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2022 | OriginalPaper | Chapter

10. How to Incorporate Characteristics into the Portfolio Construction Process

Author : Tobias Glas

Published in: Asset Pricing and Investment Styles in Digital Assets

Publisher: Springer International Publishing

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Abstract

Recent studies (see Glas (J Altern Invest 22(1):96–113, 2019) among others, and the previous chapters of this book) have uncovered the first indications of characteristics which are able to describe and explain the cross-section of digital asset returns. The standard procedure in the asset pricing and investment styles literature to harvest such characteristic premia is to construct hedge portfolios based on a specific characteristic. In digital assets, however, short selling is almost impossible. Therefore, alternative (long-only) approaches that incorporate characteristics into the portfolio construction process are described for digital asset investors.

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previous chapter Risk Factors in Digital Assets

next chapter Are the Results Robust and Still Valid?

CME, CBOE, and Nasdaq are the only regulated exchanges (of importance for institutional investors) which introduced bitcoin futures in 2017.

Fernandez-Perez et al. (2019) also question the superiority of the integrated over a simple mix approach.

That, however, also depends on the chosen risk aversion γ.

The following formula only applies approximately for continuous returns.

Trading costs for digital assets amount to 0.25% for smaller investors at the cryptocurrency exchange Bitstamp (see “Unified fee schedule,” available at https://www.bitstamp.net/fee_schedule/, accessed 23 November, 2018) and 0.26% at Kraken (see “Fee schedule,” available at https://www.kraken.com/en-us/help/fees, accessed 23 November, 2018). Since institutional investors with higher trading volume would normally not be placed in such a fee tier, I assume very conservative transaction costs of 0.25% per trade.

The following equations are reproduced in a slightly adjusted form from Fieberg et al. (2016a) and Brandt et al. (2009). These studies also applied a relative risk aversion (γ) value of 5.

For more information, see Chaps. 5, 8, and 9.

I also ran the same analysis with other datasets, as described in the next chapter.

See “1-Month Treasury Constant Maturity Rate,” available at https://fred.stlouisfed.org/series/DGS1MO#0, accessed 27 November, 2018.

For more information regarding the Jensen’s alpha regression, see Sect. 2.1.2.

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Title: How to Incorporate Characteristics into the Portfolio Construction Process
Author: Tobias Glas
Publisher: Springer International Publishing
Book: Asset Pricing and Investment Styles in Digital Assets
Print ISBN: 978-3-030-95694-3

Electronic ISBN: 978-3-030-95695-0

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-3-030-95695-0_10