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What Central Bankers Need to Know about Forecasting Oil Prices

Citations

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Cited by:

  1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
  2. Shiu-Sheng Chen, 2014. "Forecasting Crude Oil Price Movements With Oil-Sensitive Stocks," Economic Inquiry, Western Economic Association International, vol. 52(2), pages 830-844, April.
  3. Sun, Yunpeng & Gao, Pengpeng & Raza, Syed Ali & Shah, Nida & Sharif, Arshian, 2023. "The asymmetric effects of oil price shocks on the world food prices: Fresh evidence from quantile-on-quantile regression approach," Energy, Elsevier, vol. 270(C).
  4. Baumeister, Christiane & Guérin, Pierre, 2021. "A comparison of monthly global indicators for forecasting growth," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1276-1295.
  5. Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
  6. Christiane Baumeister & Lutz Kilian & Xiaoqing Zhou, 2013. "Are Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis," Staff Working Papers 13-25, Bank of Canada.
  7. Emanuel Kohlscheen, 2022. "Quantifying the Role of Interest Rates, the Dollar and Covid in Oil Prices," Papers 2208.14254, arXiv.org, revised Oct 2022.
  8. Panopoulou, Ekaterini & Pantelidis, Theologos, 2015. "Speculative behaviour and oil price predictability," Economic Modelling, Elsevier, vol. 47(C), pages 128-136.
  9. Pérez-Quirós, Gabriel & Diaz, Elena, 2020. "Daily Tracker of Global Economic Activity. A Close-Up of the Covid-19 Pandemic," CEPR Discussion Papers 15451, C.E.P.R. Discussion Papers.
  10. Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2015. "Do high-frequency financial data help forecast oil prices? The MIDAS touch at work," International Journal of Forecasting, Elsevier, vol. 31(2), pages 238-252.
  11. Christiane Baumeister & Lutz Kilian, 2015. "Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 338-351, July.
  12. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
  13. Raza, Syed Ali & Guesmi, Khaled & Belaid, Fateh & Shah, Nida, 2022. "Time-frequency causality and connectedness between oil price shocks and the world food prices," Research in International Business and Finance, Elsevier, vol. 62(C).
  14. Chu, Pyung Kun & Hoff, Kristian & Molnár, Peter & Olsvik, Magnus, 2022. "Crude oil: Does the futures price predict the spot price?," Research in International Business and Finance, Elsevier, vol. 60(C).
  15. Zeina Alsalman, 2023. "Oil price shocks and US unemployment: evidence from disentangling the duration of unemployment spells in the labor market," Empirical Economics, Springer, vol. 65(1), pages 479-511, July.
  16. Monge, Manuel & Cristóbal, Enrique, 2021. "Terrorism and the behavior of oil production and prices in OPEC," Resources Policy, Elsevier, vol. 74(C).
  17. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
  18. Nicholas Apergis, 2023. "Forecasting energy prices: Quantile‐based risk models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 17-33, January.
  19. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
  20. Conlon, Thomas & Cotter, John & Eyiah-Donkor, Emmanuel, 2022. "The illusion of oil return predictability: The choice of data matters!," Journal of Banking & Finance, Elsevier, vol. 134(C).
  21. Degiannakis, Stavros & Filis, George, 2023. "Oil price assumptions for macroeconomic policy," Energy Economics, Elsevier, vol. 117(C).
  22. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
  23. Wei, Zhaohao & Chai, Jian & Dong, Jichang & Lu, Quanying, 2022. "Understanding the linkage-dependence structure between oil and gas markets: A new perspective," Energy, Elsevier, vol. 257(C).
  24. Tian, Guangning & Peng, Yuchao & Meng, Yuhao, 2023. "Forecasting crude oil prices in the COVID-19 era: Can machine learn better?," Energy Economics, Elsevier, vol. 125(C).
  25. Lyu, Yongjian & Yi, Heling & Cao, Jin & Yang, Mo, 2022. "Time-varying monetary policy shocks and the dynamics of Chinese commodity prices," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
  26. Reinhard Ellwanger, Stephen Snudden, 2021. "Predictability of Aggregated Time Series," LCERPA Working Papers bm0127, Laurier Centre for Economic Research and Policy Analysis.
  27. Lyu, Yongjian & Yi, Heling & Wei, Yu & Yang, Mo, 2021. "Revisiting the role of economic uncertainty in oil price fluctuations: Evidence from a new time-varying oil market model," Economic Modelling, Elsevier, vol. 103(C).
  28. Samya Beidas-Strom & Mr. Andrea Pescatori, 2014. "Oil Price Volatility and the Role of Speculation," IMF Working Papers 2014/218, International Monetary Fund.
  29. Jia, Jian & Kang, Sang Baum, 2022. "Do the basis and other predictors of futures return also predict spot return with the same signs and magnitudes? Evidence from the LME," Journal of Commodity Markets, Elsevier, vol. 25(C).
  30. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
  31. Benjamin Beckers & Samya Beidas-Strom, 2015. "Forecasting the Nominal Brent Oil Price with VARs—One Model Fits All?," IMF Working Papers 2015/251, International Monetary Fund.
  32. Peng Li & Yaofu Ouyang, 2023. "Oil price shocks and China’s consumer and entrepreneur sentiment: a Bayesian structural VAR approach," Empirical Economics, Springer, vol. 65(5), pages 2241-2271, November.
  33. Frankel, Jeffrey A., 2014. "Effects of speculation and interest rates in a “carry trade” model of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 88-112.
  34. Nonejad, Nima, 2021. "The price of crude oil and (conditional) out-of-sample predictability of world industrial production," Journal of Commodity Markets, Elsevier, vol. 23(C).
  35. Ellwanger, Reinhard & Snudden, Stephen, 2023. "Forecasts of the real price of oil revisited: Do they beat the random walk?," Journal of Banking & Finance, Elsevier, vol. 154(C).
  36. Anastasios G. Malliaris & Mary Malliaris, 2021. "What Microeconomic Fundamentals Drove Global Oil Prices during 1986–2020?," JRFM, MDPI, vol. 14(8), pages 1-13, August.
  37. Zied Ftiti & Kais Tissaoui & Sahbi Boubaker, 2022. "On the relationship between oil and gas markets: a new forecasting framework based on a machine learning approach," Annals of Operations Research, Springer, vol. 313(2), pages 915-943, June.
  38. Reinhard Ellwanger, Stephen Snudden, Lenin Arango-Castillo, 2023. "Seize the Last Day: Period-End-Point Sampling for Forecasts of Temporally Aggregated Data," LCERPA Working Papers bm0142, Laurier Centre for Economic Research and Policy Analysis.
  39. George Filis & Stavros Degiannakis & Zacharias Bragoudakis, 2022. "Forecasting macroeconomic indicators for Eurozone and Greece: How useful are the oil price assumptions?," Working Papers 296, Bank of Greece.
  40. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
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