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Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index

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  • Dai, Zhifeng
  • Kang, Jie
  • Hu, Yangli

Abstract

We find the number of initial public offerings (NIPO) a simple but efficient oil price predictor, and provide new evidence that U.S. dollar index (USDX) also has significant out-of-sample forecasting power on oil price. Furthermore, we reveal the highly complementary relation between NIPO and USDX in forecasting oil price and explain it from the points of linear correlation and economic transmission mechanism. With the help of multivariate prediction methods, both the statistical and economic performance of NIPO and USDX can be tremendously boosted. The oil predictabilities of NIPO and USDX partially stem from the forecasting power on oil market sentiment and inflation, respectively, and they can be further enhanced using appropriate nonlinear model.

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  • 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).
    • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s030142072100307x
    DOI: 10.1016/j.resourpol.2021.102297
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    Cited by:

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    3. Zhao, Geya & Xue, Minggao & Cheng, Li, 2023. "A new hybrid model for multi-step WTI futures price forecasting based on self-attention mechanism and spatial–temporal graph neural network," Resources Policy, Elsevier, vol. 85(PB).
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    6. Hind Aldabagh & Xianrong Zheng & Mohammad Najand & Ravi Mukkamala, 2024. "Forecasting Crude Oil Price Using Multiple Factors," JRFM, MDPI, vol. 17(9), pages 1-15, September.
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    Keywords

    Stock market; U.S. dollar index; Oil price predictability; Out-of-sample forecasting; Asset allocation;
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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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