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Cost Harmonization LightGBM-Based Stock Market Prediction
13 references·0 citing·49 second hop
Cost Harmonization LightGBM-Based Stock Market Prediction (2023)Cost Harmonization LightGBM-Based Stock M…Stock Market Analysis and Prediction for Nifty50 using LSTM Deep Learning Approach (2022)Stock Market Analysis and Pre…ML-GAT:A Multilevel Graph Attention Model for Stock Prediction (2022)ML-GAT:A Multilevel Graph Att…Event prediction within directional change framework using a CNN-LSTM model (2022)Event prediction within direc…Deep learning in the stock market—a systematic survey of practice, backtesting, and applications (2022)Deep learning in the stock ma…Analysis and Forecasting of Financial Time Series Using CNN and LSTM-Based Deep Learning Models (2022)Analysis and Forecasting of F…Hierarchical Adaptive Temporal-Relational Modeling for Stock Trend Prediction (2021)Hierarchical Adaptive Tempora…Financial time series forecasting with multi-modality graph neural network (2021)Financial time series forecas…A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions (2021)A comprehensive survey on dee…Forecasting daily stock trend using multi-filter feature selection and deep learning (2020)Forecasting daily stock trend…Deep Leaming for Stock Market Prediction Using Technical Indicators and Financial News Articles (2018)Deep Leaming for Stock Market…A causal feature selection algorithm for stock prediction modeling (2014)A causal feature selection al…Combining News and Technical Indicators in Daily Stock Price Trends Prediction (2007)Combining News and Technical …The future of competition: co-creating unique value with customers (2004)The future of competition: co…Application of support vector machines in financial time series forecasting (2001)Financial time series forecasting using support vector machines (2003)Investor sentiment and the near-term stock market (2003)Evaluating and understanding text-based stock price prediction models (2014)An intelligent short term stock trading fuzzy system for assisting investors in portfolio management (2015)Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test (1988)Efficient Capital Markets: II (1991)The Sharpe Ratio (1994)Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese Candlestick (2015)Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models (2016)Stock market prediction and Portfolio selection models: a survey (2017)A Random Walk Down Wall Street (1973)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Twitter mood predicts the stock market (2011)Augmented Textual Features-Based Stock Market Prediction (2020)Movement forecasting of financial time series based on adaptive LSTM-BN network (2022)Stock Prediction by Integrating Sentiment Scores of Financial News and MLP-Regressor: A Machine Learning Approach (2023)A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data (2014)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)Stock Price Movement Prediction Using Sentiment Analysis and CandleStick Chart Representation (2021)Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models (2021)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Generalized autoregressive conditional heteroskedasticity (1986)Stock market index prediction based on reservoir computing models (2021)The hybrid PROPHET-SVR approach for forecasting product time series demand with seasonality (2021)An adaptive feature selection schema using improved technical indicators for predicting stock price movements (2022)The Behavior of Stock-Market Prices (1965)Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure (2016)Deep learning with long short-term memory networks for financial market predictions (2017)Investigating the informativeness of technical indicators and news sentiment in financial market price prediction (2022)Scientometric review and analysis of recent approaches to stock market forecasting: Two decades survey (2022)News-based intelligent prediction of financial markets using text mining and machine learning: A systematic literature review (2023)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)An ensemble of a boosted hybrid of deep learning models and technical analysis for forecasting stock prices (2022)Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction (2022)Data-driven stock forecasting models based on neural networks: A review (2024)Deep learning for event-driven stock prediction (2015)A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)Temporal Relational Ranking for Stock Prediction (2019)HGNN: Hierarchical graph neural network for predicting the classification of price-limit-hitting stocks (2022)VGC-GAN: A multi-graph convolution adversarial network for stock price prediction (2023)On the use of cross-validation for time series predictor evaluation (2012)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Development of a Robust Stock Market Prediction Mechanism based on Enhanced Comprehensive Learning Principles (2023)The Artificial Intelligence Revolution in Digital Finance in Saudi Arabia: A Comprehensive Review and Proposed Framework (2023)Deep learning for financial forecasting: A review of recent trends (2025)Co-creation experiences: The next practice in value creation (2004)Managing the co-creation of value (2007)The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes (2019)
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References

  • 2004The future of competition: co-creating unique value with customers2,174 cited
  • 2021Financial time series forecasting with multi-modality graph neural network431 cited
  • 2021A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions232 cited
  • 2020Forecasting daily stock trend using multi-filter feature selection and deep learning166 cited
  • 2022Deep learning in the stock market—a systematic survey of practice, backtesting, and applications139 cited
  • 2007Combining News and Technical Indicators in Daily Stock Price Trends Prediction129 cited
  • 2018Deep Leaming for Stock Market Prediction Using Technical Indicators and Financial News Articles119 cited
  • 2014A causal feature selection algorithm for stock prediction modeling91 cited
  • 2022Analysis and Forecasting of Financial Time Series Using CNN and LSTM-Based Deep Learning Models89 cited
  • 2021Hierarchical Adaptive Temporal-Relational Modeling for Stock Trend Prediction84 cited
  • 2022Stock Market Analysis and Prediction for Nifty50 using LSTM Deep Learning Approach75 cited
  • 2022Event prediction within directional change framework using a CNN-LSTM model71 cited
  • 2022ML-GAT:A Multilevel Graph Attention Model for Stock Prediction57 cited

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