Determinants of the WTI-Brent Spread Revisited...Re-examination of WTI-Brent price spreads on a...

Determinants of the WTI-Brent Spread Revisited:

Before and after the Structural Break

Andreas Rathgeber | Dauphine Université Paris | Determinants of WTI-Brent Spread Revisited1

(Work in progress)

Andreas Rathgeber* and Jerome Geyer-Klingeberg*

Dauphine Université Paris, 16th March 2018

*Institute of Materials Resource Management

University of Augsburg

Germany

2

Development of WTI and Brent crude oil

Andreas Rathgeber | Dauphine Université Paris | Determinants of WTI-Brent Spread Revisited

Source: U.S. Energy Information Administration

3

Review of the literature

Structural breaks in WTI-Brent price spread


Determinants of WTI-Brent spread

Authors Sample period Structural break test Identified breaks

Büyüksahin et al. (2013) 2000:06 – 2012:07 Chow (1960) 2008:11, 2010:12

Aruga (2015) 2001:01 – 2014:05 Bai and Perron (1998) 2003:01, 2005:01, 2007:01,

2009:02, 2011:02

Chen et al. (2015) 1988:01 – 2014:12 Leybourne et al. (2007) 2010:04

Li et al. (2015) 2004:01 – 2013:12 Hansen (1997) 2010:01

Liu et al. (2016) 2004:01 – 2010:12 Bai and Perron (1998) 2010:12

Ye and Karali (2016) 1993:12 – 2016:04 Bai and Perron (1998) 2005:05, 2010:12, 2013:04

Authors Sample period Methodology Main spread determinants

Milonas and Henker (2010) 1991:02 – 1996:01 OLS regression Convenience yield

Büyüksahin et al. (2013) 2004:04 – 2012:04 ARDL U.S. business climate, storage problems

in Cushing, open interest, position of

futures traders

Re-examination of WTI-Brent price spreads on a daily data set between

1995:01 and 2014:07 using autoregressive distributed lag models (ARDL)

Advanced tests for detection of structural breaks

Analysis of change in the spread determinants after structural break(s)

Comprehensive investigation of convenience yield as proxy for crude oil

inventories

Examination of the balancing mechanism between spot and futures market

4

Contribution


𝑃𝑡𝑊𝑇𝐼: WTI opening price

𝑃𝑡𝐵𝑟𝑒𝑛𝑡: Brent closing price

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Spread calculation and convenience yield


𝑆𝑃𝑅𝑡 = 𝑆𝑡𝑊𝑇𝐼 − 𝑆𝑡

𝐵𝑟𝑒𝑛𝑡 𝑆𝑡𝐵𝑟𝑒𝑛𝑡Normalized WTI-Brent spread:

Convenience yield: 𝐶𝑌𝑡,𝑇 = 𝑅𝑡,𝑇 + 𝐶𝑡,𝑇 −1

𝑇 − 𝑡ln 𝐹𝑡,𝑇 − ln 𝑃𝑡

𝑃𝑡,𝑇: Three month U.S. treasury bill

𝐶𝑡,𝑇: Storage costs ($0.40 according to Ederington et al. 2012)

𝐹𝑡,𝑇: Three month crude oil futures price

𝑃𝑡: 𝑃𝑡𝑊𝑇𝐼 and 𝑃𝑡

𝐵𝑟𝑒𝑛𝑡

Three step estimation procedure following term structure of yield curves (Martellini

2003):

1. Calculation of 𝐶𝑌𝑡,𝑇 for different maturities

2. Interpolation of all data points using a cubic spline function

3. Evaluation of the spline function at the desired maturity

6

Data (I/II)

Daily data set from 01/01/1995 through 23/07/2017


Variable Definition Source

𝑃𝑊𝑇𝐼 Western Texas Intermediate opening spot price (U.S. dollars per barrel) Datastream

𝑃𝐵𝑟𝑒𝑛𝑡 UK Brent nominal closing spot price (U.S. dollars per barrel) Bloomberg

𝐹𝑊𝑇𝐼 WTI opening futures crude oil price (U.S. dollars), 3 months to maturity NYMEX

𝐹𝐵𝑟𝑒𝑛𝑡 Brent closing futures crude oil price (U.S. dollars), 3 months to maturity ICE

𝑇𝑆𝑊𝑇𝐼 Term spread, defined as 𝐹𝑊𝑇𝐼 − 𝑃𝑊𝑇𝐼 Own calculation

𝑇𝑆𝐵𝑟𝑒𝑛𝑡 Term spread, defined as 𝐹𝐵𝑟𝑒𝑛𝑡 − 𝑃𝐵𝑟𝑒𝑛𝑡 Own calculation

𝑅𝐹 Three months U.S. treasury yield on actively traded non-inflation-indexed issues,

adjusted to constant maturity

Federal Reserve

𝑉𝐿𝑊𝑇𝐼 Aggregate trading volume for WTI futures contracts NYMEX

𝑉𝐿𝐵𝑟𝑒𝑛𝑡 Aggregate trading volume for Brent futures contracts ICE

𝑂𝐼𝑊𝑇𝐼 Aggregate open interest for WTI futures contracts NYMEX

𝑂𝐼𝐵𝑟𝑒𝑛𝑡 Aggregate open interest for Brent futures contracts ICE

𝐵𝐷 Baltic dry index pre-multiplied by the sign of the WTI-Brent spread Baltic Exchange

7

Data (II/II)


8

Summary statistics


Mean Median Std. Dev. Min Max N

𝑆𝑃𝑅𝑆𝑝𝑜𝑡 0.0160 0.0272 0.0852 -0.2498 0.3470 4708

𝑆𝑃𝑅𝐹𝑢𝑡𝑢𝑟𝑒 0.0175 0.0324 0.0725 -0.2297 0.2298 4708

𝐶𝑌𝑊𝑇𝐼 0.1615 0.1374 0.2288 -1.3395 1.2963 4708

𝐶𝑌𝐵𝑟𝑒𝑛𝑡 0.1791 0.1406 0.1847 -0.4825 1.1224 4708

𝑇𝑆𝑊𝑇𝐼 0.2501 0.1500 2.0408 -13.8300 15.2000 4708

𝑇𝑆𝐵𝑟𝑒𝑛𝑡 -0.0613 -0.2700 1.5073 -5.2900 8.1100 4708

𝑉𝐿𝑊𝑇𝐼 0.0005 0.0025 0.2943 -2.6140 2.9832 4708

𝑉𝐿𝐵𝑟𝑒𝑛𝑡 0.0005 0.0010 0.3376 -2.2412 2.9857 4708

𝑂𝐼𝑊𝑇𝐼 0.0003 0.0015 0.0188 -0.1899 0.2341 4708

𝑂𝐼𝐵𝑟𝑒𝑛𝑡 0.0004 0.0024 0.0335 -0.4792 0.4658 4708

𝐵𝐷 -0.0002 0.0000 0.0178 -0.2052 0.1464 4708

𝑇𝑅 0.0227 0 0.1490 0 1 4708

𝐻𝑅 0.0042 0 0.0650 0 1 4708

𝑆𝑇𝑈𝑆 0.0002 0.0007 0.0140 -0.1080 0.0942 4708

𝑆𝑇𝐸𝑈 0.0001 0.0006 0.0119 -0.0679 0.0912 4708

𝐻𝑇 0.5346 0.0000 1.4160 -3.9125 7.5875 4708

𝐶𝐿 1.2797 0.0000 3.1998 -12.2250 15.4896 4708

Notes: This table presents summary statistics for the full sample period. Variable definitions can be obtained from Table 1.

***, **, * denote statistical significance at the 1%, 5% or 10% level.

1. Detection of structural break in WTI-Brent spread

Chow-test, CUSUM, CUSUMQ, Andrews test, Hansen test

Result: 3 breaks (Only one break is always significant at 5% level)

2. Combined tests for unit root and structural break

Bai/Perron (2003), Busseti/Harvey (1998), Harvey/Mills (2001)

Lee/Strazicich(2001), Perron (1997), Zivot/Andrews (1992) and BIC

Several Break types (Shift, Crash, Trend and combinations)

Up to 5 breakpoints


Time Series Analysis - Structural Break


Histogram of Combined Unit Root and

Structural Break Tests


Results of Lee/Strazicich (2001) test


Breakpoint - Economic evaluation

Absolute low of U.S. crude oil production: Oct 2008, Jan 2008

Source: U.S. Energy Information Administration


Cointegration analysis of WTI and Brent


Response of WTI (Brent) oil price

to Cholesky One S.D. Brent (WTI) Innovation

Estimated in first differences, 𝑉𝐴𝑅(2, 𝑘)with 𝑘 ∈ {1,2}


Unit Root Tests

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ARDL model


ARDL 𝑝, 𝑞1, … , 𝑞𝑛 in following unrestricted error correction (ECM)

∆𝑆𝑃𝑅𝑡 = 𝑎0 + 𝑎1𝑡 +

𝑖=1

𝑝−1

𝜓1,𝑖∆𝑆𝑃𝑅𝑡−𝑖 +

𝑗=1

𝑛

𝑖=0

𝑞𝑗−1

𝜓𝑗+1,𝑖∆𝑋𝑗,𝑡−𝑖 + 𝜆1𝑆𝑃𝑅𝑡−1 +

𝑗=1

𝑛

𝜆𝑗+1𝑋𝑗,𝑡−1 +

𝑘=1

𝑚

𝛿𝑘𝑍𝑘,𝑡 +𝑢𝑡

𝑎0 is the drift component

𝑡 = max 𝑝, 𝑞1, … , 𝑞𝑛 , … , 𝑇 is the time trend component

𝑋 = [𝐶𝑌𝑊𝑇𝐼, 𝐶𝑌𝐵𝑟𝑒𝑛𝑡, 𝑉𝐿𝑊𝑇𝐼, 𝑉𝐿𝐵𝑟𝑒𝑛𝑡, 𝑂𝐼𝑊𝑇𝐼, 𝑂𝐼𝐵𝑟𝑒𝑛𝑡, 𝐵𝐷, 𝑆𝑇𝑈𝑆, 𝑆𝑇𝐸𝑈]

𝑍 = [𝐻𝑇, 𝐶𝐿, 𝑇𝑅, 𝐻𝑅, 𝑆𝐵]

𝑢𝑡 is the white noise error term

𝜓1,…,𝜓𝑛 symbolize the error correction dynamics

𝜆1, … , 𝜆𝑛 represent the long-run relationship

ARDL bounds test: 𝐻0𝐹: 𝜆1 = ⋯ = 𝜆𝑛+1, using critical values by Pesaran et al. (2001)

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ARDL results – Bounds test


18

ARDL results – Error correction term


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ARDL results – Long-run elasticities (I/II)


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ARDL results – Long-run elasticities (II/II)


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Concluding remarks


WTI-Brent spread shows significant structural change in 2010

The convenience yield, as proxy for crude oil inventories, is the most

important spread determinant

The impact of the convenience yield changed since the break in 2010

Also the trading volume in WTI futures markets as well as the economic

situation and temperature differences between the U.S. and Europe drive

the size of the WTI-Brent spread.

The importance of trading volume in WTI futures is reduced.

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References

Argua, K., 2015. Testing the International Crude Oil Market Integration with Structural

Breaks. Economics Bulletin 35, 641-649.

Bai, J., Perron, P., 2003. Computation and analysis of multiple structural change models.

Journal of Applied Econometrics 18, 1-22. doi: 10.1002/jae.659.

Busetti, F., Harvey, A., 2001. Testing for the Presence of a Random Walk in Series with

Structural Breaks. Journal of Time Series Analysis 22, 127-150. doi: 10.1111/1467-

9892.00216.

Büyüksahin, B., Lee, T.K., Moser, J.T., Robe, M.A., 2013. Physical Markets, Paper Markets

and the WTI-Brent Spread. The Energy Journal 34, 129-151. doi: 10.5547/01956574.34.3.7

Chen, W., Huang, Z., Yi, Y., 2015. Is there a structural change in the persistence of WTI–

Brent oil price spreads in the post-2010 period? Economic Modelling 50, 64-71. doi:

10.1016/j.econmod.2015.06.007.

Harvey, D.I., Mills, T.C., 2003. A Note on Busetti-Harvey Tests for Stationarity in Series with

Structural Breaks. Journal of Time Series Analysis 24, 159-164. doi: 10.1111/1467-

9892.00300.

Johansen, S., Juselius, K., 1990. Maximum likelihood estimation and inference on

cointegration with application to the demand for money. Oxford Bulletin of Economics and

Statistics 52, 169-210. doi: 10.1111/j.1468-0084.1990.mp52002003.x.

Lee, J., Strazicich, M.C., 2003. Minimum Lagrange Multiplier Unit Root Test with Two

Structural Breaks. The Review of Economics and Statistics 85, 1082-1089. doi:

10.1162/003465303772815961.


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References

Li, Y., Mizrach, B., Otsubo, Y., 2015. Location basis differentials in crude oil prices.

Working Paper at Rutgers University.

Liu, P., Stevens, R., Vedenov, D., 2016. Physical market and WTI/Brent price spread. 34th

USAEE/IAEE North American Conference, Tulsa, Oklahoma.

Milonas, N.T., Henker, T., 2001. Price spread and convenience yield behaviour in the

international oil market. Applied Financial Economics 11, 23-36. doi:

10.1080/09603100150210237.

Perron, P., 1997. Further Evidence on Breaking Trend Functions in Macroeconomic Variables.

Journal of Econometrics 80, 355-385. doi: 10.1016/S0304-4076(97)00049-3.

Pesaran, M.H., Yongcheol, S., Smith, R.J., 2001. Bounds testing approaches to the analysis

of level relationships. Journal of Applied Econometrics 16, 289-326. doi: 10.1002/jae.616.

Robert, E.F., Granger, C.W.J., 1987. Co-Integration and Error Correction: Representation,

Estimation, and Testing. Econometrica 55, 251-276.

Ye, S., Karali, B., 2016. Estimating Relative Price Impact: The Case of Brent and WTI. Paper

presented at 2016 Agricultulral & Applied Economics Association Annual Meeting, Boston.

Zivot, E., Andrews, D.W., 1992. Further Evidence on the Great Crash, the Oil-Price Shock,

and the Unit-Root Hypothesis. Journal of Business & Economic Statistics 10, 251-270. doi:

10.2307/1391541.


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