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.

Benchmarks

Libraries

Datasets

Subtasks

Most implemented papers

DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News

Content

Neural networks for stock price prediction

Supplementary material to “ Automatic Relevance Determination in Nonnegative Matrix Factorization with the β-Divergence ”

FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns

Artificial Counselor System for Stock Investment

Stock Price Prediction Based on Natural Language Processing1

Context-aware Frame-Semantic Role Labeling

PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance

Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models