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Multimodal market information fusion for stock price trend prediction in the pharmaceutical sector
16 references·0 citing·55 second hop
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(2003)Do Momentum-Based Strategies …Smoothing, Forecasting and Prediction of Discrete Time Series. (1964)Textual analysis of stock market prediction using breaking financial news (2009)Twitter mood predicts the stock market (2011)Enhancing Stock Movement Prediction with Adversarial Training (2019)Technical analysis and sentiment embeddings for market trend prediction (2019)Financial time series forecasting with multi-modality graph neural network (2021)Economic prediction using neural networks: the case of IBM daily stock returns (1988)Time series forecasting using a hybrid ARIMA and neural network model (2003)Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)Harvesting social media sentiment analysis to enhance stock market prediction using deep learning (2021)Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)Predicting stock market index using LSTM (2022)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks (2011)Stock Market Forecasting Using Deep Learning and Technical Analysis: A Systematic Review (2020)Stock Price Forecasting with Deep Learning: A Comparative Study (2020)Transformer-based attention network for stock movement prediction (2022)The Combination of Forecasts (1969)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)A hybrid approach of adaptive wavelet transform, long short-term memory and ARIMA-GARCH family models for the stock index prediction (2021)Survey of feature selection and extraction techniques for stock market prediction (2023)Data-driven stock forecasting models based on neural networks: A review (2024)Time Series Analysis: Forecasting and Control (1977)Deep Learning for Finance: Deep Portfolios (2016)The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction (2021)Stock Price Prediction Using CNN-BiLSTM-Attention Model (2023)TRNN: An efficient time-series recurrent neural network for stock price prediction (2023)A model of investor sentiment /Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Giving Content to Investor Sentiment: The Role of Media in the Stock Market (2007)COVID-19 and stock market volatility: An industry level analysis (2020)Deaths, Panic, Lockdowns and US Equity Markets: The Case of COVID-19 Pandemic (2020)Implications of COVID-19 Pandemic on the Global Trade Networks (2020)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 using LSTM, RNN and CNN-sliding window model (2017)Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts (2021)Stock market prediction using deep learning algorithms (2021)Deep reinforcement learning for stock portfolio optimization by connecting with modern portfolio theory (2023)Forecasting stock market movement direction with support vector machine (2004)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications (2023)The Behavior of Stock-Market Prices (1965)A Simple Model of Herd Behavior (1992)Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency (1993)Institutional Investors, Past Performance, and Dynamic Loss Aversion (2009)The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market (2009)Carry Trade and Momentum in Currency Markets (2011)Noise Trader Risk in Financial Markets (1990)Investor Psychology and Security Market Under‐ and Overreactions (1998)Investor Sentiment and the Cross‐Section of Stock Returns (2006)In Search of Attention (2011)The short of it: Investor sentiment and anomalies (2011)Policy Uncertainty and Corporate Investment (2015)
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References

  • 2020Integración de los mercados financieros Latinoamericanos por medio de MILA3,764 cited
  • 2020Stock Market Prediction Using LSTM Recurrent Neural Network642 cited
  • 2020COVID-19: Media coverage and financial markets behavior—A sectoral inquiry567 cited
  • 2020Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis467 cited
  • 2018Stock Movement Prediction from Tweets and Historical Prices433 cited
  • 2019Stock price prediction based on deep neural networks378 cited
  • 2020Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong370 cited
  • 2003Do Momentum-Based Strategies Still Work in Foreign Currency Markets?309 cited
  • 2020Forecasting method of stock market volatility in time series data based on mixed model of ARIMA and XGBoost242 cited
  • 2020Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction231 cited
  • 2020Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions214 cited
  • 2022Adaptability of Financial Time Series Prediction Based on BiLSTM202 cited
  • 2020A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network191 cited
  • 2021The impact of COVID-19 on the stock market crash risk in China

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186 cited
  • 2022RETRACTED ARTICLE: An optimal deep learning-based LSTM for stock price prediction using twitter sentiment analysis162 cited
  • 2018A study on novel filtering and relationship between input-features and target-vectors in a deep learning model for stock price prediction107 cited
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