The Charter Owned Fleet: Turning Tides

In International Shipping News 20/03/2018

The structure of ownership in the boxship sector has changed considerably over the past two decades, with the presence of a large charter owned fleet now a more prominent characteristic than had historically been the case. Meanwhile, dramatic changes have also taken place within the charter owned fleet in recent years, the extent of which warrants a closer look.

Exploring New Waters
In the early 1990s, little more than 25% of boxship capacity was held under the charter ownership model, with liner companies accounting for the lion’s share. The model rapidly gained popularity in the following years, supported in part by financial and economic incentives, until peaking at around 51% of containership fleet capacity in 2012. However, since then, the share of the fleet accounted for by charter owners has contracted, standing at 45% by the start of March 2018 (totalling 2,457 boxships of 9.6m TEU).

Stormy Weather
Recent years have seen dramatic changes within the charter owned fleet, in particular with regard to owners’ nationality. The rise, and indeed fall, of the German ‘KG’ finance system was a key driver of these changes. The system was immensely popular during the 2000s, spurring significant investment in new boxship capacity. By start 2008 almost 70% of the charter owned fleet was accounted for by German owners, while the next largest owner, Greece, accounted for 12%. However, the post financial crisis collapse of the KG system saw the share of charter owned fleet capacity accounted for by German owners fall to 35% by start 2018. Meanwhile, Greek owners more than doubled their share, to nearly 25%, while Chinese interests are also playing a more prominent role in the sector.

These changes have been clearly reflected in the recycling and S&P markets, with German owners accounting for 30% of boxship capacity scrapped since 2008, and 52% of the secondhand sales (often in distressed circumstances). Nearly a third of the capacity sold secondhand went to Greek and Chinese buyers.

Banding Together
Meanwhile, there has also been a trend towards consolidation in the charter owner sector in recent years (although to a smaller extent than in the liner sector). Tracking this can be difficult, although according to published ownership statistics, the share of the charter owned fleet accounted for by the top 10 owners has increased from around 35% at the turn of the millennium to nearly 45% based on the current fleet and orderbook. In addition, a number of joint chartering arrangements have been agreed in recent years.

Sailing Onwards
So, the charter ownership model has risen to prominence over the last few decades, alongside an evolving financial landscape. Meanwhile, movements in the boxship market, as well as some dramatic changes to the world economy, have created both challenges and opportunities, and the shape of ownership is changing. As a key feature of the containership sector, the extent of change in the charter owned fleet is one for market watchers to keep a close eye on.

Source: Clarksons

Smart Ships and how to survive the Big Data Era by adapting the “Lego” Approach

In International Shipping News 20/03/2018

Imagine the day when a Fuel Saving Indicator like the one we have in our cars will be installed on board our ships. When “Green” section, the Captain or the Chief Engineer he will know with confidence that he is sailing under the optimum conditions in terms of fuel economy.

Let’s be honest, apart from the Energy Performance addicts (like the undersigned) the marine industry does not care about the Speed Loss and the Power Speed curves, or the EEDI or whichever fancy Energy efficiency indicator you can think of.

At the end of the day Fuel Consumption is the dominant factor. If you are wondering why the Energy Performance Analysis of a Ship is so complicated the answer is quite simple. We have to have to deal with a dynamic and always evolving model.

We can’t control weather and sea environment, and we can’t predict with the maximum potential level of confidence how the ship will perform under all conditions, or can we?

If we are looking for the one and only Key Performance Indicator, that will describe the energy performance of the vessel in a absolute and holistic way, we are in trouble. At least for the time being.

I can’t say what will happen in the next 10 years when the AI models will be implemented, however for the time being it seems that the fundamental components that we need to built the complex models, that will describe the performance of the ship in a constantly changing environment are missing.

We don’t have to immerse too deep to realize that the biggest problem we have is the quality of data. Number one culprit is the accuracy of the sensors. We rely for delicate and essential information for our models on inaccurate sensors. There is a profound need for standardization in the data acquisition systems. Everybody is aware of the inaccuracies related to the Doppler Speed Log for instance and I am really quite tempted to elaborate further about the weather data accuracy and the Fuel Oil Flowmeters.

Even worst, in case where automatic data loggers are not installed and we have the human evolvement for the collection of the valuable data the situation becomes much more complicated.

For various reasons, I don’t want to sound pessimistic, mostly because at some point in the future (either near or far), we will find the “holy grail”, the one and only KPI that will be representative for the energy performance of the vessel.

Until that time comes we may consider another simplified approach. Of course, we can make complex models that will include the performance of the hull, the propeller the main engine the electrical generators and whatever you can think of.

However, the more complex is the model the more we increase the unreliability and inaccuracy of the results for the reasons I cited earlier. What if until that day comes, we adapt a simplified “LEGO” approach.

If our model is too complicated why not break it down to its fundamental blocks.

I can’t deny that there is a big correlation and interaction between the building blocks but let me elaborate further on this theory.

Instead of having the Hull-Propeller-Main Engine model we can break it down to simpler models or what I call “lego” blocks.

Main Engine Performance is not related to the hull. It may sound provocative but it’s the truth. We want the Main Engine to perform well under all loads, and we can monitor this quite efficiently through the SFOC KPI. I admit that when the hull is fouled more propulsive power is required but this is irrelevant with the performance of the main engine as long as the SFOC for the specific load is the expected.

Similarly, for the Hull- Propeller model, ISO 19030 seems to be a good “tool” in our toolbox despite the inherent problems related to filtering, corrections issues and the an-avoidable assumptions we have to make.

So, until we come up with a better tool, ISO 19030 is a quite promising aid that can be used for decision making for setting a hull propeller monitoring scheme.

At this point and for the record, I would like to comment that the practical use of the ISO at least for the undersigned should rely on the trend of the speed loss and not the absolute value.

It’s like using a not so accurate weight scale to monitor your weight. The trend in weight loss is more valuable than the accuracy of the scale itself (provided that it shows the same biased error).

Similarly, we can go after KPIs like the Electrical Generators performance the optimization of the electrical load, the optimization of the weather routing etc.

Instead of trying to optimize the total model we should optimize the performance of each individual “LEGO” block. I hope everybody understands why I am skeptical about the “BIG” data era. My main argument is the serious “quality” issue. If we don’t solve this, there is no point on transferring terabytes of useless data. Moreover, there is no point to accumulate data, if there is not a well-established performance management system in place to evaluate them.

Another critical link in the chain, maybe the most critical, is the education of our seafarers on the energy performance and the need for their active evolvement. Seafarers are our frontline, and every fancy energy saving measure is bound to fail if they are not actively involved.

I have written another article “Smart Ships vs Smart Seafarers” about this issue and I don’t want to elaborate further at this point.

There is a big chance that the Holy Grail is just a legend. I am quite sure however, that a number of romantic knights are still trying to find the mysterious castle which is guarded by a custodian called the Fisher King.

Studies say, that the average time a reader spends when reading an article is 37 seconds, (one of the cons of the digital era that is changing the way our brain neurons are functioning).

I am quite sure that you have exceeded that, so I you are reading this line I would like to thank you for your attention.

Source: Energy Efficiency Superintendent By Konstantinos Lourandos

Dry Bulk FFA: Capesize Index Still Bearish

In Dry Bulk Market, International Shipping News 20/03/2018

Highlights:
The Capesize index has broken its range support and is now bearish rather than bearish to neutral. Upside moves need to trade above USD 12,609 to create a fresh market high and signal the technical could be firming.

The Wave overlap was a concern last week and this has proved to be founded. The rolling front month technical would suggest that we are on a leg C corrective phase.

The Q3 futures are corrective. The 5 waves down on the daily chart would imply Leg A could soon be over and an upward move via leg B could soon begin.

The Cal 19 futures remain the strongest of the technical. Currently in a corrective phase, wave analysis on the daily chart would suggest an extended wave 3, implying a less aggressive correction compared to the shorter dated futures.

Capesize Index Daily

Source: Bloomberg

Resistance – 12,609, 13,569, 14,106
Support – 6,950, 4,675, 2,399

The downside breakout below the range support has resulted in further downside moves for the Capesize index; Neutral to bearish is once again a bearish.

Both the weekly and daily stochastics are in oversold territory, not a sell signal it does warn that momentum has the potential to slow down. However, in trending environments the stochastic is often at its extremes.

Fibonacci support is at USD 6,950 and USD 4,675 with resistance at USD 12,609. Upside moves that trade above this level would create a higher high and suggest the technical picture is starting to strengthen. Preferably with price action above both the 8 and 21 period EMA’s.

Upside moves that fail to trade above the USD 12,609 resistance would be considered as bearish unless a lower high has formed and been broken.

Capesize April 18 Weekly 1 Month Rolling

Source: Bloomberg

Resistance – 16,898 17,370, 17,842
Support – 12,713, 10,275, 7,258

Last week we highlighted the wave overlap below the peak of wave 1 in the April futures. This suggested a 3-wave correction of a greater degree, and this has been the case.

The chart above is the rolling front month weekly contract as we need to see a larger technical picture. Here we can see on a longer-term time frame that the rolling contract has completed a 5-wave sequence and is now on wave C of its corrective phase.

Weekly Fibonacci support is at USD 12,173 and USD 10,275. With upside resistance at USD 17,920. A close above the weekly high at USD 17,920 would imply the corrective phase was over and we could be entering a wave 3 of Elliott to one higher degree.

Market pullbacks that hold above the USD 10,275 support would increase the probability of another bullish cycle. However, the weekly chart would need to trade above USD 17,920 to confirm this.

Capesize Q3 18 Daily

Source: Bloomberg

Resistance – 18,468, 18,780, 19,091
Support – 17,295, 16,633, 16,275

Last weeks bullish divergence failed with the stochastic going on to make new lows, with the death cross between the 8 – 21 EMA’s being the dominant indicator. The 5-wave sequence down would suggest we have entered a longer-term corrective phase, and currently remain on wave A.

Technical support is at USD 17,295 and USD 16,633 with resistance between USD 18,468 and USD 19,091.

5 waves down would suggest we could soon enter a wave B corrective phase. These tend to retrace 0.618% (USD 19,091). Upside moves that fail between the USD 18,780 – USD 19,091 Fibonacci resistance zone would suggest that we could be completing leg B.

Technically the market is in a corrective phase. However, the 5 waves down on the daily chart would suggest we could soon be completing leg A, the first of two bearish impulse waves and entering a Leg B corrective (up) wave.

Capesize Cal 19 Daily

Source: Bloomberg

Resistance – 17,670, 17,830, 18,370
Support – 16,920, 16,590, 16,350

The Cal 19 futures is now in a corrective phase along with the rest of the Capsize complex as it is making lower highs and lower lows.

Near term technical support is at USD 16,920 with further support down to USD 16,350.

However, if this is a longer-term corrective phase then the weekly 38.2% Fibonacci support at USD 15,725 could be a potential target.

Technical resistance is at USD 17,670 and USD 17,830. A close above the latter resistance would have bullish implications going forward as it would create a fresh high, implying the corrective phase is over.

The Cal 19 remains the strongest of the technical at this point. It is currently corrective within a wave 3 on the weekly chart. However, Elliott Wave Analysis on the daily would suggest that this could be an extended wave 3 meaning the correction could be less aggressive that the Q3 and April futures as it looks like we may not yet have seen a wave 3 completion.

Source: Freight Investor Services (FIS)