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AdaBoost-LSTM Ensemble Learning for Financial Time Series Forecasting
15 references·2 citing·48 second hopsampled
AdaBoost-LSTM Ensemble Learning for Financial Time Series Forecasting (2018)AdaBoost-LSTM Ensemble Learning for Finan…Neural networks performance in exchange rate prediction (2015)Neural networks performance i…Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms—Support vector regression forecast combinations (2015)Modeling, forecasting and tra…Forecasting exchange rate using deep belief networks and conjugate gradient method (2015)Forecasting exchange rate usi…Forecasting Daily and Monthly Exchange Rates with Machine Learning Techniques (2015)Forecasting Daily and Monthly…A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting (2015)A decomposition–ensemble mode…Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization (2012)Forecasting foreign exchange …Forecasting exchange rate volatility using high-frequency data: Is the euro different? (2011)Forecasting exchange rate vol…Chaos-based support vector regressions for exchange rate forecasting (2010)Chaos-based support vector re…Forecasting exchange rates with a large Bayesian VAR (2009)Forecasting exchange rates wi…Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Forecasting crude oil price w…A neural-network-based nonlinear metamodeling approach to financial time series forecasting (2008)A neural-network-based nonlin…A novel nonlinear ensemble forecasting model incorporating GLAR and ANN for foreign exchange rates (2004)A novel nonlinear ensemble fo…Regression neural network for error correction in foreign exchange forecasting and trading (2003)Regression neural network for…Forecasting daily foreign exchange rates using genetically optimized neural networks (2002)Forecasting daily foreign exc…Neural network forecasting of the British Pound/US Dollar exchange rate (1998)Neural network forecasting of…Decision Fusion for Stock Market Prediction: A Systematic Review (2022)Decision Fusion for Stock Mar…Research on Quantitative Investment Strategies Based on Deep Learning (2019)Research on Quantitative Inve…The Out-of-Sample Failure of Empirical Exchange Rate Models: Sampling Error or Misspecification? (1982)Empirical exchange rate models of the seventies (1983)Using artificial neural network models in stock market index prediction (2011)Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)Foreign exchange currency rate prediction using a GRU-LSTM hybrid network (2020)Deep learning-based exchange rate prediction during the COVID-19 pandemic (2021)Comparing Predictive Accuracy (1994)Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance (1994)Comparing Predictive Accuracy (1995)A multiscale analysis for carbon price drivers (2018)Carbon price forecasting with variational mode decomposition and optimal combined model (2018)Oil price forecasting using a hybrid model (2018)Forecasting With Bayesian Vector Autoregressions—Five Years of Experience (1986)Tests of Conditional Predictive Ability (2006)Model uncertainty in Panel Vector Autoregressive models (2015)Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange (2017)Modeling and Forecasting Regional Tourism Demand Using the Bayesian Global Vector Autoregressive (BGVAR) Model (2018)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)A hybrid model for exchange rate prediction (2005)Crude oil price analysis and forecasting using wavelet decomposed ensemble model (2012)Machine learning for demand forecasting in the physical internet: a case study of agricultural products in Thailand (2020)Time Series Analysis Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Time series prediction: Forecasting the future and understanding the past (1994)Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold (2013)Machine learning in energy economics and finance: A review (2019)A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series (2020)An Empirical Assessment of Non-Linearities in Models of Exchange Rate Determination (1991)Forecasting exchange rates using feedforward and recurrent neural networks (1995)Automatic stock decision support system based on box theory and SVM algorithm (2009)Financial time series prediction using hybrids of chaos theory, multi-layer perceptron and multi-objective evolutionary algorithms (2017)Forecasting with artificial neural networks: (1998)An Empirical Analysis of Data Requirements for Financial Forecasting with Neural Networks (2001)Neural Network Forecasting of Tourism Demand (2005)The Combination of Forecasts (1969)Time series forecasting using a hybrid ARIMA and neural network model (2003)An investigation and comparison of artificial neural network and time series models for Chinese food grain price forecasting (2007)Bitcoin price forecasting with neuro-fuzzy techniques (2019)Hybrid structures in time series modeling and forecasting: A review (2019)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)A data analytic approach to forecasting daily stock returns in an emerging market (2016)Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels (2021)Economic prediction using neural networks: the case of IBM daily stock returns (1988)Portfolio formation with preselection using deep learning from long-term financial data (2019)A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions (2021)Financial applications of machine learning: A literature review (2023)
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References

  • 2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm705 cited
  • 1998Neural network forecasting of the British Pound/US Dollar exchange rate287 cited
  • 2004A novel nonlinear ensemble forecasting model incorporating GLAR and ANN for foreign exchange rates259 cited
  • 2015Forecasting exchange rate using deep belief networks and conjugate gradient method234 cited
  • 2015A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting204 cited
  • 2002Forecasting daily foreign exchange rates using genetically optimized neural networks172 cited
  • 2009Forecasting exchange rates with a large Bayesian VAR169 cited
  • 2012Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization167 cited
  • 2015Neural networks performance in exchange rate prediction160 cited
  • 2003Regression neural network for error correction in foreign exchange forecasting and trading151 cited
  • 2008A neural-network-based nonlinear metamodeling approach to financial time series forecasting125 cited
  • 2010Chaos-based support vector regressions for exchange rate forecasting119 cited
  • 2015Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms—Support vector regression forecast combinations104 cited

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2011
Forecasting exchange rate volatility using high-frequency data: Is the euro different?
80 cited
  • 2015Forecasting Daily and Monthly Exchange Rates with Machine Learning Techniques72 cited
  • Cited by

    • 2019Research on Quantitative Investment Strategies Based on Deep Learning43 cited
    • 2022Decision Fusion for Stock Market Prediction: A Systematic Review43 cited