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Monthly ship price forecasting based on multivariate variational mode decomposition
16 references·0 citing·50 second hopsampled
Monthly ship price forecasting based on multivariate variational mode decomposition (2023)Monthly ship price forecasting based on m…Bayesian optimization based dynamic ensemble for time series forecasting (2022)Bayesian optimization based d…Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels (2021)Forecasting carbon price usin…An effective rolling decomposition-ensemble model for gasoline consumption forecasting (2021)An effective rolling decompos…A novel interval decomposition ensemble model for interval carbon price forecasting (2021)A novel interval decompositio…Support Vector Machine Algorithms: An Application to Ship Price Forecasting (2020)Support Vector Machine Algori…A new crude oil price forecasting model based on variational mode decomposition (2020)A new crude oil price forecas…A survey of shipping finance research: Setting the future research agenda (2018)A survey of shipping finance …Price forecasting in the precious metal market: A multivariate EMD denoising approach (2017)Price forecasting in the prec…A new approach for Baltic Dry Index forecasting based on empirical mode decomposition and neural networks (2015)A new approach for Baltic Dry…Automatic Time Series Forecasting: The forecast Package for R (2008)Automatic Time Series Forecas…A new approach for crude oil price analysis based on Empirical Mode Decomposition (2007)A new approach for crude oil …Forecasting spot and forward prices in the international freight market (2006)Forecasting spot and forward …Forecasting Tanker Market Using Artificial Neural Networks (2004)Forecasting Tanker Market Usi…A case study on using neural networks to perform technical forecasting of forex (2000)A case study on using neural …The forward pricing function of the shipping freight futures market (1999)The forward pricing function …Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Financial time series forecasting using support vector machines (2003)Time series forecasting using a hybrid ARIMA and neural network model (2003)Imperfect Competition and the Effects of Energy Price Increases on Economic Activity (1996)The Long-Run Evolution of Energy Prices (1999)Applications of Hilbert–Huang transform to non‐stationary financial time series analysis (2003)Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method (2009)A novel hybrid method for crude oil price forecasting (2015)A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting (2018)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Testing for a Unit Root in Time Series Regression (1988)Dynamics of time-varying volatility in the dry bulk and tanker freight markets (2012)Volatility forecasting across tanker freight rates: The role of oil price shocks (2018)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Another look at measures of forecast accuracy (2006)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Chaos and order in the capital markets (1991)How effective are neural networks at forecasting and prediction? 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References

  • 1998Forecasting with artificial neural networks:4,225 cited
  • 2008Automatic Time Series Forecasting: The forecast Package for R3,538 cited
  • 2007A new approach for crude oil price analysis based on Empirical Mode Decomposition447 cited
  • 2000A case study on using neural networks to perform technical forecasting of forex398 cited
  • 2022Bayesian optimization based dynamic ensemble for time series forecasting215 cited
  • 2020A new crude oil price forecasting model based on variational mode decomposition172 cited
  • 2006Forecasting spot and forward prices in the international freight market164 cited
  • 2018A survey of shipping finance research: Setting the future research agenda133 cited
  • 2021Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels125 cited
  • 1999The forward pricing function of the shipping freight futures market89 cited
  • 2021A novel interval decomposition ensemble model for interval carbon price forecasting76 cited
  • 2021An effective rolling decomposition-ensemble model for gasoline consumption forecasting70 cited
  • 2004Forecasting Tanker Market Using Artificial Neural Networks69 cited
  • 2017Price forecasting in the precious metal market: A multivariate EMD denoising approach64 cited

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  • 2020Support Vector Machine Algorithms: An Application to Ship Price Forecasting61 cited
  • 2015A new approach for Baltic Dry Index forecasting based on empirical mode decomposition and neural networks54 cited
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