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Effective energy commodity risk management on Indonesia

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  • Kuntadi, Cris

Abstract

Energy commodities present significant interest for the world market and energy organizations worldwide. The comprehension of the asset returns and risk has played a main role in managing returns for the world market. The energy portfolios present challenges as they are highly volatile. The present study is concerned with evaluating and describing the joint return of energy-related commodities in the Indonesian market. Power, oil, coal, gas, and carbon are the main commodities being considered. The study presents the empirical evaluation of the returns from the multivariate hyperbolic distributions. Also, the study presents the method with which the risk measures can be evaluated for the commodity portfolios based on the generic assumptions of the hyperbole. The study's main findings are that the estimates of risk based on the normal distribution have statistically significant hyperbolic distributions. These are flexible and include accurate estimates of risk. The study indicates that the carbon allowances can be used to risk exposure for a typical energy portfolio for a power plant.

Suggested Citation

  • Kuntadi, Cris, 2022. "Effective energy commodity risk management on Indonesia," Resources Policy, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:jrpoli:v:78:y:2022:i:c:s0301420722003208
    DOI: 10.1016/j.resourpol.2022.102875
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    1. Halkos, George & Zisiadou, Argyro, 2018. "Reporting the natural environmental hazards occurrences and fatalities over the last century," MPRA Paper 87936, University Library of Munich, Germany.
    2. Halkos, George & Zisiadou, Argyro, 2018. "Analysing last century’s occurrence and impacts of technological and complex environmental hazards," MPRA Paper 90503, University Library of Munich, Germany.
    3. Ales Kresta & Tomas Tichy, 2012. "International Equity Portfolio Risk Modeling: The Case of the NIG Model and Ordinary Copula Functions," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(2), pages 141-161, May.
    4. Shrimali, Gireesh & Konda, Charith & Farooquee, Arsalan Ali, 2016. "Designing renewable energy auctions for India: Managing risks to maximize deployment and cost-effectiveness," Renewable Energy, Elsevier, vol. 97(C), pages 656-670.
    5. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    6. Sarwar, Suleman & Tiwari, Aviral Kumar & Tingqiu, Cao, 2020. "Analyzing volatility spillovers between oil market and Asian stock markets," Resources Policy, Elsevier, vol. 66(C).
    7. Sarwar, Suleman & Shahbaz, Muhammad & Anwar, Awais & Tiwari, Aviral Kumar, 2019. "The importance of oil assets for portfolio optimization: The analysis of firm level stocks," Energy Economics, Elsevier, vol. 78(C), pages 217-234.
    8. Zeineb Attafi & Ahmed Ghorbel & Younes Boujelbene, 2019. "Measuring portfolio risk of non-energy commodity using time-varying vine copula," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 7(2), pages 163-190.
    9. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
    10. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
    11. Mensi, Walid & Hammoudeh, Shawkat & Kang, Sang Hoon, 2015. "Precious metals, cereal, oil and stock market linkages and portfolio risk management: Evidence from Saudi Arabia," Economic Modelling, Elsevier, vol. 51(C), pages 340-358.
    12. Jonek-Kowalska, Izabela, 2019. "Efficiency of Enterprise Risk Management (ERM) systems. Comparative analysis in the fuel sector and energy sector on the basis of Central-European companies listed on the Warsaw Stock Exchange," Resources Policy, Elsevier, vol. 62(C), pages 405-415.
    13. Johan Braeken & Francis Tuerlinckx & Paul Boeck, 2007. "Copula Functions for Residual Dependency," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 393-411, September.
    14. Chen, Liyuan & Zerilli, Paola & Baum, Christopher F., 2019. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Energy Economics, Elsevier, vol. 79(C), pages 111-129.
    15. Muhammad Shafiullah & Sajid M. Chaudhry & Muhammad Shahbaz & Juan C. Reboredo, 2021. "Quantile causality and dependence between crude oil and precious metal prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6264-6280, October.
    16. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    17. Khalfaoui, Rabeh & Sarwar, Suleman & Tiwari, Aviral Kumar, 2019. "Analysing volatility spillover between the oil market and the stock market in oil-importing and oil-exporting countries: Implications on portfolio management," Resources Policy, Elsevier, vol. 62(C), pages 22-32.
    18. Herrera, Gabriel Paes & Constantino, Michel & Tabak, Benjamin Miranda & Pistori, Hemerson & Su, Jen-Je & Naranpanawa, Athula, 2019. "Long-term forecast of energy commodities price using machine learning," Energy, Elsevier, vol. 179(C), pages 214-221.
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