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Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets
14 references·13 citing·43 second hop
Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets (2017)Predictability of machine learning techni…Proximal support vector machine based hybrid prediction models for trend forecasting in financial markets (2016)Proximal support vector machi…Application of artificial neural network for the prediction of stock market returns: The case of the Japanese stock market (2016)Application of artificial neu…Application of artificial neural network models and principal component analysis method in predicting stock prices on Tehran Stock Exchange (2015)Application of artificial neu…Quantifying Trading Behavior in Financial Markets Using Google Trends (2013)Quantifying Trading Behavior …Predicting the Present with Google Trends (2012)Predicting the Present with G…Using artificial neural network models in stock market index prediction (2011)Using artificial neural netwo…In Search of Attention (2011)In Search of AttentionStock trend prediction based on fractal feature selection and support vector machine (2010)Stock trend prediction based …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…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…Predicting stock price performance: a neural network approach (2002)Predicting stock price perfor…A comparison of artificial neural network and time series models for forecasting commodity prices (1996)A comparison of artificial ne…Using a novel clustered 3D-CNN model for improving crop future price prediction (2022)Using a novel clustered 3D-CN…Machine Learning Models in Stock Market Prediction (2022)Machine Learning Models in St…Hybrid models for intraday stock price forecasting based on artificial neural networks and metaheuristic algorithms (2021)Hybrid models for intraday st…Financial Forecasting with Machine Learning: Price Vs Return (2021)Financial Forecasting with Ma…Stock price forecast with deep learning (2020)Stock price forecast with dee…Sailing through the COVID-19 Crisis by Using AI for Financial Market Predictions (2020)Sailing through the COVID-19 …Innovations in Management Forecast: Time Development of Stock Prices with Neural Networks (2020)Innovations in Management For…Exploring the financial indicators to improve the pattern recognition of economic data based on machine learning (2020)Exploring the financial indic…Financial series prediction using Attention LSTM (2019)Financial series prediction u…Deep Learning Based Forecasting in Stock Market with Big Data Analytics (2019)Deep Learning Based Forecasti…An Effective Time Series Analysis for Equity Market Prediction Using Deep Learning Model (2019)An Effective Time Series Anal…A Novel Hybrid Model for Stock Price Forecasting Based on Metaheuristics and Support Vector Machine (2019)A Novel Hybrid Model for Stoc…Macroeconomic indicators alone can predict the monthly closing price of major U.S. indices: Insights from artificial intelligence, time-series analysis and hybrid models (2018)Macroeconomic indicators alon…Time Series Analysis Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Time series forecasting using a hybrid ARIMA and neural network model (2003)Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Forecasting with artificial neural networks: (1998)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Stock market's price movement prediction with LSTM neural networks (2017)The Cross-Section of Expected Stock Returns (1992)Application of support vector machines in financial time series forecasting (2001)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Financial time series forecasting model based on CEEMDAN and LSTM (2018)A Comprehensive Comparative Study of Artificial Neural Network (ANN) and Support Vector Machines (SVM) on Stock Forecasting (2021)A NEW MEASURE OF RANK CORRELATION (1938)A BEHAVIORAL MODEL OF RATIONAL CHOICE (1955)Computational Social Science (2009)BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era (2013)The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy (2014)COVID-19, lockdowns and well-being: Evidence from Google Trends (2020)Chaos and Nonlinear Dynamics: Application to Financial Markets (1991)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Time series forecasting for nonlinear and non-stationary processes: a review and comparative study (2015)Corn cash price forecasting with neural networks (2021)Forecasting wholesale prices of yellow corn through the Gaussian process regression (2024)Evolutionary games on multilayer networks: a colloquium (2015)Evolutionary games on multilayer networks: a colloquium (2015)Predicting the direction of stock markets using optimized neural networks with Google Trends (2018)Stock Market Forecasting Using Computational Intelligence: A Survey (2020)Financial applications of machine learning: A literature review (2023)Risk, Return, and Equilibrium: Empirical Tests (1973)Common risk factors in the returns on stocks and bonds (1993)Investor Sentiment and the Cross‐Section of Stock Returns (2006)The Sum of All FEARS Investor Sentiment and Asset Prices (2014)Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media (2014)Attention to Global Warming (2019)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Applications of deep learning in stock market prediction: Recent progress (2021)Big data in tourism research: A literature review (2018)Text as Data (2019)
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References

  • 2011In Search of Attention3,088 cited
  • 2012Predicting the Present with Google Trends2,353 cited
  • 2003Financial time series forecasting using support vector machines1,734 cited
  • 2004Forecasting stock market movement direction with support vector machine1,119 cited
  • 2004A hybrid ARIMA and support vector machines model in stock price forecasting1,000 cited
  • 2013Quantifying Trading Behavior in Financial Markets Using Google Trends947 cited
  • 2010Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange880 cited
  • 2011Using artificial neural network models in stock market index prediction787 cited
  • 1996A comparison of artificial neural network and time series models for forecasting commodity prices293 cited
  • 2016Application of artificial neural network for the prediction of stock market returns: The case of the Japanese stock market230 cited
  • 2002Predicting stock price performance: a neural network approach182 cited
  • 2010Stock trend prediction based on fractal feature selection and support vector machine121 cited
  • 2015Application of artificial neural network models and principal component analysis method in predicting stock prices on Tehran Stock Exchange113 cited
  • 2016Proximal support vector machine based hybrid prediction models for trend forecasting in financial markets

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  • 2022Machine Learning Models in Stock Market Prediction47 cited
  • 2019Financial series prediction using Attention LSTM47 cited
  • 2018Macroeconomic indicators alone can predict the monthly closing price of major U.S. indices: Insights from artificial intelligence, time-series analysis and hybrid models46 cited
  • 2020Stock price forecast with deep learning44 cited
  • 2020Innovations in Management Forecast: Time Development of Stock Prices with Neural Networks35 cited
  • 2019Deep Learning Based Forecasting in Stock Market with Big Data Analytics34 cited
  • 2020Sailing through the COVID-19 Crisis by Using AI for Financial Market Predictions34 cited
  • 2019An Effective Time Series Analysis for Equity Market Prediction Using Deep Learning Model29 cited
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