Publication: Shrinking in COMFORT
Shrinking in COMFORT
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Hediger, S., & Näf, J. (2022). Shrinking in COMFORT (No. 4069441; SSRN). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4069441
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The present paper combines nonlinear shrinkage with the Multivariate Generalized Hyperbolic (MGHyp) distribution to account for heavy tails in estimating the first and second moments in high dimensions. An Expectation-Maximization (EM) algorithm is developed that is fast, stable, and applicable in high dimensions. Theoretical arguments for the monotonicity of the proposed algorithm are provided and it is shown in simulations that it is able to accurately retrieve parameter estimates. Finally, in an extensive Markowitz portfolio optimi
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Hediger, S., & Näf, J. (2022). Shrinking in COMFORT (No. 4069441; SSRN). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4069441
