Understanding and Harnessing Oil Price Assessments with ZEMA
Given that oil has a large impact on infrastructure, transportation, and production in most countries, it is no surprise that the availability and price of oil is monitored carefully by many governments and traders worldwide. One aspect of the global oil market that fascinates me is oil price assessments, or average prices for different grades and types of oil that take into account a variety of market factors. Price assessments are used by industry participants to make important trade and investment decisions on a daily basis.
Price assessments, developed by price reporting agencies (PRAs), are certainly a lynchpin in the global oil industry. However, in order for assessment data to be made useful for industry participants, it must be displayed alongside other relevant market data and manipulated. ZEMA, ZE’s end-to-end data management solution, makes it possible for clients to aggregate relevant assessment data, display it according to their preferences, and transform it into graphs for enhanced decision making.
ZE’s products are additionally relevant to oil industry participants because two of ZE’s many partners are Platts and Argus, key oil industry PRAs. ZE and its partners host several data-related events each year to help clients apply the power of ZEMA to PRA assessment products. For example, early in December 2013, Platts and ZE hosted a joint webinar about the U.S. crude oil market. Webinar participants learned about the impact that the shale gas boom has had upon the U.S. crude oil market using Platts’s data, which was aggregated and transformed into relevant analyses in ZEMA.
The methodology that Platts and Argus employ to create oil price assessments, as well as the way ZEMA can be used to manipulate assessment data, is discussed in further detail below.
How Are Oil Price Assessments Created?
PRAs have unique methodologies and algorithms that they use to generate oil assessments. Both Platts and Argus publish assessments primarily for physical oil markets.
Central to the oil assessments generated by both Argus and Platts are references to real-time market trades and information received from a variety of market participants within limited time periods (usually one trading day in a particular time zone). Trading days are defined differently for each product and are based on times when markets are suitably liquid. Both Platts and Argus collect market information from a range of participants, including oil refiners, producers, traders, and brokers. These market participants voluntarily submit lists of oil transactions, including prices, volumes, bids, offers, and counterparties, as well as information on spread values between oil grades, locations, and timings (Platts Methodology and Specifications Guide). Platts and Argus do publicly release the reference points their reporters use to generate assessments.
Market participants submit relevant information to Platts and Argus prior to a strict time cut-off. These time cut-offs differ depending on the organization’s unique assessment calculation methodologies and the product itself. Platts and Argus reporters then analyze all data submitted and apply tests to determine if transactional data should be subjected to further scrutiny. Some assessments must be subjected to an internal review process that requires both organizations to inquire further within a data source’s company to assess the data’s relevance. In some instances, if data is missing, or an illiquid market makes it difficult for a reporter to generate an assessment, reporters create assessments based on their own judgment. Both organizations then produce assessments that are time-stamped—that is, representative of trade values at particularly liquid points in the trade day. Platts terms their time-stamping procedure a “Market on Close” (MOC) system.
Although the procedures Platts and Argus follow to produce oil price assessments are somewhat similar, their resulting outputs are often quite different, largely due to the fact that their sources of market information are not the same. Another key difference between the two organizations is the way in which their reporters create oil assessments when faced with a lack of deal evidence. Argus reporters will consider grade differentials of deals done throughout a day, placing them in the context of absolute market price levels and time differentials at their assessment cut-off points (Oil Price Reporting Agencies). By contrast, Platts reporters will consider information collected throughout the day, with a particular focus on the half hour prior to 1630 PM London time (Oil Price Reporting Agencies).
ZEMA and Assessment Data
As many PRAs produce a range of assessments each day for benchmark crudes, oil industry participants frequently struggle to collect and display these assessments in a way that enables them to gain a truly accurate, reflective market snapshot.
The graph below is an example of one of the many ways in which ZEMA can be deployed to solve this dilemma. The graph displays calendar swap futures from 2009-2013 for three key oil benchmarks—Dated Brent, WTI, and Dubai. These benchmarks are assessed on a daily basis by a wide range of PRAs. The Dated Brent and WTI series are fed by NYMEX data; the Dubai series is fed by Platts’s data. ZEMA graphs like this can significantly enhance oil industry participants’ decision making processes, as they enable participants to recognize large market trends, such as the divergence in swap future prices that occurred early in 2011.
ZEMA also automates data collection and validation processes, ensuring that oil industry participants can trust the accuracy and timeliness of their data. In addition, in ZEMA allows industry participants to manipulate relevant assessment data in one centralized workspace, displaying forward curves, charts, graphs, and news updates next to one another—a feature which helps users gain an enhanced perspective of the volatile oil market.