Forecasting the price tag on Oil

Forecasting the buying price of Oil

Researchers seek approaches to improve current methodologies

Oil is a closely watched commodity, so when your buck moves, whole industries and whole economies might 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 previous boom. The price tag on oil is indeed critical to the entire process of E&P firms that some of the largest ones inside the U.S. south declined to be on record about the resources they watch and rehearse to create forecasts and earn profitable business decisions continue. So, precisely what is behind the all-important expense of oil and what�s the existing thinking on the way to anticipate its next move? Oilman spoken with two professors in the University of Texas at Austin McCombs School of economic to find out.

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Market Status at Year-End 2015

In accordance 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 often a de facto acknowledgment of current oil market reality. IEA asserted the exporter group has effectively been pumping as you desire since Saudi Arabia convinced folks recently to try to keep from supply cuts and defend share of the market up against the ongoing rise in non-OPEC supply.

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

The U.S. Energy Information Administration (EIA) in the Dec. 8 Short-Term Energy Outlook estimated that total U.S. oil production declined by about 60,000 b/d in November weighed against October. Crude oil production is forecast to diminish through 3Q16 before growth resumes late in 2016. In addition, projected U.S. oil production averages 9.3 million b/d in 2015 and 8.8 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 crude oil prices average $4/b under the Brent price in 2015 and $5/b lower in 2016.

Forecasting

The price per barrel of oil is set though many decisions that influence the production of oil as well as demand. Forecasting the price tag on oil, therefore, has traditionally been just a few predicting those decisions. Because firms that find trustworthy forecasting models can proceed through boom and bust cycles with vision, researchers still seek out methods to enhance current methodologies.

About three in the past, professors James Dyer and Joe Hahn from the McCombs School of Business designed a new tool that utilizes details about value of 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 years of historical oil futures prices to model and forecast prices.

The research was portion of a plan of study that Hahn originally began focusing on for his dissertation and has continued to work on included in a bigger project on energy prices. One of the primary inputs for the appliances Hahn was creating would have been a forecast of commodity prices, and oil was one particular commodities.

Hahn and Dyer centered on developing a model that allowed them to develop forecasts that diverted from traditional subjective thinking contained in models depending on demand and supply.

�We�ve been considering models that allows us to come up with forecasts which can be in some sense objective,� Dyer said.

Models depending on demand and supply, Dyer said, will be more complex mixers try to collect information regarding various indicators of activities with regards to the production and utilization of a commodity, including oil or natural gas, and the balance between your rates of the production and also the rates people of these commodities. Those models then require some assumptions regarding how prices might reply to modifications in supply and demand, he explained.

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

�Some of this change may be estimated from market information, in other cases, there exists relatively more subjectivity in the type of models compared to the sort of model we’ve been developing,� Dyer said.

The model produced by Hahn and Dyer relies on information which can be found in the marketplace and is reproduced by other individuals using the same techniques. Their model, Hahn said, is based on �the wisdom of the crowd, for the reason that we look at what are the companies are buying and selling regards to futures data for oil.�

Individuals trading those markets are running their very own proprietary fundamental/economic models, and they’re placing bets on whether or not the prices are planning to rise or down or what level the price will likely be at in the future.

�That�s all impounded in market data through futures prices,� he explained. �We use that data in the market – as well as the composite of everyone�s individual expectations that impounds itself in futures prices – to calibrate our model. So we�re not putting any one of your own subjective judgments in the model.�

The forecast that comes from the goal model now offers bounds, Hahn said, explaining that regardless of the expected value is in any forecast, it is likely to be wrong.

�What our forecast tries to provide is expectation with the error bound around what that expectation has ended time,� he explained. �So in case you have a look at where prices have fallen to today, it would be close to the lower bound of that forecast.�

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

�That�s not something that’s picked up in most models and couldn�t are already grabbed in the market-based model in the event the market participants weren�t anticipating it,� he said.

Since there are a variety of unforeseeable factors that can come forward and influence the buying price of oil, Hahn claimed it is critical to update the target model as that information turns up on the market.

Although Hahn and Dyer have not updated the model since study was published in 2014, the trainer told us an addendum towards the study with an update would be timely.

In the meantime, these are working on a similar forecasting model for propane.

�We�re building some appliances relate to the price tag on electricity, along with a forecast with the price of gas will be a fundamental part of those models,� Dyer said. �We have a much those models available on a public website for use or manipulation through the public ideally within the next six months�

Dyer and Hahn intend to update the cost-of-electricity models often to enable them to be run with current forecast estimates that are determined by changes in the market more knowledge about futures prices. The website, Dyer said, could be supplied by the force Institute for the University of Texas campus.

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