However, whether these models can work on stock market movement prediction has not been studied. In this paper, based on the stock index data of the United States and China, we try to compare and predict the movement by two machine learning models and four deep learning models for different...
Predictions on stock market prices are a great challenge due to the fact that it is an immensely complex, chaotic and dynamic environment. There are many studies from various areas aiming to take on that challenge and Machine Learning approaches have been the focus of many of them. There are...
METHODS AND SYSTEMS FOR PREDICTING MARKET BEHAVIOR BASED ON NEWS AND SENTIMENT ANALYSIS The present invention provides a method, system and software that provide a predictive model responsive to the correlation of news articles to stock price movement. The invention analyzes the derivative or ratio of...
Mehtab, S, Sen, J (2019) A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processing. Available at SSRN: https://ssrn.com/abstract=3502624 Nelson, DM, Pereira, AC, & de Oliveira, RA (2017) Stock market’s price movement prediction with LSTM ne...
Stock price/movement prediction is an extremely difficult task. Personally, I don't think any of the stock prediction models out there shouldn't be taken for granted and blindly rely on them. However, models might be able to predict stock price movement correctly most of the time, but not ...
2.1 Stock Prediction 股票预测 对于给定的股票 ∈ S,一个目标预测日期 ,以及相关的历史价格和新闻数据,我们定义了一个时期 T 天内的股票移动预测标签如下: For a given stock ∈ S, a target prediction date , and related historical prices and news data, we define stock movement prediction label over ...
In the era of big data, deep learning for predicting stock market prices and trends has become even more popular than before. We collected 2 years of data from Chinese stock market and proposed a comprehensive customization of feature engineering an
Multi-source aggregated classification for stock price movement prediction 2023, Information Fusion Citation Excerpt : However, these methods have two shortcomings: (1) Annotating a huge domain-specific sentiment analysis dataset is expensive and time-consuming; (2) The sentiment polarities based on sem...
Machine learning for stock market prediction has recently been popular for identifying stock selection strategies and providing market insights. In this study, we adopted machine learning algorithms to analyze technical indicators, and Google Trends search terms based on the Thai stock market. This study...
Yumo Xu and Shay B. Cohen. 2018.Stock Movement Prediction from Tweets and Historical Prices. In Proceedings of the 56st Annual Meeting of the Association for Computational Linguistics. Melbourne, Australia, volume 1. Stock movement prediction is a challenging problem: the market is highlystochastic...