Stock Price Prediction

25 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.

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 20 Dec 2019

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.

Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models

amanjain252002/Stock-Price-Prediction 20 Sep 2020

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

getzlab/signatureanalyzer 25 Nov 2011

This paper addresses the estimation of the latent dimensionality in nonnegative matrix factorization (NMF) with the \beta-divergence.

Neural networks for stock price prediction

xrndai/DeepDayTrade 29 May 2018

Due to the extremely volatile nature of financial markets, it is commonly accepted that stock price prediction is a task full of challenge.

Artificial Counselor System for Stock Investment

bghojogh/Fuzzy-Investment-Counselor Proceedings of the AAAI Conference on Artificial Intelligence 2019

This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment.

Stock Price Prediction Based on Natural Language Processing

thlzm/codeforpaper Complexity 2022

The keywords used in traditional stock price prediction are mainly based on literature and experience.

Context-aware Frame-Semantic Role Labeling

microth/mateplus TACL 2015

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 13 Aug 2017

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 11 Dec 2018

Stock market forecasting is very important in the planning of business activities.