IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1811.02382.html
   My bibliography  Save this paper

Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures

Author

Listed:
  • Hayette Gatfaoui

Abstract

Energy markets are strategic to governments and economic development. Several commodities compete as substitutable energy sources and energy diversifiers. Such competition reduces the energy vulnerability of countries as well as portfolios' risk exposure. Vulnerability results mainly from price trends and fluctuations, following supply and demand shocks. Such energy price uncertainty attracts many market participants in the energy commodity markets. First, energy producers and consumers hedge adverse price changes with energy derivatives. Second, financial market participants use commodities and commodity derivatives to diversify their conventional portfolios. For that reason, we consider the joint dependence between the United States (U.S.) natural gas, crude oil and stock markets. We use Gatfaoui's (2015) time varying multivariate copula analysis and related variance regimes. Such approach handles structural changes in asset prices. In this light, we draw implications for portfolio optimization, when investors diversify their stock portfolios with natural gas and crude oil assets. We minimize the portfolio's variance, semi-variance and tail risk, in the presence and the absence of constraints on the portfolio's expected return and/or U.S. stock investment. The return constraint reduces the performance of the optimal portfolio. Moreover, the regime-specific portfolio optimization helps implement an enhanced active management strategy over the whole sample period. Under a return constraint, the semi-variance optimal portfolio offers the best risk-return tradeoff, whereas the tail-risk optimal portfolio offers the best tradeoff in the absence of a return constraint.

Suggested Citation

  • Hayette Gatfaoui, 2018. "Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures," Papers 1811.02382, arXiv.org.
  • Handle: RePEc:arx:papers:1811.02382
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1811.02382
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Y. Malevergne & D. Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Quantitative Finance, Taylor & Francis Journals, vol. 3(4), pages 231-250.
    2. Kevin Dowd & David Blake, 2006. "After VaR: The Theory, Estimation, and Insurance Applications of Quantile‐Based Risk Measures," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(2), pages 193-229, June.
    3. Unser, Matthias, 2000. "Lower partial moments as measures of perceived risk: An experimental study," Journal of Economic Psychology, Elsevier, vol. 21(3), pages 253-280, June.
    4. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    5. Julien Chevallier & Mathieu Gatumel & Florian Ielpo, 2014. "Commodity markets through the business cycle," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1597-1618, September.
    6. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    7. Lutz Kilian & Cheolbeom Park, 2009. "The Impact Of Oil Price Shocks On The U.S. Stock Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(4), pages 1267-1287, November.
    8. Dietrich Domanski & Alexandra Heath, 2007. "Financial investors and commodity markets," BIS Quarterly Review, Bank for International Settlements, March.
    9. Julien Chevallier & Florian Ielpo, 2013. "The Economics of Commodity Markets," Post-Print hal-02879507, HAL.
    10. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    11. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521896955, October.
    12. Hayette Gatfaoui, 2010. "Investigating the dependence structure between credit default swap spreads and the U.S. financial market," Annals of Finance, Springer, vol. 6(4), pages 511-535, October.
    13. Yanbo Jin & Philippe Jorion, 2006. "Firm Value and Hedging: Evidence from U.S. Oil and Gas Producers," Journal of Finance, American Finance Association, vol. 61(2), pages 893-919, April.
    14. Peter R. Hartley and Kenneth B. Medlock III, 2014. "The Relationship between Crude Oil and Natural Gas Prices: The Role of the Exchange Rate," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    15. Karolyi, G. Andrew & Lee, Kuan-Hui & van Dijk, Mathijs A., 2012. "Understanding commonality in liquidity around the world," Journal of Financial Economics, Elsevier, vol. 105(1), pages 82-112.
    16. Cheung, C. Sherman & Miu, Peter, 2010. "Diversification benefits of commodity futures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 451-474, December.
    17. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    18. Robert B. Barsky & Lutz Kilian, 2004. "Oil and the Macroeconomy Since the 1970s," Journal of Economic Perspectives, American Economic Association, vol. 18(4), pages 115-134, Fall.
    19. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    20. James D. Hamilton, 1985. "Historical Causes of Postwar Oil Shocks and Recessions," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 97-116.
    21. Frans A. De Roon & Theo E. Nijman & Chris Veld, 2000. "Hedging Pressure Effects in Futures Markets," Journal of Finance, American Finance Association, vol. 55(3), pages 1437-1456, June.
    22. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    23. Miller, J. Isaac & Ratti, Ronald A., 2009. "Crude oil and stock markets: Stability, instability, and bubbles," Energy Economics, Elsevier, vol. 31(4), pages 559-568, July.
    24. John Parsons, 2010. "Black Gold and Fool’s Gold: Speculation in the Oil Futures Market," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 81-116, January.
    25. Gatfaoui, Hayette, 2016. "Linking the gas and oil markets with the stock market: Investigating the U.S. relationship," Energy Economics, Elsevier, vol. 53(C), pages 5-16.
    26. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Dependence and extreme dependence of crude oil and natural gas prices with applications to risk management," Energy Economics, Elsevier, vol. 42(C), pages 332-342.
    27. Stephen P. A. Brown & Mine K. Yucel, 2008. "What Drives Natural Gas Prices?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 45-60.
    28. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    29. David J. Ramberg and John E. Parsons, 2012. "The Weak Tie Between Natural Gas and Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    30. Gerald R. Jensen & Robert R. Johnson & Jeffrey M. Mercer, 2000. "Efficient use of commodity futures in diversified portfolios," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(5), pages 489-506, May.
    31. Zhongjun Qu & Pierre Perron, 2007. "Estimating and Testing Structural Changes in Multivariate Regressions," Econometrica, Econometric Society, vol. 75(2), pages 459-502, March.
    32. Todd Mitton & Keith Vorkink, 2007. "Equilibrium Underdiversification and the Preference for Skewness," Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1255-1288.
    33. Jushan Bai & Pierre Perron, 2003. "Critical values for multiple structural change tests," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 72-78, June.
    34. Brigida, Matthew, 2014. "The switching relationship between natural gas and crude oil prices," Energy Economics, Elsevier, vol. 43(C), pages 48-55.
    35. Buckley, Ian & Saunders, David & Seco, Luis, 2008. "Portfolio optimization when asset returns have the Gaussian mixture distribution," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1434-1461, March.
    36. Kim, Min Jae & Kim, Sehyun & Jo, Yong Hwan & Kim, Soo Yong, 2011. "Dependence structure of the commodity and stock markets, and relevant multi-spread strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3842-3854.
    37. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    38. Paul A. Samuelson, 1970. "The Fundamental Approximation Theorem of Portfolio Analysis in terms of Means, Variances and Higher Moments," Review of Economic Studies, Oxford University Press, vol. 37(4), pages 537-542.
    39. Fulga, Cristinca, 2016. "Portfolio optimization under loss aversion," European Journal of Operational Research, Elsevier, vol. 251(1), pages 310-322.
    40. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    41. Conlon, Thomas & Cotter, John, 2013. "Downside risk and the energy hedger's horizon," Energy Economics, Elsevier, vol. 36(C), pages 371-379.
    42. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    43. Kraus, Alan & Litzenberger, Robert H, 1976. "Skewness Preference and the Valuation of Risk Assets," Journal of Finance, American Finance Association, vol. 31(4), pages 1085-1100, September.
    44. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    45. Kakouris, Iakovos & Rustem, Berç, 2014. "Robust portfolio optimization with copulas," European Journal of Operational Research, Elsevier, vol. 235(1), pages 28-37.
    46. Mathieu Gatumel & Florian Ielpo, 2014. "Commodity Markets through the business cycle," Post-Print hal-01302479, HAL.
    47. Robert Jarrow & Feng Zhao, 2006. "Downside Loss Aversion and Portfolio Management," Management Science, INFORMS, vol. 52(4), pages 558-566, April.
    48. Michał Falkowski, 2011. "Financialization of commodities," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 5(4), December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    2. Zhou, Wei & Chen, Yan & Chen, Jin, 2022. "Risk spread in multiple energy markets: Extreme volatility spillover network analysis before and during the COVID-19 pandemic," Energy, Elsevier, vol. 256(C).
    3. Ma, Yilin & Wang, Yudong & Wang, Weizhong & Zhang, Chong, 2023. "Portfolios with return and volatility prediction for the energy stock market," Energy, Elsevier, vol. 270(C).
    4. Wei, Zhaohao & Chai, Jian & Dong, Jichang & Lu, Quanying, 2022. "Understanding the linkage-dependence structure between oil and gas markets: A new perspective," Energy, Elsevier, vol. 257(C).
    5. Goodell, John W. & Gurdgiev, Constantin & Paltrinieri, Andrea & Piserà, Stefano, 2023. "Global energy supply risk: Evidence from the reactions of European natural gas futures to Nord Stream announcements," Energy Economics, Elsevier, vol. 125(C).
    6. Giovanni Masala & Filippo Petroni, 2023. "Drawdown risk measures for asset portfolios with high frequency data," Annals of Finance, Springer, vol. 19(2), pages 265-289, June.
    7. Chen, Chen & Liu, Dinghao & Xian, Liang & Pan, Lin & Wang, Lihua & Yang, Min & Quan, Li, 2020. "Best-case scenario robust portfolio for energy stock market," Energy, Elsevier, vol. 213(C).
    8. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
    9. Su, Kuangxi & Yao, Yinhong & Zheng, Chengli & Xie, Wenzhao, 2023. "A novel hybrid strategy for crude oil future hedging based on the combination of three minimum-CVaR models," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 35-50.
    10. Donia Aloui & Stéphane Goutte & Khaled Guesmi & Rafla Hchaichi, 2020. "COVID 19's impact on crude oil and natural gas S&P GS Indexes," Working Papers halshs-02613280, HAL.
    11. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    12. John Weirstrass Muteba Mwamba & Sutene Mwambetania Mwambi, 2021. "Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula," IJFS, MDPI, vol. 9(2), pages 1-22, May.
    13. Mazin A.M. Al Janabi, 2021. "Is optimum always optimal? A revisit of the mean‐variance method under nonlinear measures of dependence and non‐normal liquidity constraints," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 387-415, April.
    14. Lu Wang & Ferhana Ahmad & Gong-li Luo & Muhammad Umar & Dervis Kirikkaleli, 2022. "Portfolio optimization of financial commodities with energy futures," Annals of Operations Research, Springer, vol. 313(1), pages 401-439, June.
    15. Naeem, Muhammad Abubakr & Karim, Sitara & Hasan, Mudassar & Lucey, Brian M. & Kang, Sang Hoon, 2022. "Nexus between oil shocks and agriculture commodities: Evidence from time and frequency domain," Energy Economics, Elsevier, vol. 112(C).
    16. Ahmed, Maruf Yakubu & Sarkodie, Samuel Asumadu, 2021. "Counterfactual shock in energy commodities affects stock market dynamics: Evidence from the United States," Resources Policy, Elsevier, vol. 72(C).
    17. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Shao, Xuefeng & Le, TN-Lan & Gyamfi, Matthew Ntow, 2023. "Financial technology stocks, green financial assets, and energy markets: A quantile causality and dependence analysis," Energy Economics, Elsevier, vol. 118(C).
    18. Algieri, Bernardina & Leccadito, Arturo, 2019. "Ask CARL: Forecasting tail probabilities for energy commodities," Energy Economics, Elsevier, vol. 84(C).
    19. Stoupos, Nikolaos & Kiohos, Apostolos, 2021. "Energy commodities and advanced stock markets: A post-crisis approach," Resources Policy, Elsevier, vol. 70(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gatfaoui, Hayette, 2016. "Linking the gas and oil markets with the stock market: Investigating the U.S. relationship," Energy Economics, Elsevier, vol. 53(C), pages 5-16.
    2. Hailemariam, Abebe & Smyth, Russell, 2019. "What drives volatility in natural gas prices?," Energy Economics, Elsevier, vol. 80(C), pages 731-742.
    3. Emmanuel Jurczenko & Bertrand Maillet & Paul Merlin, 2008. "Efficient Frontier for Robust Higher-order Moment Portfolio Selection," Post-Print halshs-00336475, HAL.
    4. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    5. Hadhri, Sinda & Ftiti, Zied, 2019. "Asset allocation and investment opportunities in emerging stock markets: Evidence from return asymmetry-based analysis," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 187-200.
    6. Ali, Sajid & Raza, Naveed & Vinh Vo, Xuan & Le, Van, 2022. "Modelling the joint dynamics of financial assets using MGARCH family models: Insights into hedging and diversification strategies," Resources Policy, Elsevier, vol. 78(C).
    7. Ahmed, Walid M.A., 2020. "Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin," Journal of Economics and Business, Elsevier, vol. 108(C).
    8. Lambert, M. & Hübner, G., 2013. "Comoment risk and stock returns," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 191-205.
    9. Mo, Xuan & Su, Zhi & Yin, Libo, 2019. "Can the skewness of oil returns affect stock returns? Evidence from China’s A-Share markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    10. Jang, Jeewon & Kang, Jangkoo, 2017. "An intertemporal CAPM with higher-order moments," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 314-337.
    11. Wang, TianTian & Zhang, Dayong & Clive Broadstock, David, 2019. "Financialization, fundamentals, and the time-varying determinants of US natural gas prices," Energy Economics, Elsevier, vol. 80(C), pages 707-719.
    12. Charfeddine, Lanouar & Benlagha, Noureddine, 2016. "A time-varying copula approach for modelling dependency: New evidence from commodity and stock markets," Journal of Multinational Financial Management, Elsevier, vol. 37, pages 168-189.
    13. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
    14. Drachal, Krzysztof, 2018. "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, vol. 74(C), pages 208-251.
    15. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
    16. Fan, Ying & Xu, Jin-Hua, 2011. "What has driven oil prices since 2000? A structural change perspective," Energy Economics, Elsevier, vol. 33(6), pages 1082-1094.
    17. Broadstock, David C. & Filis, George, 2014. "Oil price shocks and stock market returns: New evidence from the United States and China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 417-433.
    18. Annaert, Jan & De Ceuster, Marc & Van Cappellen, Jef, 2023. "Can average skewness really predict financial returns? The euro area case," Finance Research Letters, Elsevier, vol. 52(C).
    19. Duc Khuong Nguyen & Nikolas Topaloglou & Thomas Walther, 2020. "Asset Classes and Portfolio Diversification: Evidence from a Stochastic Spanning Approach," Working Papers 2020-009, Department of Research, Ipag Business School.
    20. Ayadi, Mohamed A. & Cao, Xu & Lazrak, Skander & Wang, Yan, 2019. "Do idiosyncratic skewness and kurtosis really matter?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).

    More about this item

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1811.02382. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.