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Global financial markets and oil price shocks in real time

Author

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  • Venditti, Fabrizio
  • Veronese, Giovanni

Abstract

The role that the price of oil plays in economic analysis in central banks as well as in financial markets has evolved over time. Oil is not seen anymore just as a input to production but also as a barometer of global economic activity as well as a financial asset. A high frequency structural decomposition of the price of oil can therefore inform on the state of the global business cycle as well as on global financial market sentiment. In this paper we develop a method to identify structural sources of oil price fluctuations at the daily frequency and in real time. The identification strategy blends sign, narrative restrictions and instrumental variable techniques. By using data on asset prices, oil production and global economic activity we account for the double nature of oil: a financial asset as well as a physical commodity. The model offers novel insights on the relationship between the price of oil and asset prices. We also illustrate how the model could have been used in real time to interpret oil price movements in periods of high geopolitical tensions between the US and Iran and to read the drop of crude prices due to fears related to the Corona virus. JEL Classification: Q43, C32, E32, C53

Suggested Citation

  • Venditti, Fabrizio & Veronese, Giovanni, 2020. "Global financial markets and oil price shocks in real time," Working Paper Series 2472, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20202472
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    as
    1. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    2. Andrea Gazzani & Alejandro Vicondoa, 2020. "Bridge Proxy-SVAR: estimating the macroeconomic effects of shocks identified at high-frequency," Temi di discussione (Economic working papers) 1274, Bank of Italy, Economic Research and International Relations Area.
    3. Karel Mertens & Morten O. Ravn, 2013. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States," American Economic Review, American Economic Association, vol. 103(4), pages 1212-1247, June.
    4. Robin Braun & Ralf Brüggemann, 2017. "Identification of SVAR Models by Combining Sign Restrictions With External Instruments," Working Paper Series of the Department of Economics, University of Konstanz 2017-07, Department of Economics, University of Konstanz.
    5. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    6. Peersman, Gert & Rüth, Sebastian K. & Van der Veken, Wouter, 2021. "The interplay between oil and food commodity prices: Has it changed over time?," Journal of International Economics, Elsevier, vol. 133(C).
    7. Ambrogio Cesa-Bianchi & M Hashem Pesaran & Alessandro Rebucci & Stijn Van Nieuwerburgh, 2020. "Uncertainty and Economic Activity: A Multicountry Perspective," The Review of Financial Studies, Society for Financial Studies, vol. 33(8), pages 3393-3445.
    8. Kilian, Lutz & Zhou, Xiaoqing, 2022. "Oil prices, exchange rates and interest rates," Journal of International Money and Finance, Elsevier, vol. 126(C).
    9. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    10. Andr? Kurmann & Christopher Otrok, 2013. "News Shocks and the Slope of the Term Structure of Interest Rates," American Economic Review, American Economic Association, vol. 103(6), pages 2612-2632, October.
    11. Xavier Gabaix & Matteo Maggiori, 2015. "International Liquidity and Exchange Rate Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(3), pages 1369-1420.
    12. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    13. Andrew Lilley & Matteo Maggiori & Brent Neiman & Jesse Schreger, 2019. "Exchange Rate Reconnect," NBER Working Papers 26046, National Bureau of Economic Research, Inc.
    14. Juan Antolín-Díaz & Juan F. Rubio-Ramírez, 2018. "Narrative Sign Restrictions for SVARs," American Economic Review, American Economic Association, vol. 108(10), pages 2802-2829, October.
    15. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    16. Michele Piffer & Maximilian Podstawski, 2018. "Identifying Uncertainty Shocks Using the Price of Gold," Economic Journal, Royal Economic Society, vol. 128(616), pages 3266-3284, December.
    17. Lutz Kilian & Cheolbeom Park, 2009. "The Impact Of Oil Price Shocks On The U.S. Stock Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(4), pages 1267-1287, November.
    18. Geske, Robert, 1979. "The valuation of compound options," Journal of Financial Economics, Elsevier, vol. 7(1), pages 63-81, March.
    19. Böninghausen, Benjamin & Kidd, Gregory & de Vincent-Humphreys, Rupert, 2018. "Interpreting recent developments in market based indicators of longer term inflation expectations," Economic Bulletin Articles, European Central Bank, vol. 6.
    20. Q. Farooq Akram, 2004. "Oil prices and exchange rates: Norwegian evidence," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 476-504, December.
    21. Leland Bybee & Bryan T. Kelly & Asaf Manela & Dacheng Xiu, 2020. "The Structure of Economic News," NBER Working Papers 26648, National Bureau of Economic Research, Inc.
    22. Francesco Lippi & Andrea Nobili, 2012. "Oil And The Macroeconomy: A Quantitative Structural Analysis," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1059-1083, October.
    23. Cesa-Bianchi, Ambrogio & Sokol, Andrej, 2022. "Financial shocks, credit spreads, and the international credit channel," Journal of International Economics, Elsevier, vol. 135(C).
    24. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
    25. Alessio Anzuini & Patrizio Pagano & Massimiliano Pisani, 2015. "Macroeconomic Effects of Precautionary Demand for Oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(6), pages 968-986, September.
    26. Lutz Kilian, 2008. "A Comparison of the Effects of Exogenous Oil Supply Shocks on Output and Inflation in the G7 Countries," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 78-121, March.
    27. Silvia Miranda-Agrippino & Hélène Rey, 2020. "U.S. Monetary Policy and the Global Financial Cycle," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(6), pages 2754-2776.
    28. Juan Antolin-Diaz & Juan F. Rubio-Ramirez, 2016. "Narrative Sign Restrictions for SVARs," FRB Atlanta Working Paper 2016-16, Federal Reserve Bank of Atlanta.
    29. Pascal Paul, 2020. "The Time-Varying Effect of Monetary Policy on Asset Prices," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 690-704, October.
    30. Jan J. J. Groen & Kevin McNeil & Menno Middeldorp, 2013. "A New Approach for Identifying Demand and Supply Shocks in the Oil Market," Liberty Street Economics 20130325, Federal Reserve Bank of New York.
    31. Backus, David K. & Crucini, Mario J., 2000. "Oil prices and the terms of trade," Journal of International Economics, Elsevier, vol. 50(1), pages 185-213, February.
    32. Kilian, Lutz & Rebucci, Alessandro & Spatafora, Nikola, 2009. "Oil shocks and external balances," Journal of International Economics, Elsevier, vol. 77(2), pages 181-194, April.
    33. Alejandro Perez-Segura & Robert J. Vigfusson, 2016. "The Relationship Between Oil Prices and Inflation Compensation," IFDP Notes 2016-04-06, Board of Governors of the Federal Reserve System (U.S.).
    34. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
    35. Michel A. Robe & Jonathan Wallen, 2016. "Fundamentals, Derivatives Market Information and Oil Price Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(4), pages 317-344, April.
    36. Katarzyna Budnik & Gerhard Rünstler, 2023. "Identifying structural VARs from sparse narrative instruments: Dynamic effects of US macroprudential policies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 186-201, March.
    37. Luciana Juvenal & Ivan Petrella, 2015. "Speculation in the Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 621-649, June.
    38. Caldara, Dario & Cavallo, Michele & Iacoviello, Matteo, 2019. "Oil price elasticities and oil price fluctuations," Journal of Monetary Economics, Elsevier, vol. 103(C), pages 1-20.
    39. Habib, Maurizio M. & Stracca, Livio, 2012. "Getting beyond carry trade: What makes a safe haven currency?," Journal of International Economics, Elsevier, vol. 87(1), pages 50-64.
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    2. Marcus Vinicius Santos & Fernando Morgado-Dias & Thiago C. Silva, 2023. "Oil Sector and Sentiment Analysis—A Review," Energies, MDPI, vol. 16(12), pages 1-29, June.
    3. Valenti, Daniele & Bastianin, Andrea & Manera, Matteo, 2023. "A weekly structural VAR model of the US crude oil market," Energy Economics, Elsevier, vol. 121(C).
    4. Baumann, Ursel & Darracq Pariès, Matthieu & Westermann, Thomas & Riggi, Marianna & Bobeica, Elena & Meyler, Aidan & Böninghausen, Benjamin & Fritzer, Friedrich & Trezzi, Riccardo & Jonckheere, Jana & , 2021. "Inflation expectations and their role in Eurosystem forecasting," Occasional Paper Series 264, European Central Bank.
    5. Lodge, David & Manu, Ana-Simona, 2022. "EME financial conditions: Which global shocks matter?," Journal of International Money and Finance, Elsevier, vol. 120(C).
    6. Degasperi, Riccardo, 2023. "Identification of Expectational Shocks in the Oil Market using OPEC Announcements," The Warwick Economics Research Paper Series (TWERPS) 1464, University of Warwick, Department of Economics.
    7. Khan, Asad Ul Islam & Shahbaz, Muhammad & Napari, Ayuba, 2023. "Subsample stability, change detection and dynamics of oil and metal markets: A recursive approach," Resources Policy, Elsevier, vol. 83(C).

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    More about this item

    Keywords

    oil prices; proxy-SVAR; sign restrictions; VAR;
    All these keywords.

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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