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Evaluating and understanding text-based stock price prediction models

Enric Junqué de Fortuny, Tom De Smedt, David Martens, Walter Daelemans
2014 Information Processing & Management  
Finally, we discuss how to gain insight into text-mining-based stock price prediction models in order to evaluate, validate and refine the models.  ...  In the first part of this study we design novel stock price prediction models, based on stateof-the-art text-mining techniques to assert whether we can predict the movement of stock prices more accurately  ...  insight into text-mining-based stock-prediction models?  ... 
doi:10.1016/j.ipm.2013.12.002 fatcat:ujvgvq7zrfe7dc7rr2gn6qbjme

Predicting the Effects of News Sentiments on the Stock Market [article]

Dev Shah, Haruna Isah, Farhana Zulkernine
2018 arXiv   pre-print
Our main contributions include the development of a sentiment analysis dictionary for the financial sector, the development of a dictionary-based sentiment analysis model, and the evaluation of the model  ...  Stock price prediction has attracted many researchers in multiple disciplines including computer science, statistics, economics, finance, and operations research.  ...  (LSTM) neural network model, using stock prices and sentiment analysis model based on social media and news data, may provide more accurate predictions of long and short-term stock price movements.  ... 
arXiv:1812.04199v1 fatcat:mh4gwuudrfgt7olpyxft7oogyy

Events Extracting From Stock Markets on the Web

Dr. Eng. Yousef Abuzir, Dr. Mohammad Dweib, Dr. Eng. Yousef Sabbah, Mr. AbdulRahman M. Baraka
2019 Zenodo  
Based on the unstructured data we collected, we propose a set of rules and techniques to analyze, evaluate and understand the meaning of the events taking place in stock markets.  ...  Accordingly, we have proposed some approaches and rules for data analysis and evaluation to understand the events meanings in stock markets.  ...  Based on the structured data collected, they have proposed a set of rules and techniques to analyze, evaluate and understand the meaning of the events taking place in stock markets.  ... 
doi:10.5281/zenodo.2582942 fatcat:7dt55dhfjfbwfl7sg3fumzioeu

Events Extracting From Stock Markets on the Web

Dr. Eng. Yousef Abuzir, Dr. Mohammad Dweib, Dr. Eng. Yousef Sabbah, Mr. AbdulRahman M. Baraka
2019 Zenodo  
Based on the unstructured data we collected, we propose a set of rules and techniques to analyze, evaluate and understand the meaning of the events taking place in stock markets.  ...  Accordingly, we have proposed some approaches and rules for data analysis and evaluation to understand the events meanings in stock markets.  ...  Based on the structured data collected, they have proposed a set of rules and techniques to analyze, evaluate and understand the meaning of the events taking place in stock markets.  ... 
doi:10.5281/zenodo.2576349 fatcat:b4cw6c4r2ze45j3vifrxfe4sf4

The impact of word sense disambiguation on stock price prediction

Alexander Hogenboom, Alex Brojba-Micu, Flavius Frasincar
2021 Expert systems with applications  
Then, we propose and evaluate our pipeline for event-based WSD-enabled stock price prediction in Sections 3 and 4, respectively.  ...  We assess the merit of word sense disambiguation in event-based stock price prediction in two evaluation scenarios for NASDAQ-100 companies, based on historical stock prices and news articles retrieved  ...  In our first scenario, we use our predicted stock price movements to generate buy (positive predicted change) and sell (negative predicted change) signals, and evaluate the precision of these signals based  ... 
doi:10.1016/j.eswa.2021.115568 fatcat:ojssxqawwng4rofv7wojzwqgoy

Stock Price Prediction Based on Natural Language Processing1

Xiaobin Tang, Nuo Lei, Manru Dong, Dan Ma, Atila Bueno
2022 Complexity  
The keywords used in traditional stock price prediction are mainly based on literature and experience.  ...  price prediction.  ...  not only enriches the index system of stock price prediction but also helps regulators and investors to evaluate stock price trends and control stock price risks.  ... 
doi:10.1155/2022/9031900 fatcat:qstlgv5dnre2jbcird3t2l6pou

Applied Text-Mining Algorithms for Stock Price Prediction Based on Financial News Articles

2019 Managing Global Transitions  
This article includes a developed model and well-defined process that one should undertake in order to contribute in the prediction of the potential stock price fluctuation solely based on financial news  ...  Our proposed model relies on existing text-mining techniques used for sentiment analysis, combined with historical data from relevant news sources as well as stock data.  ...  . proposed model for stock predictions based on financial news In our study we worked towards analyzing data, concretely news articles and historical stock prices to make future predictions about stock  ... 
doi:10.26493/1854-6935.17.335-351 fatcat:kxkonvzxzzdp7i4msubujypgci

A Hybrid Data Analytics Framework with Sentiment Convergence and Multi-Feature Fusion for Stock Trend Prediction

Mohammad Kamel Daradkeh
2022 Electronics  
We evaluated the proposed framework using two case studies from the real estate and communications sectors based on data collected from the Dubai Financial Market (DFM) between 1 January 2020 and 1 December  ...  news events and sentiment trends with quantitative financial data on predicting stock trends.  ...  They also reported that the prediction accuracy can be improved when both stock-related news texts and tweets are counted and used as input for stock price prediction.  ... 
doi:10.3390/electronics11020250 fatcat:mshbaquu3fcftpoaphojl6cu4m

News sensitive stock market prediction: literature review and suggestions

Shazia Usmani, Jawwad A. Shamsi
2021 PeerJ Computer Science  
Stock market prediction is a challenging task as it requires deep insights for extraction of news events, analysis of historic data, and impact of news events on stock price trends.  ...  The challenge is further exacerbated due to the high volatility of stock price trends. However, a detailed overview that discusses the overall context of stock prediction is elusive in literature.  ...  The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  ... 
doi:10.7717/peerj-cs.490 pmid:34013029 pmcid:PMC8114814 fatcat:wuxzdb2avzh73nsbmwfdjybcte

NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-Task Financial Forecasting

Linyi Yang, Jiazheng Li, Ruihai Dong, Yue Zhang, Barry Smyth
2022 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
This paper describes a numeric-oriented hierarchical transformer model (NumHTML) to predict stock returns, and financial risk using multi-modal aligned earnings calls data by taking advantage of the different  ...  Earnings conference call data, including text and audio, is an important source of unstructured data that has been used for various prediction tasks using deep earning and related approaches.  ...  Acknowledgments We acknowledge with thanks the discussion with Boyuan Zheng and Cunxiang Wang from Westlake University, as well as the many others who have.  ... 
doi:10.1609/aaai.v36i10.21414 fatcat:iskx4ojbqnb6zdqaszvif2q5nq

Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model [article]

Jinan Zou, Haiyao Cao, Lingqiao Liu, Yuhao Lin, Ehsan Abbasnejad, Javen Qinfeng Shi
2022 arXiv   pre-print
Based on SRLP, we further incorporate other stock factors to make the final prediction.  ...  Such a design allows us to develop and evaluate NLP-aided stock auto-trading algorithms in a more realistic setting.  ...  Furthermore, we observe that the proposed trading strategies work well in practice. 2 Related Work Text-based Stock Prediction In recent years, the use of text-based information, especially news and  ... 
arXiv:2206.06606v1 fatcat:wy3jaxd7jbbere5cbgnzlbsgyi

Stock Price Prediction: Using Transfer Learning Techniques

Sohan Shetty, Santosh Kurade, Dolly Yadav, Poonam Thakur
2022 International Journal for Research in Applied Science and Engineering Technology  
Abstract: The project is designed to predict the Price of a Stock listed in Indian National Stock Exchange (NSE). Application will run on Microsoft Windows.  ...  The current systems are extremely technical and hard to understand and used by an average Stock market trader who is not skilled in technical aspects of computer.  ...  So to make it happen we are developing a system which will predict the prices of the stock and will be easy to use and understand. II.  ... 
doi:10.22214/ijraset.2022.41807 fatcat:mtxmb2s2mnaqpgek4tku6ovy6e

An Activation Method of Topic Dictionary to Expand Training Data for Trend Rule Discovery

Shigeaki Sakurai, Kyoko Makino, Shigeru Matsumoto
2014 Applied Computational Intelligence and Soft Computing  
This paper applies the method to a task which predicts attractive stock brands based on both news headlines and stock price sequences.  ...  They are inductively acquired from text sequential data and numerical sequential data. The method assigns evaluation objects to the text sequential data by activating a topic dictionary.  ...  The models are used for the prediction. Mittermayer and Knolmayer [11] propose a method that automatically classifies news articles to predict the trends of stock prices.  ... 
doi:10.1155/2014/871412 fatcat:jwwfrilbebembdeuju7ysaspqu

Recent Advances in Stock Market Prediction Using Text Mining: A Survey [chapter]

Faten Subhi Alzazah, Xiaochun Cheng
2020 E-Business [Working Title]  
While many papers reviewed the prediction techniques based on technical analysis methods, the papers that concentrate on the use of text mining methods were scarce.  ...  Technical analysis focuses on analyzing the direction of prices to predict future prices, while fundamental analysis depends on analyzing unstructured textual information like financial news and earning  ...  CNN use for stock market prediction based on text mining results.  ... 
doi:10.5772/intechopen.92253 fatcat:ptioootolbg4fb5kzuovz2af5m

Stock Market Forecasting Based on Text Mining Technology: A Support Vector Machine Method

Yancong Xie
2017 Journal of Computers  
In this paper, we use text mining and sentiment analysis on Chinese online financial news, to predict Chinese stock tendency and stock prices based on support vector machine (SVM).  ...  Secondly, based on this dataset, a specific domain stop-word dictionary and a precise sentiment dictionary are formed. Thirdly, we propose a forecasting model using SVM.  ...  Conclusions and Discussions In general, the SVM method based on text mining technology shows an outstanding result in predicting stock market especially when predicting the specific stock price.  ... 
doi:10.17706/jcp.12.6.500-510 fatcat:mzj7fej4f5e2xhlhogvssipmdm
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