Economic Evaluation of Cryptocurrency Investment

Ryuta Sakemoto

MPRA Paper from University Library of Munich, Germany

Abstract: This study proposes a method to enhance cryptocurrency portfolios constructed by forecast models. This study forecasts returns on four liquid cryptocurrencies (Bitcoin, Litecoin, Ripple, and Dash) and determines the weights on the cryptocurrencies based upon a dynamic allocation framework. We assess the performances of the portfolios using the performance fee measure. Our results present that the proposed portfolios outperform the benchmark portfolio with the conventional level of the risk aversion parameter. The economic gain for an investor is equivalent to 12% per week. The economic gain is sensitive to a change in the risk aversion parameter, which contrasts with the studies of exchange rates which is due to the high volatility on the cryptocurrencies. Our predictors are related to the price momentum effects and they outperform widely used network factors.

Keywords: Cryptocurrency; Bitcoin; Portfolio evaluation; Forecast model; Risk aversion (search for similar items in EconPapers)
JEL-codes: G10 G11 G17 (search for similar items in EconPapers)
Date: 2021-06-13
New Economics Papers: this item is included in nep-cwa, nep-pay and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/108283/1/MPRA_paper_108283.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:108283

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().