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Mean–variance optimization under affine GARCH: A utility-based solution

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  • Escobar-Anel, Marcos
  • Spies, Ben
  • Zagst, Rudi

Abstract

Affine GARCH models have recently been explored in the context of portfolio optimization, although in a quite narrow setting in terms of utility functions and risk aversion. This work notably extends existing results, accommodating a richer class of objective functions for a large family of GARCH models. In particular, our approach allows for connections to constant proportion portfolio insurance (CPPI) and mean–variance portfolio strategies. We explore the latter numerically based on S&P 500 market data, revealing that a GARCH model clearly outperforms a homoscedastic variant in terms of the efficient frontier.

Suggested Citation

  • Escobar-Anel, Marcos & Spies, Ben & Zagst, Rudi, 2024. "Mean–variance optimization under affine GARCH: A utility-based solution," Finance Research Letters, Elsevier, vol. 59(C).
    • Handle: RePEc:eee:finlet:v:59:y:2024:i:c:s1544612323011212
    DOI: 10.1016/j.frl.2023.104749
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    1. Christoffersen, Peter & Heston, Steve & Jacobs, Kris, 2006. "Option valuation with conditional skewness," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 253-284.
    2. Ornthanalai, Chayawat, 2014. "Lévy jump risk: Evidence from options and returns," Journal of Financial Economics, Elsevier, vol. 112(1), pages 69-90.
    3. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    4. Zhu, Yichen & Escobar-Anel, Marcos, 2022. "Polynomial affine approach to HARA utility maximization with applications to OrnsteinUhlenbeck 4/2 models," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    7. Escobar-Anel, Marcos & Gollart, Maximilian & Zagst, Rudi, 2022. "Closed-form portfolio optimization under GARCH models," Operations Research Perspectives, Elsevier, vol. 9(C).
    8. Alexandru Badescu & Zhenyu Cui & Juan-Pablo Ortega, 2019. "Closed-form variance swap prices under general affine GARCH models and their continuous-time limits," Annals of Operations Research, Springer, vol. 282(1), pages 27-57, November.
    9. Campbell Harvey & John Liechty & Merrill Liechty & Peter Muller, 2010. "Portfolio selection with higher moments," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 469-485.
    10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    11. Hongkai Cao & Alexandru Badescu & Zhenyu Cui & Sarath Kumar Jayaraman, 2020. "Valuation of VIX and target volatility options with affine GARCH models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(12), pages 1880-1917, December.
    12. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," The Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    13. Massimo Guidolin & Allan Timmermann, 2008. "International asset allocation under regime switching, skew, and kurtosis preferences," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 889-935, April.
    14. John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 433-495.
    15. Escobar-Anel, Marcos & Rastegari, Javad & Stentoft, Lars, 2020. "Affine multivariate GARCH models," Journal of Banking & Finance, Elsevier, vol. 118(C).
    16. Maciej Augustyniak & Alexandru Badescu, 2021. "On the computation of hedging strategies in affine GARCH models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 710-735, May.
    17. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    18. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François, 2023. "A discrete-time hedging framework with multiple factors and fat tails: On what matters," Journal of Econometrics, Elsevier, vol. 232(2), pages 416-444.
    19. Jun Liu, 2007. "Portfolio Selection in Stochastic Environments," The Review of Financial Studies, Society for Financial Studies, vol. 20(1), pages 1-39, January.
    20. Marcos Escobar-Anel & Ben Spies & Rudi Zagst, 2021. "Expected Utility Theory on General Affine GARCH Models," Applied Mathematical Finance, Taylor & Francis Journals, vol. 28(6), pages 477-507, November.
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    More about this item

    Keywords

    Dynamic portfolio optimization; Affine GARCH models; Mean–variance; Efficient frontier; HARA utility; CPPI strategy;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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