Abstract
AbstractThis paper employs an applied econometric study concerning forecasting spot prices in bulk shipping in both markets of tankers and bulk carriers in a disaggregated level. This research is essential, as spot market is one of the most volatile markets and there is a great uncertainty about the future development of spot prices. This uncertainty could be reduced by using estimates of ex-post and ex-ante forecasts. Econometric analysis focuses in the comparison of different econometric models from two important categories of econometrics: (1) multivariate models (VAR and VECM) and (2) univariate time series models (ARIMA, GARCH and E-GARCH) in order to derive the best predicting model for each ship type. Also, forecasts can be modified to yield an improved performance of forecasting accuracy via the theory of combining methods. Ex-post and ex-ante forecasts are estimated on the basis of best predicting model’s performance. Results show that the combining methodology can reduce even more the forecastin...
Highlights
Shipping is characterized by complexity and uncertainty as it is one of the most globalized industries in the world
The results show that multivariate models give more precise forecasts revealing the relation of interdependence and feedback, which exists among the shipping markets
The extensive analysis of different econometric models and from different econometric methodologies results a number of important conclusions
Summary
Shipping is characterized by complexity and uncertainty as it is one of the most globalized industries in the world. This model doesn’t include other endogenous or exogenous variables, because the authors consider the spot market as efficient This hypothesis leads to large forecast errors, because of the existence of common stochastic trend among the six different time series of routes. The comparison of forecasted series with actual series from models with different lags of ARCH and GARCH terms shows that the models with the lowest SIC and AIC generate the best static ex-post forecasts This method of ARCH specification is followed by this research. Forecasting procedure Spot markets are too complicated and researchers cannot depend only on the theory of shipping economy in order to generate accurate decisions about the future values of spot prices. The comparison of excluded estimations according to ex-post and ex-ante forecasts provides useful knowledge and information about the variables that affect spot markets and each vessel type. The quantitative criterions, which evaluate the forecasts, are Root Mean Square Error (RMSE) and Theil’s Inequality Coefficient
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
