Search Results - subject:"Algorithmic Trading"

The good, the bad, and latency : exploratory trading on Bybit and Binance

Albers, Jakob; Cucuringu, Mihai; Howison, Sam; … - In: Quantitative finance 25 (2025) 6, pp. 919-947

Persistent link: https://www.econbiz.de/10015534166

Deep limit order book forecasting : a microstructural guide

Briola, Antonio; Bartolucci, Silvia; Aste, Tomaso - In: Quantitative finance 25 (2025) 7, pp. 1101-1131

Persistent link: https://www.econbiz.de/10015534180

High-frequency dynamics of Bitcoin futures : an examination of market microstructure

Pinto, Mateus Gonzalez de Freitas - In: Borsa Istanbul Review 25 (2025) 6, pp. 1378-1390

We investigate the high-frequency dynamics of Bitcoin and Ethereum perpetual futures traded on Binance from January 2020 to December 2024. After a thorough discussion of the stylized facts and particularities of Bitcoin perpetual futures, based on previous research in futures markets, we...

Persistent link: https://www.econbiz.de/10015551385

Electronic foreign exchange trading (e-FX) : developments in and implications for the Tokyo FX market

Onishi, Fuyuko; Hirai, Yuichiro; Aruga, Ryo; Bessho, Hidemi - In: Bank of Japan review (2025) 4, pp. 1-7

Persistent link: https://www.econbiz.de/10015573413

Dual-market quantitative trading : the dynamics of liquidity and turnover in financial markets

Zhu, Qing; Han, Chenyu; Li, Yuze - In: Data science and management : DSM 8 (2025) 1, pp. 48-58

Financial market liquidity is a popular research topic. Investor-driven research uses the turnover rate to measure liquidity and generally finds that the higher the stock turnover rate, the lower the returns. However, the traditional financial liquidity theory has been impacted by new...

Persistent link: https://www.econbiz.de/10015454715

Machine Learning in Finance : Trends, Developments and Business Practices in the Financial Sector

Gün, Musa (ed.); Kartal, Burcu (ed.) - 2025

Through Algorithmic Trading (Ahmet AKUSTA) -- Chapter 11. Assessing Bitcoin Return Extrema in the Context of Extreme Value …, gain insights from data, and make more informed decisions in real time. This edited book covers algorithmic trading, risk …

Persistent link: https://www.econbiz.de/10015340069

Algorithmic trading, liquidity and volatility : evidence from Poland

Gurgul, Henryk; Syrek, Robert - In: Economics and business review 11 (2025) 4, pp. 139-158

Persistent link: https://www.econbiz.de/10015616456

Does AI change everything in data licensing?

Reichenbach, Stefan; Lawrence, Debbie - In: Journal of securities operations & custody 17 (2025) 4, pp. 369-376

Persistent link: https://www.econbiz.de/10015643248

Daily and intraday application of various architectures of the LSTM model in algorithmic investment strategies on Bitcoin and the S&P 500 Index

Kryńska, Katarzyna; Ślepaczuk, Robert - 2022

Persistent link: https://www.econbiz.de/10013473995

AI-driven market manipulation and limits of the EU law enforcement regime to credible deterrence

Azzutti, Alessio - 2022

. A growing number of financial market players have in fact been adopting AI tools within the ramification of algorithmic … trading. While AI trading is expected to deliver several efficiency gains, it can also bring unprecedented risks due to the …

Persistent link: https://www.econbiz.de/10012807066