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HGNN: Hierarchical graph neural network for predicting the classification of price-limit-hitting stocks
16 references·0 citing·44 second hop
HGNN: Hierarchical graph neural network for predicting the classification of price-limit-hitting stocks (2022)HGNN: Hierarchical graph neural network f…Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction (2020)Hierarchical Multi-Scale Gaus…A novel graph convolutional feature based convolutional neural network for stock trend prediction (2020)A novel graph convolutional f…A Multimodal Event-Driven LSTM Model for Stock Prediction Using Online News (2020)A Multimodal Event-Driven LST…Temporal Relational Ranking for Stock Prediction (2019)Temporal Relational Ranking f…Enhancing Stock Movement Prediction with Adversarial Training (2019)Enhancing Stock Movement Pred…Technical Analysis of Stock Trends (2018)Technical Analysis of Stock T…Incorporating Corporation Relationship via Graph Convolutional Neural Networks for Stock Price Prediction (2018)Incorporating Corporation Rel…Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (2017)Stock Price Prediction via Di…Stock market's price movement prediction with LSTM neural networks (2017)Stock market's price movement…A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)A Dual-Stage Attention-Based …Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches (2010)Combining multiple feature se…Proceedings of the International Joint Conference on Neural Networks, 2003. (2003)Proceedings of the Internatio…Financial time series forecasting using support vector machines (2003)Financial time series forecas…Price Limit Performance: Evidence from the Tokyo Stock Exchange (1997)Price Limit Performance: Evid…Mean reversion in stock prices (1988)Mean reversion in stock pricesThe Behavior of Stock-Market Prices (1965)The Behavior of Stock-Market …The Extreme Value Method for Estimating the Variance of the Rate of Return (1980)The Relation Between Price Changes and Trading Volume: A Survey (1987)Why Does Stock Market Volatility Change Over Time? (1989)Limits of arbitrage and idiosyncratic volatility: Evidence from China stock market (2016)Daily price limits and destructive market behavior (2018)Pandemic-Related Financial Market Volatility Spillovers: Evidence from the Chinese COVID-19 Epicentre (2020)Forecasting with artificial neural networks: (1998)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)Random Walks in Stock Market Prices (1995)Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation (2000)Predicting short-term stock prices using ensemble methods and online data sources (2018)Evaluation of Tree-Based Ensemble Machine Learning Models in Predicting Stock Price Direction of Movement (2020)Stock market index prediction using deep Transformer model (2022)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)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)A Survey of Forex and Stock Price Prediction Using Deep Learning (2021)Applications of deep learning in stock market prediction: Recent progress (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)Predicting stock market index using fusion of machine learning techniques (2014)Listening to Chaotic Whispers (2018)A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions (2021)Textual analysis of stock market prediction using breaking financial news (2009)Wikidata (2014)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)Transformer-based attention network for stock movement prediction (2022)Asset Prices in an Exchange Economy (1978)Does the Stock Market Overreact? (1985)Positive Feedback Investment Strategies and Destabilizing Rational Speculation (1990)Simple Technical Trading Rules and the Stochastic Properties of Stock Returns (1992)Investor Psychology and Asset Pricing (2001)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)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong (2020)Stock market movement forecast: A Systematic review (2020)
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References

  • 1965The Behavior of Stock-Market Prices8,707 cited
  • 1988Mean reversion in stock prices1,888 cited
  • 2003Financial time series forecasting using support vector machines1,734 cited
  • 2003Proceedings of the International Joint Conference on Neural Networks, 2003.1,674 cited
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  • 2017Stock market's price movement prediction with LSTM neural networks943 cited
  • 2019Temporal Relational Ranking for Stock Prediction551 cited
  • 2017Stock Price Prediction via Discovering Multi-Frequency Trading Patterns476 cited
  • 2010Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches378 cited
  • 1997Price Limit Performance: Evidence from the Tokyo Stock Exchange377 cited
  • 2020A novel graph convolutional feature based convolutional neural network for stock trend prediction284 cited
  • 2019Enhancing Stock Movement Prediction with Adversarial Training279 cited
  • 2018Technical Analysis of Stock Trends266 cited
  • 2018Incorporating Corporation Relationship via Graph Convolutional Neural Networks for Stock Price Prediction253 cited
  • 2020Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction

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231 cited
  • 2020A Multimodal Event-Driven LSTM Model for Stock Prediction Using Online News213 cited
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