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Stock price index forecasting using a multiscale modelling strategy based on frequency components analysis and intelligent optimization
16 references·1 citing·51 second hopsampled
Stock price index forecasting using a multiscale modelling strategy based on frequency components analysis and intelligent optimization (2022)Stock price index forecasting using a mul…Forecasting stock index price using the CEEMDAN-LSTM model (2021)Forecasting stock index price…Ensemble system for short term carbon dioxide emissions forecasting based on multi-objective tangent search algorithm (2021)Ensemble system for short ter…Carbon price forecasting system based on error correction and divide-conquer strategies (2021)Carbon price forecasting syst…A hybrid approach of adaptive wavelet transform, long short-term memory and ARIMA-GARCH family models for the stock index prediction (2021)A hybrid approach of adaptive…An improved deep learning model for predicting stock market price time series (2020)An improved deep learning mod…Stock market prediction using Firefly algorithm with evolutionary framework optimized feature reduction for OSELM method (2019)Stock market prediction using…Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition (2019)Improving forecasting accurac…Forecasting stock price volatility: New evidence from the GARCH-MIDAS model (2019)Forecasting stock price volat…Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)Hybrid Variational Mode Decom…Financial time series forecasting model based on CEEMDAN and LSTM (2018)Financial time series forecas…Multidimensional k -nearest neighbor model based on EEMD for financial time series forecasting (2017)Multidimensional k -nearest n…Forecasting stochastic neural network based on financial empirical mode decomposition (2017)Forecasting stochastic neural…Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Deep learning networks for st…Forecasting stock index price based on M-factors fuzzy time series and particle swarm optimization (2013)Forecasting stock index price…A PSO based integrated functional link net and interval type-2 fuzzy logic system for predicting stock market indices (2011)A PSO based integrated functi…Comparing Predictive Accuracy (1995)Comparing Predictive AccuracyA Stock Price Forecasting Model Integrating Complementary Ensemble Empirical Mode Decomposition and Independent Component Analysis (2022)A Stock Price Forecasting Mod…Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index (2002)Time series forecasting using a hybrid ARIMA and neural network model (2003)A new approach for crude oil price analysis based on Empirical Mode Decomposition (2007)Literature review: Machine learning techniques applied to financial market prediction (2019)Multidimensional KNN algorithm based on EEMD and complexity measures in financial time series forecasting (2020)Machine learning techniques and data for stock market forecasting: A literature review (2022)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)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Applications of deep learning in stock market prediction: Recent progress (2021)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Generalized autoregressive conditional heteroskedasticity (1986)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)A new financial data forecasting model using genetic algorithm and long short-term memory network (2020)Mean–variance portfolio optimization using machine learning-based stock price prediction (2020)Application of support vector machines in financial time series forecasting (2001)Introduction to Time Series and Forecasting (2002)Forecasting Volatility in Financial Markets: A Review (2003)Stock price prediction using deep learning and frequency decomposition (2020)Carbon price forecasting based on CEEMDAN and LSTM (2022)ARIMA forecasting of primary energy demand by fuel in Turkey (2006)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)An optimized model using LSTM network for demand forecasting (2020)ARIMA Model for Accurate Time Series Stocks Forecasting (2020)Comparing Predictive Accuracy (1994)Modeling and Forecasting Realized Volatility (2003)Historical geopolitical risk and the behaviour of stock returns in advanced economies (2021)Does climate policy uncertainty affect Chinese stock market volatility? (2022)Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach (2022)Oil prices, US stock return, and the dependence between their quantiles (2015)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Predicting the direction of stock market prices using tree-based classifiers (2018)Multivariate CNN‐LSTM Model for Multiple Parallel Financial Time‐Series Prediction (2021)Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022 (2023)Forecasting stock market movement direction with support vector machine (2004)Deep learning with long short-term memory networks for financial market predictions (2017)Integration of genetic algorithm with artificial neural network for stock market forecasting (2021)Forecasting crude oil futures prices using BiLSTM-Attention-CNN model with Wavelet transform (2022)Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition (2022)Fractionally integrated generalized autoregressive conditional heteroskedasticity (1996)A Simple Approximate Long-Memory Model of Realized Volatility (2008)Stock market's price movement prediction with LSTM neural networks (2017)A novel carbon price combination forecasting approach based on multi-source information fusion and hybrid multi-scale decomposition (2022)Prediction of realized volatility and implied volatility indices using AI and machine learning: A review (2024)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Combining forecasts: A review and annotated bibliography (1989)Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation (1991)Testing the equality of prediction mean squared errors (1997)Consumption, Aggregate Wealth, and Expected Stock Returns (2001)
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References

  • 1995Comparing Predictive Accuracy5,370 cited
  • 2017Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies854 cited
  • 2018Financial time series forecasting model based on CEEMDAN and LSTM718 cited
  • 2019Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition340 cited
  • 2021Forecasting stock index price using the CEEMDAN-LSTM model189 cited
  • 2019Forecasting stock price volatility: New evidence from the GARCH-MIDAS model182 cited
  • 2020An improved deep learning model for predicting stock market price time series173 cited
  • 2018Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis156 cited
  • 2021A hybrid approach of adaptive wavelet transform, long short-term memory and ARIMA-GARCH family models for the stock index prediction149 cited
  • 2017Multidimensional k -nearest neighbor model based on EEMD for financial time series forecasting134 cited
  • 2011A PSO based integrated functional link net and interval type-2 fuzzy logic system for predicting stock market indices119 cited
  • 2021Carbon price forecasting system based on error correction and divide-conquer strategies113 cited
  • 2017Forecasting stochastic neural network based on financial empirical mode decomposition110 cited

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  • 2021Ensemble system for short term carbon dioxide emissions forecasting based on multi-objective tangent search algorithm102 cited
  • 2013Forecasting stock index price based on M-factors fuzzy time series and particle swarm optimization101 cited
  • 2019Stock market prediction using Firefly algorithm with evolutionary framework optimized feature reduction for OSELM method70 cited
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    • 2022A Stock Price Forecasting Model Integrating Complementary Ensemble Empirical Mode Decomposition and Independent Component Analysis24 cited