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BERT-Driven stock price trend prediction utilizing tokenized stock data and multi-step optimization approach
16 references·0 citing·44 second hopsampled
BERT-Driven stock price trend prediction utilizing tokenized stock data and multi-step optimization approach (2024)BERT-Driven stock price trend prediction …TRNN: An efficient time-series recurrent neural network for stock price prediction (2023)TRNN: An efficient time-serie…Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm (2023)Stock price prediction with o…Stock market index prediction using deep Transformer model (2022)Stock market index prediction…Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks (2021)Modeling the Momentum Spillov…CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)CNNpred: CNN-based stock mark…Cascading logistic regression onto gradient boosted decision trees for forecasting and trading stock indices (2019)Cascading logistic regression…Stock price prediction using support vector regression on daily and up to the minute prices (2018)Stock price prediction using …Stock Movement Prediction from Tweets and Historical Prices (2018)Stock Movement Prediction fro…ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module (2018)ModAugNet: A new forecasting …Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (2017)Stock Price Prediction via Di…A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)A Dual-Stage Attention-Based …A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)A deep learning framework for…Sentiment analysis of Twitter data for predicting stock market movements (2016)Sentiment analysis of Twitter…Predicting stock market index using fusion of machine learning techniques (2014)Predicting stock market index…An SVM-based approach for stock market trend prediction (2013)An SVM-based approach for sto…Financial time series forecasting using support vector machines (2003)Financial time series forecas…Generalized autoregressive conditional heteroskedasticity (1986)Chaos and Nonlinear Dynamics: Application to Financial Markets (1991)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Sentiment analysis on social media for stock movement prediction (2015)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Applications of deep learning in stock market prediction: Recent progress (2021)Forecasting with artificial neural networks: (1998)Application of support vector machines in financial time series forecasting (2001)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Stock market's price movement prediction with LSTM neural networks (2017)BUSINESS RESEARCH METHODS (PHƯƠNG PHÁP NGHIÊN CỨU TRONG KINH DOANH) (2023)The Behavior of Stock-Market Prices (1965)Predicting the Future with Social Media (2010)Twitter mood predicts the stock market (2011)Stock Market Analysis: A Review and Taxonomy of Prediction Techniques (2019)A Comprehensive Comparative Study of Artificial Neural Network (ANN) and Support Vector Machines (SVM) on Stock Forecasting (2021)Distributed Representations, Simple Recurrent Networks, and Grammatical Structure (1991)Dynamic Covariance Models for Multivariate Financial Time Series (2013)ARIMA Models and the Box-Jenkins Methodology (2016)A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (2019)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Forecasting stock market movement direction with support vector machine (2004)Deep learning for event-driven stock prediction (2015)Computational Intelligence and Financial Markets: A Survey and Future Directions (2016)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)A Bayesian regularized artificial neural network for stock market forecasting (2013)Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction (2014)Deep learning for financial applications : A survey (2020)Smoothing, Forecasting and Prediction of Discrete Time Series. 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References

  • 2003Financial time series forecasting using support vector machines1,746 cited
  • 2017A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction1,700 cited
  • 2017A deep learning framework for financial time series using stacked autoencoders and long-short term memory1,177 cited
  • 2019CNNpred: CNN-based stock market prediction using a diverse set of variables671 cited
  • 2014Predicting stock market index using fusion of machine learning techniques627 cited
  • 2016Sentiment analysis of Twitter data for predicting stock market movements499 cited
  • 2017Stock Price Prediction via Discovering Multi-Frequency Trading Patterns489 cited
  • 2018Stock Movement Prediction from Tweets and Historical Prices462 cited
  • 2022Stock market index prediction using deep Transformer model399 cited
  • 2018ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module385 cited
  • 2023Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm381 cited
  • 2018Stock price prediction using support vector regression on daily and up to the minute prices359 cited
  • 2023TRNN: An efficient time-series recurrent neural network for stock price prediction191 cited
  • 2013An SVM-based approach for stock market trend prediction

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178 cited
  • 2019Cascading logistic regression onto gradient boosted decision trees for forecasting and trading stock indices125 cited
  • 2021Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks120 cited
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