Download Trend Forecast on World Oil Price Fluctuations

Trend Forecast on World Oil Price Fluctuations
LUO Binyuan, MA Yuling
The Economic Management School, Henan Polytechnic University, P.R.China, 454000
The Economic Management School, Jiaozuo University, P.R.China, 454000
Abstract
Oil issue has drawn worldwide attention. The shortage of oil have led to "oil crisis" twice
in Western world, and the price of oil have impacted the stability of the world economy to a large extent.
There are various factors to impact on the current international oil price. This paper, mainly considering
economy factor, forecasts future trend of international oil prices in demonstration.
Keywords Oil price, The trend forecasts, Non-linear regression model, Fluctuations, Demonstration
Analysis
1 Introduction
Part scholar abroad particularly emphasis the method or model analyzing and forecasting on oil price
fluctuation. The HSAF method making use of the VaR History Simulation (HS) method to combine with
ARMA forecast model each other has carried out by Cabedo and Moya on international crude oil price
risks studying, having improved standard HS method and been more effective than the ARCH model.
Cortazar and Schwartz have built oil forward price random model. Michael and Zyrenetal have
developed the short-term month forecast model, from the conclusion that the forecast model gain has
provided a good marketplace indicator to crude oil price change.
The research to oil price is quiet many in homeland, but major among them are the qualitative
analysis and intrinsic characteristics basis on economics theory or simple fundamentals condition. For
example, Hu Rong and Lv Ning have analyzed the factor affecting oil price except supply and demand,
such as forward market , oil stock , the climate and OPEC's influence. Wei Taoyuan has analyzed how
our country economy is effected by world oil price going up. Up to now, a part of document have carried
out the quantify or demonstration on oil price fluctuation studying. For example, Mei Xiaofeng has been
on the march to the cause that international market oil price fluctuation produces analyzes. Yu Bo, Chi
Chunjie and Su Guofu analyses with throwing into output a model an impact of the fluctuation having
calculated oil price over our country economy.
2 Demonstration Assumes
The factor affecting current international oil price is many-sided: The imbalance of supply and
demand is the main reason; Geopolitics risk brings along the scared oil price; The reduced of exchange
rate of US dollar makes oil price higher; The international speculate is the artificial factor; Unexpected
event is the short-term factor; The alternate energy source is able to affect oil price indirectly, but whose
effect is difficult to appear in a short time. Generally, supply-demand relations are the bases deciding oil
price. Other factor produces an effect especially when the supply and demand is imbalance.
3 Data Chooses
Because oil price of Brant and WTI have influenced comparatively more present international oil
market, the author will assume demonstration analysis basis on this two kinds criterion oil price of Brant
and USA WTI. Through observing the price fluctuation trend of Brant oil and WTI oil(as follow), we
decide to adopt the price from 1986 to 2003, because prices fluctuations in 1985, 2004, 2005, 2006 is
abnormal.
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Figure 1 Two criterion oil cash price fluctuation pursue
4 Demonstration Analysis
Under condition of frequently acute fluctuation of international oil price, if we still make use of
customary linearity regression to forecast oil price, the forecast value and actual value sometimes will be
very distant from each other and lead to the forecast fault. Therefore it is imperative to improve the past
customary forecast model. The international petroleum marketplace has blown hot and cold, and has
entered a new fluctuation scheduled time. There is both linearity and fluctuation of oil price, so we make
use of a improved model, which is Four-Non-linear regression model.
Figure 1 had demonstrated 1985-2003 year price change of Brant and the WTI, which are
representative international crude oil. We can see that in figure 1 the world typical oil price is always
changing, and the fluctuation undulation is its basic characteristic.
Through observing the figure, we adopt the Fourth polynomial to simulate. We will use Eviews3.1
statistical software to achieve. Figure 2 and Figure 3 shows the Simulate condition as follow.
35
30
25
20
10
15
5
10
0
-5
-10
02
04
06
Residual
08
10
Actual
12
14
16
Fitted
Figure2 Oil price of Brant fluctuation and simulate result
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18
35
30
25
10
20
15
5
10
0
-5
-10
02
04
06
08
10
Residual
12
14
Actual
16
18
Fitted
Figure 3 Oil price of WTI fluctuation and simulate result
4.1 Brant paints price
Simulate result as follows:
Y Brant = 23.00657734 - 0.009873985832×T3 + 0.0006184802128×T4
Every modulus is notable in 5% notable level. Table 1 shows it's t checkout value and determination
coefficient.
Table 1: Brant oil price assay
Included observations: 18
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
T3
T4
23.00658
-0.009874
0.000618
1.420523
0.003752
0.000215
16.19585
-2.631681
2.871544
0.0000
0.0189
0.0116
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.431283
0.355454
3.518157
185.6614
-46.54287
1.832453
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
21.82167
4.382161
5.504763
5.653159
5.687580
0.014512
From figure 4, we can see absolute average error of forecast is 2.499, and average absolute error is
12.17%. Because oil prices have been impacted greater by other factors (particularly of a sudden and
speculative factors), error is larger.
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40
Forecast: BRTF
Actual: BRT
Forecast sample: 1901 1918
Included observations: 18
35
30
Root Mean Squared Error3.211623
Mean Absolute Error
2.499339
Mean Abs. Percent Error12.17073
Theil Inequality Coefficient
0.072606
Bias Proportion
0.000000
Variance Proportion 0.207204
Covariance Proportion
0.792796
25
20
15
10
02
04
06
08
10
BRTF
12
14
16
18
?2 S.E.
Figure 4 Brant oil price simulate and forecast result
4.2 WTI oil price
Simulate result as follows:
YWTI = 24.35153585 - 0.009759274807×T3 + 0.0006160434589×T4
Every modulus is notable in 5% notable level. Table 2 shows it's t checkout value and determination
coefficient.
Table 2 WTI oil price assays
Included observations: 18
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
3
24.35154
-0.009759
1.430131
0.003777
17.02749
-2.583633
0.0000
0.0208
4
0.000616
0.000217
2.841016
0.0124
0.438858
0.364039
3.541952
188.1814
-46.66420
1.826518
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
T
T
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
23.29444
4.441479
5.518245
5.666640
5.865608
0.013123
From figure 5, we can see absolute average error of forecast is 2.539, and average absolute error is
11.46%. Because oil prices have been impacted greater by other factors (particularly of a sudden and
speculative factors), error is larger.
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45
Forecast: WTIF
Actual: WTI
Forecast sample: 1901 1918
Included observations: 18
40
35
Root Mean Squared Error 3.233345
Mean Absolute Error
2.539473
Mean Abs. Percent Error 11.45679
Theil Inequality Coefficient 0.068561
Bias Proportion
0.000000
Variance Proportion 0.203034
Covariance Proportion 0.796966
30
25
20
15
10
02
04
06
08
WTIF
10
12
14
16
18
?2 S.E.
Figure 5 WTI oil price simulate and forecast result
From two above models, we can be forecast oil price in 2004, 2005, 2006 and 2007.The result is as
follows:
Table 3
2004
oil price forecasts result
2005
2006
Year
Oil
Brant
2007
35.88
42.97
51.85
63.74
WTI
37.70
44.84
53.78
65.17
Through contrasting the real price in the schedule in 2004 and 2005, we find that the error between
the 2004 price We forecast and the real price is within the scope of average absolute error .The error is
grater in 2005 and 2006, which is mainly caused by unexpected events (and this model is not involved).
Such as, in January as "Ivan" hurricane Gulf of Mexico, in June Iran oil city blast occurred, New
Orleans in August the United States encountered the "Katrina" hurricane attack, and each time has
caused international oil prices move up in short-term. It is estimated that there are around 10-15 U.S.
dollars "terror premium." of international oil prices in 2005. Excluding this factor, in 2005 and 2006 the
forecast price and the reality is basically the same price. Therefore, it can be said that the model
predicted the outcome and the reality of fitting better, Without considering factors unexpected incidents
under the premise forecast to be conservative, in 2007 the oil price will be in Brant (63.74 ± 2.539) U.S.
dollars / barrel about volatility WTI oil prices will be in (65.17 ± 2.539) U.S. dollars / barrel around
fluctuations.
5 Conclusion
Short-term international oil prices will continue to remain above 50 U.S. dollars / barrel, the
high-profile period. Specific empirical results of Brant in oil prices will be (63.74 ± 2.539) U.S. dollars /
barrel, and WTI oil prices will be (65.17 ± 2.539) U.S. dollars / barrel around fluctuations. The analysis
of long-term oil prices will be from the main factors. Overall impacts of change in trend, we estimate oil
prices will likely have a tendency in the next five years (2010), but it is expected to stabilize at a
reasonable price range.
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References
[1] J. David Cabedo, Ismael Moya, Estimating oil price Value at Risk using the historical simulation
approach[J],Energy Economics,2003(25),p12 15
[2]Cortazar, Eduardo S. Schwartz, Implimenting a stochastic model for oil futures prices[J],Energy
Economics,2003(25),p19 21
[3] Wei Taoyuan,,The effect going up to our country economy analyses world oil price, quantity
economy technical economy studies[J],2005(10),p4 8,in Chinese
[4] Zhao Nong ,petroleum fluctuations in prices analysis [J].world economy,2006(5),p18 20,in
Chinese
[5] Mei Xiaofeng , International petroleum fluctuations , prices analyse, 2007(3),p13 16. ,in Chinese
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Year
Schedule international oil price in 1985-2006 (U. S. dollar/ barrel)
Brant
WTI
Year
Brant
WTI
1985
39.29
40.14
1996
21.24
22.74
1986
20.38
21.19
1997
19.38
20.88
1987
24.91
26.02
1998
12.71
14.36
1988
19.56
20.96
1999
18.06
19.38
1989
22.9
24.65
2000
28.63
30.5
1990
28.18
29.28
2001
24.45
25.89
1991
23.26
24.97
2002
25.1
26.26
1992
21.73
23.13
2003
28.83
31.06
1993
18.67
20.27
2004
38.21
41.41
1994
16.94
18.44
2005
54.38
56.44
1995
17.86
19.32
2006
67.18
69.24
Explanation: 1. Before 1985, Brent and WTI oil is not the benchmark oil;
2. Basing on 2005 constant prices, we use the GDP inflation rate to be deducted;
3. The data originates: "World petroleum trend " in 2006.
The author can be contacted from e-mail : [email protected]
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