Research article

The heterogeneous linkage of economic policy uncertainty and oil return risks

  • Received: 12 February 2019 Accepted: 05 March 2019 Published: 18 March 2019
  • JEL Codes: C51, E65, G14, G18

  • The recent financial crisis and its aftermath boost the research of economic policy uncertainty and its relevant topics. In this paper, we forecast the oil return risks based on the CAViaR method and further depict the dynamic and heterogeneous features during the crisis (or non-crisis) period, as well as in different markets via DCC-GARCH models. The empirical results show the linkage of economic policy uncertainty and oil return risks, indicating an increasing trend and stronger relationship with major events. Further study shows the heterogeneous feature existing during crisis or non-crisis period, and there is heterogeneity in values and variations of their linkage in different markets. Therefore, policymakers should intervene timely in the crude oil market, release good news, and stabilize oil prices during the crisis period. During the non-crisis period, however, investors need to rationally analyze the price trend of the oil market, thereby preventing possible risks in the market.

    Citation: Hao Dong, Yue Liu, Jiaqi Chang. The heterogeneous linkage of economic policy uncertainty and oil return risks[J]. Green Finance, 2019, 1(1): 46-66. doi: 10.3934/GF.2019.1.46

    Related Papers:

  • The recent financial crisis and its aftermath boost the research of economic policy uncertainty and its relevant topics. In this paper, we forecast the oil return risks based on the CAViaR method and further depict the dynamic and heterogeneous features during the crisis (or non-crisis) period, as well as in different markets via DCC-GARCH models. The empirical results show the linkage of economic policy uncertainty and oil return risks, indicating an increasing trend and stronger relationship with major events. Further study shows the heterogeneous feature existing during crisis or non-crisis period, and there is heterogeneity in values and variations of their linkage in different markets. Therefore, policymakers should intervene timely in the crude oil market, release good news, and stabilize oil prices during the crisis period. During the non-crisis period, however, investors need to rationally analyze the price trend of the oil market, thereby preventing possible risks in the market.


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    [1] Aastveit KA, Bjørnland HC, Thorsrud LA (2015) What drives oil prices? Emerging versus developed economies. J Appl Econ 30: 1013–1028.
    [2] Aastveit KA, Natvik GJ, Sola S (2017) Economic uncertainty and the influence of monetary policy. J Int Money Finance 76: 50–67.
    [3] Alexopoulos M, Cohen J (2015) The power of print: Uncertainty shocks, markets, and the economy. Int Rev Econ Finance 40: 8–28.
    [4] Aloui R, Gupta R, Miller SM (2016) Uncertainty and crude oil returns. Energy Econ 55: 92–100.
    [5] Antonakakis N, Chatziantoniou I, Filis G (2014) Dynamic spillovers of oil price shocks and economic policy uncertainty. Energy Econ, 44: 433–447.
    [6] Aye G, Gupta R, Hammoudeh S, et al. (2015) Forecasting the price of gold using dynamic model averaging. Int Rev Financ Anal 41: 257–266.
    [7] Baker SR, Bloom N, Davis SJ (2016) Measuring economic policy uncertainty. Q J Econ 131: 1593–1636.
    [8] Balcilar M, Bekiros S, Gupta R (2017) The role of news-based uncertainty indices in predicting oil markets: A hybrid nonparametric quantile causality method. Empirical Econ 53: 879–889.
    [9] Balcilar M, Gupta R, Kyei C, et al. (2016) Does economic policy uncertainty predict exchange rate returns and volatility? Evidence from a nonparametric causality-in-quantiles test. Open Econ Rev 27: 229–250.
    [10] Baumeister C, Kilian L (2015) Forecasting the real price of oil in a changing world: A forecast combination approach. J Bus Econ Stat 33: 338–351.
    [11] Baumeister C, Kilian L (2016) Forty years of oil price fluctuations: Why the price of oil may still surprise us. J Econ Perspect 30: 139–60.
    [12] Baumeister C, Peersman G (2013) The role of time‐varying price elasticities in accounting for volatility changes in the crude oil market. J Appl Econ 28: 1087–1109.
    [13] Berger T, Uddin GS (2016) On the dynamic dependence between equity markets, commodity futures and economic uncertainty indexes. Energy Econ 56: 374–383.
    [14] Bekiros S, Gupta R, Paccagnini A (2015) Oil price forecastability and economic uncertainty. Econ Lett 132: 125–128.
    [15] Bernal O, Gnabo JY, Guilmin G (2016) Economic policy uncertainty and risk spillovers in the Eurozone. J Int Money Finance 65: 24–45.
    [16] Bernardi M, Catania L (2016) Comparison of Value-at-Risk models using the MCS approach. Comput Stat 31: 579–608.
    [17] Bollerslev T, Engle RF, Wooldridge JM (1988) A capital asset pricing model with time-varying covariances. J Political Econ 96: 116–131.
    [18] Bordo MD, Duca JV, Koch C (2016a) Economic policy uncertainty and the credit channel: Aggregate and bank level US evidence over several decades. J Financ Stab 26: 90–106.
    [19] Bordo MD, Meissner CM (2016b) Fiscal and financial crises. NBER Working Paper, No. 22059.
    [20] Brogaard J, Detzel A (2015) The asset-pricing implications of government economic policy uncertainty. Manage Sci 61: 3–18.
    [21] Caggiano G, Castelnuovo E, Figueres JM (2017) Economic policy uncertainty and unemployment in the United States: A nonlinear approach. Econ Lett 151: 31–34.
    [22] Caporale GM, AliF M, Spagnolo N (2015) Oil price uncertainty and sectoral stock returns in China: A time-varying approach. China Econ Rev 34: 311–321.
    [23] Çolak G, Durnev A, Qian Y (2017) Political uncertainty and IPO activity: Evidence from US gubernatorial elections. J Financ Quant Anal 52: 2523–2564.
    [24] Cunado J, Jo S, de Gracia FP (2015) Macroeconomic impacts of oil price shocks in Asian economies. Energy Policy 86: 867–879.
    [25] Dai Y, Xie W, Jiang Z, et al. (2016) Correlation structure and principal components in the global crude oil market. Empirical Econ 51: 1501–1519.
    [26] Engle R (2002) Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. J Bus Econ Stat 20: 339–350.
    [27] Engle RF, Manganelli S (2004) CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. J Bus Econ Stat 22: 367–381.
    [28] Ferraty F, Quintela-Del-Río A (2016) Conditional VAR and Expected Shortfall: A New Functional Approach. Econ Rev 35: 263–292.
    [29] Ftiti Z, Guesmi K, Teulon F (2014) Oil shocks and Economic Growth in OPEC countries No. 2014–064.
    [30] Gao R, Zhang B (2016) How does economic policy uncertainty drive gold–stock correlations? Evidence from the UK. Appl Econ 48: 3081–3087.
    [31] Gkillas K, Katsiampa P (2018) An application of extreme value theory to cryptocurrencies. Econ Lett 164: 109–111.
    [32] Gong X, Wen F, Xia X, et al. (2017) Investigating the risk-return trade-off for crude oil futures using high-frequency data. Appl energy 196: 152–161.
    [33] Handley K, Limão N (2017) Policy uncertainty, trade, and welfare: Theory and evidence for China and the United States. Am Econ Rev 107: 2731–2783.
    [34] Jia X, An H, Fang W, et al. (2015) How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective. Energy Econ 49: 588–598.
    [35] Juvenal L, Petrella I (2015) Speculation in the oil market. J Appl Econ 30: 621–649.
    [36] Kang W, de Gracia FP, Ratti RA (2017) Oil price shocks, policy uncertainty, and stock returns of oil and gas corporations. J Int Money Finance 70: 344–359.
    [37] Kang W, Ratti RA (2015) Oil shocks, policy uncertainty and stock returns in China. Econ Transition 23: 657–676.
    [38] Kellogg R (2014) The effect of uncertainty on investment: Evidence from Texas oil drilling. Am Econ Rev 104: 1698–1734.
    [39] Laporta AG, L Merlo, Petrella L (2018) Selection of Value at Risk Models for Energy Commodities. Energy Econ 74: 628–643.
    [40] Li Z, Wang C, Nie P, et al. (2018) Green loan and subsidy for promoting clean production innovation. J Cleaner Prod 187: 421–431.
    [41] Li, X, Peng L (2017) US economic policy uncertainty and linkages between Chinese and US stock markets. Econ Modell 61: 27–39.
    [42] Li X, Ma J, Wang S, et al. (2015) How does Google search affect trader positions and crude oil prices? Econ Modell 49: 162–171.
    [43] Li Z, Dong H, Huang Z, et al. (2018) Asymmetric Effects on Risks of Virtual Financial Assets (VFAs) in different regimes: A Case of Bitcoin. Quant Finance Econ 2: 860–883.
    [44] Liu Z, Ye Y, Ma F, et al. (2017) Can economic policy uncertainty help to forecast the volatility: A multifractal perspective. Phys A: Stat Mech its Appl 482: 181–188.
    [45] Mensi W, Hammoudeh S, Shahzad SJH, et al. (2017) Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method. J Banking Finance 75: 258–279.
    [46] Narayan PK, Gupta R (2015) Has oil price predicted stock returns for over a century? Energy Economics 48: 18–23.
    [47] Naser H (2016) Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach. Energy Econ 56: 75–87.
    [48] Phan DHB, Sharma SS, Narayan PK (2015) Oil price and stock returns of consumers and producers of crude oil. J Int Finan Markets, Inst Money 34: 245–262.
    [49] Qureshi K (2016) Value-at-Risk: The Effect of Autoregression in a Quantile Process. arXiv preprint arXiv: 1605.04940.
    [50] Reboredo JC, Uddin GS (2016) Do financial stress and policy uncertainty have an impact on the energy and metals markets? A quantile regression approach. Int Rev Econ Finance 43: 284–298.
    [51] Sim N, Zhou H (2015) Oil prices, US stock return, and the dependence between their quantiles. J Banking Finance 55: 1–8.
    [52] Singleton KJ (2013) Investor flows and the 2008 boom/bust in oil prices. Manage Sci 60: 300–318.
    [53] Tsai IC (2017) The source of global stock market risk: A viewpoint of economic policy uncertainty. Econ Modell 60: 122–131.
    [54] Waisman M, Ye P, Zhu Y (2015) The effect of political uncertainty on the cost of corporate debt. J Finan Stab 16: 106–117.
    [55] Wang J, Wang J (2016) Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations. Energy 102: 365–374.
    [56] Wen F, Xiao J, Huang C, et al. (2018) Interaction between oil and US dollar exchange rate: Nonlinear causality, time-varying influence and structural breaks in volatility. Appl Econ 50: 319–334.
    [57] Wisniewski TP, Lambe BJ (2015) Does economic policy uncertainty drive CDS spreads? Int Rev Finan Anal 42: 447–458.
    [58] Yin L (2016) Does oil price respond to macroeconomic uncertainty? New evidence. Empirical Econ 51: 921–938.
    [59] You W, Guo Y, Zhu H, et al. (2017) Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression. Energy Econ 68: 1–18.
    [60] Zhang J, Zhang Y, Zhang L (2015) A novel hybrid method for crude oil price forecasting. Energy Econ 49: 649–659.
    [61] Zhang YJ, Zhang L (2015) Interpreting the crude oil price movements: Evidence from the Markov regime switching model. Appl Energy 143: 96–109.
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