SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Stock index forecasting based on multivariate empirical mode decomposition and temporal convolutional networks
16 references·2 citing·47 second hop
Stock index forecasting based on multivariate empirical mode decomposition and temporal convolutional networks (2023)Stock index forecasting based on multivar…StockNet—GRU based stock index prediction (2022)StockNet—GRU based stock inde…Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition (2022)Multi-step-ahead stock price …Forecasting stock index price using the CEEMDAN-LSTM model (2021)Forecasting stock index price…A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction (2021)A hybrid model integrating de…A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network (2020)A hybrid stock price index fo…A CNN-LSTM-Based Model to Forecast Stock Prices (2020)A CNN-LSTM-Based Model to For…Stock Market Trend Prediction Using High-Order Information of Time Series (2019)Stock Market Trend Prediction…Knowledge-Driven Stock Trend Prediction and Explanation via Temporal Convolutional Network (2019)Knowledge-Driven Stock Trend …Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Deep learning networks for st…A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)A deep learning framework for…A novel forecasting method based on multi-order fuzzy time series and technical analysis (2016)A novel forecasting method ba…Gold price volatility: A forecasting approach using the Artificial Neural Network–GARCH model (2015)Gold price volatility: A fore…A hybrid fuzzy time series model based on granular computing for stock price forecasting (2014)A hybrid fuzzy time series mo…Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices (2013)Beyond one-step-ahead forecas…Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India (2010)Time series models (Grey-Mark…Another look at measures of forecast accuracy (2006)Another look at measures of f…Enhancing stock market Forecasting: A hybrid model for accurate prediction of S&P 500 and CSI 300 future prices (2024)Enhancing stock market Foreca…McVCsB: A new hybrid deep learning network for stock index prediction (2023)McVCsB: A new hybrid deep lea…Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)A new fuzzy time series forecasting model combined with ant colony optimization and auto-regression (2014)Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)Fine-tuned support vector regression model for stock predictions (2021)Control problems of grey systems (1982)Grey prediction with rolling mechanism for electricity demand forecasting of Turkey (2007)Forecasting the annual electricity consumption of Turkey using an optimized grey model (2014)Urbanization, energy consumption and emissions in the Indian context A review (2017)Forecasting China's electricity consumption using a new grey prediction model (2018)Does the Stock Market Overreact? (1985)Hierarchical structure in financial markets (1999)Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average? (2007)A systematic review of fundamental and technical analysis of stock market predictions (2019)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Applications of deep learning in stock market prediction: Recent progress (2021)Forecasting stock market movement direction with support vector machine (2004)Temporal Relational Ranking for Stock Prediction (2019)Application of support vector machines in financial time series forecasting (2001)Financial time series forecasting using support vector machines (2003)Deep learning with long short-term memory networks for financial market predictions (2017)Stock market prediction using deep learning algorithms (2021)Stock-Price Forecasting Based on XGBoost and LSTM (2021)Framework for Predicting and Modeling Stock Market Prices Based on Deep Learning Algorithms (2022)The Behavior of Stock-Market Prices (1965)Wikidata (2014)A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations (2020)RETRACTED ARTICLE: An optimal deep learning-based LSTM for stock price prediction using twitter sentiment analysis (2022)Data-driven stock forecasting models based on neural networks: A review (2024)Dynamic Conditional Correlation (2002)Forecasting volatility of oil price using an artificial neural network-GARCH model (2016)Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM (2022)Peanut oil price change forecasts through the neural network (2025)Time series forecasting using a hybrid ARIMA and neural network model (2003)Stock Price Prediction Using the ARIMA Model (2014)Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models (2018)The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction (2021)Cryptocurrency trading: a comprehensive survey (2022)Machine learning techniques and data for stock market forecasting: A literature review (2022)Automatic Time Series Forecasting: The forecast Package for R (2008)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Stock market forecasting using a multi-task approach integrating long short-term memory and the random forest framework (2021)A comprehensive review on multiple hybrid deep learning approaches for stock prediction (2022)Effects of investor sentiment on stock volatility: new evidences from multi-source data in China’s green stock markets (2022)
this work references cited by second hop

References

  • 2006Another look at measures of forecast accuracy5,736 cited
  • 2017A deep learning framework for financial time series using stacked autoencoders and long-short term memory1,131 cited
  • 2017Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies833 cited
  • 2020A CNN-LSTM-Based Model to Forecast Stock Prices564 cited
  • 2021A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction364 cited
  • 2010Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India356 cited
  • 2014A hybrid fuzzy time series model based on granular computing for stock price forecasting228 cited
  • 2015Gold price volatility: A forecasting approach using the Artificial Neural Network–GARCH model219 cited
  • 2019Knowledge-Driven Stock Trend Prediction and Explanation via Temporal Convolutional Network198 cited
  • 2019Stock Market Trend Prediction Using High-Order Information of Time Series191 cited
  • 2020A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network191 cited
  • 2021Forecasting stock index price using the CEEMDAN-LSTM model189 cited
  • 2013Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices167 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

2022
StockNet—GRU based stock index prediction
133 cited
  • 2016A novel forecasting method based on multi-order fuzzy time series and technical analysis118 cited
  • 2022Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition117 cited
  • Cited by

    • 2024Enhancing stock market Forecasting: A hybrid model for accurate prediction of S&P 500 and CSI 300 future prices49 cited
    • 2023McVCsB: A new hybrid deep learning network for stock index prediction45 cited