A long-term view of worldwide fossil fuel prices

doi:10.1016/j.apenergy.2009.09.012

Applied Energy

Volume 87, Issue 3, March 2010, Pages 988-1000

https://doi.org/10.1016/j.apenergy.2009.09.012 Get rights and content

Abstract

This paper reviews a long-term trend of worldwide fossil fuel prices in the future by introducing a new method to forecast oil, natural gas and coal prices. The first section of this study analyses the global fossil fuel market and the historical trend of real and nominal fossil fuel prices from 1950 to 2008. Historical fossil fuel price analysis shows that coal prices are decreasing, while natural gas prices are increasing. The second section reviews previously available price modelling techniques and proposes a new comprehensive version of the long-term trend reverting jump and dip diffusion model. The third section uses the new model to forecast fossil fuel prices in nominal and real terms from 2009 to 2018. The new model follows the extrapolation of the historical sinusoidal trend of nominal and real fossil fuel prices. The historical trends show an increase in nominal/real oil and natural gas prices plus nominal coal prices, as well as a decrease in real coal prices. Furthermore, the new model forecasts that oil, natural gas and coal will stay in jump for the next couple of years and after that they will revert back to the long-term trend until 2018.

Introduction

Fossil fuel prices have escalated dramatically from 2003 to the beginning of 2008. This inflationary increase in energy prices has played an important role in the current global financial crisis. In other words, the upward trend of the worldwide fossil fuel market in the last five years has lead to a downturn in global share markets. In this critical situation and recession, some solutions such as bailout plans have failed to save the Dow Jones from sinking and stock market bankruptcies. Moreover, in 2008 oil, natural gas and coal prices had the highest volatility in the historical trend of fossil fuel prices. Oil prices have plunged more than 70% in the last 6 month of 2008 from $145 to $40 per barrels. These oil price fluctuations plus weaknesses in other fossil fuels prices in the short-term are another factor that has significantly influenced in the current global financial crisis [3]. Consequently, most companies are looking forward to analyse the long-term trend of fossil fuel prices in the future to make the best use of the current market situation.

This paper individually predicts all types of fossil fuel prices in the future by a new method that considers the role of oil, natural gas and coal prices at the same time. The novel technique has examined other crucial variables in the model such as depletion time, consumption and production of fossil fuel. The depletion time for oil, natural gas and coal are diverse, however fossil fuel consumption is relatively similar [42], [44]. Furthermore, the lack of investment, exploration and development will cause issues in the future such as a decline in the world’s fossil fuel resources or increase in prices thus shifting downward demand. Subsequently, demand and supply for oil, natural gas and coal will play a vital role in anticipating the expected price for fossil fuel in the long-term.

The first section of this paper analyses the fossil fuel market and trend of oil, natural gas and coal prices in the last half century. In particular, the study focuses on significant fossil fuel price variables in that era, such as depletion time, production, consumption and carbon dioxide emission. The second section reviews a number of currently available methods used to estimate commodity prices in the future, such as Geometric Brownian Motion, mean reversion, stochastic price forecasting and mean reverting jump diffusion. The last section introduces a new comprehensive model of the mean reverting jump diffusion model for forecasting fossil fuel prices. Subsequently, this model is applied to predict fossil fuel prices in nominal and real terms for the next 10 years.

Section snippets

Data sources

To forecast future fossil fuel prices, a variety of sources used for data set collection. The data used for this paper is based on Energy Information Administration (EIA) in 2008 and British Petroleum (BP) in 2009. The EIA data is obtained from the release of the Annual Energy Review for the US, while BP data considers worldwide trends. The EIA data for oil and natural gas prices are similar to other fossil fuel resource prices’s data such as the International Energy Agency (IEA), BP, West

Historical trend of fossil fuel prices and their correlation

This section reviews the long-term trend of real and nominal prices of fossil fuel. Fig. 1, Fig. 2 depict the average yearly nominal and real price historical trend of oil, natural gas and coal from 1950 to 2008, respectively. Fig. 1 demonstrates that oil, natural gas and coal prices have fluctuated very closely from 1950 to 2000. After 2000 the oil and natural gas price vacillation moves differently with coal prices. Fig. 1 shows that oil and natural gas prices significantly increased from

Geometric Brownian Motion (GBM)

In mathematics, the Wiener process is a continuous-time stochastic process named in honour of Norbert Wiener but is often called Brownian motion. The most prospected price process is Brownian motion put forward by Robert Brown in 1827. Since then the Brownian motion has been used in many fields, including finance literature, where it came to be called the Random Walk [8]. This theory attracted a lot of attention in 1973 when author Burton Malkiel wrote his famous book called “A Random Walk Down

Forecasting fossil fuel prices in the future

Fossil fuel price prediction in the future is a dilemma. In 2008, fossil fuel price fluctuations were one of the crucial elements for oil, natural gas and coal producers. Between all types of fossil fuel, oil price prediction is more volatile and highlighted more than others. Nominal oil prices reached over US $145 per barrel in July 2008 and then the trend started to revert to around US $45 per barrel in December 2008. This range of nominal oil price fluctuation was not exactly estimated by

Conclusion

The inflationary spiral by energy price escalations played an important role in the current global financial crisis. Correctly predicting fossil fuel prices in the future can greatly assist with making the best policy decision for the worldwide economy. Reviewing fossil fuel prices showed that nominal oil, natural gas and coal prices reached the peaks in 2008. Real oil and natural gas also reached their peak value in 2008, while real coal price in 1976 was still two times greater than real coal

Acknowledgements

The authors are pleased to acknowledge the contribution made by Micah Nehring and Jade Little towards this paper.

References (51)

W.A. Ahrens et al.
Trends in natural resource commodity prices: deterministic or stochastic?
J Environ Econ Manage
(1997)
M. Balat et al.
Recent trends in global production and utilization of bio-ethanol fuel
Appl Energy
(2009)
P. Berck et al.
Natural resource prices: will they ever turn up?
J Environ Econ Manage
(1996)
W.-S. Chung et al.
An estimation of energy and GHG emission intensity caused by energy consumption in Korea: an energy IO approach
Appl Energy
(2009)
J.C. Cox et al.
Option pricing: a simplified approach
J Financ Econ
(1979)
E. Jun et al.
The analysis of security cost for different energy sources
Appl Energy
(2009)
J. Lee et al.
Non-renewable resource prices: deterministic or stochastic trends?
J Environ Econ Manage
(2006)
M.J. Mueller et al.
Informative trends in natural resource commodity prices: a comment on slade
J Environ Econ Manage
(1985)
R. Sari et al.
Are global warming and economic growth compatible? Evidence from five OPEC countries?
Appl Energy
(2009)
S. Shafiee et al.
An econometrics view of worldwide fossil fuel consumption and the role of US
Energy Policy
(2008)

S. Shafiee et al.

When will fossil fuel reserves be diminished?

Energy Policy

(2009)

M.E. Slade

Trends in natural-resource commodity prices: an analysis of the time domain

J Environ Econ Manage

(1982)

M.E. Slade

Noninformative trends in natural resource commodity prices U-shaped price paths exonerated

J Environ Econ Manage

(1985)

M.E. Slade

Grade selection under uncertainty: least cost last and other anomalies

J Environ Econ Manage

(1988)

M.P. Baker et al.

Alternative models of uncertain commodity prices for use with modern asset pricing methods

Energ J

(1998)

H. Bessembinder et al.

Mean reversion in equilibrium asset prices: evidence from the futures term structure

J Financ

(1995)

F. Black et al.

The pricing of options and corporate liabilities

J Polit Econ

(1973)

V. Blais et al.

Using real options to incorporate price risk into the valuation of a multi-mineral mine

Blanco C, Choi S, Soronow D. Energy price processes used for derivatives pricing and risk management. Commodities now...

Blanco C, Soronow D. Jump diffusion processes-energy price processes used for derivatives pricing and risk management....

Blanco C, Soronow D. Mean reverting process-energy price processes used for derivatives pricing and risk management....

BP. Statistical review of world energy full report 2009. British Petroleum;...

P.A. Dafas

Estimating the parameters of a mean-reverting Markov-switching jump-diffusion model for crude oil spot prices

Dias MAG. Hybrid real options with petroleum applications. In: Departamento de Engenharia Industrial. Rio de Janeiro:...

Dias MAG and Rocha KMC. Petroleum concessions with extendible options using mean reversion wiht jumps to model oil...

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A long-term view of worldwide fossil fuel prices

Abstract

Introduction

Section snippets

Data sources

Historical trend of fossil fuel prices and their correlation

Geometric Brownian Motion (GBM)

Forecasting fossil fuel prices in the future

Conclusion

Acknowledgements

J Environ Econ Manage

Appl Energy

J Environ Econ Manage

Appl Energy

J Financ Econ

Appl Energy

J Environ Econ Manage

J Environ Econ Manage

Appl Energy

Energy Policy

Energy Policy

J Environ Econ Manage

J Environ Econ Manage

J Environ Econ Manage

Alternative models of uncertain commodity prices for use with modern asset pricing methods

Energ J

Mean reversion in equilibrium asset prices: evidence from the futures term structure

J Financ

The pricing of options and corporate liabilities

J Polit Econ

Using real options to incorporate price risk into the valuation of a multi-mineral mine

Estimating the parameters of a mean-reverting Markov-switching jump-diffusion model for crude oil spot prices