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Closed-form portfolio optimization under GARCH models

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  • Marcos Escobar-Anel
  • Maximilian Gollart
  • Rudi Zagst

Abstract

This paper develops the first closed-form optimal portfolio allocation formula for a spot asset whose variance follows a GARCH(1,1) process. We consider an investor with constant relative risk aversion (CRRA) utility who wants to maximize the expected utility from terminal wealth under a Heston and Nandi (2000) GARCH (HN-GARCH) model. We obtain closed formulas for the optimal investment strategy, the value function and the optimal terminal wealth. We find the optimal strategy is independent of the development of the risky asset, and the solution converges to that of a continuous-time Heston stochastic volatility model, albeit under additional conditions. For a daily trading scenario, the optimal solutions are quite robust to variations in the parameters, while the numerical wealth equivalent loss (WEL) analysis shows good performance of the Heston solution, with a quite inferior performance of the Merton solution.

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  • Marcos Escobar-Anel & Maximilian Gollart & Rudi Zagst, 2021. "Closed-form portfolio optimization under GARCH models," Papers 2109.00433, arXiv.org.
    • Handle: RePEc:arx:papers:2109.00433
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    Cited by:

    1. 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).
    2. Marcos Escobar-Anel & Ben Spies & Rudi Zagst, 2024. "Optimal consumption and investment in general affine GARCH models," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(3), pages 987-1026, September.
    3. Marcos Escobar-Anel & Eric Molter & Rudi Zagst, 2024. "The power of derivatives in portfolio optimization under affine GARCH models," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 47(1), pages 151-181, June.

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    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics

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