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A Novel Hybrid Model for Financial Forecasting Based on CEEMDAN-SE and ARIMA-CNN-LSTM
16 references·0 citing·49 second hopsampled
A Novel Hybrid Model for Financial Forecasting Based on CEEMDAN-SE and ARIMA-CNN-LSTM (2024)A Novel Hybrid Model for Financial Foreca…Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM (2022)Forecasting gold price using …Using SARIMA–CNN–LSTM approach to forecast daily tourism demand (2021)Using SARIMA–CNN–LSTM approac…Gold volatility prediction using a CNN-LSTM approach (2020)Gold volatility prediction us…Deep Learning for Stock Market Prediction (2020)Deep Learning for Stock Marke…A CNN–LSTM model for gold price time-series forecasting (2020)A CNN–LSTM model for gold pri…Stock price forecasting model based on modified convolution neural network and financial time series analysis (2019)Stock price forecasting model…Novel Deep Learning Model with CNN and Bi-Directional LSTM for Improved Stock Market Index Prediction (2019)Novel Deep Learning Model wit…CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)CNNpred: CNN-based stock mark…Cascading logistic regression onto gradient boosted decision trees for forecasting and trading stock indices (2019)Cascading logistic regression…A novel hybrid model on the prediction of time series and its application for the gold price analysis and forecasting (2019)A novel hybrid model on the p…Improving financial trading decisions using deep Q-learning: Predicting the number of shares, action strategies, and transfer learning (2018)Improving financial trading d…Financial time series forecasting model based on CEEMDAN and LSTM (2018)Financial time series forecas…An innovative neural network approach for stock market prediction (2018)An innovative neural network …A randomized-algorithm-based decomposition-ensemble learning methodology for energy price forecasting (2018)A randomized-algorithm-based …A SVM Stock Selection Model within PCA (2014)A SVM Stock Selection Model w…Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Forecasting crude oil price w…Time Series Analysis Forecasting and Control. 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International evidence (2010)Relationship between gold and stock markets during the global financial crisis: Evidence from nonlinear causality tests (2015)A CNN-BiLSTM-AM method for stock price prediction (2020)Cryptocurrency trading: a comprehensive survey (2022)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold (2009)Stock Price Prediction Using CNN-BiLSTM-Attention Model (2023)A forecast comparison of volatility models: does anything beat a GARCH(1,1)? (2005)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)A new decomposition ensemble model for stock price forecasting based on system clustering and particle swarm optimization (2022)A novel deep learning carbon price short-term prediction model with dual-stage attention mechanism (2023)Forecasting carbon price in China unified carbon market using a novel hybrid method with three-stage algorithm and long short-term memory neural networks (2023)
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References

  • 2020A CNN–LSTM model for gold price time-series forecasting900 cited
  • 2018Financial time series forecasting model based on CEEMDAN and LSTM718 cited
  • 2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm706 cited
  • 2019CNNpred: CNN-based stock market prediction using a diverse set of variables671 cited
  • 2020Deep Learning for Stock Market Prediction503 cited
  • 2018An innovative neural network approach for stock market prediction501 cited
  • 2020Gold volatility prediction using a CNN-LSTM approach274 cited
  • 2022Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM206 cited
  • 2018Improving financial trading decisions using deep Q-learning: Predicting the number of shares, action strategies, and transfer learning204 cited
  • 2019Novel Deep Learning Model with CNN and Bi-Directional LSTM for Improved Stock Market Index Prediction180 cited
  • 2021Using SARIMA–CNN–LSTM approach to forecast daily tourism demand130 cited
  • 2019Cascading logistic regression onto gradient boosted decision trees for forecasting and trading stock indices125 cited
  • 2019Stock price forecasting model based on modified convolution neural network and financial time series analysis120 cited
  • 2014A SVM Stock Selection Model within PCA106 cited

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  • 2018A randomized-algorithm-based decomposition-ensemble learning methodology for energy price forecasting66 cited
  • 2019A novel hybrid model on the prediction of time series and its application for the gold price analysis and forecasting61 cited
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