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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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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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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
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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
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A Hybrid Deep Reinforcement Learning Approach for Algorithmic Trading in Commodity Futures Markets [PDF]
Applied Computational Intelligence and Soft ComputingThe financial markets have been affected extensively in recent years, due to algorithmic trading, predominantly concerning commodity futures. This research provides a novel hybrid approach combining classical machine learning algorithms (random forest ...
Baljinder Kaur +2 more
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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.
europepmc +4 more sources
Algorithmic Trading and Information [PDF]
SSRN Electronic Journal, 2011 We examine algorithmic trades (AT) and their role in the price discovery process in the 30 DAX stocks on the Deutsche Boerse. AT liquidity demand represents 52% of volume and AT supplies liquidity on 50% of volume. AT act strategically by monitoring the market for liquidity and deviations of price from fundamental value. AT consume liquidity when it is
Terrence Hendershott, Ryan Riordan
openaire +5 more sources
Algorithmic crypto trading using information-driven bars, triple barrier labeling and deep learning
Financial InnovationThis paper investigates the optimization of data sampling and target labeling techniques to enhance algorithmic trading strategies in cryptocurrency markets, focusing on Bitcoin (BTC) and Ethereum (ETH).
Przemysław Grądzki +2 more
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ArrayAlgorithmic trading has revolutionized financial markets, offering rapid and efficient trade execution. The integration of deep learning (DL) into these systems has further enhanced predictive capabilities, providing sophisticated models that capture ...
MD Shahriar Mahmud Bhuiyan +6 more
doaj +2 more sources