2017 Container Shipping Outlook - A tragedy in three acts

Transcription

1 217 Container Shipping Outlook - A tragedy in three acts Alan Murphy CEO and Co-Founder SeaIntel Maritime Analysis March 21 st, 217 ILSS 217 1

2 SeaIntel Container Shipping Analysts - Founded January 1 st, Fully independent, private company with no interests from brokers, banks or others Analysts, Developers & Consultants in Copenhagen and Hong Kong. - Management Team with combined 35 years of experience in Container Shipping Core values: - Integrity - Methodology - Assumptions - Data Quality Major Milestones: - 9+ Research & Analysis articles published since March 211-5,+ citations in Industry Press (Lloyd s List, JoC, etc.) - Official Knowledge Partner of the Global Institute of Logistics - World s most comprehensive database on Carrier Reliability - Curriculum provider at the World Maritime University - Curriculum provider at the Blue MBA at Copenhagen Business School 2

3 SeaIntel subscription reports SeaIntel Sunday Spotlight (SSS) - Weekly Global Liner Performance (GLP) report - Monthly Tradelane Capacity Outlook (TCO) report - Weekly Weekly report on relevant container market analysis Quantitative insights into important market drivers Regular topics include: Supply/Demand, deployment patterns, freight rate analysis, environmental issues, reliability, and much more World s largest study of carrier on-time performance Report covering 65+ carriers, 3+ distinct carrier services/loops, 3+ ports, across 34 trade lanes 116 pages including global carrier performance Top2 and niche operators, benchmarking alliances and detailed trade performance 12-week future outlook on container space supply Most accurate and updated capacity deployment figures for 23 trade lanes between Asia, Europe, North and South America Based on actual vessel schedules of individual named vessels on all services in the trade lanes 3

4 Prologue: 8 Years of over-supply 4

5 Gap in Supply/Demand opened in 29 Index 1 Supply/Demand growth on Index basis, adjusted for structural factor Demand Supply Supply, Adj. 5

6 Freight rates were down, starting to come up 2,5 SCFI: Asia-NE and Asia-Med 5 SCFI: Asia-USWC and Asia-USEC 16 SCFI: Asia-MEA 2, , , N.EUR MED USWC USEC SCFI: ANZ SCFI: Asia-WAF and Asia-SAF SCFI: Asia-ECSA WAF SAF 1 5 6

7 USD/TEU Freight rate volatility is through the roof USD 1 +4 USD +75 USD +4 USD +5 USD +5 USD +6 USD Asia-N.Europe Spot Rates and Announced Increases +4 USD +7 USD +35 USD +35 USD +525 USD +5 USD +575 USD +45 USD +95 USD Rate data based on SCFI from Shanghai Shipping Exchange +75 USD +95 USD +425 USD +525 USD +5 USD +525 USD +5 USD +55 USD +55 USD +475 USD +55 USD +7 USD +85 USD +55 USD +8 USD +1 USD +525USD +575 USD +6USD +1 USD +3 USD +55 USD +8 USD +92 USD +95 USD +92 USD +1 USD +95 USD +9 USD +74 USD +48 USD +75 USD +9 USD +95 USD +42 USD +7 USD +11 USD +5 USD +3 USD 7

8 Carriers P&L were the worst years since 29 in terms of over-capacity, tanking freight rates, weak demand, price wars and rate erosions, etc. - Why did they end up with a profit of 2.7 bn USD for 215? And why a 1.1bn loss in 216? - (answer to follow ) 8

9 Carriers P&L per Transported TEU USD/TEU P&L per TEU,

10 Prologue II: Impact of BAF-delay 1

11 Impact of oil price and BAF delay USD/MT 8 TSA Bunker Price (USD/MT) vs. TSA BAF (USD/FFE) - Asia-USWC USD/FFE Source: Bunkerworld, TSA Carriers TSA Bunker price - Asia-USWC TSA BAF, Asia-USWC, USD/FFE - Bunker oil prices lead BAF charges by approximately 3 months - When oil prices fall, carrier get a cash injection as their BAF only drops 1-2 quarters later - When oil prices rise, carriers have a cash drain, as costs go up but the BAF is delayed 11

12 Impact of oil price and BAF delay II USD/MT TSA Bunker Price (USD/MT) vs. TSA BAF (USD/FFE) - Asia-USWC USD/bbl Source: Bunkerworld, TSA Carriers, World Bank TSA Bunker Bunker Est. WB Crude Crude Est Using crude oil forecasts from the World Bank, we can create a forecast of Bunker Oil prices - The two variables are very strongly correlated 12

13 Billion USD Impact of oil price and BAF delay III 3. Industry Cash Flow effect from BAF delay saw a net cash injection of 4.13 bn USD to the industry saw a cash drain of bn USD in Q2-Q4-217-Q1 will be challenging with a cash drain of 57M USD - FY 218 will see 35M USD cash drain, while FY is projected at 16-18M USD 13

14 Act 1: Service disruptions, blank sailings and Schedule Reliability 14

15 Visualizing service launches and suspensions I 15

16 Visualizing service launches and suspensions III 16

17 Blank sailings

18 Visualizing blanks sailings I Active services in Asia-North Europe 18

19 Visualizing blanks sailings II Active services in Asia-USWC 19

20 Global Reliability Developments Global developments The global schedule reliability continued the downward trend for the fourth consecutive month and decreased by 9.7 percentage points from 78.9% in December 216 to 69.2% in January 217. On a Y/Y level, on-time performance experienced a deterioration of 1. percentage points compared to 79.2% seen in January last year and it is the second lowest January score ever recorded, and the thir-lowest all-time score. On-time performance was based on 12,731 vessel arrivals in January 217. N.B.: Starting from September 215, we have introduced a new feature to measure vessel arrival delays. Importantly, the chart below to the right shows the average delay based ONLY on the vessels that are recorded as being late. In January the global average delay for LATE vessel arrivals continued on its negative trend and increased by.31 days from 3.27 days in December 216 to 3.57 days in January 217, showing a Y/Y increase of.38 days. 9% Global schedule reliability 6 Global - Avg. delay for LATE vessel arrivals 85% 5 8% 75% 7% % Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Global Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec ,2% 76,7% 79,9% 83,4% 85,5% 85,9% 84,8% 85,4% 85,5% 84,6% 83,4% 78,9% Schedule ,2% Reliability Change -1,% Avg. delay 216 3,19 3, 3,2 2,94 2,92 3,9 3,23 3,28 3,98 3,23 3,13 3,27 of LATE 217 3,57 vessels Change,38 2

21 Alliance On-time Performance Total East/West Alliance Performance Total East/West In January, the total East/West alliance schedule reliability continued on its downward trajectory and dropped for the fifth consecutive month, deteriorating by 1.8 percentage points from December last year to 67.7% in January 217. For the third month in a row, CKYHE retained the best schedule reliability across the alliances with a score of 77.2%, despite a decline of 8.1 percentage points. 2M was the second best performing alliance with a score of 67.3%, decreasing by 13.1 percentage points. G6 and Ocean Three were the poorest performing alliances, seeing their reliability figures declining for the 4th consecutive month. G6 and Ocean Three on-time performances declined M/M by 1. and 11.9 percentage points to reach 64.5% and 64.2%, respectively. PLEASE NOTE: Services included for each alliance are outlined in the methodology section on page 115. As the alliance analysis is on a trade lane level, schedule reliability is based on a 2-months rolling average, so the figures are comparable to the other trade lane sections in the report. This means that on-time performance in July is based on vessel arrivals in both June and July. 95% 9% Total East/West Alliance schedule reliability 12% Schedule Reliability +/- compared to industry average in recent month 85% 1% 8% 8% 75% 6% 7% 4% 65% 2% 6% % -2% -4% 2M CKYHE G6 O3-6% 2M CKYHE G6 O3 21

22 Act 3: New Mega-Alliances 22

23 Alliances are not a new thing Source: Wang, Mariner: The Formation of Shipping Conference and Rise of Shipping Alliances International Journal of Business, Vol. 6, issue 5,

24 They just controlled much less capacity Source: Lu, Cheng and Lee (26): AN EVALUATION OF STRATEGIC ALLIANCES IN LINER SHIPPING - AN EMPIRICAL STUDY OF CKYH, Journal of Marine Science and Technology, Vol. 14, No. 4, pp (26) 6,, 5,, 4,, 3,, 2,, 1,, MSC Maersk Line Global TEU Fleet UASC CSCL CMA CGM K Line Yang Ming Hanjin Evergreen COSCO HMM NYK APL MOL OOCL Hapag-Lloyd 2M O3 CKYHE G6 On 1/1/25, Alliance carriers controlled: GA: 1,12,197 TEU 12.2% CKYH: 935,611 TEU 1.3% NWA: 669,478 TEU 7.3% TOTAL: 2,77,286 TEU 29.8% On 1/1/21, Alliance carriers controlled: GA: TEU 8.9% CKYH: TEU 11.2% NWA: TEU 8.7% TOTAL: 2,77,286 TEU 28.8% In 214, six carriers became alliance members: Maersk Line (1 st ), MSC (2 nd ), CMA CGM (3 rd ), Evergreen(5 th ), CSCL (7 th ) & UASC (15 th ) On 1/1/216, Alliance carriers controlled: 2M: TEU 28.1% G6: TEU 17.6% CKYHE: TEU 16.5% O3: TEU 14.2% TOTAL: TEU 76.4% 24

25 What are the new (April 217) alliances? 1 st 2 nd 3 rd 7 th 5 th 5 th 6 th 9 th 13 th 16 th 4 th 1 th 11 th 12 th 15 th 17 th April 216 2M Alliance Ocean Three CKYHE G6 Alliance May 216 (announced) 2M Alliance Ocean Alliance THE Alliance 1 st 2 nd 3 rd 4 th 5 th 9 th 12 th 6 th 8 th 11 th 13 th 14 th 16 th 1 th 15 th April 217 (reality) 2 nd 1 st 11 th 4 th 7 th 8 th 3 rd 5 th 9 th 6 th 2M Alliance Ocean Alliance THE Alliance F+O TEU 3.19M 4.25M.47M 2.22M 1.31M.71M 2.37M 1.74M.68M 1.53M 25

26 Alliance Capacity Market Shares No. of weekly services in TP & AE Asia-N. Europe Asia-MED Asia-USEC Asia-USWC 2, 18, 16, 14, 12, 1, 8, 6, 4, 2, Weighted average vessel size per trade lane Asia-N. Europe Asia-MED Asia-USEC Asia-USWC The Alliance 2M Ocean Alliance The Alliance 2M Ocean Alliance 12, Weekly average capacity in TP & AE 1% Alliance Capacity Maket Shares in TP & AE 1, 9% 8% 8, 6, 7% 6% 5% 4, 2, 4% 3% 2% Asia-N. Europe Asia-MED Asia-USEC Asia-USWC The Alliance 2M Ocean Alliance 1% % Asia-N. Europe Asia-MED Asia-USEC Asia-USWC 2M The Alliance Ocean Alliance 26

27 Old vs. New alliances: An example I 27

28 Old vs. New alliances: An example II 28

29 Old vs. New alliances: port-pairs & transit times Asia-Europe/Transpacific - Port-pairs & Transit Times Asia-USWC Asia-USEC Asia-MED Asia-NEUR Lost Total PP Lost Distinct PP Gained Total PP Gained Distinct PP Better TT Unchanged TT Worse TT Shortened TT days Longer TT days 29

30 Consolidation 3

31 Capacity (TEU) Capacity (TEU) Capacity (TEU) The level of consolidation is unprecedented 25, 2, 15, 1, 5, - Disappearances in top-2 Jan Dec , 5, 4, 3, 2, 1, - Disappearances in top-2 Jan 2 - Dec 214 3,, 2,5, 2,, 1,5, 1,, 5, - Disappearances in top-2 Jan present day 31

32 The level of consolidation is unprecedented 1,, 2,, 3,, 4,, 1,, 2,, 3,, 4,, 5,, Maersk ML/HS Maersk Line HS MSC CMA CGM MSC Evergreen Hapag-Lloyd CMA CGM CMA CGM APL COSCO COSCON COSCO CSCL CSCL Hamburg Süd Hanjin J3 HL/UASC MOL NYK K Line Hapag-Lloyd UASC Fleet Order OOCL MOL UASC APL Yang Ming NYK HMM K Line Zim PIL Wan Hai Fleet Order Evergreen OOCL Yang Ming PIL HMM Zim Wan Hai 32

33 Epilogue: Forecast for

34 Rate erosion better on all trades, except Asia-USWC Asia-North Europe 12-week Average rate erosion Asia-Mediterranean 12-week Average rate erosion Asia-USWC 12-week Average rate erosion Asia-USEC 12-week Average rate erosion

35 CCFI Index (1998=1) CCFI Index (1998=1) SCFI: USD/FFE CCFI Index (1998 = 1) 216/17 TP Contracts were set too low Fig.1: SCFI versus CCFI on US West Coast SCFI-USWC CCFI-USWC % 86% 84% 82% 8% 78% 76% 74% 72% 7% Fig.2: SCFI-CCFI Correlation Weeks in advance (SCFI vs CCFI) Fig.3: USWC vs model USWC USEC Fig.4: USEC vs model Mar-9 Mar-1 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16 Mar-17 CCFI-USWC Predicted USWC CCFI-USEC Predicted USEC 35

36 216/17 TP Contracts were set too low Fig.5: Deviation from SCFI model indication Mar-9 Mar-1 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16 Mar-17 USWC deviation 12 week average USEC deviation 12 week average 1% 5% % -5% -1% -15% -2% -25% -3% Fig.7: USWC deviation from model 3% 2% 1% % -1% -2% -3% -4% -5% 15% 1% 5% % -5% -1% -15% -2% -25% Fig.6: USWC contract rate deviation from model Weeks into the contract May'9-Apr'1 May'1-Apr'11 May'11-Apr'12 May'12-Apr'13 May'13-Apr'14 May'14-Apr'15 May'15-Apr'16 May'16-Apr'17 Fig.8: USEC deviation from model 36

37 Demand index (211 = 1) Nautical miles Shorter sailing distances has weakened demand 5,5 5,4 5,3 5,2 5,1 5, 4,9 4,8 4,7 4,6 4, Average sailing distance per TEU Global demand development TEU demand TEU Miles demand 6.% 5.% 4.% 3.% 2.% 1.%.% Annual demand growth TEU TEU Miles World GDP 3.1% 3.4% 3.6% AE 1.6% 1.9% 2.% EMDE 4.1% 4.5% 4.8% World Trade 1.9% 3.8% 4.1% AE 2.% 3.6% 3.8% EMDE 1.9% 4.% 4.7% AE = Advanced economies. EMDE = Emerging market and developing economies 37

38 Nominal TEU capacity Total Fleet (Mio TEU) Annual growth Capacity Outlook Confirmed orderbook less scrappings Large vessels as share of total fleet 23 1% 3% Global Fleet Capacity Annual Fleet Growth 8% 6% 4% 2% % -2% 25% 2% 15% 1% 5% % >18 TEU TEU 6% 5% 4% 3% 2% 1% % Trade (demand) growth Container volume (CTS) Merchandize trade (WTO) Necessary scrapping to maintain status quo 1,, , 6, 4, 2, - Low growth Average growth High growth 38

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