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Risk analysis of energy in Vietnam

Author

Listed:
  • Duc Hong Vo

    (Business and Economics Research Group Ho Chi Minh City Open University, Vietnam.)

  • Ngoc Phu Tran

    (Business and Economics Research Group Ho Chi Minh City Open University, Vietnam.)

  • Tam Nguyen-Thanh Duong

    (Business and Economics Research Group Ho Chi Minh City Open University, Vietnam.)

  • Michael McAleer

    ( Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute Erasmus School of Economics Erasmus University Rotterdam, The Netherlands and Department of Quantitative Economics Complutense University of Madrid, Spain And Institute of Advanced Sciences Yokohama National University, Japan.)

Abstract

The purpose of the paper is to estimate market risk for the ten major industries in Vietnam. The focus is on the Energy sector, which has been designated as one of the four key industries, together with Services, Food, and Telecommunications, targeted for economic development by the Vietnam Government through to 2020. Oil and Gas is a separate energy-related major industry. The data set is from 2009 to 2017, which is decomposed into two distinct sub-periods after the Global Financial Crisis (GFC), namely the immediate post-GFC (2009-2011) period and the normal (2012-2017) period, in order to identify the behaviour of market risk for Vietnam major industries. Two widely-used approaches to measure and analyze risk are used in the empirical analysis, namely Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). The empirical findings indicate that Energy and Pharmaceuticals are the least risky industries, whereas Oil and Gas and Securities have the greatest risk. In general, there is strong empirical evidence that the four key industries display relatively low risk. For public policy, the Vietnam Government’s pro-active emphasis on the targeted industries, including Energy, to achieve sustainable economic growth and national economic development, seems to be working effectively.

Suggested Citation

  • Duc Hong Vo & Ngoc Phu Tran & Tam Nguyen-Thanh Duong & Michael McAleer, 2019. "Risk analysis of energy in Vietnam," Documentos de Trabajo del ICAE 2019-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Handle: RePEc:ucm:doicae:1914
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    References listed on IDEAS

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    1. Fotios C. Harmantzis & Linyan Miao & Yifan Chien, 2006. "Empirical study of value‐at‐risk and expected shortfall models with heavy tails," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 7(2), pages 117-135, March.
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    3. Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & Maasoumi, Esfandiar & McAleer, Michael & Pérez-Amaral, Teodosio, 2019. "Choosing expected shortfall over VaR in Basel III using stochastic dominance," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 95-113.
    4. Allen, David E & Powell, Robert, 2008. "Structural Credit Modelling and Its Relationship to Market Value at Risk: An Australian Sectoral Perspective," MPRA Paper 47206, University Library of Munich, Germany.
    5. David Edmund Allen & Robert John Powell & Abhay Kumar Singh, 2012. "Beyond reasonable doubt: multiple tail risk measures applied to European industries," Applied Economics Letters, Taylor & Francis Journals, vol. 19(7), pages 671-676, May.
    6. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    7. Boubaker, Heni & Sghaier, Nadia, 2013. "Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 361-377.
    8. Carole Toque & Virginie Terraza, 2014. "Histogram-valued data on value at risk measures: a symbolic approach for risk attribution," Applied Economics Letters, Taylor & Francis Journals, vol. 21(17), pages 1243-1251, November.
    9. L. Kourouma & Denis Dupré & G. Sanfilippo & O. Taramasco, 2011. "Extreme Value at Risk and Expected Shortfall during Financial Crisis," Post-Print halshs-00658495, HAL.
    10. Ron Bird & Harry Liem & Susan Thorp, 2012. "The Tortoise and the Hare: Risk Premium Versus Alternative Asset Portfolios," Working Paper Series 16, The Paul Woolley Centre for Capital Market Dysfunctionality, University of Technology, Sydney.
    11. Fotios C. Harmantzis & Linyan Miao & Yifan Chien, 2006. "Empirical study of value-at-risk and expected shortfall models with heavy tails," Journal of Risk Finance, Emerald Group Publishing, vol. 7(2), pages 117-135, March.
    12. L. Kourouma & Denis Dupré & O. Taramasco & G. Sanfilippo, 2011. "Extreme Value at Risk and Expected Shortfall during Financial Crisis," Post-Print halshs-00650913, HAL.
    13. David E. Allen & Robert Powell, 2009. "Transitional credit modelling and its relationship to market value at risk: an Australian sectoral perspective," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(3), pages 425-444, September.
    14. Allen, D.E. & Powell, R.J. & Singh, A.K., 2016. "Take it to the limit: Innovative CVaR applications to extreme credit risk measurement," European Journal of Operational Research, Elsevier, vol. 249(2), pages 465-475.
    15. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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    Cited by:

    1. Thang Cong Nguyen & Tan Ngoc Vu & Duc Hong Vo & Michael McAleer, 2020. "Systematic Risk at the Industry Level: A Case Study of Australia," Risks, MDPI, vol. 8(2), pages 1-12, April.
    2. Ahmed Imran Hunjra & Tahar Tayachi & Rashid Mehmood & Sidra Malik & Zoya Malik, 2020. "Impact of Credit Risk on Momentum and Contrarian Strategies: Evidence from South Asian Markets," Risks, MDPI, vol. 8(2), pages 1-14, April.

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    More about this item

    Keywords

    Market risk; Energy; Industries; Value-at-Risk; Conditional Value-at-Risk; Sustainable growth; Economic development; Vietnam.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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