Does the financial crisis change the economic risk perception of crude oil traders? A MIDAS quantile regression approach
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DOI: 10.1016/j.frl.2018.10.016
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Citations
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Cited by:
- Hao-Lin Shao & Ying-Hui Shao & Yan-Hong Yang, 2021. "New insights into price drivers of crude oil futures markets: Evidence from quantile ARDL approach," Papers 2110.02693, arXiv.org.
- Ha, Le Thanh & Nham, Nguyen Thi Hong, 2022. "An application of a TVP-VAR extended joint connected approach to explore connectedness between WTI crude oil, gold, stock and cryptocurrencies during the COVID-19 health crisis," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
- Bai, Lan & Wei, Yu & Wei, Guiwu & Li, Xiafei & Zhang, Songyun, 2021. "Infectious disease pandemic and permanent volatility of international stock markets: A long-term perspective," Finance Research Letters, Elsevier, vol. 40(C).
- Sarit Maitra, 2023. "Impact of Economic Uncertainty, Geopolitical Risk, Pandemic, Financial & Macroeconomic Factors on Crude Oil Returns -- An Empirical Investigation," Papers 2310.01123, arXiv.org, revised Oct 2023.
- Ye, Wuyi & Jiang, Kunliang & Liu, Xiaoquan, 2021. "Financial contagion and the TIR-MIDAS model," Finance Research Letters, Elsevier, vol. 39(C).
- Li, Xiafei & Li, Bo & Wei, Guiwu & Bai, Lan & Wei, Yu & Liang, Chao, 2021. "Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US," Resources Policy, Elsevier, vol. 73(C).
- Cao, Yan & Cheng, Sheng & Li, Xinran, 2023. "How economic policy uncertainty affects asymmetric spillovers in food and oil prices: Evidence from wavelet analysis," Resources Policy, Elsevier, vol. 86(PB).
- Jiang, Cuixia & Xiong, Wei & Xu, Qifa & Liu, Yezheng, 2021. "Predicting default of listed companies in mainland China via U-MIDAS Logit model with group lasso penalty," Finance Research Letters, Elsevier, vol. 38(C).
- Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.
- Avik Sinha & Arshian Sharif & Arnab Adhikari & Ankit Sharma, 2022.
"Dependence structure between Indian financial market and energy commodities: a cross-quantilogram based evidence,"
Annals of Operations Research, Springer, vol. 313(1), pages 257-287, June.
- Sinha, Avik & Sharif, Arshian & Adhikari, Arnab & Sharma, Ankit, 2021. "Dependence Structure between Indian Financial Market and Energy Commodities: A Cross-quantilogram based Evidence," MPRA Paper 111181, University Library of Munich, Germany, revised 2021.
- Zhang, Hongwei & Hong, Huojun & Guo, Yaoqi & Yang, Cai, 2022. "Information spillover effects from media coverage to the crude oil, gold, and Bitcoin markets during the COVID-19 pandemic: Evidence from the time and frequency domains," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 267-285.
- Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
- Bouazizi, Tarek & Galariotis, Emilios & Guesmi, Khaled & Makrychoriti, Panagiota, 2023. "Investigating the nature of interaction between crypto-currency and commodity markets," International Review of Financial Analysis, Elsevier, vol. 88(C).
- Yang, Kun & Wei, Yu & Li, Shouwei & Liu, Liang & Wang, Lei, 2021. "Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics," Energy Economics, Elsevier, vol. 96(C).
- Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
- Sheng Cheng & Wei Liu & Qisheng Jiang & Yan Cao, 2023. "Multi–Scale Risk Connectedness Between Economic Policy Uncertainty of China and Global Oil Prices in Time–Frequency Domains," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1593-1616, April.
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More about this item
Keywords
Crude oil market; Oil financialization; MIDAS quantile regression; Economic policy uncertainty;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
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