Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/27697
Appears in Collections:Accounting and Finance Journal Articles
Peer Review Status: Refereed
Title: Volatility forecasting across tanker freight rates: the role of oil price shocks
Author(s): Gavriilidis, Konstantinos
Kambouroudis, Dimos S
Tsakou, Katerina
Tsouknidis, Dimitris A
Contact Email: konstantinos.gavriilidis@stir.ac.uk
Keywords: volatility forecasts
tanker freight rates
oil price shocks
GARCH-X models
Issue Date: 31-Oct-2018
Citation: Gavriilidis K, Kambouroudis DS, Tsakou K & Tsouknidis DA (2018) Volatility forecasting across tanker freight rates: the role of oil price shocks. Transportation Research Part E: Logistics and Transportation Review, 118, pp. 376-391. https://doi.org/10.1016/j.tre.2018.08.012.
Abstract: This paper examines whether the inclusion of oil price shocks of different origin as exogenous variables in a wide set of GARCH-X models improves the accuracy of their volatility forecasts for spot and 1-year time-charter tanker freight rates. Kilian's (2009) oil price shocks of different origin enter GARCH-X models which, among other stylized facts of the tanker freight rates examined, take into account the presence of asymmetric and long-memory effects. The results reveal that the inclusion of aggregate oil demand and oil-specific (precautionary) demand shocks improves significantly the accuracy of the volatility forecasts drawn.
DOI Link: 10.1016/j.tre.2018.08.012
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Gavriilidis K, Kambouroudis DS, Tsakou K & Tsouknidis DA (2018) Volatility forecasting across tanker freight rates: the role of oil price shocks. Transportation Research Part E: Logistics and Transportation Review, 118, pp. 376-391. DOI: 10.1016/j.tre.2018.08.012 © 2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

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