Crypto-assets portfolio optimization under the omega measure

Abstract

Crypto-currencies, or crypto-assets, represent a new class of investment assets. The traditional portfolio analysis approach of Markowitz is not appropriate for use with portfolios containing crypto-assets, as the model requires that the investor have a quadratic utility function or that the returns be normally distributed, which isn’t the case for crypto-assets. We develop a portfolio optimization model based on the Omega measure which is more comprehensive than the Markowitz model, and apply this to four crypto-asset investment portfolios by means of a numerical application. The results indicate that these portfolios should favor traditional market assets over crypto-assets. In the case of portfolios formed only by crypto-assets, there is no clear preference in favor of any crypto-asset in particular.

Acknowledgments

We thank Felipe Van de Sande Araújo for helpful suggestions in the literature review on crypto-currencies.

Notes

1 We thank the Editor in Chief for suggesting this proof

Additional information

Funding

This work was supported by the National Council for Scientific and Technological Development – CNPq Brazil (grant n° 305422/2014-6) and the Foundation for Research Support of the State of Rio de Janeiro (FAPERJ) (grant E-26/202.868/2018).

Notes on contributors

Javier Gutiérrez Castro

JAVIER GUTIÉRREZ CASTRO holds a PhD in Finance and a MSc. in Industrial Engineering from PUC-Rio and currently is a full-time Professor at the Department of Production and Systems Engineering at UFSC. He has extensive experience in economic and financial valuation of investment projects in oil, mining, electricity, port management, public-private partnerships and specialized consulting. His areas of expertise include corporate finance, valuation, real options, portfolio optimization, risk analysis, financial planning, project management and blockchain economics.

Edison Américo Huarsaya Tito

EDISON AMERICO HUARSAYA TITO holds a PhD and a MSc. in Electrical Engineering from PUC-Rio and currently is a Postdoctoral researcher at the IAG Business School at PUC-Rio. He has extensive industry experience in the petroleum sector, and his research interests include portfolio and risk management, blockchain economics and artificial intelligence.

Luiz Eduardo Teixeira Brandão

LUIZ EDUARDO T. BRANDÃO holds a PhD in Finance from PUC-Rio, and MSc. in Civil Engineering from Stanford University and a MBA from the Stanford Graduate School of Business. Dr. Brandão is currently an Associate Professor at the IAG Business School at PUC-Rio, Dean for Graduate Studies and a Class PQ 1D researcher at CNPq -National Council for Scientific and Technological Development. His research interests include real options, energy finance, blockchain economics and project risk management.

Leonardo Lima Gomes

LEONARDO LIMA GOMES holds a Ph.D and MSc. in Industrial Engineering and Finance from PUC-Rio), is an assistant professor at the IAG Business School at PUC-Rio. He has extensive industry experience in the energy sector, and his research interests include portfolio and risk management, blockchain economics, innovation, energy trading and market analysis for energy companies.