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Stock Price Prediction

Stock Price Prediction is the task of forecasting future stock prices based on historical data and various market indicators. It involves using statistical models and machine learning algorithms to analyze financial data and make predictions about the future performance of a stock. The goal of stock price prediction is to help investors make informed investment decisions by providing a forecast of future stock prices.

Papers

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Showing 26–50 of 137 papers

TitleStatusHype
Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price PredictionCode2
Transfer learning for financial data predictions: a systematic review—0
LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRUCode1
StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction—0
SETN: Stock Embedding Enhanced with Textual and Network Information—0
Probabilistic Deep Learning and Transfer Learning for Robust Cryptocurrency Price PredictionCode0
Exploring Sectoral Profitability in the Indian Stock Market Using Deep Learning—0
Review of deep learning models for crypto price prediction: implementation and evaluationCode1
A Hybrid Deep Learning Framework for Stock Price Prediction Considering the Investor Sentiment of Online Forum Enhanced by Popularity—0
Time Series Stock Price Forecasting Based on Genetic Algorithm (GA)-Long Short-Term Memory Network (LSTM) Optimization—0
BERTopic-Driven Stock Market Predictions: Unraveling Sentiment Insights—0
Tweet Influence on Market Trends: Analyzing the Impact of Social Media Sentiment on Biotech Stocks—0
Natural Language Processing and Multimodal Stock Price Prediction—0
Fine-tuning and Utilization Methods of Domain-specific LLMs—0
ResNLS: An Improved Model for Stock Price ForecastingCode1
Boosting Stock Price Prediction with Anticipated Macro Policy Changes—0
Feature selection and regression methods for stock price prediction using technical indicators—0
Generalized Mixture Model for Extreme Events Forecasting in Time Series Data—0
A Generalization Bound of Deep Neural Networks for Dependent Data—0
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernelsCode1
The Potential of Quantum Techniques for Stock Price Prediction—0
Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price PredictionCode1
Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey—0
Contrasting the efficiency of stock price prediction models using various types of LSTM models aided with sentiment analysis—0
Stock Price Prediction using Dynamic Neural Networks—0
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