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Mean-variance optimization under affine GARCH: A utility-based solution
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DOI：10.1016/j.frl.2023.104749.png)
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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.
Keyword:
Dynamic portfolio optimization Affine GARCH models Mean-variance Efficient frontier HARA utility CPPI strategy
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6.9
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