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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.
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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
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Social signals and algorithmic trading of Bitcoin [PDF]
Royal Society Open Science, 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.
David Garcia, Frank Schweitzer
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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
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A Data Science Pipeline for Algorithmic Trading: A Comparative Study of Applications for Finance and Cryptoeconomics [PDF]
International Congress on Blockchain and Applications, 2022 Recent advances in Artificial Intelligence (AI) have made algorithmic trading play a central role in finance. However, current research and applications are disconnected information islands.
Luyao Zhang +4 more
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Using algorithmic trading to analyze short term profitability of Bitcoin [PDF]
PeerJ Computer Science, 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.
Iftikhar Ahmad +4 more
doaj +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
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How Complexity and Uncertainty Grew with Algorithmic Trading [PDF]
Entropy, 2020 The machine-learning paradigm promises traders to reduce uncertainty through better predictions done by ever more complex algorithms. We ask about detectable results of both uncertainty and complexity at the aggregated market level.
Martin Hilbert, David Darmon
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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.
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IEEE Access, 2021 Algorithmic trading allows investors to avoid emotional and irrational trading decisions and helps them make profits using modern computer technology. In recent years, reinforcement learning has yielded promising results for algorithmic trading.
Deog-Yeong Park, Ki-Hoon Lee
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