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Adaptive stock trading strategies with deep reinforcement learning methods
6 references·16 citing·52 second hop
Adaptive stock trading strategies with deep reinforcement learning methods (2020)Adaptive stock trading strategies with de…Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting (2019)Class-imbalanced dynamic fina…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)A deep learning framework for…Forecasting daily stock market return using dimensionality reduction (2016)Forecasting daily stock marke…Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble (2016)Dynamic financial distress pr…Deep Direct Reinforcement Learning for Financial Signal Representation and Trading (2016)Deep Direct Reinforcement Lea…What Is Quantitative Research? 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learning for algorithmic trading (2022)Multi-type data fusion framew…Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition (2022)Multi-step-ahead stock price …Multi-scale local cues and hierarchical attention-based LSTM for stock price trend prediction (2022)Multi-scale local cues and hi…Learning financial asset-specific trading rules via deep reinforcement learning (2022)Learning financial asset-spec…Price graphs: Utilizing the structural information of financial time series for stock prediction (2021)Price graphs: Utilizing the s…Learning to trade in financial time series using high-frequency through wavelet transformation and deep reinforcement learning (2021)Learning to trade in financia…Deep Reinforcement Learning for Trading—A Critical Survey (2021)Deep Reinforcement Learning f…Deep reinforcement learning for portfolio management of markets with a dynamic number of assets (2020)Deep reinforcement learning 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market movement direction with support vector machine (2004)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Temporal Relational Ranking for Stock Prediction (2019)Financial Ratios As Predictors of Failure (1966)Long-Term Memory in Stock Market Prices (1991)From time series to complex networks: The visibility graph (2008)A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)GCNET: Graph-based prediction of stock price movement using graph convolutional network (2022)LSTM-ReGAT: A network-centric approach for cryptocurrency price trend prediction (2023)Quantitative stock portfolio optimization by multi-task learning risk and return (2023)Comparing Predictive Accuracy (1995)Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting (2013)A novel graph convolutional feature based convolutional neural network for stock trend prediction (2020)A novel hybrid model for 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References

  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
  • 2017A deep learning framework for financial time series using stacked autoencoders and long-short term memory1,131 cited
  • 2016Deep Direct Reinforcement Learning for Financial Signal Representation and Trading821 cited
  • 2016Forecasting daily stock market return using dimensionality reduction395 cited
  • 2019Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting363 cited
  • 2016Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble173 cited

Cited by

  • 2023An Overview of Machine Learning, Deep Learning, and Reinforcement Learning-Based Techniques in Quantitative Finance: Recent Progress and Challenges211 cited
  • 2024What Is Quantitative Research? An Overview and Guidelines165 cited
  • 2022Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition117 cited
  • 2021Price graphs: Utilizing the structural information of financial time series for stock prediction92 cited
  • 2020Deep reinforcement learning for portfolio management of markets with a dynamic number of assets85 cited
  • 2023Deep LSTM and LSTM-Attention Q-learning based reinforcement learning in oil and gas sector prediction83 cited
  • 2023

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A multi-agent reinforcement learning framework for optimizing financial trading strategies based on TimesNet
77 cited
  • 2023Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach77 cited
  • 2020A Q-learning agent for automated trading in equity stock markets74 cited
  • 2022Multi-scale local cues and hierarchical attention-based LSTM for stock price trend prediction73 cited
  • 2024Artificial intelligence techniques in financial trading: A systematic literature review73 cited
  • 2022Learning financial asset-specific trading rules via deep reinforcement learning66 cited
  • 2022Multi-type data fusion framework based on deep reinforcement learning for algorithmic trading57 cited
  • 2023Stock ranking prediction using a graph aggregation network based on stock price and stock relationship information57 cited
  • 2021Learning to trade in financial time series using high-frequency through wavelet transformation and deep reinforcement learning55 cited
  • 2021Deep Reinforcement Learning for Trading—A Critical Survey53 cited