When will the next shipping recovery for crude oil tanker industry arrive?

• Main Author: Chew, Min Yu
• Other Authors: Kenneth Tan Siah-Ann
• Format: Final Year Project
• Language: English
• Published: 2017
• Subjects: DRNTU::Engineering::Maritime studies
• Online Access: http://hdl.handle.net/10356/71612
• Institution: Nanyang Technological University

Shipping is a cyclical business with no absolute winners or losers at every stage. In January 2016, the entire shipping market crashed when global oil prices plummeted to its lowest since 2003, at $27.67/barrel. This historic trough caught the world off guard as overcapacity problems worsen. Following the bankruptcies of big names in the shipping industry, companies sought to tide through this downturn and anticipate the next market recovery. As such, this paper analysed the signs and triggers that can potentially generate an upward force in the shipping sector, especially in the crude oil tanker sector. The study of the demand and supply forces and market sentiments are imperative in determining the prospects of a recovery. Adopting a mixed approach of both quantitative and qualitative analysis, the patterns and drivers of market fundamentals are studied and applied to the current cycle in 2016. Concurrently, insights and views from 60 survey respondents and 18 interviewees verified the viability of the proposed market recovery between the 2017 – 2022 period, in terms of magnitude and duration. Study of market drivers such as the world economy and global fleet growth concludes that the upward turning point of the crude tanker market to be driven by increased crude oil demand and signs of improved industry sentiments predominantly. Although these drivers allow us to have a glimpse of the future market condition, the volatile shipping market is exposed to uncertainty led by political ‘wildcards’ and other unforeseeable events. As a result, shipping companies must stay resilient and engage in sustainable business strategies to survive, and prepare for the upcoming recovery. Due to the lack of technical knowledge and resources in designing a mathematical model, future papers can consider developing forecasting models of moderate accuracy based on correlation studies.