Stock Market Prediction
41 papers with code • 3 benchmarks • 4 datasets
Libraries
Use these libraries to find Stock Market Prediction models and implementations
StockNet
Latest papers with no code
Distributed Stochastic Bandit Learning with Delayed Context Observation
We consider the problem where M agents collaboratively interact with an instance of a stochastic K-armed contextual bandit, where K>>M.
Univariate and Multivariate LSTM Model for Short-Term Stock Market Prediction
In the first approach, closing prices of two selected companies are directly applied on univariate LSTM model.
Stock Price Prediction using Sentiment Analysis and Deep Learning for Indian Markets
Two models were used as part of the exercise, LSTM was the first model with historical prices as the independent variable.
Machine Learning Models in Stock Market Prediction
The techniques used for empirical study are Adaptive Boost (AdaBoost), k-Nearest Neighbors (kNN), Linear Regression (LR), Artificial Neural Network (ANN), Random Forest (RF), Stochastic Gradient Descent (SGD), Support Vector Machine (SVM) and Decision Trees (DT).
A Novel Deep Reinforcement Learning Based Stock Direction Prediction using Knowledge Graph and Community Aware Sentiments
In this study, we propose a novel method that is based on deep reinforcement learning methodologies for the direction prediction of stocks using sentiments of community and knowledge graph.
A comparative study of Different Machine Learning Regressors For Stock Market Prediction
For the development of successful share trading strategies, forecasting the course of action of the stock market index is important.
Stock2Vec: A Hybrid Deep Learning Framework for Stock Market Prediction with Representation Learning and Temporal Convolutional Network
We have proposed to develop a global hybrid deep learning framework to predict the daily prices in the stock market.
A Novel Distributed Representation of News (DRNews) for Stock Market Predictions
In this study, a novel Distributed Representation of News (DRNews) model is developed and applied in deep learning-based stock market predictions.
NLP Analytics in Finance with DoRe: A French 250M Tokens Corpus of Corporate Annual Reports
Recent advances in neural computing and word embeddings for semantic processing open many new applications areas which had been left unaddressed so far because of inadequate language understanding capacity.
Deep learning for Stock Market Prediction
This paper concentrates on the future prediction of stock market groups.
