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Artificial neural networks in freight rate forecasting
16 references·1 citing·37 second hop
Artificial neural networks in freight rate forecasting (2019)Artificial neural networks in freight rat…Volatility forecasting across tanker freight rates: The role of oil price shocks (2018)Volatility forecasting across…A Novel Approach to Forecasting the Bulk Freight Market (2017)A Novel Approach to Forecasti…Forecasting container shipping freight rates for the Far East – Northern Europe trade lane (2016)Forecasting container shippin…A fuzzy integrated logical forecasting model for dry bulk shipping index forecasting: An improved fuzzy time series approach (2010)A fuzzy integrated logical fo…Introduction to time series analysis and forecasting (2008)Introduction to time series a…Forecasting turning points in shipping freight rates: lessons from 30 years of practical effort (2007)Forecasting turning points in…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 dynamic artificial neural network model for forecasting time series events (2004)A dynamic artificial neural n…Price Discovery, Causality and Forecasting in the Freight Futures Market (2003)Price Discovery, Causality an…Market interactions in returns and volatilities between spot and forward shipping freight markets (2003)Market interactions in return…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Transportation Research, Part A: Policy and Practice (1997)Transportation Research, Part…Forecasting tanker freight rate using neural networks (1997)Forecasting tanker freight ra…A co-integration approach to forecasting freight rates in the dry bulk shipping sector (1997)A co-integration approach to …COMPARISONS OF VOLATILITY IN THE DRY-CARGO SECTOR: SPOT VERSUS TIME CHARTERS, AND SMALLER VERSUS LARGER VESSELS. (1996)COMPARISONS OF VOLATILITY IN …State-space TBATS model for container freight rate forecasting with improved accuracy (2022)State-space TBATS model for c…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)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)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)A survey of shipping finance research: Setting the future research agenda (2018)Comparing Predictive Accuracy (1994)Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting (2008)Forecasting stock market indexes using principle component analysis and stochastic time effective neural networks (2015)Forecasting daily stock trend using multi-filter feature selection and deep learning (2020)Fuzzy sets (1965)Forecasting methods and applications (1993)Fuzzy sets (1996)Forecasting bunker prices; A nonstationary, multivariate methodology (2013)A novel high-order weighted fuzzy time series model and its application in nonlinear time series prediction (2017)Optimal selection of heterogeneous ensemble strategies of time series forecasting with multi-objective programming (2020)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)An analysis of freight rate volatility in dry bulk shipping markets (2008)Forecasting container freight rates using the Prophet forecasting method (2023)Generalized autoregressive conditional heteroskedasticity (1986)Commodity and transportation economic market interactions revisited: New evidence from a dynamic factor model (2020)Role of green technologies, climate uncertainties and energy prices on the supply chain: Policy-based analysis through the lens of sustainable development (2023)Investigating Causal Relations by Econometric Models and Cross-spectral Methods (1969)A new approach for Baltic Dry Index forecasting based on empirical mode decomposition and neural networks (2015)Time series forecasting methods for the Baltic dry index (2021)A comparison of three different approaches to tourist arrival forecasting (2003)Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model (2019)Bayesian optimization based dynamic ensemble for time series forecasting (2022)Price discovery and investor structure in stock index futures (2010)Comparing circular and network buffers to examine the influence of land use on walking for leisure and errands (2007)Virtual Work: Bridging Research Clusters (2018)Sustainable Business Models: A Review (2019)
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References

  • 1998Forecasting with artificial neural networks:4,225 cited
  • 2008Introduction to time series analysis and forecasting1,405 cited
  • 1997Transportation Research, Part A: Policy and Practice855 cited
  • 2004A dynamic artificial neural network model for forecasting time series events257 cited
  • 2006Forecasting spot and forward prices in the international freight market164 cited
  • 2003Market interactions in returns and volatilities between spot and forward shipping freight markets161 cited
  • 1997A co-integration approach to forecasting freight rates in the dry bulk shipping sector113 cited
  • 2018Volatility forecasting across tanker freight rates: The role of oil price shocks105 cited
  • 2003Price Discovery, Causality and Forecasting in the Freight Futures Market101 cited
  • 2010A fuzzy integrated logical forecasting model for dry bulk shipping index forecasting: An improved fuzzy time series approach84 cited
  • 2007Forecasting turning points in shipping freight rates: lessons from 30 years of practical effort81 cited
  • 2016Forecasting container shipping freight rates for the Far East – Northern Europe trade lane76 cited
  • 2004Forecasting Tanker Market Using Artificial Neural Networks69 cited
  • 1996COMPARISONS OF VOLATILITY IN THE DRY-CARGO SECTOR: SPOT VERSUS TIME CHARTERS, AND SMALLER VERSUS LARGER VESSELS.

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66 cited
  • 2017A Novel Approach to Forecasting the Bulk Freight Market66 cited
  • 1997Forecasting tanker freight rate using neural networks63 cited
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    • 2022State-space TBATS model for container freight rate forecasting with improved accuracy37 cited