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Practical machine learning: Forecasting daily financial markets directions
16 references·0 citing·37 second hopsampled
Practical machine learning: Forecasting daily financial markets directions (2023)Practical machine learning: Forecasting d…Human Trust in Artificial Intelligence: Review of Empirical Research (2020)Human Trust in Artificial Int…Literature review: Machine learning techniques applied to financial market prediction (2019)Literature review: Machine le…Computational Intelligence and Financial Markets: A Survey and Future Directions (2016)Computational Intelligence an…Evaluating multiple classifiers for stock price direction prediction (2015)Evaluating multiple classifie…Predicting stock market index using fusion of machine learning techniques (2014)Predicting stock market index…Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Predicting stock and stock pr…Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting direction of stock…Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)Surveying stock market foreca…Forecasting stock market movement direction with support vector machine (2004)Forecasting stock market move…A hybrid ARIMA and support vector machines model in stock price forecasting (2004)A hybrid ARIMA and support ve…Financial time series forecasting using support vector machines (2003)Financial time series forecas…Application of support vector machines in financial time series forecasting (2001)Application of support vector…Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index (2000)Genetic algorithms approach t…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Efficient Capital Markets: II (1991)Efficient Capital Markets: IIEFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)EFFICIENT CAPITAL MARKETS: A …Book Review: Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Time Series Analysis Forecasting and Control. (1971)Time series forecasting using a hybrid ARIMA and neural network model (2003)Stock Price Prediction Using the ARIMA Model (2014)Stock market prediction system with modular neural networks (1990)Introduction to financial forecasting (1996)Neural network forecasting of the British Pound/US Dollar exchange rate (1998)Support vector machine with adaptive parameters in financial time series forecasting (2003)Stock market's price movement prediction with LSTM neural networks (2017)BUSINESS RESEARCH METHODS (PHƯƠNG PHÁP NGHIÊN CỨU TRONG KINH DOANH) (2023)The arbitrage theory of capital asset pricing (1976)Economic Forces and the Stock Market (1986)The Cross-Section of Expected Stock Returns (1992)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)Corporate financing and investment decisions when firms have information that investors do not have (1984)Common risk factors in the returns on stocks and bonds (1993)Twitter mood predicts the stock market (2011)ESG and financial performance: aggregated evidence from more than 2000 empirical studies (2015)The Behavior of Stock-Market Prices (1965)The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets (1965)ON THE PRICING OF CORPORATE DEBT: THE RISK STRUCTURE OF INTEREST RATES* (1974)Theory of the firm: Managerial behavior, agency costs and ownership structure (1976)Users of the world, unite! The challenges and opportunities of Social Media (2009)Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology (1989)An Integrative Model Of Organizational Trust (1995)Not So Different After All: A Cross-Discipline View Of Trust (1998)Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education (2022)Trust in AI and Its Role in the Acceptance of AI Technologies (2022)Unlocking the value of artificial intelligence in human resource management through AI capability framework (2022)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Applications of deep learning in stock market prediction: Recent progress (2021)Sentiment analysis on social media for stock movement prediction (2015)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)
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References

  • 1970EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*24,470 cited
  • 1991Efficient Capital Markets: II6,030 cited
  • 1998Forecasting with artificial neural networks:4,282 cited
  • 2020Human Trust in Artificial Intelligence: Review of Empirical Research3,634 cited
  • 2003Financial time series forecasting using support vector machines1,746 cited
  • 2001Application of support vector machines in financial time series forecasting1,271 cited
  • 2014Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques1,174 cited
  • 2004Forecasting stock market movement direction with support vector machine1,163 cited
  • 2004A hybrid ARIMA and support vector machines model in stock price forecasting1,019 cited
  • 2010Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange892 cited
  • 2008Surveying stock market forecasting techniques – Part II: Soft computing methods861 cited
  • 2000Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index758 cited
  • 2014Predicting stock market index using fusion of machine learning techniques627 cited
  • 2015Evaluating multiple classifiers for stock price direction prediction

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611 cited
  • 2016Computational Intelligence and Financial Markets: A Survey and Future Directions610 cited
  • 2019Literature review: Machine learning techniques applied to financial market prediction585 cited
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