Online learning: A comprehensive survey

SCH Hoi, D Sahoo, J Lu, P Zhao - Neurocomputing, 2021 - Elsevier
Online learning represents a family of machine learning methods, where a learner attempts
to tackle some predictive (or any type of decision-making) task by learning from a sequence …

Online portfolio selection: A survey

B Li, SCH Hoi - ACM Computing Surveys (CSUR), 2014 - dl.acm.org
Online portfolio selection is a fundamental problem in computational finance, which has
been extensively studied across several research communities, including finance, statistics …

A deep reinforcement learning framework for the financial portfolio management problem

Z Jiang, D Xu, J Liang - arxiv preprint arxiv:1706.10059, 2017 - arxiv.org
Financial portfolio management is the process of constant redistribution of a fund into
different financial products. This paper presents a financial-model-free Reinforcement …

Reinforcement learning for quantitative trading

S Sun, R Wang, B An - ACM Transactions on Intelligent Systems and …, 2023 - dl.acm.org
Quantitative trading (QT), which refers to the usage of mathematical models and data-driven
techniques in analyzing the financial market, has been a popular topic in both academia and …

Alphastock: A buying-winners-and-selling-losers investment strategy using interpretable deep reinforcement attention networks

J Wang, Y Zhang, K Tang, J Wu, Z **ong - Proceedings of the 25th ACM …, 2019 - dl.acm.org
Recent years have witnessed the successful marriage of finance innovations and AI
techniques in various finance applications including quantitative trading (QT). Despite great …

Cost-sensitive portfolio selection via deep reinforcement learning

Y Zhang, P Zhao, Q Wu, B Li, J Huang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Portfolio Selection is an important real-world financial task and has attracted extensive
attention in artificial intelligence communities. This task, however, has two main difficulties:(i) …

[HTML][HTML] An asset subset-constrained minimax optimization framework for online portfolio selection

J Yin, A Zhong, X **ao, R Wang, JZ Huang - Expert Systems with …, 2024 - Elsevier
Effective online portfolio selection necessitates seamless integration of three key properties:
diversity, sparsity, and risk control. However, existing algorithms often prioritize one property …

[HTML][HTML] Moving average reversion strategy for on-line portfolio selection

B Li, SCH Hoi, D Sahoo, ZY Liu - Artificial Intelligence, 2015 - Elsevier
On-line portfolio selection, a fundamental problem in computational finance, has attracted
increasing interest from artificial intelligence and machine learning communities in recent …

Online portfolio management via deep reinforcement learning with high-frequency data

J Li, Y Zhang, X Yang, L Chen - Information Processing & Management, 2023 - Elsevier
Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior
results in many sequence modeling tasks. The ability of Transformer to capture long-range …

Application of deep q-network in portfolio management

Z Gao, Y Gao, Y Hu, Z Jiang, J Su - 2020 5th IEEE International …, 2020 - ieeexplore.ieee.org
Machine Learning algorithms and Neural Networks are widely applied to many different
areas such as stock market prediction, facial recognition and automatic machine translation …