Portfolio management with cryptocurrencies: The role of estimation risk

By Emmanouil Platanakis, Andrew Urquhart. Economics Letters, 2019

131 citations recorded by the source corpus.

This paper contributes to the literature on cryptocurrencies, portfolio management and estimation risk by comparing the performance of naive 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.

Subfields: Economics and Econometrics, Finance, Information Systems

View Paper: https://www.semanticscholar.org/paper/c6738f89bb1df67574fa55f6ebe3fd850e66d81c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

  1. Emmanouil Platanakis
  2. Andrew Urquhart
  3. Paraskevi Katsiampa
  4. Pengfei Wang
  5. Dehua Shen
  6. Tetsuya Takaishi
  7. Ahmet Sensoy
  8. Aurelio Fernández Bariviera

In Finance

  1. Andrew Urquhart
  2. Emmanouil Platanakis

In Information Systems

  1. Emmanouil Platanakis
  2. Andrew Urquhart
  3. Paraskevi Katsiampa
  4. Pengfei Wang
  5. Dehua Shen
  6. Tetsuya Takaishi
  7. Ahmet Sensoy
  8. Aurelio Fernández Bariviera

Citations in the corpus