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Portfolio management with cryptocurrencies: The role of estimation risk

Emmanouil Platanakis and Andrew Urquhart

Economics Letters, 2019, vol. 177, issue C, 76-80

Abstract: This paper contributes to the literature on cryptocurrencies, portfolio management and estimation risk by comparing the performance of naïve diversification, Markowitz diversification and the advanced Black–Litterman model with VBCs that controls for estimation errors in a portfolio of cryptocurrencies. We show that the advanced Black–Litterman model with VBCs yields superior out-of-sample risk-adjusted returns as well as lower risks. Our results are robust to the inclusion of transaction costs and short-selling, indicating that sophisticated portfolio techniques that control for estimation errors are preferred when managing cryptocurrency portfolios.

Keywords: Cryptocurrencies; Estimation errors; Portfolio optimization (search for similar items in EconPapers)
JEL-codes: G1 G11 G2 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (58)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:177:y:2019:i:c:p:76-80

DOI: 10.1016/j.econlet.2019.01.019

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