Information processing in freight and freight forward markets: an event study on OPEC announcements

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Zusammenfassung / AbstractIn this paper, information processing in spot and forward freight markets with respect to the Organization of the Petroleum Exporting Countries (OPEC) output announcements is investigated. We use the event study methodology to study returns in tanker freight spot and forward markets around OPEC conferences from 2003 to 2014. Significant abnormal returns indicate that the output decisions are informationally important for the pricing of crude oil transportation services. We consistently find patterns of positive abnormal returns around production increase announcements and negative abnormal returns around announcements of production cuts. Our analysis also suggests that market participants appear to trade three to five days prior to the final announcement based on their anticipation of the actual output announcements. This is consistent with findings from related studies on crude oil returns. Persistence of abnormal returns in the post-event period indicates incomplete initial reactions or at least slow adjustment to disseminated information.

COVID–19 impact on the shipping industry: An event study approach

“…The initial assignment in an event study is the assessment of expected returns. According to the previous literature, three basic models have been used to calculate abnormal returns: the average adjusted return rate model, the market index adjusted return rate model, and the market model, whereby the last one is the most used and has very good prognostic ability ( Lauenstein and Simic, 2017 ). According to Zoogah (2014) , the market model reflects fluctuations in the market and stock earnings as a correction to risk when estimating stock earnings during incidents that never existed.…”