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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
16 references·16 citing·37 second hopsampled
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 framework fo…Stock market's price movement prediction with LSTM neural networks (2017)Stock market's price movement…Machine Learning With Big Data: Challenges and Approaches (2017)Machine Learning With Big Dat…Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Deep learning networks for st…A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)A deep learning framework for…A LSTM-based method for stock returns prediction: A case study of China stock market (2015)A LSTM-based method for stock…Stock Price Prediction Using the ARIMA Model (2014)Stock Price Prediction Using …Predicting stock market index using fusion of machine learning techniques (2014)Predicting stock market index…Comparing Predictive Accuracy (2002)Comparing Predictive AccuracyApplication of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index (2002)Application of neural network…Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index (2000)Genetic algorithms approach t…Comparing Predictive Accuracy (1994)Comparing Predictive AccuracyTime Series Analysis: Forecasting and Control. (1978)Time Series Analysis: Forecas…Time Series Analysis Forecasting and Control. (1971)Time Series Analysis Forecast…EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)EFFICIENT CAPITAL MARKETS: A …The Behavior of Stock-Market Prices (1965)The Behavior of Stock-Market …Théorie de la spéculation (1900)Théorie de la spéculationStockNet—GRU based stock index prediction (2022)StockNet—GRU based stock inde…Deep Learning-based Integrated Framework for stock price movement prediction (2022)Deep Learning-based Integrate…Deep learning in the stock market—a systematic survey of practice, backtesting, and applications (2022)Deep learning in the stock ma…BiCuDNNLSTM-1dCNN — A hybrid deep learning-based predictive model for stock price prediction (2022)BiCuDNNLSTM-1dCNN — A hybrid …A survey on machine learning models for financial time series forecasting (2022)A survey on machine learning …Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions (2021)Stock Market Prediction Using…Stock market forecasting using a multi-task approach integrating long short-term memory and the random forest framework (2021)Stock market forecasting usin…NGCU: A New RNN Model for Time-Series Data Prediction (2021)NGCU: A New RNN Model for Tim…Forecasting stock index price using the CEEMDAN-LSTM model (2021)Forecasting stock index price…A stock price prediction method based on deep learning technology (2021)A stock price prediction meth…A seasonal-trend decomposition-based dendritic neuron model for financial time series prediction (2021)A seasonal-trend decompositio…Stock Price Prediction Using CNN and LSTM-Based Deep Learning Models (2020)Stock Price Prediction Using …Deep learning in finance and banking: A literature review and classification (2020)Deep learning in finance and …A novel deep learning framework: Prediction and analysis of financial time series using CEEMD and LSTM (2020)A novel deep learning framewo…A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network (2020)A hybrid stock price index fo…Portfolio formation with preselection using deep learning from long-term financial data (2019)Portfolio formation with pres…DISTRIBUTION OF INCOMES OF CORPORATIONS AMONG DIVIDENDS, RETAINED EARNINGS AND TAXES (1956)Portfolio Selection: Efficient Diversification of Investments (1959)Dividend Policy, Growth, and the Valuation of Shares (1961)Risk, Return, and Equilibrium: Empirical Tests (1973)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets (1965)ON THE PRICING OF CORPORATE DEBT: THE RISK STRUCTURE OF INTEREST RATES* (1974)Theory of the firm: Managerial behavior, agency costs and ownership structure (1976)Users of the world, unite! 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References

  • 1970EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*15,723 cited
  • 1965The Behavior of Stock-Market Prices8,707 cited
  • 1971Time Series Analysis Forecasting and Control.6,714 cited
  • 1994Comparing Predictive Accuracy5,495 cited
  • 1978Time Series Analysis: Forecasting and Control.5,299 cited
  • 1900Théorie de la spéculation2,605 cited
  • 2002Comparing Predictive Accuracy1,745 cited
  • 2014Stock Price Prediction Using the ARIMA Model1,153 cited
  • 2017A deep learning framework for financial time series using stacked autoencoders and long-short term memory1,131 cited
  • 2017Machine Learning With Big Data: Challenges and Approaches1,023 cited
  • 2017Stock market's price movement prediction with LSTM neural networks943 cited
  • 2017Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies833 cited
  • 2000Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index758 cited
  • 2015A LSTM-based method for stock returns prediction: A case study of China stock market734 cited
  • 2014Predicting stock market index using fusion of machine learning techniques

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608 cited
  • 2002Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index527 cited
  • Cited by

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    • 2022Deep Learning-based Integrated Framework for stock price movement prediction147 cited
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