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Forecasting the price tag on Oil

Forecasting the buying price of Oil

Researchers seek approaches to improve current methodologies

Oil is really a monitored commodity, so when its cost moves, whole industries and whole economies could be shaped and defined. Using the tariff of oil�s decline in December 2015 to below $35 per barrel the first time since 2009, the U.S. oil exploration and production (E&P) sector has slowed with a blip of the company's previous boom. The price of oil is so necessary to the process of E&P firms that a few of the largest ones inside the U.S. south declined to be on record about the resources they watch and make use of to make forecasts and make profitable business decisions continue. So, what exactly is behind the all-important expense of oil and what�s the present thinking on the way to anticipate its next move? Oilman spoke with two professors at the University of Texas at Austin McCombs School of economic to discover. Oil and Gas News

Market Status at Year-End 2015

In line with the International Energy Agency�s (IEA) December 2015 Oil Market Report, OPEC�s decision to scrap its official production ceiling and oil flowing is a de facto acknowledgment of current oil market reality. IEA declared that the exporter group has effectively been pumping at will since Saudi Arabia convinced fellow members last year to avoid supply cuts and defend market share contrary to the ongoing rise in non-OPEC supply.

IEA�s World Energy Outlook for 2015 exactly what to one scenario where oil prices remain low on an extended period, with a new market equilibrium emerging at prices in a $50/bbl to $60/bbl range that lasts well in to the 2020s before climbing to $85/bbl in 2040. That scenario makes certain market assumptions, including sluggish near-term economic growth; a comfortable Middle East through which key producers turn to grow their business; and resilient performance from key non-OPEC producers, particularly U.S. tight oil.

The U.S. Energy Information Administration (EIA) rolling around in its Dec. 8 Short-Term Energy Outlook estimated that total U.S. oil production declined by about 60,000 b/d in November in comparison with October. Oil production is forecast to decrease through 3Q16 before growth resumes late in 2016. Moreover, projected U.S. crude oil production averages 9.3 million b/d in 2015 and eight.8 million b/d in 2016.

EIA forecasts that Brent crude oil prices will average $53/b in 2015 and $56/b in 2016. Forecast West Texas Intermediate oil prices average $4/b below the Brent price in 2015 and $5/b reduced in 2016.


The charge per barrel of oil is established though an array of decisions that influence the availability of oil and it is demand. Forecasting the price of oil, therefore, has traditionally been reliant on predicting those decisions. Because businesses that find trustworthy forecasting models can undertake boom and bust cycles with vision, researchers still seek out solutions to make improvements to current methodologies.

Around three in the past, professors James Dyer and Joe Hahn in the McCombs School of commercial designed a new tool which uses information about the need for assets in real estate markets to estimate basic principles of oil supply and demand and also the resulting price. Their study, that has been originally published in Energy Economics in 2014, analyzes 23 many years of historical oil futures prices to model and forecast prices.

The study was section of an application of study that Hahn originally began focusing on for his dissertation and that he has continued to work on included in a larger project on energy prices. One of the main inputs on the mixers Hahn was creating was obviously a forecast of commodity prices, and oil was among those commodities.

Hahn and Dyer focused on creating a model that allowed them to develop forecasts that diverted from traditional subjective thinking contained in models determined by supply and demand.

�We�ve been enthusiastic about models that will allow us to create forecasts which are in most sense objective,� Dyer said.

Models depending on supply and demand, Dyer said, tend to be more complex models that try and collect specifics of various indicators of activities the production and utilization of an asset, such as oil or gas main, along with the balance between the rates with the production and also the rates of use of the commodities. Those models then require some assumptions regarding how prices might react to the changes in demand and supply, he stated.

One of the challenges of these models, he added, would be that the people that build the models make assumptions that reflect their different views or opinions and various estimates from the relative impact of modifications in oil and gas prices as supplies and demands change.

�Some of the change might be estimated from market information, but in other cases, there is relatively more subjectivity in the type of models when compared to the type of model that we have been developing,� Dyer said.

The model developed by Hahn and Dyer relies on information that can be found available and could be reproduced by other people using the same techniques. Their model, Hahn said, is founded on �the wisdom from the crowd, for the reason that we glance at what are the marketplace is buying and selling relation to futures data for oil.�

The people trading in those finance industry is running their very own proprietary fundamental/economic models, and they are generally placing bets on whether or not the price is planning to increase or down or what level the price will be at later on.

�That�s all impounded in market data through futures prices,� he said. �We use that data through the market - and the composite of everyone�s individual expectations that impounds itself in futures prices - to calibrate our model. So we�re not putting any of our personal subjective judgments in the model.�

The forecast that comes from the goal model offers bounds, Hahn said, explaining that regardless of the expected value is a forecast, chances are it will be wrong.

�What our forecast tries to provide is expectation having an error bound around what that expectation is over time,� he was quoted saying. �So in case you examine where prices have fallen to today, it would be near to the lower bound of these forecast.�

Hahn noted that a majority of fundamental forecasts missed the reality that OPEC would adopt the availability policy that has led to the current supply glut.

�That�s not something which was grabbed generally in most models and couldn�t have already been picked up in the market-based model if the market participants weren�t anticipating it,� he explained.

Because there are numerous unforeseeable factors that will forward and influence the buying price of oil, Hahn said it is very important to update the objective model as that information turns up on the market.

Although Hahn and Dyer never have updated the model since study was published in 2014, i was told that an addendum for the study with the update would be timely.

For the time being, they're taking care of a similar forecasting model for gas.

�We�re building some models that relate to the price tag on electricity, and a forecast with the cost of natural gas will be a fundamental part of those models,� Dyer said. �We expect to have those models available on a public website to use or manipulation from the public ideally over the following six months�

Dyer and Hahn plan to update the cost-of-electricity models frequently in order to be run with current forecast estimates which are based on modifications in industry information regarding futures prices. The site, Dyer said, will be given by the vitality Institute about the University of Texas campus. Oil and Gas News

Post by energy3news (2016-08-04 12:57)

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