Stock Price Prediction

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

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

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

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 30 papers with code (137 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.

• Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models
  20 Sep 2020 4 repositories listed
  In this work, we propose an approach of hybrid modeling for stock price prediction building different machine learning and deep learning-based models.
• 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…
• FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns
  28 Jun 2022 3 repositories listed
  As an asset pricing model in economics and finance, factor model has been widely used in quantitative investment.
• Neural networks for stock price prediction
  29 May 2018 3 repositories listed
  Due to the extremely volatile nature of financial markets, it is commonly accepted that stock price prediction is a task full of challenge.
• Automatic Relevance Determination in Nonnegative Matrix Factorization with the β-Divergence
  25 Nov 2011 3 repositories listed Syntology ran 0 of 17 samples · 17 unverified
  This paper addresses the estimation of the latent dimensionality in nonnegative matrix factorization (NMF) with the \beta-divergence.
• Review of deep learning models for crypto price prediction: implementation and evaluation
  19 May 2024 2 repositories listed
  In this study, we review the literature about deep learning for cryptocurrency price forecasting and evaluate novel deep learning models for cryptocurrency stock price prediction.
• PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
  8 Jun 2023 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  This paper introduces PIXIU, a comprehensive framework including the first financial LLM based on fine-tuning LLaMA with instruction data, the first instruction data with 136K data samples to support the fine-tuning,…
• Stock Price Prediction Based on Natural Language Processing
  6 May 2022 2 repositories listed
  The keywords used in traditional stock price prediction are mainly based on literature and experience.
• The Power of Linear Recurrent Neural Networks
  9 Feb 2018 2 repositories listed
  Recurrent neural networks are a powerful means to cope with time series.
• Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction
  26 Sep 2024 1 repository listed
  Stock markets play an important role in the global economy, where accurate stock price predictions can lead to significant financial returns.
• LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU
  26 Aug 2024 1 repository listed Syntology ran 9 of 9 samples · 0 unverified · 9 pointer-only (licence)
  However, existing methods mostly focus on the short-term dynamic relationships of stocks and directly integrating relationship information with temporal information.
• Probabilistic Deep Learning and Transfer Learning for Robust Cryptocurrency Price Prediction
  19 Jun 2024 1 repository listed
  This research is driven by the central goal of introducing a specialized deep learning model tailored to predict digital currency prices, with a specific emphasis on BTC.
• ResNLS: An Improved Model for Stock Price Forecasting
  2 Dec 2023 1 repository listed
  Stock prices forecasting has always been a challenging task.
• Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernels
  25 Sep 2023 1 repository listed
  On the largest binary UCR dataset, Detach-ROCKET improves test accuracy by 0.
• 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…
• A Multifactor Analysis Model for Stock Market Prediction
  5 Mar 2023 1 repository listed
  Stock Market predictions have historically been a problem tackled by different singular approaches even though markets are influenced by many different factors.
• DSE Stock Price Prediction using Hidden Markov Model
  26 Jan 2023 1 repository listed
  An HMM is trained by analyzing the fractional change in the stock price as well as the intraday high and low values.
• Multi-step-ahead Stock Price Prediction Using Recurrent Fuzzy Neural Network and Variational Mode Decomposition
  24 Dec 2022 1 repository listed
  In the prediction and reconstruction phase, each of the IMFs is given to a separate MFRFNN for prediction, and predicted signals are summed to reconstruct the output.
• MFRFNN: Multi-Functional Recurrent Fuzzy Neural Network for Chaotic Time Series Prediction
  1 Aug 2022 1 repository listed
  MFRFNN consists of two fuzzy neural networks with Takagi-Sugeno-Kang fuzzy rules, one is used to produce the output, and the other to determine the system’s state.
• 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.
• HYPHEN: Hyperbolic Hawkes Attention For Text Streams
  1 May 2022 1 repository listed
  Analyzing the temporal sequence of texts from sources such as social media, news, and parliamentary debates is a challenging problem as it exhibits time-varying scale-free properties and fine-grained timing…
• S&P 500 Stock Price Prediction Using Technical, Fundamental and Text Data
  24 Aug 2021 1 repository listed
  We summarized both common and novel predictive models used for stock price prediction and combined them with technical indices, fundamental characteristics and text-based sentiment data to predict S&P stock prices.
• 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…
• Deep Stock Predictions
  8 Jun 2020 1 repository listed
  Forecasting stock prices can be interpreted as a time series prediction problem, for which Long Short Term Memory (LSTM) neural networks are often used due to their architecture specifically built to solve such problems.
• A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processing
  9 Dec 2019 1 repository listed
  Based on the data of 2015 to 2017, we build various predictive models using machine learning, and then use those models to predict the closing value of NIFTY 50 for the period January 2018 till June 2019 with a…
• Particle Filter Recurrent Neural Networks
  30 May 2019 1 repository listed
  Recurrent neural networks (RNNs) have been extraordinarily successful for prediction with sequential data.
• Predicting the Effects of News Sentiments on the Stock Market
  11 Dec 2018 1 repository listed
  Stock market forecasting is very important in the planning of business activities.
• Stock Price Prediction via Discovering Multi-Frequency Trading Patterns
  13 Aug 2017 1 repository listed
  Then the future stock prices are predicted as a nonlinear mapping of the combination of these components in an Inverse Fourier Transform (IFT) fashion.
• Context-aware Frame-Semantic Role Labeling
  1 Jan 2015 1 repository listed
  Frame semantic representations have been useful in several applications ranging from text-to-scene generation, to question answering and social network analysis.

Syntology lines on 5 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.