Explainable artificial intelligence (XAI) in finance: a systematic literature review
J Černevičienė, A Kabašinskas - Artificial Intelligence Review, 2024 - Springer
As the range of decisions made by Artificial Intelligence (AI) expands, the need for
Explainable AI (XAI) becomes increasingly critical. The reasoning behind the specific …
Explainable AI (XAI) becomes increasingly critical. The reasoning behind the specific …
Deep reinforcement learning in quantitative algorithmic trading: A review
TV Pricope - arxiv preprint arxiv:2106.00123, 2021 - arxiv.org
Algorithmic stock trading has become a staple in today's financial market, the majority of
trades being now fully automated. Deep Reinforcement Learning (DRL) agents proved to be …
trades being now fully automated. Deep Reinforcement Learning (DRL) agents proved to be …
Accurate multivariate stock movement prediction via data-axis transformer with multi-level contexts
How can we efficiently correlate multiple stocks for accurate stock movement prediction?
Stock movement prediction has received growing interest in data mining and machine …
Stock movement prediction has received growing interest in data mining and machine …
Fusing topology contexts and logical rules in language models for knowledge graph completion
Abstract Knowledge graph completion (KGC) aims to infer missing facts based on the
observed ones, which is significant for many downstream applications. Given the success of …
observed ones, which is significant for many downstream applications. Given the success of …
Deep learning in the stock market—a systematic survey of practice, backtesting, and applications
K Olorunnimbe, H Viktor - Artificial Intelligence Review, 2023 - Springer
The widespread usage of machine learning in different mainstream contexts has made deep
learning the technique of choice in various domains, including finance. This systematic …
learning the technique of choice in various domains, including finance. This systematic …
The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning
Whether investor sentiment affects stock prices is an issue of long-standing interest for
economists. We conduct a comprehensive study of the predictability of investor sentiment …
economists. We conduct a comprehensive study of the predictability of investor sentiment …
Knowledge graph-based event embedding framework for financial quantitative investments
Event representative learning aims to embed news events into continuous space vectors for
capturing syntactic and semantic information from text corpus, which is benefit to event …
capturing syntactic and semantic information from text corpus, which is benefit to event …
DeepTrader: a deep reinforcement learning approach for risk-return balanced portfolio management with market conditions Embedding
Most existing reinforcement learning (RL)-based portfolio management models do not take
into account the market conditions, which limits their performance in risk-return balancing. In …
into account the market conditions, which limits their performance in risk-return balancing. In …
Multi-scale local cues and hierarchical attention-based LSTM for stock price trend prediction
X Teng, X Zhang, Z Luo - Neurocomputing, 2022 - Elsevier
Stock price trend prediction is to seek profit maximum of stock investment by estimating
future stock price tendency. Nevertheless, it is still a tough task due to noisy and non …
future stock price tendency. Nevertheless, it is still a tough task due to noisy and non …
Reinforcement learning for quantitative trading
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 …
techniques in analyzing the financial market, has been a popular topic in both academia and …