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Decision Fusion for Stock Market Prediction: A Systematic Review
16 references·0 citing·47 second hop
Decision Fusion for Stock Market Prediction: A Systematic Review (2022)Decision Fusion for Stock Market Predicti…Stock price prediction using deep learning and frequency decomposition (2020)Stock price prediction using …Stock market movement forecast: A Systematic review (2020)Stock market movement forecas…Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions (2020)Fusion in stock market predic…A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network (2020)A hybrid stock price index fo…Systematic analysis and review of stock market prediction techniques (2019)Systematic analysis and revie…Bitcoin price prediction using machine learning: An approach to sample dimension engineering (2019)Bitcoin price prediction usin…A systematic review of fundamental and technical analysis of stock market predictions (2019)A systematic review of fundam…Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets (2018)Stock Market Prediction on Hi…Predicting the direction of stock market prices using tree-based classifiers (2018)Predicting the direction of s…Financial time series forecasting model based on CEEMDAN and LSTM (2018)Financial time series forecas…An Ensemble of LSTM Neural Networks for High-Frequency Stock Market Classification (2018)An Ensemble of LSTM Neural Ne…Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)Deep neural networks, gradien…Predicting stock market index using fusion of machine learning techniques (2014)Predicting stock market index…Combining expert forecasts: Can anything beat the simple average? (2012)Combining expert forecasts: C…Stock market prediction with multiple classifiers (2006)Stock market prediction with …Combining forecasts: A review and annotated bibliography (1989)Combining forecasts: A review…Expert judgment: Some necessary conditions and an example. (1974)The M3-Competition: results, conclusions and implications (2000)25 years of time series forecasting (2006)Chapter 4 Forecast Combinations (2006)Generalized autoregressive conditional heteroskedasticity (1986)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Sentiment analysis on social media for stock movement prediction (2015)Computational Intelligence and Financial Markets: A Survey and Future Directions (2016)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)On Persistence in Mutual Fund Performance (1997)A five-factor asset pricing model (2014)Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series (2019)Literature review: Machine learning techniques applied to financial market prediction (2019)Deep learning for financial applications : A survey (2020)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)The Efficient Market Hypothesis and Its Critics (2003)Time Series Momentum (2011)Mean–variance portfolio optimization using machine learning-based stock price prediction (2020)Forecasting gold price with the XGBoost algorithm and SHAP interaction values (2021)Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)Application of support vector machines in financial time series forecasting (2001)Introduction to Time Series and Forecasting (2002)Forecasting Volatility in Financial Markets: A Review (2003)A graph-based CNN-LSTM stock price prediction algorithm with leading indicators (2021)Carbon price forecasting based on CEEMDAN and LSTM (2022)BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era (2013)Bitcoin, gold and the dollar – A GARCH volatility analysis (2015)What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis (2015)A Gated Recurrent Unit Approach to Bitcoin Price Prediction (2020)A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms (2021)Forecasting and trading cryptocurrencies with machine learning under changing market conditions (2021)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)Twitter mood predicts the stock market (2011)A comprehensive evaluation of ensemble learning for stock-market prediction (2020)Cryptocurrency trading: a comprehensive survey (2022)Proceedings of the International Joint Conference on Neural Networks, 2003. (2003)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Stock Price Prediction Using the ARIMA Model (2014)Portfolio optimization with return prediction using deep learning and machine learning (2020)The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction (2021)Deep learning with long short-term memory networks for financial market predictions (2017)Transformer-based attention network for stock movement prediction (2022)Survey of feature selection and extraction techniques for stock market prediction (2023)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022 (2023)Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm (2023)TRNN: An efficient time-series recurrent neural network for stock price prediction (2023)
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References

  • 1989Combining forecasts: A review and annotated bibliography2,170 cited
  • 2016Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500749 cited
  • 2018Financial time series forecasting model based on CEEMDAN and LSTM712 cited
  • 2014Predicting stock market index using fusion of machine learning techniques608 cited
  • 2019A systematic review of fundamental and technical analysis of stock market predictions545 cited
  • 2019Bitcoin price prediction using machine learning: An approach to sample dimension engineering420 cited
  • 2018Predicting the direction of stock market prices using tree-based classifiers376 cited
  • 2020Stock market movement forecast: A Systematic review374 cited
  • 2020Stock price prediction using deep learning and frequency decomposition373 cited
  • 2019Systematic analysis and review of stock market prediction techniques335 cited
  • 2012Combining expert forecasts: Can anything beat the simple average?314 cited
  • 2018Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets262 cited
  • 2006Stock market prediction with multiple classifiers239 cited
  • 2018An Ensemble of LSTM Neural Networks for High-Frequency Stock Market Classification230 cited

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2020
Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions
214 cited
  • 2020A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network191 cited
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