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News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices

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  • Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy

Abstract

We develop two news-based investor attention measures from the news trends function of the Bloomberg terminal and investigate their predictive power for returns on crude oil futures contracts with various maturities. Our main results after controlling for relevant macroeconomic variables show that the Oil-based Institutional Attention Index is useful in predicting oil futures returns, especially during price downturn periods, while the forecasting accuracy is further improved when the Commodity Market Institutional Attention Index is used. This forecasting accuracy decreases, however, with the maturity of oil futures contracts. Moreover, we find some evidence of Granger-causality and regime-dependent interactions between investor attention measures and oil futures returns. Finally, variable selection algorithms matter before making predictions since they create the best forecasting results in many cases considered. These findings are important for informed traders and policymakers to better understand the price dynamics of the oil markets.

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  • Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy, 2022. "News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
  • Handle: RePEc:aen:journl:ej43-si1-nguyen
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    1. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    2. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    3. Rossi, Barbara, 2005. "Optimal Tests For Nested Model Selection With Underlying Parameter Instability," Econometric Theory, Cambridge University Press, vol. 21(5), pages 962-990, October.
    4. Zhengke Ye, Chunyan Hu, Linjie He, Guangda Ouyang, and Fenghua Wen, 2020. "The Dynamic Time-frequency Relationship between International Oil Prices and Investor Sentiment in China: A Wavelet Coherence Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5), pages 251-270.
    5. Zagaglia, Paolo, 2010. "Macroeconomic factors and oil futures prices: A data-rich model," Energy Economics, Elsevier, vol. 32(2), pages 409-417, March.
    6. Veldkamp, Laura & Wolfers, Justin, 2007. "Aggregate shocks or aggregate information? Costly information and business cycle comovement," Journal of Monetary Economics, Elsevier, vol. 54(Supplemen), pages 37-55, September.
    7. Heidorn, Thomas & Mokinski, Frieder & Rühl, Christoph & Schmaltz, Christian, 2015. "The impact of fundamental and financial traders on the term structure of oil," Energy Economics, Elsevier, vol. 48(C), pages 276-287.
    8. Xiao, Jihong & Wang, Yudong, 2021. "Investor attention and oil market volatility: Does economic policy uncertainty matter?," Energy Economics, Elsevier, vol. 97(C).
    9. Yao, Ting & Zhang, Yue-Jun & Ma, Chao-Qun, 2017. "How does investor attention affect international crude oil prices?," Applied Energy, Elsevier, vol. 205(C), pages 336-344.
    10. Nikitopoulos, Christina Sklibosios & Squires, Matthew & Thorp, Susan & Yeung, Danny, 2017. "Determinants of the crude oil futures curve: Inventory, consumption and volatility," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 53-67.
    11. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    12. Selim Elekdag & René Lalonde & Douglas Laxton & Dirk Muir & Paolo Pesenti, 2008. "Oil Price Movements and the Global Economy: A Model-Based Assessment," IMF Staff Papers, Palgrave Macmillan, vol. 55(2), pages 297-311, June.
    13. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    14. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    15. Groen, Jan J.J. & Kapetanios, George, 2016. "Revisiting useful approaches to data-rich macroeconomic forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 221-239.
    16. Lardic, Sandrine & Mignon, Valérie, 2008. "Oil prices and economic activity: An asymmetric cointegration approach," Energy Economics, Elsevier, vol. 30(3), pages 847-855, May.
    17. Baruník, Jozef & Malinská, Barbora, 2016. "Forecasting the term structure of crude oil futures prices with neural networks," Applied Energy, Elsevier, vol. 164(C), pages 366-379.
    18. Azi Ben-Rephael & Zhi Da & Ryan D. Israelsen, 2017. "It Depends on Where You Search: Institutional Investor Attention and Underreaction to News," Review of Financial Studies, Society for Financial Studies, vol. 30(9), pages 3009-3047.
    19. Brahmasrene, Tantatape & Huang, Jui-Chi & Sissoko, Yaya, 2014. "Crude oil prices and exchange rates: Causality, variance decomposition and impulse response," Energy Economics, Elsevier, vol. 44(C), pages 407-412.
    20. Fredj Jawadi, Waël Louhichi, Hachmi Ben Ameur, and Zied Ftiti, 2019. "Do Jumps and Co-jumps Improve Volatility Forecasting of Oil and Currency Markets?," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    21. Chen, Shuning & Zhang, Wei & Feng, Xu & Xiong, Xiong, 2020. "Asymmetry of retail investors’ attention and asymmetric volatility: Evidence from China," Finance Research Letters, Elsevier, vol. 36(C).
    22. Nikos K. Nomikos & Panos K. Pouliasis, 2015. "Petroleum Term Structure Dynamics and the Role of Regimes," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(2), pages 163-185, February.
    23. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
    24. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    25. Li, Lei & Yin, Libo & Zhou, Yimin, 2016. "Exogenous shocks and the spillover effects between uncertainty and oil price," Energy Economics, Elsevier, vol. 54(C), pages 224-234.
    26. Kou, Yi & Ye, Qiang & Zhao, Feng & Wang, Xiaolin, 2018. "Effects of investor attention on commodity futures markets," Finance Research Letters, Elsevier, vol. 25(C), pages 190-195.
    27. Wang, Hua & Xu, Liao & Sharma, Susan Sunila, 2021. "Does investor attention increase stock market volatility during the COVID-19 pandemic?," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    28. Barbara Rossi & Yiru Wang, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," Stata Journal, StataCorp LP, vol. 19(4), pages 883-899, December.
    29. Ernesto Garnier and Reinhard Madlener, 2016. "The Influence of Policy Regime Risks on Investments in Innovative Energy Technology," The Energy Journal, International Association for Energy Economics, vol. 0(Bollino-M).
    30. Niels S. GrØnborg & Asger Lunde, 2016. "Analyzing Oil Futures with a Dynamic Nelson‐Siegel Model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(2), pages 153-173, February.
    31. Manickavasagam, Jeevananthan & Visalakshmi, S. & Apergis, Nicholas, 2020. "A novel hybrid approach to forecast crude oil futures using intraday data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    32. Wu, Chih-Chiang & Chung, Huimin & Chang, Yu-Hsien, 2012. "The economic value of co-movement between oil price and exchange rate using copula-based GARCH models," Energy Economics, Elsevier, vol. 34(1), pages 270-282.
    33. Li, Xin & Ma, Jian & Wang, Shouyang & Zhang, Xun, 2015. "How does Google search affect trader positions and crude oil prices?," Economic Modelling, Elsevier, vol. 49(C), pages 162-171.
    34. Han, Liyan & Lv, Qiuna & Yin, Libo, 2017. "Can investor attention predict oil prices?," Energy Economics, Elsevier, vol. 66(C), pages 547-558.
    35. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    36. Xiao, Jihong & Zhou, Min & Wen, Fengming & Wen, Fenghua, 2018. "Asymmetric impacts of oil price uncertainty on Chinese stock returns under different market conditions: Evidence from oil volatility index," Energy Economics, Elsevier, vol. 74(C), pages 777-786.
    37. Cedric Mbanga & Ali F. Darrat & Jung Chul Park, 2019. "Investor sentiment and aggregate stock returns: the role of investor attention," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 397-428, August.
    38. Pal, Debdatta & Mitra, Subrata Kumar, 2019. "Asymmetric oil price transmission to the purchasing power of the U.S. dollar: A multiple threshold NARDL modelling approach," Resources Policy, Elsevier, vol. 64(C).
    39. Lutz Kilian & Bruce Hicks, 2013. "Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003–2008?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 385-394, August.
    40. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    41. Geiger, Martin & Scharler, Johann, 2019. "How do consumers assess the macroeconomic effects of oil price fluctuations? Evidence from U.S. survey data," Journal of Macroeconomics, Elsevier, vol. 62(C).
    42. Li, Sufang & Zhang, Hu & Yuan, Di, 2019. "Investor attention and crude oil prices: Evidence from nonlinear Granger causality tests," Energy Economics, Elsevier, vol. 84(C).
    43. Hamilton, James D, 1983. "Oil and the Macroeconomy since World War II," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 228-248, April.
    44. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    45. Bijl, Laurens & Kringhaug, Glenn & Molnár, Peter & Sandvik, Eirik, 2016. "Google searches and stock returns," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 150-156.
    46. Smales, L.A., 2021. "Investor attention and global market returns during the COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 73(C).
    47. Dzieliński, Michał & Rieger, Marc Oliver & Talpsepp, Tõnn, 2018. "Asymmetric attention and volatility asymmetry," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 59-67.
    48. David Hirshleifer & Sonya S. Lim & Siew Hong Teoh, 2011. "Limited Investor Attention and Stock Market Misreactions to Accounting Information," The Review of Asset Pricing Studies, Oxford University Press, vol. 1(1), pages 35-73.
    49. Vozlyublennaia, Nadia, 2014. "Investor attention, index performance, and return predictability," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 17-35.
    50. repec:dau:papers:123456789/5465 is not listed on IDEAS
    51. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    52. Almansour, Abdullah, 2016. "Convenience yield in commodity price modeling: A regime switching approach," Energy Economics, Elsevier, vol. 53(C), pages 238-247.
    53. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2011. "New evidence on oil price and firm returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3253-3262.
    54. Prange, Philipp, 2021. "Does online investor attention drive the co-movement of stock-, commodity-, and energy markets? Insights from Google searches," Energy Economics, Elsevier, vol. 99(C).
    55. Hyunjoo Kim Karlsson, Kristofer Månsson, and Pär Sjölander, 2020. "Unveiling the Time-dependent Dynamics between Oil Prices and Exchange Rates: A Wavelet-based Panel Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6), pages 87-106.
    56. Ali E. Abbas & N. Onur Bakır & Georgia-Ann Klutke & Zhengwei Sun, 2013. "Effects of Risk Aversion on the Value of Information in Two-Action Decision Problems," Decision Analysis, INFORMS, vol. 10(3), pages 257-275, September.
    57. Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R., 2019. "Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 555-572.
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