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Macroeconomic Factors and Oil Futures Prices: A Data-Rich Model

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Author Info
Zagaglia, Paolo () (Dept. of Economics, Stockholm University)

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Abstract

I study the dynamics of oil futures prices in the NYMEX using a large panel dataset that includes global macroeconomic indicators, financial market indices, quantities and prices of energy products. I extract common factors from these series and estimate a Factor-Augmented Vector Autoregression for the maturity structure of oil futures prices. I find that latent factors generate information that, once combined with that of the yields, improves the forecasting performance for oil prices. Furthermore, I show that a factor correlated to purely financial developments contributes to the model performance, in addition to factors related to energy quantities and prices.

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Publisher Info
Paper provided by Stockholm University, Department of Economics in its series Research Papers in Economics with number 2009:7.

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Length: 27 pages
Date of creation: 10 Feb 2009
Date of revision:
Handle: RePEc:hhs:sunrpe:2009_0007

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Postal: Department of Economics, Stockholm, S-106 91 Stockholm, Sweden
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Web page: http://www.ne.su.se/
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Related research
Keywords: Crude Oil; Futures Markets; Factor Models;

Find related papers by JEL classification:
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
D51 - Microeconomics - - General Equilibrium and Disequilibrium - - - Exchange and Production Economies
E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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References listed on IDEAS
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  1. Emanuel Mönch, 2005. "Forecasting the yield curve in a data-rich environment - a no-arbitrage factor-augmented VAR approach," Working Paper Series 544, European Central Bank. [Downloadable!]
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  2. Gary B. Gorton & Fumio Hayashi & K. Geert Rouwenhorst, 2007. "The Fundamentals of Commodity Futures Returns," NBER Working Papers 13249, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  3. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July. [Downloadable!] (restricted)
    Other versions:
  4. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November. [Downloadable!] (restricted)
    Other versions:
  5. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-74, January. [Downloadable!] (restricted)
  6. Vincent Brousseau & Fabio Scacciavillani, 1999. "A global hazard index for the world foreign exchange markets," Working Paper Series 1, European Central Bank. [Downloadable!]
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This page was last updated on 2009-11-19.

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