Stock Prediction
27 papers with code • 0 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Stock Prediction
StockNet
Most implemented papers
DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News
Xinyi6/DP-LSTM-Differential-Privacy-inspired-LSTM-for-Stock-Prediction-Using-Financial-News
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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 privacy mechanism.
Temporal Relational Ranking for Stock Prediction
hennande/Temporal_Relational_Stock_Ranking
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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.
HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction
dmis-lab/hats
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Methods that use relational data for stock market prediction have been recently proposed, but they are still in their infancy.
Stock trend prediction using news sentiment analysis
nicklamonica/stock-sentiment-analysis
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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%.
Artificial Counselor System for Stock Investment
This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment.
Enhancing Stock Movement Prediction with Adversarial Training
yuxiangalvin/Stock-Move-Prediction-with-Adversarial-Training-Replicate
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The key novelty is that we propose to employ adversarial training to improve the generalization of a neural network prediction model.
Improving S&P stock prediction with time series stock similarity
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.
Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction
However, it is well known that an individual stock price is correlated with prices of other stocks in complex ways.
Stock price prediction using Generative Adversarial Networks
ChickenBenny/Stock-prediction-with-GAN-and-WGAN
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Journal of Computer Science 2021
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 Convolutional Neural Network (CNN) as a discriminator to discriminate between the real stock price and generated stock price.
Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading
Zhihan1996/TradeTheEvent
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Findings (ACL) 2021
In this paper, we introduce an event-driven trading strategy that predicts stock movements by detecting corporate events from news articles.
