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Importance of Machine Learning in Making Investment Decision in Stock Market
15 references·0 citing·53 second hopsampled
Importance of Machine Learning in Making Investment Decision in Stock Market (2021)Importance of Machine Learning in Making …Sentiment and Knowledge Based Algorithmic Trading with Deep Reinforcement Learning (2022)Sentiment and Knowledge Based…Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis (2020)Predicting Stock Market Trend…Stock Price Prediction using Technical Indicators: A Predictive Model using Optimal Deep Learning (2019)Stock Price Prediction using …Stock Price Prediction Using LSTM on Indian Share Market (2019)Stock Price Prediction Using …Reinforcement Learning in Financial Markets (2019)Reinforcement Learning in Fin…Predicting the daily return direction of the stock market using hybrid machine learning algorithms (2019)Predicting the daily return d…Reinforcement learning applied to Forex trading (2018)Reinforcement learning applie…NSE Stock Market Prediction Using Deep-Learning Models (2018)NSE Stock Market Prediction U…Listening to Chaotic Whispers (2018)Listening to Chaotic WhispersA Comparative Study of LSTM and DNN for Stock Market Forecasting (2018)A Comparative Study of LSTM a…Stock market one-day ahead movement prediction using disparate data sources (2017)Stock market one-day ahead mo…A Stock Market Trading System Using Deep Neural Network (2017)A Stock Market Trading System…Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend (2016)Artificial Neural Network and…A hybrid stock trading framework integrating technical analysis with machine learning techniques (2016)A hybrid stock trading framew…Optimization of trading systems and portfolios (2002)Optimization of trading syste…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)Evaluating multiple classifiers for stock price direction prediction (2015)Machine Learning Stock Market Prediction Studies: Review and Research Directions (2020)Stock Market Forecasting Using Computational Intelligence: A Survey (2020)Technical analysis strategy optimization using a machine learning approach in stock market indices (2021)The Behavior of Stock-Market Prices (1965)Efficient Capital Markets: II (1991)Review : Knowledge Management and Knowledge Management Systems: Conceptual Foundations And Research Issues1,2 (2001)Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions (2020)Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction (2020)Financial applications of machine learning: A literature review (2023)Giving Content to Investor Sentiment: The Role of Media in the Stock Market (2007)Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction (2014)Predicting stock market index using fusion of machine learning techniques (2014)Knowledge-Driven Stock Trend Prediction and Explanation via Temporal Convolutional Network (2019)Forecasting daily stock trend using multi-filter feature selection and deep learning (2020)A novel ensemble deep learning model for stock prediction based on stock prices and news (2021)Forecasting with artificial neural networks: (1998)Time series forecasting using a hybrid ARIMA and neural network model (2003)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Stock Market Analysis: A Review and Taxonomy of Prediction Techniques (2019)Optimizing LSTM for time series prediction in Indian stock market (2020)Stock price prediction using deep learning and frequency decomposition (2020)WHAT DO WE KNOW ABOUT THE PROFITABILITY OF TECHNICAL ANALYSIS? (2007)Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market (2014)Deep Direct Reinforcement Learning for Financial Signal Representation and Trading (2016)Forecasting stock market for an efficient portfolio by combining XGBoost and Hilbert–Huang transform (2022)Forex market forecasting using machine learning: Systematic Literature Review and meta-analysis (2023)Artificial intelligence techniques in financial trading: A systematic literature review (2024)Market efficiency, long-term returns, and behavioral finance1The comments of Brad Barber, David Hirshleifer, S.P. Kothari, Owen Lamont, Mark Mitchell, Hersh Shefrin, Robert Shiller, Rex Sinquefield, Richard Thaler, Theo Vermaelen, Robert Vishny, Ivo Welch, and a referee have been helpful. Kenneth French and Jay Ritter get special thanks.1 (1998)Stock index forecasting based on a hybrid model (2011)Stock Price Prediction Using the ARIMA Model (2014)Augmented Textual Features-Based Stock Market Prediction (2020)Comparison of Stock Price Prediction Models using Pre-trained Neural Networks (2021)Data science approach to stock prices forecasting in Indonesia during Covid-19 using Long Short-Term Memory (LSTM) (2021)Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction (2021)An Overview of Machine Learning, Deep Learning, and Reinforcement Learning-Based Techniques in Quantitative Finance: Recent Progress and Challenges (2023)Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications (2023)Performance functions and reinforcement learning for trading systems and portfolios (1998)Learning to trade via direct reinforcement (2001)Improving financial trading decisions using deep Q-learning: Predicting the number of shares, action strategies, and transfer learning (2018)Corporate Bankruptcy Prediction: An Approach Towards Better Corporate World (2020)Deep Reinforcement Learning Approach for Trading Automation in the Stock Market (2022)Machine learning in business and finance: a literature review and research opportunities (2024)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data (2019)Explainable stock prices prediction from financial news articles using sentiment analysis (2021)A comprehensive review on multiple hybrid deep learning approaches for stock prediction (2022)Stock Market Prediction with High Accuracy using Machine Learning Techniques (2022)Forecasting stock market movement direction with support vector machine (2004)Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)
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References

  • 2018NSE Stock Market Prediction Using Deep-Learning Models615 cited
  • 2020Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis467 cited
  • 2019Predicting the daily return direction of the stock market using hybrid machine learning algorithms276 cited
  • 2018Listening to Chaotic Whispers274 cited
  • 2017Stock market one-day ahead movement prediction using disparate data sources240 cited
  • 2016A hybrid stock trading framework integrating technical analysis with machine learning techniques215 cited
  • 2019Reinforcement Learning in Financial Markets150 cited
  • 2019Stock Price Prediction Using LSTM on Indian Share Market146 cited
  • 2018A Comparative Study of LSTM and DNN for Stock Market Forecasting144 cited
  • 2018Reinforcement learning applied to Forex trading114 cited
  • 2016Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend90 cited
  • 2002Optimization of trading systems and portfolios67 cited
  • 2017A Stock Market Trading System Using Deep Neural Network50 cited
  • 2019Stock Price Prediction using Technical Indicators: A Predictive Model using Optimal Deep Learning46 cited

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2022
Sentiment and Knowledge Based Algorithmic Trading with Deep Reinforcement Learning
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