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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. 111 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 112 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. 113 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. 114 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. 115 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 ~ ~ ~ ~ ~ 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] 116