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A hybrid ANFIS model based on empirical mode decomposition for stock time series forecasting
16 references·16 citing·26 second hopsampled
A hybrid ANFIS model based on empirical mode decomposition for stock time series forecasting (2016)A hybrid ANFIS model based on empirical m…A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data (2014)A moving-average filter based…SVR with hybrid chaotic genetic algorithms for tourism demand forecasting (2010)SVR with hybrid chaotic genet…Financial time series forecasting using independent component analysis and support vector regression (2009)Financial time series forecas…Forecasting enrollments using high-order fuzzy time series and genetic algorithms (2006)Forecasting enrollments using…The application of neural networks to forecast fuzzy time series (2005)The application of neural net…Weighted fuzzy time series models for TAIEX forecasting (2004)Weighted fuzzy time series mo…Proceedings of the International Joint Conference on Neural Networks, 2003. (2003)Proceedings of the Internatio…Financial time series forecasting using support vector machines (2003)Financial time series forecas…Effective lengths of intervals to improve forecasting in fuzzy time series (2001)Effective lengths of interval…Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index (2000)Genetic algorithms approach t…Forecasting enrollments based on fuzzy time series (1996)Forecasting enrollments based…Forecasting enrollments with fuzzy time series — Part I (1993)Forecasting enrollments with …Stock market prediction system with modular neural networks (1990)Stock market prediction syste…Generalized autoregressive conditional heteroskedasticity (1986)Generalized autoregressive co…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Autoregressive Conditional He…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…Centralized decomposition approach in LSTM for Bitcoin price prediction (2023)Centralized decomposition app…A stock series prediction model based on variational mode decomposition and dual-channel attention network (2023)A stock series prediction mod…A novel hybrid model for stock price forecasting integrating Encoder Forest and Informer (2023)A novel hybrid model for stoc…Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model (2022)Analysis of market efficiency…A new decomposition ensemble model for stock price forecasting based on system clustering and particle swarm optimization (2022)A new decomposition ensemble …Predicting the Direction Movement of Financial Time Series Using Artificial Neural Network and Support Vector Machine (2021)Predicting the Direction Move…Forecasting stock index price using the CEEMDAN-LSTM model (2021)Forecasting stock index price…A new hybrid financial time series prediction model (2020)A new hybrid financial time s…Designing fuzzy time series forecasting models: A survey (2019)Designing fuzzy time series f…Cascading logistic regression onto gradient boosted decision trees for forecasting and trading stock indices (2019)Cascading logistic regression…Prediction of Bitcoin prices with machine learning methods using time series data (2018)Prediction of Bitcoin prices …A New Approach for Stock Price Analysis and Prediction Based on SSA and SVM (2018)A New Approach for Stock Pric…Hybrid ARIMA-BPNN model for time series prediction of the Chinese stock market (2017)Hybrid ARIMA-BPNN model for t…A novel high-order weighted fuzzy time series model and its application in nonlinear time series prediction (2017)A novel high-order weighted f…A new hybrid method for time series forecasting: AR–ANFIS (2016)A new hybrid method for time …A hybrid fuzzy time series model based on ANFIS and integrated nonlinear feature selection method for forecasting stock (2016)A hybrid fuzzy time series mo…Fuzzy sets (1965)The concept of a linguistic variable and its application to approximate reasoning—II (1975)Fuzzy sets (1996)FORECASTING ENROLLMENTS BASED ON HIGH-ORDER FUZZY TIME SERIES (2002)Forecasting enrollments with fuzzy time series — part II (1994)Ratio-based lengths of intervals to improve fuzzy time series forecasting (2006)Time Series Analysis: Forecasting and Control (1977)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)Multivariate Simultaneous Generalized ARCH (1995)Forecasting with artificial neural networks: (1998)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)Stock market's price movement prediction with LSTM neural networks (2017)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Econometric Analysis of Cross Section and Panel Data (2001)How effective are neural networks at forecasting and prediction? A review and evaluation (1998)An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange (2010)Literature review: Machine learning techniques applied to financial market prediction (2019)Financial time series forecasting model based on CEEMDAN and LSTM (2018)NSE Stock Market Prediction Using Deep-Learning Models (2018)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong (2020)Stock market movement forecast: A Systematic review (2020)
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References

  • 1986Generalized autoregressive conditional heteroskedasticity22,329 cited
  • 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation20,684 cited
  • 1977Time Series Analysis: Forecasting and Control19,200 cited
  • 2003Financial time series forecasting using support vector machines1,734 cited
  • 2003Proceedings of the International Joint Conference on Neural Networks, 2003.1,674 cited
  • 1993Forecasting enrollments with fuzzy time series — Part I1,255 cited
  • 1996Forecasting enrollments based on fuzzy time series1,186 cited
  • 2000Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index758 cited
  • 1990Stock market prediction system with modular neural networks654 cited
  • 2001Effective lengths of intervals to improve forecasting in fuzzy time series583 cited
  • 2009Financial time series forecasting using independent component analysis and support vector regression538 cited
  • 2014A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data505 cited
  • 2004Weighted fuzzy time series models for TAIEX forecasting463 cited
  • 2005The application of neural networks to forecast fuzzy time series308 cited

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2010
SVR with hybrid chaotic genetic algorithms for tourism demand forecasting
264 cited
  • 2006Forecasting enrollments using high-order fuzzy time series and genetic algorithms252 cited
  • Cited by

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    • 2023A novel hybrid model for stock price forecasting integrating Encoder Forest and Informer62 cited
    • 2023A stock series prediction model based on variational mode decomposition and dual-channel attention network53 cited
    • 2017A novel high-order weighted fuzzy time series model and its application in nonlinear time series prediction52 cited
    • 2022A new decomposition ensemble model for stock price forecasting based on system clustering and particle swarm optimization51 cited
    • 2022Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model45 cited
    • 2023Centralized decomposition approach in LSTM for Bitcoin price prediction43 cited
    • 2017Hybrid ARIMA-BPNN model for time series prediction of the Chinese stock market41 cited
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