Results 121 to 130 of about 488,225 (292)
Advanced Materials, EarlyView.ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh +2 more
wiley +1 more source
Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Trading Confidence: Comprehensive Uncertainty Estimation in Algorithmic Trading
Reinforcement Learning (RL) has emerged as a powerful approach in financial trading, enabling agents to learn optimal strategies through direct market interaction. However, financial markets are highly uncertain, with price fluctuations driven by stochastic volatility, model limitations, and regime shifts.
Lin Li +3 more
openaire +3 more sources
Algorithmic trading in volatile markets
, 2014 This paper considers algorithmic trading (AT) during the most volatile trading days on the Australian Securities Exchange from October 2008 till October 2009.
Kalev, P.S., Lian, G.A., Zhou, H.
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Flying by the seat of their pants:What can High Frequency Trading learn from aviation? [PDF]
, 2013 As we build increasingly large scale systems (and systems of systems), the level of complexity is also rising. We still expect people to intervene when things go wrong, however, and to diagnose and fix the problems.
Baxter, Gordon, Cartlidge, John
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A Framework for Testing Algorithmic Trading Strategies
, 2008 Algorithmic trading and artificial stock markets have generated huge interest not only among brokers and traders in the financial markets but also across various disciplines in the academia.
Raghavendra, Srinivas +2 more
core +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
An artificial market model for the forex market
Humanities & Social Sciences CommunicationsAs financial markets have transitioned toward electronic trading, there has been a corresponding increase in the number of algorithmic strategies and degree of transaction frequency. This move to high-frequency trading at the millisecond level, propelled
Kimihiko Sasaki, Daisuke Yokouchi
doaj +1 more source
MathematicsAlgorithmic trading heavily relies on the optimization of rule-based strategies to maximize profitability and ensure robustness under volatile market conditions.
Kaled Hernández-Romo +4 more
doaj +1 more source
High frequency trading and end-of-day price dislocation : [Version 28 Oktober 2013] [PDF]
, 2013 We show that the presence of high frequency trading (HFT) has significantly mitigated the frequency and severity of end-of-day price dislocation, counter to recent concerns expressed in the media.
Zhan, Feng +2 more
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