Stock Prediction

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

3 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

29 shown of 29 papers with code (102 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News
  20 Dec 2019 4 repositories listed
  In this paper, we propose a novel deep neural network DP-LSTM for stock price prediction, which incorporates the news articles as hidden information and integrates difference news sources through the differential…
• HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction
  7 Aug 2019 3 repositories listed
  Methods that use relational data for stock market prediction have been recently proposed, but they are still in their infancy.
• Temporal Relational Ranking for Stock Prediction
  25 Sep 2018 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  Our RSR method advances existing solutions in two major aspects: 1) tailoring the deep learning models for stock ranking, and 2) capturing the stock relations in a time-sensitive manner.
• Stock trend prediction using news sentiment analysis
  7 Jul 2016 2 repositories listed
  The accuracy of the prediction model is more than 80% and in comparison with news random labeling with 50% of accuracy; the model has increased the accuracy by 30%.
• ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models
  26 May 2025 1 repository listed
  Large language models (LLMs) face significant challenges in ex-ante reasoning, where analysis, inference, or predictions must be made without access to information from future events.
• GRU-PFG: Extract Inter-Stock Correlation from Stock Factors with Graph Neural Network
  28 Nov 2024 1 repository listed
  It achieves prediction results that not only outperform the others models relies solely on stock factors, but also achieve comparable performance to the second category models.
• FLAG: Financial Long Document Classification via AMR-based GNN
  2 Oct 2024 1 repository listed
  We propose FLAG: Financial Long document classification via AMR-based GNN, an AMR graph based framework to generate document-level embeddings for long financial document classification.
• Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models
  6 Feb 2024 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)
  The training samples for the PPO trainer are also the responses generated during the reflective process, which eliminates the need for human annotators.
• Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction
  18 Aug 2023 1 repository listed Syntology ran 11 of 14 samples · 3 unverified · 14 pointer-only (licence)
  The hierarchical VAE allows us to learn the complex and low-level latent variables for stock prediction, while the diffusion probabilistic model trains the predictor to handle stock price stochasticity by progressively…
• Stock Broad-Index Trend Patterns Learning via Domain Knowledge Informed Generative Network
  27 Feb 2023 1 repository listed
  Predicting the Stock movement attracts much attention from both industry and academia.
• Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model
  14 Jun 2022 1 repository listed
  In addition, we propose a self-supervised learning strategy based on SRLP to enhance the out-of-distribution generalization performance of our system.
• A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Predictions
  1 May 2022 1 repository listed
  More and more investors and machine learning models rely on social media (e.
• Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction
  6 Apr 2022 1 repository listed
  Due to the complex volatility of the stock market, the research and prediction on the change of the stock price, can avoid the risk for the investors.
• Differential equation and probability inspired graph neural networks for latent variable learning
  28 Feb 2022 1 repository listed
  Probabilistic theory and differential equation are powerful tools for the interpretability and guidance of the design of machine learning models, especially for illuminating the mathematical motivation of learning…
• Graph-Based Stock Recommendation by Time-Aware Relational Attention Network
  1 Feb 2022 1 repository listed
  For a given group of stocks, the proposed TRAN model can output the ranking results of stocks according to their return ratios.
• A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction
  16 Jan 2022 1 repository listed
  More and more investors and machine learning models rely on social media (e.
• DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
  11 Jan 2022 1 repository listed
  To handle concept drift, previous methods first detect when/where the concept drift happens and then adapt models to fit the distribution of the latest data.
• Stock Movement Prediction Based on Bi-typed Hybrid-relational Market Knowledge Graph via Dual Attention Networks
  11 Jan 2022 1 repository listed
  Stock Movement Prediction (SMP) aims at predicting listed companies' stock future price trend, which is a challenging task due to the volatile nature of financial markets.
• Multi-modal Attention Network for Stock Movements Prediction
  27 Dec 2021 1 repository listed
  Traditionally, the prediction of future stock movements is based on the historical trading record.
• Long Term Stock Prediction based on Financial Statements
  1 Nov 2021 1 repository listed
  This paper proposes a model with LSTM and fully connected layers to predict long term stock trendings based on financial statements.
• Measuring Financial Time Series Similarity With a View to Identifying Profitable Stock Market Opportunities
  7 Jul 2021 1 repository listed
  Forecasting stock returns is a challenging problem due to the highly stochastic nature of the market and the vast array of factors and events that can influence trading volume and prices.
• Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
  24 Jun 2021 1 repository listed
  In this paper, we propose a novel architecture, Temporal Routing Adaptor (TRA), to empower existing stock prediction models with the ability to model multiple stock trading patterns.
• Price graphs: Utilizing the structural information of financial time series for stock prediction
  4 Jun 2021 1 repository listed
  Then, structural information, referring to associations among temporal points and the node weights, is extracted from the mapped graphs to resolve the problems regarding long-range dependencies and the chaotic property.
• Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading
  26 May 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we introduce an event-driven trading strategy that predicts stock movements by detecting corporate events from news articles.
• Stock price prediction using Generative Adversarial Networks
  2 Apr 2021 1 repository listed
  In this paper, it proposes a stock prediction model using Generative Adversarial Network (GAN) with Gated Recurrent Units (GRU) used as a generator that inputs historical stock price and generates future stock price and…
• AlphaEvolve: A Learning Framework to Discover Novel Alphas in Quantitative Investment
  30 Mar 2021 1 repository listed
  In this paper, we introduce a new class of alphas to model scalar, vector, and matrix features which possess the strengths of these two existing classes.
• Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction
  11 May 2020 1 repository listed
  However, it is well known that an individual stock price is correlated with prices of other stocks in complex ways.
• Improving S&P stock prediction with time series stock similarity
  8 Feb 2020 1 repository listed
  Stock market prediction with forecasting algorithms is a popular topic these days where most of the forecasting algorithms train only on data collected on a particular stock.
• Enhancing Stock Movement Prediction with Adversarial Training
  13 Oct 2018 1 repository listed
  The key novelty is that we propose to employ adversarial training to improve the generalization of a neural network prediction model.

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.