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RCSAN residual enhanced channel spatial attention network for stock price forecasting
16 references·0 citing·45 second hopsampled
RCSAN residual enhanced channel spatial attention network for stock price forecasting (2025)RCSAN residual enhanced channel spatial a…Stock market index prediction using deep Transformer model (2022)Stock market index prediction…Machine learning in finance: A topic modeling approach (2021)Machine learning in finance: …Forecasting stock prices with long-short term memory neural network based on attention mechanism (2020)Forecasting stock prices with…Empirical Asset Pricing via Machine Learning (2020)Empirical Asset Pricing via M…Deep learning for financial applications : A survey (2020)Deep learning for financial a…A CNN-LSTM-Based Model to Forecast Stock Prices (2020)A CNN-LSTM-Based Model to For…CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)CNNpred: CNN-based stock mark…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 …Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach (2018)Algorithmic financial trading…Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Stock price prediction using …Stock market's price movement prediction with LSTM neural networks (2017)Stock market's price movement…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)A Dual-Stage Attention-Based …Deep Learning for Finance: Deep Portfolios (2016)Deep Learning for Finance: De…Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Predicting stock and stock pr…Multivariate GARCH models: a surveyMultivariate GARCH models: a …EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Financial time series forecasting using support vector machines (2003)Forecasting stock market movement direction with support vector machine (2004)Evaluating multiple classifiers for stock price direction prediction (2015)Sentiment analysis on social media for stock movement prediction (2015)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)The Cross-Section of Expected Stock Returns (1992)Market Reactions to Tangible and Intangible Information (2006)Stock Market Prediction Using LSTM Recurrent Neural Network (2020)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (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)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)On Persistence in Mutual Fund Performance (1997)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)A Random Walk Down Wall Street (1973)Applications of deep learning in stock market prediction: Recent progress (2021)Time Series Analysis Forecasting and Control. 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References

  • 2017Deep learning with long short-term memory networks for financial market predictions3,010 cited
  • 2020Empirical Asset Pricing via Machine Learning2,685 cited
  • n.d.Multivariate GARCH models: a survey2,055 cited
  • 2017A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction1,700 cited
  • 2014Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques1,174 cited
  • 2017Stock price prediction using LSTM, RNN and CNN-sliding window model1,134 cited
  • 2017Stock market's price movement prediction with LSTM neural networks986 cited
  • 2016Deep Learning for Finance: Deep Portfolios954 cited
  • 2019CNNpred: CNN-based stock market prediction using a diverse set of variables671 cited
  • 2020A CNN-LSTM-Based Model to Forecast Stock Prices595 cited
  • 2020Deep learning for financial applications : A survey582 cited
  • 2018Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach448 cited
  • 2020Forecasting stock prices with long-short term memory neural network based on attention mechanism403 cited
  • 2022Stock market index prediction using deep Transformer model399 cited
  • 2018

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ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module
385 cited
  • 2021Machine learning in finance: A topic modeling approach198 cited
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