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Financial sentiment analysis: Techniques and applications
Financial Sentiment Analysis (FSA) is an important domain application of sentiment analysis
that has gained increasing attention in the past decade. FSA research falls into two main …
that has gained increasing attention in the past decade. FSA research falls into two main …
[HTML][HTML] Applying artificial intelligence in cryptocurrency markets: A survey
The total capital in cryptocurrency markets is around two trillion dollars in 2022, which is
almost the same as Apple's market capitalisation at the same time. Increasingly …
almost the same as Apple's market capitalisation at the same time. Increasingly …
Deep reinforcement learning for stock portfolio optimization by connecting with modern portfolio theory
With artificial intelligence and data quality development, portfolio optimization has improved
rapidly. Traditionally, researchers in the financial market have utilized the modern portfolio …
rapidly. Traditionally, researchers in the financial market have utilized the modern portfolio …
[HTML][HTML] Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach
Portfolio optimization concerns with periodically allocating the limited funds to invest in a
variety of potential assets in order to satisfy investors' appetites for risk and return goals …
variety of potential assets in order to satisfy investors' appetites for risk and return goals …
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 …
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 …
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 …
A multimodal foundation agent for financial trading: Tool-augmented, diversified, and generalist
Financial trading is a crucial component of the markets, informed by a multimodal
information landscape encompassing news, prices, and Kline charts, and encompasses …
information landscape encompassing news, prices, and Kline charts, and encompasses …
Stock movement prediction via gated recurrent unit network based on reinforcement learning with incorporated attention mechanisms
The recent advances usually mine market information from the chaotic data to conduct a
stock movement prediction task. However, the current stock price movement prediction …
stock movement prediction task. However, the current stock price movement prediction …
Crop: Certifying robust policies for reinforcement learning through functional smoothing
As reinforcement learning (RL) has achieved great success and been even adopted in
safety-critical domains such as autonomous vehicles, a range of empirical studies have …
safety-critical domains such as autonomous vehicles, a range of empirical studies have …