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PEN: Prediction-Explanation Network to Forecast Stock Price Movement with Better Explainability
13 references·0 citing·43 second hop
PEN: Prediction-Explanation Network to Forecast Stock Price Movement with Better Explainability (2023)PEN: Prediction-Explanation Network to Fo…Explainable Machine Learning Exploiting News and Domain-Specific Lexicon for Stock Market Forecasting (2021)Explainable Machine Learning …Coupling Macro-Sector-Micro Financial Indicators for Learning Stock Representations with Less Uncertainty (2021)Coupling Macro-Sector-Micro F…Applications of deep learning in stock market prediction: Recent progress (2021)Applications of deep learning…Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts (2021)Accurate Multivariate Stock M…Technical Analysis of Stock Trends (2018)Technical Analysis of Stock T…Stock Movement Prediction from Tweets and Historical Prices (2018)Stock Movement Prediction fro…Natural language based financial forecasting: a survey (2017)Natural language based financ…Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction (2017)Listening to Chaotic Whispers…Sentiment analysis of Twitter data for predicting stock market movements (2016)Sentiment analysis of Twitter…Text mining of news-headlines for FOREX market prediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment (2014)Text mining of news-headlines…News impact on stock price return via sentiment analysis (2014)News impact on stock price re…Exploiting Topic based Twitter Sentiment for Stock Prediction (2013)Exploiting Topic based Twitte…Twitter mood predicts the stock market (2011)Twitter mood predicts the sto…Giving Content to Investor Sentiment: The Role of Media in the Stock Market (2007)More Than Words: Quantifying Language to Measure Firms' Fundamentals (2008)When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks (2011)Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong (2020)The predictive power of public Twitter sentiment for forecasting cryptocurrency prices (2020)Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards (2004)A survey of the applications of text mining in financial domain (2016)Deep learning for stock market prediction from financial news articles (2017)Listening to Chaotic Whispers (2018)Prospect Theory: An Analysis of Decision under Risk (1979)Prospect theory: An analysis of decision under risk (1988)Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach (2013)Social media and loneliness: Why an Instagram picture may be worth more than a thousand Twitter words (2016)Text as Data (2019)Textual analysis of stock market prediction using breaking financial news (2009)Correlating financial time series with micro-blogging activity (2012)A novel data-driven stock price trend prediction system (2017)Improving stock market prediction via heterogeneous information fusion (2017)A local and global event sentiment based efficient stock exchange forecasting using deep learning (2019)The Behavior of Stock-Market Prices (1965)Predicting the Future with Social Media (2010)Stock Market Analysis: A Review and Taxonomy of Prediction Techniques (2019)Stock market movement forecast: A Systematic review (2020)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos (2018)Technical analysis and sentiment embeddings for market trend prediction (2019)Smoothing, Forecasting and Prediction of Discrete Time Series. (1964)Enhancing Stock Movement Prediction with Adversarial Training (2019)Financial time series forecasting with multi-modality graph neural network (2021)Generalized autoregressive conditional heteroskedasticity (1986)Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency (1993)Machine learning techniques and data for stock market forecasting: A literature review (2022)Stock market index prediction using deep Transformer model (2022)Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications (2023)A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)Stock market's price movement prediction with LSTM neural networks (2017)Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (2017)MetaTrader (2022)Hybrid Information Mixing Module for Stock Movement Prediction (2023)StockMixer: A Simple Yet Strong MLP-Based Architecture for Stock Price Forecasting (2024)Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation (2000)Reexamining the Profitability of Technical Analysis with Data Snooping Checks (2005)
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References

  • 2011Twitter mood predicts the stock market5,204 cited
  • 2021Applications of deep learning in stock market prediction: Recent progress725 cited
  • 2014News impact on stock price return via sentiment analysis506 cited
  • 2016Sentiment analysis of Twitter data for predicting stock market movements482 cited
  • 2018Stock Movement Prediction from Tweets and Historical Prices433 cited
  • 2017Natural language based financial forecasting: a survey399 cited
  • 2014Text mining of news-headlines for FOREX market prediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment276 cited
  • 2018Technical Analysis of Stock Trends266 cited
  • 2013Exploiting Topic based Twitter Sentiment for Stock Prediction210 cited
  • 2021Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts151 cited
  • 2017Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction91 cited
  • 2021Explainable Machine Learning Exploiting News and Domain-Specific Lexicon for Stock Market Forecasting83 cited
  • 2021Coupling Macro-Sector-Micro Financial Indicators for Learning Stock Representations with Less Uncertainty42 cited

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