that uses minutes bars ...
Gil Cohen, Mahmoud Qadan
doaj +3 more sources
Systemic failures and organizational risk management in algorithmic trading: Normal accidents and high reliability in financial markets. [PDF]
Soc Stud Sci, 2022 This article examines algorithmic trading and some key failures and risks associated with it, including so-called algorithmic ‘flash crashes’. Drawing on documentary sources, 189 interviews with market participants, and fieldwork conducted at an ...
Min BH, Borch C.
europepmc +2 more sources
Using algorithmic trading to analyze short term profitability of Bitcoin. [PDF]
PeerJ Comput Sci, 2021 Cryptocurrencies such as Bitcoin (BTC) have seen a surge in value in the recent past and appeared as a useful investment opportunity for traders. However, their short term profitability using algorithmic trading strategies remains unanswered.
Ahmad I +4 more
europepmc +3 more sources
Flexible Decision Support System for Algorithmic Trading: Empirical Application on Crude Oil Markets
IEEE Access, 2022 Generating reliable trading signals is a challenging task for financial market professionals. This research designs a novel decision-support system (DSS) for algorithmic trading and applies it empirically on two main crude oil markets.
Cristiana Tudor, Robert Sova
doaj +2 more sources
Algorithmic trading in turbulent markets☆ [PDF]
Pacific-Basin Finance Journal, 2020 Does Algorithmic Trading (AT) exacerbate price swings in turbulent markets? We find that stocks with high AT experience less price drops (surges) on days when the market declines (increases) for more than 2%. This result is consistent with the view that AT minimizes price pressures and mitigates transitory pricing errors. Further analyses show that the
Zhou H, Kalev P, Frino A.
europepmc +5 more sources
Intelligent Algorithmic Trading Strategy Using Reinforcement Learning and Directional Change
IEEE Access, 2021 Designing a profitable trading strategy plays a critical role in algorithmic trading, where the algorithm can manage and execute automated trading decisions.
Monira Essa Aloud, Nora Alkhamees
doaj +2 more sources
Algorithmic Trading Using Continuous Action Space Deep Reinforcement Learning [PDF]
arXiv, 2022 Price movement prediction has always been one of the traders' concerns in financial market trading. In order to increase their profit, they can analyze the historical data and predict the price movement.
Naseh Majidi +2 more
semanticscholar +2 more sources