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Enhancing Stock Market Prediction: A Robust LSTM-DNN Model Analysis on 26 Real-Life Datasets
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Enhancing Stock Market Prediction: A Robust LSTM-DNN Model Analysis on 26 Real-Life Datasets (2024)Enhancing Stock Market Prediction: A Robu…Harnessing a Hybrid CNN-LSTM Model for Portfolio Performance: A Case Study on Stock Selection and Optimization (2023)Harnessing a Hybrid CNN-LSTM …A Stock Price Prediction Method Based on BiLSTM and Improved Transformer (2023)A Stock Price Prediction Meth…Stock Market Analysis and Prediction for Nifty50 using LSTM Deep Learning Approach (2022)Stock Market Analysis and Pre…Adaptability of Financial Time Series Prediction Based on BiLSTM (2022)Adaptability of Financial Tim…A Hybrid Prediction Model Integrating GARCH Models With a Distribution Manipulation Strategy Based on LSTM Networks for Stock Market Volatility (2022)A Hybrid Prediction Model Int…A Stock Closing Price Prediction Model Based on CNN‐BiSLSTM (2021)A Stock Closing Price Predict…Stock Closing Price Prediction using Machine Learning Techniques (2020)Stock Closing Price Predictio…A Multimodal Event-Driven LSTM Model for Stock Prediction Using Online News (2020)A Multimodal Event-Driven LST…Improving Stock Closing Price Prediction Using Recurrent Neural Network and Technical Indicators (2018)Improving Stock Closing Price…Price Trend Prediction of Stock Market Using Outlier Data Mining Algorithm (2015)Price Trend Prediction of Sto…Forecasting with artificial neural networks: (1998)Illiquidity and stock returns: cross-section and time-series effects (2002)The Efficient Market Hypothesis and Its Critics (2003)Stock Market Prediction using Machine Learning Algorithms: A Classification Study (2018)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Another look at measures of forecast accuracy (2006)A LSTM-based method for stock returns prediction: A case study of China stock market (2015)Portfolio management system in equity market neutral using reinforcement learning (2021)A Black Swan event-based hybrid model for Indian stock markets’ trends prediction (2022)Convolutional neural network for stock trading using technical indicators (2022)Common risk factors in the returns on stocks and bonds (1993)Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency (1993)A Survey of Corporate Governance (1997)Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks (2021)Multi-source aggregated classification for stock price movement prediction (2022)Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction (2022)Time series forecasting using a hybrid ARIMA and neural network model (2003)Forecasting stock market movement direction with support vector machine (2004)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Feature selection and deep neural networks for stock price direction forecasting using technical analysis indicators (2021)Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere—a bibliometric analysis (2023)SMP-DL: a novel stock market prediction approach based on deep learning for effective trend forecasting (2023)Deep learning with long short-term memory networks for financial market predictions (2017)Stock market's price movement prediction with LSTM neural networks (2017)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Dynamic Black Litterman portfolios with views derived via CNN-BiLSTM predictions (2022)Deep Learning for Financial Time Series Prediction: A State-of-the-Art Review of Standalone and Hybrid Models (2023)Forecasting multistep daily stock prices for long-term investment decisions: A study of deep learning models on global indices (2023)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Stock Price Prediction Using the ARIMA Model (2014)Markowitz Mean-Variance Portfolio Optimization with Predictive Stock Selection Using Machine Learning (2022)Data-driven stock forecasting models based on neural networks: A review (2024)Deep learning systems for forecasting the prices of crude oil and precious metals (2024)Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)What do the AI methods tell us about predicting price volatility of key natural resources: Evidence from hyperparameter tuning (2022)An Enhanced IHHO-LSTM Model for Predicting Online Public Opinion Trends in Public Health Emergencies (2024)Advanced AI and big data techniques in E-finance: a comprehensive survey (2025)A feature weighted support vector machine and K-nearest neighbor algorithm for stock market indices prediction (2017)A CNN-BiLSTM-AM method for stock price prediction (2020)A CNN-LSTM-Based Model to Forecast Stock Prices (2020)PORTFOLIO SELECTION* (1952)On the use of cross-validation for time series predictor evaluation (2012)
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References

  • 2020Stock Closing Price Prediction using Machine Learning Techniques638 cited
  • 2020A Multimodal Event-Driven LSTM Model for Stock Prediction Using Online News213 cited
  • 2022Adaptability of Financial Time Series Prediction Based on BiLSTM202 cited
  • 2023A Stock Price Prediction Method Based on BiLSTM and Improved Transformer125 cited
  • 2018Improving Stock Closing Price Prediction Using Recurrent Neural Network and Technical Indicators92 cited
  • 2022Stock Market Analysis and Prediction for Nifty50 using LSTM Deep Learning Approach75 cited
  • 2021A Stock Closing Price Prediction Model Based on CNN‐BiSLSTM72 cited
  • 2022A Hybrid Prediction Model Integrating GARCH Models With a Distribution Manipulation Strategy Based on LSTM Networks for Stock Market Volatility71 cited
  • 2023Harnessing a Hybrid CNN-LSTM Model for Portfolio Performance: A Case Study on Stock Selection and Optimization67 cited
  • 2015Price Trend Prediction of Stock Market Using Outlier Data Mining Algorithm48 cited

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