Papers Stock Trend Prediction
“Stock Trend Prediction” 태그가 달린 논문 31편 · 필터 해제
MaGNet: A Mamba Dual-Hypergraph Network for Stock Prediction via Temporal-Causal and Global Relational Learning
Stock trend prediction is crucial for profitable trading strategies and portfolio management yet remains challenging due to market volatility, complex temporal dynamics and multifaceted inter-stock relationships. Existin…
Stock Trend PredictionRelational ReasoningFinKario: Event-Enhanced Automated Construction of Financial Knowledge Graph
Individual investors are significantly outnumbered and disadvantaged in financial markets, overwhelmed by abundant information and lacking professional analysis. Equity research reports stand out as crucial resources, of…
Stock Trend PredictionA Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction
Stock trend prediction involves forecasting the future price movements by analyzing historical data and various market indicators. With the advancement of machine learning, graph neural networks (GNNs) have been extensiv…
Graph Neural NetworkPredictionStock PredictionStock Trend PredictionPerforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks
The neurons of artificial neural networks were originally invented when much less was known about biological neurons than is known today. Our work explores a modification to the core neuron unit to make it more parallel …
Drug DiscoveryLanguage ModelingModel CompressionStock Trend PredictionDynamic Graph Representation with Contrastive Learning for Financial Market Prediction: Integrating Temporal Evolution and Static Relations
Temporal Graph Learning (TGL) is crucial for capturing the evolving nature of stock markets. Traditional methods often ignore the interplay between dynamic temporal changes and static relational structures between stocks…
Contrastive LearningGraph LearningStock Trend PredictionA Stock Price Prediction Approach Based on Time Series Decomposition and Multi-Scale CNN using OHLCT Images
Recently, deep learning in stock prediction has become an important branch. Image-based methods show potential by capturing complex visual patterns and spatial correlations, offering advantages in interpretability over t…
Stock PredictionStock Price PredictionStock Trend PredictionTime SeriesComparative Analysis of LSTM, GRU, and Transformer Models for Stock Price Prediction
In recent fast-paced financial markets, investors constantly seek ways to gain an edge and make informed decisions. Although achieving perfect accuracy in stock price predictions remains elusive, artificial intelligence …
Stock Price PredictionStock Trend PredictionLeveraging Fundamental Analysis for Stock Trend Prediction for Profit
This paper investigates the application of machine learning models, Long Short-Term Memory (LSTM), one-dimensional Convolutional Neural Networks (1D CNN), and Logistic Regression (LR), for predicting stock trends based o…
Decision MakingPredictionSentiment AnalysisStock Prediction+1FLAG: Financial Long Document Classification via AMR-based GNN
The advent of large language models (LLMs) has initiated much research into their various financial applications. However, in applying LLMs on long documents, semantic relations are not explicitly incorporated, and a ful…
Abstract Meaning RepresentationDocument ClassificationStock PredictionStock Trend Prediction+3LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU
Stock price prediction is a challenging problem in the field of finance and receives widespread attention. In recent years, with the rapid development of technologies such as deep learning and graph neural networks, more…
Algorithmic TradingStock Price PredictionStock Trend PredictionEnhancing Few-Shot Stock Trend Prediction with Large Language Models
The goal of stock trend prediction is to forecast future market movements for informed investment decisions. Existing methods mostly focus on predicting stock trends with supervised models trained on extensive annotated …
DenoisingPredictionStock PredictionStock Trend PredictionAlphaFin: Benchmarking Financial Analysis with Retrieval-Augmented Stock-Chain Framework
The task of financial analysis primarily encompasses two key areas: stock trend prediction and the corresponding financial question answering. Currently, machine learning and deep learning algorithms (ML&DL) have been wi…
BenchmarkingFinancial AnalysisQuestion AnsweringRAG+3Microstructure-Empowered Stock Factor Extraction and Utilization
High-frequency quantitative investment is a crucial aspect of stock investment. Notably, order flow data plays a critical role as it provides the most detailed level of information among high-frequency trading data, incl…
Stock Trend PredictionLOB-Based Deep Learning Models for Stock Price Trend Prediction: A Benchmark Study
The recent advancements in Deep Learning (DL) research have notably influenced the finance sector. We examine the robustness and generalizability of fifteen state-of-the-art DL models focusing on Stock Price Trend Predic…
Stock Trend PredictionSupport for Stock Trend Prediction Using Transformers and Sentiment Analysis
Stock trend analysis has been an influential time-series prediction topic due to its lucrative and inherently chaotic nature. Many models looking to accurately predict the trend of stocks have been based on Recurrent Neu…
Sentiment AnalysisStock PredictionStock Trend PredictionTime Series+1Stock Trend Prediction: A Semantic Segmentation Approach
Market financial forecasting is a trending area in deep learning. Deep learning models are capable of tackling the classic challenges in stock market data, such as its extremely complicated dynamics as well as long-term …
PredictionSemantic SegmentationStock Trend PredictionTime SeriesFactor Investing with a Deep Multi-Factor Model
Modeling and characterizing multiple factors is perhaps the most important step in achieving excess returns over market benchmarks. Both academia and industry are striving to find new factors that have good explanatory p…
Graph AttentionManagementmodelStock Trend PredictionAstock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model
Natural Language Processing(NLP) demonstrates a great potential to support financial decision-making by analyzing the text from social media or news outlets. In this work, we build a platform to study the NLP-aided stock…
Decision MakingNews ClassificationOut-of-Distribution GeneralizationSelf-Supervised Learning+6DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
In many real-world scenarios, we often deal with streaming data that is sequentially collected over time. Due to the non-stationary nature of the environment, the streaming data distribution may change in unpredictable w…
Stock Market PredictionStock PredictionStock Trend PredictionDynamic Inference
Traditional statistical estimation, or statistical inference in general, is static, in the sense that the estimate of the quantity of interest does not change the future evolution of the quantity. In some sequential esti…
Imitation LearningPredictionProduct RecommendationStock Price Prediction+1