Papers Stock Price Prediction
“Stock Price Prediction” 태그가 달린 논문 150편 · 필터 해제
From Index to Equity: Pre-Training Transformers for Stock Return Prediction
This research aims to leverage machine learning to improve stock price prediction and support informed investment decisions related to buying, selling, and holding assets. Specifically, this work investigates transformer…
Stock Price PredictionAdaptive Regime-Aware Stock Price Prediction Using Autoencoder-Gated Dual Node Transformers with Reinforcement Learning Control
Stock markets exhibit regime-dependent behavior where prediction models optimized for stable conditions often fail during volatile periods. Existing approaches typically treat all market states uniformly or require manua…
Stock Price PredictionReinforcement LearningGeneralized Stock Price Prediction for Multiple Stocks Combined with News Fusion
Predicting stock prices presents challenges in financial forecasting. While traditional approaches such as ARIMA and RNNs are prevalent, recent developments in Large Language Models (LLMs) offer alternative methodologies…
Stock Price PredictionPriceSeer: Evaluating Large Language Models in Real-Time Stock Prediction
Stock prediction, a subject closely related to people's investment activities in fully dynamic and live environments, has been widely studied. Current large language models (LLMs) have shown remarkable potential in vario…
Stock Price PredictionStockMem: An Event-Reflection Memory Framework for Stock Forecasting
Stock price prediction is challenging due to market volatility and its sensitivity to real-time events. While large language models (LLMs) offer new avenues for text-based forecasting, their application in finance is hin…
Stock Price PredictionKnowledge Graph Construction for Stock Markets with LLM-Based Explainable Reasoning
The stock market is inherently complex, with interdependent relationships among companies, sectors, and financial indicators. Traditional research has largely focused on time-series forecasting and single-company analysi…
Stock Price PredictionAnswer GenerationKnowledge GraphsOptimizing Chain-of-Thought Confidence via Topological and Dirichlet Risk Analysis
Chain-of-thought (CoT) prompting enables Large Language Models to solve complex problems, but deploying these models safely requires reliable confidence estimates, a capability where existing methods suffer from poor cal…
Stock Price PredictionGroupSHAP-Guided Integration of Financial News Keywords and Technical Indicators for Stock Price Prediction
Recent advances in finance-specific language models such as FinBERT have enabled the quantification of public sentiment into index-based measures, yet compressing diverse linguistic signals into single metrics overlooks …
Stock Price PredictionIKNet: Interpretable Stock Price Prediction via Keyword-Guided Integration of News and Technical Indicators
The increasing influence of unstructured external information, such as news articles, on stock prices has attracted growing attention in financial markets. Despite recent advances, most existing newsbased forecasting mod…
Stock Price PredictionGraph Signal Generative Diffusion Models
We introduce U-shaped encoder-decoder graph neural networks (U-GNNs) for stochastic graph signal generation using denoising diffusion processes. The architecture learns node features at different resolutions with skip co…
Stock Price PredictionImage GenerationPrediction of Stocks Index Price using Quantum GANs
This paper investigates the application of Quantum Generative Adversarial Networks (QGANs) for stock price prediction. Financial markets are inherently complex, marked by high volatility and intricate patterns that tradi…
Quantum Machine LearningStock Price PredictionMitigating Distribution Shift in Stock Price Data via Return-Volatility Normalization for Accurate Prediction
How can we address distribution shifts in stock price data to improve stock price prediction accuracy? Stock price prediction has attracted attention from both academia and industry, driven by its potential to uncover co…
Stock Price PredictionHolistic Explainable AI (H-XAI): Extending Transparency Beyond Developers in AI-Driven Decision Making
As AI systems increasingly mediate decisions in domains such as credit scoring and financial forecasting, their lack of transparency and bias raises critical concerns for fairness and public trust. Existing explainable A…
Stock Price PredictionDecision MakingA Study of Dynamic Stock Relationship Modeling and S&P500 Price Forecasting Based on Differential Graph Transformer
Stock price prediction is vital for investment decisions and risk management, yet remains challenging due to markets' nonlinear dynamics and time-varying inter-stock correlations. Traditional static-correlation models fa…
ClusteringStock Price PredictionTime Series PredictionHAELT: A Hybrid Attentive Ensemble Learning Transformer Framework for High-Frequency Stock Price Forecasting
High-frequency stock price prediction is challenging due to non-stationarity, noise, and volatility. To tackle these issues, we propose the Hybrid Attentive Ensemble Learning Transformer (HAELT), a deep learning framewor…
Algorithmic TradingEnsemble LearningStock Price PredictionExplainable-AI powered stock price prediction using time series transformers: A Case Study on BIST100
Financial literacy is increasingly dependent on the ability to interpret complex financial data and utilize advanced forecasting tools. In this context, this study proposes a novel approach that combines transformer-base…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Interpretable Machine LearningStock Price Prediction+1Gradient Boosting Decision Tree with LSTM for Investment Prediction
This paper proposes a hybrid framework combining LSTM (Long Short-Term Memory) networks with LightGBM and CatBoost for stock price prediction. The framework processes time-series financial data and evaluates performance …
Stock Price PredictionVISTA: Vision-Language Inference for Training-Free Stock Time-Series Analysis
Stock price prediction remains a complex and high-stakes task in financial analysis, traditionally addressed using statistical models or, more recently, language models. In this work, we introduce VISTA (Vision-Language …
Financial AnalysisStock Price PredictionTime SeriesTime Series AnalysisFrom Local Patterns to Global Understanding: Cross-Stock Trend Integration for Enhanced Predictive Modeling
Stock price prediction is a critical area of financial forecasting, traditionally approached by training models using the historical price data of individual stocks. While these models effectively capture single-stock pa…
Federated LearningStock Price PredictionEvaluating Financial Sentiment Analysis with Annotators Instruction Assisted Prompting: Enhancing Contextual Interpretation and Stock Prediction Accuracy
Financial sentiment analysis (FSA) presents unique challenges to LLMs that surpass those in typical sentiment analysis due to the nuanced language used in financial contexts. The prowess of these models is often undermin…
BenchmarkingSentiment AnalysisStock PredictionStock Price Prediction