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Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models

Author

Listed:
  • Feng Ma
  • Xinjie Lu
  • Lu Wang
  • Julien Chevallier

    (LED - Laboratoire d'Economie Dionysien - UP8 - Université Paris 8 Vincennes-Saint-Denis)

Abstract

This paper explores the effects of global economic policy uncertainty (GEPU) on conditional volatility in the gold futures market using Markov regime‐switching GARCH‐MIDAS models. The in‐sample empirical results suggest that GEPU indeed contains predictive information for the gold futures market, and higher GEPU leads to higher volatility within the gold futures market. Moreover, the novel model, which adds Markov regime switching with time‐varying transition probabilities and the GEPU index, achieves relatively better performance than those of the other competing models from a statistical point of view. Furthermore, we discuss the asymmetric effects of different changes in GEPU on the gold futures market and the models' performances with different horizons, and we find that our new model has better predictive performance under negative changes in GEPU than under positive changes in GEPU. Further discussion also confirms that our previous findings are robust during two special cases, the global financial crisis and European debt crisis, during which the market suffered from fierce fluctuations and was fraught with considerable uncertainty.

Suggested Citation

  • Feng Ma & Xinjie Lu & Lu Wang & Julien Chevallier, 2021. "Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models," Post-Print halshs-04250272, HAL.
    • Handle: RePEc:hal:journl:halshs-04250272
    DOI: 10.1002/for.2753
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    Cited by:

    1. Peng, Lijuan & Liang, Chao & Yang, Baoying & Wang, Lu, 2024. "Crude oil volatility forecasting: Insights from a novel time-varying parameter GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 94(C).
    2. Wang, Zhuqing & Wang, Xinyu & Cheng, Qiuying & Shi, Song, 2024. "Heterogeneous impact of economic and political uncertainty on green bond volatility: Evidence from the MRS-GARCH-MIDAS-Skewed T model," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    3. Pham, Son D. & Nguyen, Thao T.T. & Do, Hung X., 2024. "Impact of climate policy uncertainty on return spillover among green assets and portfolio implications," Energy Economics, Elsevier, vol. 134(C).
    4. Duan, Huayou & Zhao, Chenchen & Wang, Lu & Liu, Guangqiang, 2024. "The relationship between renewable energy attention and volatility: A HAR model with markov time-varying transition probability," Research in International Business and Finance, Elsevier, vol. 71(C).
    5. Guo, Xiaozhu & Lu, Xinjie & Mu, Shaobo & Zhang, Min, 2024. "New roles for energy and financial markets in spillover connections: context under COVID-19 and the Russia–Ukraine conflict," Research in International Business and Finance, Elsevier, vol. 71(C).
    6. Mei, Xueting & Wang, Xinyu, 2024. "Forecasting stock volatility using time-distance weighting fundamental’s shocks," Finance Research Letters, Elsevier, vol. 65(C).
    7. Dutta, Anupam & Park, Donghyun & Uddin, Gazi Salah & Kanjilal, Kakali & Ghosh, Sajal, 2024. "Do dirty and clean energy investments react to infectious disease-induced uncertainty?," Technological Forecasting and Social Change, Elsevier, vol. 205(C).

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