Vortexa, based in London, Houston and Singapore, provides real-time data analytics of liquid oil and tanker movements by subscription. The service is delivered through a web based interface that allows anyone to easily interrogate the data to ask various questions around waterborne oil.
In addition to this, they have created a software development kit (SDK) to make the data easily accessible for data scientists. To query the data, you will need to be able to construct a query using Python, which is a standard competency of data scientists. You can download sample Python queries free online at www.github.com/VorTECHsa/python-sdk
The service is designed for anyone who has an interest in global oil flows or tankers. The purpose of the data set is to enable clients to gain an understanding of the global supply and demand of oil.
Traders gain an ‘edge’ through access to insights that other traders don’t have – and Vortexa is designed to provide this.
The company was founded by Fabio Kuhn, former Head of Trading Technology and Analytics at BP, who serves as CEO, and Etienne Amic, former Head of European Energy at JP Morgan and Mercuria, who serves as chairman.
The database covers everything from crude oil to LPG and allows users to isolate specific grades of crude oil or individual specifications of refined products.
Example use cases include seeing all the oil cargo movements that took place on any given date.
This is not exactly the same as the vessel movements – because oil being carried from an origin to a destination may have been on multiple vessels, and a vessel can stop at multiple terminals on its voyage. Also some vessels are being used as storage rather than freight.
Similarly, you can interrogate the database to find out the volume of oil currently in storage (not being moved) in different parts of the world, although some of the oil may be in a freight agreement with the shipowner rather than a storage agreement.
“The more we share with people, the more we learn about other use cases for the data,” says Syed Ahmad, market analyst with Vortexa. “Our clients will sometimes surprise us with a new use case we haven't thought of.”
Data sources
To populate the database, the company “relies on hard data as much as possible,” says Kit Burgess, data scientist.
If you know what cargo is booked on a vessel, or what the vessel is doing, you can get a lot of inference from that.
Data is brought in from a number of sources, including agents and brokers. “We try to harmonise all of that data to give you one clean consistent view of the global oil market,” he says.
The company looks for stationary vessels using satellite data.
If data is not available, the company has models which are used to try to make a prediction.
The company also employs in-house analysts who are trying to spot new trends.
The company can have data on loadings going 1-2 months into the future – with knowledge about arrivals going further into the future (2-3 months).
Floating storage
Floating storage is a complex market to understand. At a basic level it is driven by the “calendar spread” – the difference between today’s prices and the future prices (which can be bought today as a ‘future’) – whether it works out profitable to store oil, given the cost of the tanker storage per day.
When future prices are higher than today’s prices, “you can see people trying to slow vessels down, delay discharge, do anything they can to push pricing windows into the future,” says Vortexa’s Mr Ahmad.
But also, in a time of Covid-19, there is reduced oil demand, which means a reduced requirement from customers for tankers for freight. There is also high demand for tankers for freight in other areas, as refineries seek a way to offload excess product, such as jet fuel.
Floating storage is split into two categories – short term (7 days to 30 days), and longer term.
The markets for floating storage can work differently in different parts of the world.
“It was building more in Asia when I last looked at it,” Mr Ahmad said.
“Asia tends to be quite a hub for floating storage. There is a huge flotilla of vessels around Singapore.”
At the time of the interview in April 2020, there was a question about how much oil the tanker sector could store.
Vortexa was trying to model this, considering both the drop off in demand for tankers (due to less oil being shipped), price incentive for shipowners to provide vessels for storage rather than freight, and futures price justifying storing oil.
“Shipowners will constantly be making this decision - if it is more economical for them to put vessels into storage - or take normal cargo from point A to point B,” Mr Ahmad said.