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A multi-layer and multi-ensemble stock trader using deep learning and deep reinforcement learning
8 references·16 citing·47 second hop
A multi-layer and multi-ensemble stock trader using deep learning and deep reinforcement learning (2020)A multi-layer and multi-ensemble stock tr…Stock market prediction using machine learning classifiers and social media, news (2020)Stock market prediction using…Deep learning and time series-to-image encoding for financial forecasting (2020)Deep learning and time series…Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data (2019)Forecasting stock prices with…Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach (2018)Algorithmic financial trading…Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network (2008)Stock market prediction of S&…Performance functions and reinforcement learning for trading systems and portfolios (1998)Performance functions and rei…Stock price pattern recognition-a recurrent neural network approach (1990)Stock price pattern recogniti…Stock market prediction system with modular neural networks (1990)Stock market prediction syste…Speech Emotion Recognition Using Convolution Neural Networks and Multi-Head Convolutional Transformer (2023)Speech Emotion Recognition Us…Deep reinforcement learning for portfolio management (2023)Deep reinforcement learning f…A novel deep reinforcement learning framework with BiLSTM-Attention networks for algorithmic trading (2023)A novel deep reinforcement le…A multi-agent reinforcement learning framework for optimizing financial trading strategies based on TimesNet (2023)A multi-agent reinforcement l…Stock Trading Strategies Based on Deep Reinforcement Learning (2022)Stock Trading Strategies Base…Multi-type data fusion framework based on deep reinforcement learning for algorithmic trading (2022)Multi-type data fusion framew…Forecasting the overnight return direction of stock market index combining global market indices: A multiple-branch deep learning approach (2022)Forecasting the overnight ret…Dynamic stock-decision ensemble strategy based on deep reinforcement learning (2022)Dynamic stock-decision ensemb…A multi-agent deep reinforcement learning framework for algorithmic trading in financial markets (2022)A multi-agent deep reinforcem…A Deep Reinforcement Learning-Based Decision Support System for Automated Stock Market Trading (2022)A Deep Reinforcement Learning…Learning to trade in financial time series using high-frequency through wavelet transformation and deep reinforcement learning (2021)Learning to trade in financia…Explainable Machine Learning Exploiting News and Domain-Specific Lexicon for Stock Market Forecasting (2021)Explainable Machine Learning …Deep learning-based exchange rate prediction during the COVID-19 pandemic (2021)Deep learning-based exchange …A machine learning approach for forecasting hierarchical time series (2021)A machine learning approach f…A Hybrid Method Based on Extreme Learning Machine and Wavelet Transform Denoising for Stock Prediction (2021)A Hybrid Method Based on Extr…CLSTM: Deep Feature-Based Speech Emotion Recognition Using the Hierarchical ConvLSTM Network (2020)CLSTM: Deep Feature-Based Spe…Exposition of a New Theory on the Measurement of Risk (1954)Portfolio Selection: Efficient Diversification of Investments (1959)Mutual Fund Performance (1966)PAMR: Passive aggressive mean reversion strategy for portfolio selection (2012)Online portfolio selection (2014)An adaptive portfolio trading system: A risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown (2017)Time Series Analysis, Forecasting and Control. 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A review and evaluation (1998)An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange (2010)Literature review: Machine learning techniques applied to financial market prediction (2019)Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting (2010)Stock index forecasting based on a hybrid model (2011)Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology (2012)An artificial neural network-GARCH model for international stock return volatility (1997)Forecasting exchange rates using general regression neural networks (2000)Multi-DQN: An ensemble of Deep Q-learning agents for stock market forecasting (2020)
this work references cited by second hop

References

  • 1990Stock market prediction system with modular neural networks654 cited
  • 2018Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach433 cited
  • 2008Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network423 cited
  • 2019Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data342 cited
  • 2020Stock market prediction using machine learning classifiers and social media, news336 cited
  • 1998Performance functions and reinforcement learning for trading systems and portfolios292 cited
  • 2020Deep learning and time series-to-image encoding for financial forecasting267 cited
  • 1990Stock price pattern recognition-a recurrent neural network approach255 cited

Cited by

  • 2020CLSTM: Deep Feature-Based Speech Emotion Recognition Using the Hierarchical ConvLSTM Network145 cited
  • 2021Deep learning-based exchange rate prediction during the COVID-19 pandemic134 cited
  • 2022A multi-agent deep reinforcement learning framework for algorithmic trading in financial markets119 cited
  • 2021Explainable Machine Learning Exploiting News and Domain-Specific Lexicon for Stock Market Forecasting83 cited
  • 2023A multi-agent reinforcement learning framework for optimizing financial trading strategies based on TimesNet77 cited

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  • 2021A machine learning approach for forecasting hierarchical time series74 cited
  • 2023Speech Emotion Recognition Using Convolution Neural Networks and Multi-Head Convolutional Transformer73 cited
  • 2022Multi-type data fusion framework based on deep reinforcement learning for algorithmic trading57 cited
  • 2023A novel deep reinforcement learning framework with BiLSTM-Attention networks for algorithmic trading56 cited
  • 2021Learning to trade in financial time series using high-frequency through wavelet transformation and deep reinforcement learning55 cited
  • 2022A Deep Reinforcement Learning-Based Decision Support System for Automated Stock Market Trading50 cited
  • 2021A Hybrid Method Based on Extreme Learning Machine and Wavelet Transform Denoising for Stock Prediction45 cited
  • 2023Deep reinforcement learning for portfolio management45 cited
  • 2022Forecasting the overnight return direction of stock market index combining global market indices: A multiple-branch deep learning approach44 cited
  • 2022Stock Trading Strategies Based on Deep Reinforcement Learning40 cited
  • 2022Dynamic stock-decision ensemble strategy based on deep reinforcement learning36 cited