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A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network
13 references·16 citing·52 second hop
A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network (2020)A hybrid stock price index forecasting mo…Study on the prediction of stock price based on the associated network model of LSTM (2019)Study on the prediction of st…Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network (2019)Non-ferrous metals price fore…Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data (2019)Forecasting stock prices with…Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting (2019)Class-imbalanced dynamic fina…ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module (2018)ModAugNet: A new forecasting …Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models (2018)Forecasting the volatility of…Financial time series forecasting model based on CEEMDAN and LSTM (2018)Financial time series forecas…Exploring the use of deep neural networks for sales forecasting in fashion retail (2018)Exploring the use of deep neu…Decision support from financial disclosures with deep neural networks and transfer learning (2017)Decision support from financi…Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble (2016)Dynamic financial distress pr…A variational mode decompoisition approach for analysis and forecasting of economic and financial time series (2016)A variational mode decompoisi…A combination of artificial neural network and random walk models for financial time series forecasting (2013)A combination of artificial n…Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Forecasting crude oil price w…Recurrent ensemble random vector functional link neural network for financial time series forecasting (2024)Recurrent ensemble random vec…VGC-GAN: A multi-graph convolution adversarial network for stock price prediction (2023)VGC-GAN: A multi-graph convol…Stock index forecasting based on multivariate empirical mode decomposition and temporal convolutional networks (2023)Stock index forecasting based…Multi-step-ahead stock price prediction using recurrent fuzzy neural network and variational mode decomposition (2023)Multi-step-ahead stock price …Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022 (2023)Deep learning models for pric…Deep Learning for Financial Time Series Prediction: A State-of-the-Art Review of Standalone and Hybrid Models (2023)Deep Learning for Financial T…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…A novel deep learning carbon price short-term prediction model with dual-stage attention mechanism (2023)A novel deep learning carbon …Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition (2022)Multi-step-ahead stock price …Extending machine learning prediction capabilities by explainable AI in financial time series prediction (2022)Extending machine learning pr…Asian stock markets closing index forecast based on secondary decomposition, multi-factor analysis and attention-based LSTM model (2022)Asian stock markets closing i…A stock price prediction method based on meta-learning and variational mode decomposition (2022)A stock price prediction meth…A new decomposition ensemble model for stock price forecasting based on system clustering and particle swarm optimization (2022)A new decomposition ensemble …A Hybrid Stock Price Prediction Model Based on PRE and Deep Neural Network (2022)A Hybrid Stock Price Predicti…A Hybrid Prediction Model Integrating GARCH Models With a Distribution Manipulation Strategy Based on LSTM Networks for Stock Market Volatility (2022)A Hybrid Prediction Model Int…Time Series Analysis Forecasting and Control. 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References

  • 2018Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models786 cited
  • 2018Financial time series forecasting model based on CEEMDAN and LSTM712 cited
  • 2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm705 cited
  • 2018ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module373 cited
  • 2019Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting363 cited
  • 2019Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data342 cited
  • 2017Decision support from financial disclosures with deep neural networks and transfer learning316 cited
  • 2019Study on the prediction of stock price based on the associated network model of LSTM288 cited
  • 2018Exploring the use of deep neural networks for sales forecasting in fashion retail262 cited
  • 2019Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network254 cited
  • 2016A variational mode decompoisition approach for analysis and forecasting of economic and financial time series214 cited
  • 2013A combination of artificial neural network and random walk models for financial time series forecasting194 cited
  • 2016Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble

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173 cited

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