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Forecasting Directional Movement of Stock Prices using Deep Learning
9 references·4 citing·49 second hop
Forecasting Directional Movement of Stock Prices using Deep Learning (2022)Forecasting Directional Movement of Stock…Advances in Big Data Analytics (2022)Advances in Big Data AnalyticsStock Market Forecasting Using Computational Intelligence: A Survey (2020)Stock Market Forecasting Usin…Stock Closing Price Prediction using Machine Learning Techniques (2020)Stock Closing Price Predictio…Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data (2019)Forecasting stock prices with…Deep learning for stock market prediction from financial news articles (2017)Deep learning for stock marke…A multiple support vector machine approach to stock index forecasting with mixed frequency sampling (2017)A multiple support vector mac…Using Structured Events to Predict Stock Price Movement: An Empirical Investigation (2014)Using Structured Events to Pr…Forecasting stock market movement direction with support vector machine (2004)Forecasting stock market move…The Behavior of Stock-Market Prices (1965)The Behavior of Stock-Market …Deep learning for financial forecasting: A review of recent trends (2025)Deep learning for financial f…Stock Market Trend Prediction Using Deep Learning Approach (2024)Stock Market Trend Prediction…Enhancing the Prediction of Stock Market Movement Using Neutrosophic-Logic-Based Sentiment Analysis (2024)Enhancing the Prediction of S…Integrated GCN-LSTM stock prices movement prediction based on knowledge-incorporated graphs construction (2023)Integrated GCN-LSTM stock pri…The Cross-Section of Expected Stock Returns (1992)Application of support vector machines in financial time series forecasting (2001)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)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)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)Does the Stock Market Overreact? 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(1978)Introduction to Time Series and Forecasting (2002)Forecasting stock price using integrated artificial neural network and metaheuristic algorithms compared to time series models (2021)Neural Networks for Financial Time Series Forecasting (2022)Time series forecasting using a hybrid ARIMA and neural network model (2003)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)EVALUATION OF CLASSIFICATION ALGORITHMS USING MCDM AND RANK CORRELATION (2012)Automatic Merging of Scopus and Web of Science Data for Simplified and Effective Bibliometric Analysis (2022)Determining the Factors Influencing Business Analytics Adoption at Organizational Level: A Systematic Literature Review (2023)From Bricks to Clicks: The Potential of Big Data Analytics for Revolutionizing the Information Landscape in Higher Education Sector (2023)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)Deep learning for financial applications : A survey (2020)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)
this work references cited by second hop

References

  • 1965The Behavior of Stock-Market Prices8,707 cited
  • 2004Forecasting stock market movement direction with support vector machine1,119 cited
  • 2020Stock Closing Price Prediction using Machine Learning Techniques638 cited
  • 2019Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data342 cited
  • 2014Using Structured Events to Predict Stock Price Movement: An Empirical Investigation283 cited
  • 2017Deep learning for stock market prediction from financial news articles238 cited
  • 2020Stock Market Forecasting Using Computational Intelligence: A Survey209 cited
  • 2022Advances in Big Data Analytics207 cited
  • 2017A multiple support vector machine approach to stock index forecasting with mixed frequency sampling78 cited

Cited by

  • 2025Deep learning for financial forecasting: A review of recent trends61 cited
  • 2023Integrated GCN-LSTM stock prices movement prediction based on knowledge-incorporated graphs construction53 cited
  • 2024Enhancing the Prediction of Stock Market Movement Using Neutrosophic-Logic-Based Sentiment Analysis49 cited
  • 2024Stock Market Trend Prediction Using Deep Learning Approach44 cited

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