Forecasting Crude Oil Prices

By: Keith Cochran

Joseph Singh

Julio Urenda

Dave White

Justin Adams

Inquiry:

Are Crude Oil Prices Destined to Rise this Summer?

Crude Oil Prices

Crude Oil Prices

Economic Background

Oil prices fall due to weak world demand (largely as a result of economic recession in the United States) and OPEC overproduction.

Oil prices decline sharply following the September 11, 2001 terrorist attacks, largely on increased fears of a worldwide economic downturn (and therefore lower oil demand). 

Continued unrest in Venezuela and oil traders' anticipation of imminent military action in Iraq causes prices to rise in January and February, 2003.

Economic Significance

U.S. highly dependent upon Oil.

Price of Crude Oil has direct influence on Gasoline Prices.

Higher Oil Prices can create Inflationary pressures/ higher prices of goods and services.

Data

Weekly data beginning in January 1997

Data taken from Department of Energy

Weekly data captures price fluctuations more accurately

Representative of collective OPEC countries

Crude Oil Prices (1997-May, 2004)

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30

35

40

1/03/97 12/04/98 11/03/00 10/04/02

CRUDE

First Dickey-Fuller Test

ADF Test Statistic

-0.94077

1% Critical Value*

-3.4495

5% Critical Value

-2.8693

10% Critical Value

-2.5709

Accept null hypothesis that there is a unit root. The data is evolutionary.

Data now Stationary

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1/03/97 12/04/98 11/03/00 10/04/02

DLNCRUDE

Histogram

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50

-0.15 -0.10 -0.05 0.00 0.05 0.10 0.15

Series: DLNCRUDESample 1/10/1997 5/21/2004Observations 385

Mean 0.001154Median 0.002630Maximum 0.176661Minimum -0.164543Std. Dev. 0.042484Skewness -0.340912Kurtosis 4.456788

Jarque-Bera 41.50163Probability 0.000000

Second Dickey-Fuller Test

ADF Test Statistic

-8.05749

1% Critical Value*

-3.4496

5% Critical Value

-2.8694

10% Critical Value

-2.5709 Reject null hypothesis that there is a unit root. The sample is now

stationary.

Correlogram of dlncrude

ARMA ModelDependent Variable: DLNCRUDEMethod: Least SquaresDate: 05/28/04 Time: 03:52Sample(adjusted): 1/17/1997 5/21/2004Included observations: 384 after adjusting endpointsConvergence achieved after 6 iterationsBackcast: 7/19/1996 1/10/1997

Variable Coefficient Std. Error t-Statistic Prob.

AR(1) 0.26557 0.04958 5.356343 0MA(3) 0.143536 0.050184 2.860181 0.0045MA(23) -0.096147 0.051574 -1.864243 0.0631MA(26) 0.12458 0.051984 2.396506 0.017

R-squared 0.096152 Mean dependent var 0.00108Adjusted R-squared0.089016 S.D. dependent var 0.042515S.E. of regression0.040579 Akaike info criterion -3.56078Sum squared resid0.625723 Schwarz criterion -3.519628Log likelihood687.6698 F-statistic 13.4749Durbin-Watson stat1.946557 Prob(F-statistic) 0

Residual Graph

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1/17/97 12/18/98 11/17/00 10/18/02

Residual Actual Fitted

Histogram

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-0.15 -0.10 -0.05 0.00 0.05 0.10 0.15

Series: ResidualsSample 1/17/1997 5/21/2004Observations 384

Mean 0.000712Median 0.004541Maximum 0.182268Minimum -0.166564Std. Dev. 0.040413Skewness -0.316552Kurtosis 4.840981

Jarque-Bera 60.64049Probability 0.000000

Correlogram of Residuals

Trace of Residual Squared

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1/03/97 12/04/98 11/03/00 10/04/02 9/03/04

RESID02SQ

Correlogram of Residual Squared

ARCH-GARCH Model

Forecast for 1/3/04 to 5/21/04

First Difference of Price of Crude Price of CrudeWeek in 2004 forecast arch dln forecast normal dln actual dln forecast arch forecast normal actual1 (1/3/2004) -0.003537 -0.003537 -0.003537 28.22 28.22 28.22

2 0.005163 0.005012 0.034138 28.36607663 28.36179368 29.23 -0.005762 -0.00578 0.025961 28.20310128 28.19833536 29.9684 -0.006439 -0.0062 -0.015062 28.02208492 28.02404653 29.525 0.000392 0.000383 -0.023305 28.03307173 28.0347818 28.846 0.007355 0.006858 -0.050126 28.24001507 28.22770511 27.437 0.005244 0.004996 0.000656 28.38849469 28.3690836 27.4488 0.000928 0.000944 0.048221 28.41485144 28.39587666 28.8049 0.00217 0.002248 0.014134 28.47657861 28.45978239 29.214

10 -0.008603 -0.007984 0.044389 28.23264539 28.23346415 30.5411 -0.011064 -0.010541 0.012463 27.92200106 27.93741826 30.92312 -0.008752 -0.008425 0.010839 27.67869397 27.70303424 31.2613 -0.003482 -0.003458 0.000512 27.58248435 27.60740259 31.27614 0.014239 0.013557 -0.040954 27.97804083 27.98422466 30.02115 0.009292 0.00881 0.004089 28.23922437 28.23185489 30.14416 0.010864 0.010232 0.038654 28.54768784 28.52220613 31.33217 -0.012544 -0.011999 0.002837 28.1918223 28.18201325 31.42118 -0.005065 -0.004897 0.01538 28.04939173 28.04434329 31.90819 -0.00074 -0.000649 0.055323 28.02864286 28.02614842 33.72320 0.007561 0.007242 0.036739 28.24137063 28.2298505 34.985

21 (5/21/04) 0.000165 0.000157 0.02796 28.24603084 28.23428293 35.977

Forecast for Normal Model

Forecast values for ARCH-GARCH

Forecasting 5/21/04 – 9/03/04

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5/28 6/11 6/25 7/09 7/23 8/06 8/20 9/03

DLNCRUDEF ± 2 S.E.

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-0.20

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0.00

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1/11/02 12/27/02 12/12/03

DLNCRUDEB

AER

Conclusions

There is an upward trend in oil prices for the

Have significant impact on Consumer Price Index (CPI)

Economic Significance of Results

Crude Oil Prices are increasing this summer

This is largely due to a steady increase in oil demand in the United States and China

However, supply disruptions are impossible to predict and could affect oil prices