Stock Price Prediction
13 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Stock Price Prediction
| Trend | Dataset | Best Model | Paper | Code | Compare |
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EDT
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.
Neural networks for stock price prediction
Due to the extremely volatile nature of financial markets, it is commonly accepted that stock price prediction is a task full of challenge.
Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models
In this work, we propose an approach of hybrid modeling for stock price prediction building different machine learning and deep learning-based models.
Automatic Relevance Determination in Nonnegative Matrix Factorization with the β-Divergence
broadinstitute/getzlab-SignatureAnalyzer
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This paper addresses the estimation of the latent dimensionality in nonnegative matrix factorization (NMF) with the \beta-divergence.
Artificial Counselor System for Stock Investment
This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment.
Context-aware Frame-Semantic Role Labeling
Frame semantic representations have been useful in several applications ranging from text-to-scene generation, to question answering and social network analysis.
Stock Price Prediction via Discovering Multi-Frequency Trading Patterns
microsoft/qlib
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Then the future stock prices are predicted as a nonlinear mapping of the combination of these components in an Inverse Fourier Transform (IFT) fashion.
Predicting the Effects of News Sentiments on the Stock Market
nicklamonica/stock-sentiment-analysis
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Stock market forecasting is very important in the planning of business activities.
Particle Filter Recurrent Neural Networks
Yusufma03/pfrnns
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Recurrent neural networks (RNNs) have been extraordinarily successful for prediction with sequential data.
A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processing
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 prediction horizon of one week.
