Stock Price Prediction
26 papers with code • 1 benchmarks • 2 datasets
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.
Astock
Latest papers
Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading
Zhihan1996/TradeTheEvent
•
•
Findings (ACL) 2021
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
ChickenBenny/Stock-prediction-with-GAN-and-WGAN
•
•
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.
Trader-Company Method: A Metaheuristic for Interpretable Stock Price Prediction
We show the effectiveness of our method by conducting experiments on real market data.
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.
Deep Stock Predictions
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.
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
•
•
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.
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.
Particle Filter Recurrent Neural Networks
Yusufma03/pfrnns
•
•
Recurrent neural networks (RNNs) have been extraordinarily successful for prediction with sequential data.
Artificial Counselor System for Stock Investment
This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment.
Predicting the Effects of News Sentiments on the Stock Market
nicklamonica/stock-sentiment-analysis
•
•
Stock market forecasting is very important in the planning of business activities.
