Results 71 to 80 of about 6,744,718 (372)
Online (Weston, Conn.)This article explores how robo-advisors are transforming wealth management by integrating big data and artificial intelligence into algorithmic trading strategies. It discusses the ability of AI technologies, such as machine learning and natural language
Lu Liu +4 more
semanticscholar +1 more source
Advanced Engineering Materials, EarlyView.A numerical model resulting from irreversible thermodynamics for describing transport processes is introduced, focusing on thermodynamic activity gradients as the actual driving force for diffusion. Implemented in CUDA C++ and using CalPhaD methods for determining the necessary activity data, the model accurately simulates interdiffusion in aluminum ...
Ulrich Holländer +3 more
wiley +1 more source
Deep Learning can Replicate Adaptive Traders in a Limit-Order-Book Financial Market [PDF]
, 2018 We report successful results from using deep learning neural networks (DLNNs) to learn, purely by observation, the behavior of profitable traders in an electronic market closely modelled on the limit-order-book (LOB) market mechanisms that are commonly ...
Calvez, Arthur le, Cliff, Dave
core +3 more sources
Advanced Engineering Materials, EarlyView.Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source
Applying Deep Reinforcement Learning to Algorithmic Trading
Современные информационные технологии и IT-образование, 2020 At the moment, there is a large volume of literature on exchange trading. Obviously, every year the mathematical base of work is becoming more complicated along with an increase in computing power, machines can process more metrics from year to year and ...
Petr Nikitin +3 more
doaj +1 more source
Data Science in Finance: Challenges and Opportunities
AI, 2023 Data science has become increasingly popular due to emerging technologies, including generative AI, big data, deep learning, etc. It can provide insights from data that are hard to determine from a human perspective.
Xianrong Zheng +4 more
doaj +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Support Resistance Levels towards Profitability in Intelligent Algorithmic Trading Models
Mathematics, 2022 Past studies showed that more advanced model architectures and techniques are being developed for intelligent algorithm trading, but the input features of the models across these studies are very similar.
Jireh Yi-Le Chan +3 more
doaj +1 more source
Optimal Execution Trajectories. Linear Market Impact with Exponential Decay [PDF]
, 2013 Optimal execution of portfolio transactions is the essential part of algorithmic trading. In this paper we present in simple analytical form the optimal trajectory for risk-averse trader with the assumption of exponential market recovery and short-time ...
Skachkov, Igor
core
Machine learning and social theory: Collective machine behaviour in algorithmic trading
European Journal of Social Theory, 2021 This article examines what the rise in machine learning (ML) systems might mean for social theory. Focusing on financial markets, in which algorithmic securities trading founded on ML-based decision-making is gaining traction, I discuss the extent to ...
C. Borch
semanticscholar +1 more source