IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v12y2024i5p75-d1387035.html
   My bibliography  Save this article

Analyzing the Influence of Risk Models and Investor Risk-Aversion Disparity on Portfolio Selection in Community Solar Projects: A Comparative Case Study

Author

Listed:
  • Mahmoud Shakouri

    (Department of Construction Management, Colorado State University, Fort Collins, CO 80523, USA)

  • Chukwuma Nnaji

    (Department of Construction Science, Texas A&M University, College Station, TX 77843-3337, USA)

  • Saeed Banihashemi

    (School of Built Environment, Faculty of Design, Architecture, and Building, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia)

  • Khoung Le Nguyen

    (School of Design and Built Environment, University of Canberra, Canberra 2617, Australia)

Abstract

This study examines the impact of risk models and investors’ risk aversion on the selection of community solar portfolios. Various risk models to account for the volatility in the electrical power output of community solar, namely variance (Var), SemiVariance (SemiVar), mean absolute deviation (MAD), and conditional value at risk (CVaR), were considered. A statistical model based on modern portfolio theory was employed to simulate investors’ risk aversion in the context of community solar portfolio selection. The results of this study showed that the choice of risk model that aligns with investors’ risk-aversion level plays a key role in realizing more return and safeguarding against volatility in power generation. In particular, the findings of this research revealed that the CVaR model provides higher returns at the cost of greater volatility in power generation compared to other risk models. In contrast, the MAD model offered a better tradeoff between risk and return, which can appeal more to risk-averse investors. Based on the simulation results, a new approach was proposed for optimizing the portfolio selection process for investors with divergent risk-aversion levels by averaging the utility functions of investors and identifying the most probable outcome.

Suggested Citation

  • Mahmoud Shakouri & Chukwuma Nnaji & Saeed Banihashemi & Khoung Le Nguyen, 2024. "Analyzing the Influence of Risk Models and Investor Risk-Aversion Disparity on Portfolio Selection in Community Solar Projects: A Comparative Case Study," Risks, MDPI, vol. 12(5), pages 1-16, April.
  • Handle: RePEc:gam:jrisks:v:12:y:2024:i:5:p:75-:d:1387035
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/12/5/75/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-9091/12/5/75/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 9-51.
    2. Dusonchet, Luigi & Telaretti, Enrico, 2010. "Economic analysis of different supporting policies for the production of electrical energy by solar photovoltaics in western European Union countries," Energy Policy, Elsevier, vol. 38(7), pages 3297-3308, July.
    Full references (including those not matched with items on IDEAS)

    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. Thomas F. Crossley & Hamish W. Low, 2011. "Is The Elasticity Of Intertemporal Substitution Constant?," Journal of the European Economic Association, European Economic Association, vol. 9(1), pages 87-105, February.
    2. Marins, Jaqueline Terra Moura & Vicente, José Valentim Machado, 2017. "Do the central bank actions reduce interest rate volatility?," Economic Modelling, Elsevier, vol. 65(C), pages 129-137.
    3. Damian S. Damianov & Diego Escobari, 2021. "Getting on and Moving Up the Property Ladder: Real Hedging in the U.S. Housing Market Before and After the Crisis," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(4), pages 1201-1237, December.
    4. Jurczenko, Emmanuel & Maillet, Bertrand & Negrea, Bogdan, 2002. "Revisited multi-moment approximate option pricing models: a general comparison (Part 1)," LSE Research Online Documents on Economics 24950, London School of Economics and Political Science, LSE Library.
    5. Christoffersen, Peter & Heston, Steven & Jacobs, Kris, 2010. "Option Anomalies and the Pricing Kernel," Working Papers 11-17, University of Pennsylvania, Wharton School, Weiss Center.
    6. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.
    7. repec:dau:papers:123456789/56 is not listed on IDEAS
    8. Lüders, Erik & Lüders-Amann, Inge & Schröder, Michael, 2004. "The Power Law and Dividend Yields," ZEW Discussion Papers 04-51, ZEW - Leibniz Centre for European Economic Research.
    9. Carole Bernard & Oleg Bondarenko & Steven Vanduffel, 2021. "A model-free approach to multivariate option pricing," Review of Derivatives Research, Springer, vol. 24(2), pages 135-155, July.
    10. Gobong Choi & Eunnyeong Heo & Chul-Yong Lee, 2018. "Dynamic Economic Analysis of Subsidies for New and Renewable Energy in South Korea," Sustainability, MDPI, vol. 10(6), pages 1-19, June.
    11. Ricardo Crisóstomo, 2021. "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1797-1823, November.
    12. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    13. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    14. Jaroslav Borovička & Lars Peter Hansen & José A. Scheinkman, 2016. "Misspecified Recovery," Journal of Finance, American Finance Association, vol. 71(6), pages 2493-2544, December.
    15. Guégan, Dominique & Ielpo, Florian & Lalaharison, Hanjarivo, 2013. "Option pricing with discrete time jump processes," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2417-2445.
    16. David Backus & Mikhail Chernov & Ian Martin, 2011. "Disasters Implied by Equity Index Options," Journal of Finance, American Finance Association, vol. 66(6), pages 1969-2012, December.
    17. Boris Ter-Avanesov & Homayoon Beigi, 2024. "MLP, XGBoost, KAN, TDNN, and LSTM-GRU Hybrid RNN with Attention for SPX and NDX European Call Option Pricing," Papers 2409.06724, arXiv.org, revised Oct 2024.
    18. Jan K. Kazak & Joanna A. Kamińska & Rafał Madej & Marta Bochenkiewicz, 2020. "Where Renewable Energy Sources Funds are Invested? Spatial Analysis of Energy Production Potential and Public Support," Energies, MDPI, vol. 13(21), pages 1-26, October.
    19. Haghi, Ehsan & Raahemifar, Kaamran & Fowler, Michael, 2018. "Investigating the effect of renewable energy incentives and hydrogen storage on advantages of stakeholders in a microgrid," Energy Policy, Elsevier, vol. 113(C), pages 206-222.
    20. Jens Hilscher & Alon Raviv & Ricardo Reis, 2022. "Inflating Away the Public Debt? An Empirical Assessment," The Review of Financial Studies, Society for Financial Studies, vol. 35(3), pages 1553-1595.
    21. Thomas F. Crossley & Hamish W. Low, 2005. "Unexploited Connections Between Intra- and Inter-temporal Allocation," Social and Economic Dimensions of an Aging Population Research Papers 131, McMaster University.

    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:gam:jrisks:v:12:y:2024:i:5:p:75-:d:1387035. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.