Risk-adjusted performance, performance persistence, and portfolio diversification of multi-crypto exchange-traded products

Authors

DOI:

https://doi.org/10.26905/afr.v9i2.17399

Keywords:

Cryptocurrency exchange-traded products, Performance persistence, Portfolio diversification, Risk-adjusted performance, Walk-forward backtesting

Abstract

The proliferation of cryptocurrency-based exchange-traded products (ETPs) presents investors with a product-selection and portfolio-allocation challenge that the existing literature has examined only partially. This study constructs an exploratory, integrated four-stage investor-facing framework, including: risk-adjusted performance, out-of-sample persistence, cross-asset positioning, and portfolio diversification. The framework was applied to fifteen multi-crypto ETPs spanning Canada, Switzerland, the United States, and Brazil over 1 June 2022 to 31 December 2025. The performance varies; annual returns ranged from −34.68% to 46.24% and rankings shift materially when downside-risk metrics were applied. The persistence evidence is statistically insignificant; the Top-minus-Bottom spread is 0.64% per month (Newey-West t = 0.63), implying that historical alpha has limited predictive value. The ETPs occupy a distinct risk–return profile relative to BTC, ETH, gold, and the domestic equity index. In the portfolio stage, a 10% BTC sleeve shows the largest improvement in which the annualized return of +4.00%, Sharpe +0.253, with stable volatility and improved downside, thus combining a return effect and a diversification effect. A diversified ETP sleeve provides the most convincing ETP-based alternative, consistently outperforming a single-product sleeve on risk-adjusted metrics and turnover. The explained advantage widens once transaction costs are applied. Ultimately, the value of cryptocurrency exposure is conditional, depending on instrument form, allocation size, and investor access to spot assets.

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References

Adrian, T., Iyer, T., & Qureshi, M. S. (2022, January 11). Crypto prices move more in sync with stocks, posing new risks [Internet]. International Monetary Fund (IMF) Blog. Retrieved from: https://www.imf.org/en/Blogs/Articles/2022/01/11/crypto-prices-move-more-in-sync-with-stocks-posing-new-risks

Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177-189. https://doi.org/10.1016/j.intfin.2017.12.004

Baur, D. G., & Lucey, B. M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), 217-229. https://doi.org/10.1111/j.1540-6288.2010.00244.x

Bianchi, D., & Babiak, M. (2022). On the performance of cryptocurrency funds. Journal of Banking & Finance, 138, 106467. https://doi.org/10.1016/j.jbankfin.2022.106467

Conlon, T., De Mingo‐López, D. V., & Urquhart, A. (2025). Persistence and market timing ability of cryptocurrency funds. Financial Management, 54(4), 791-816. https://doi.org/10.1111/fima.12498

DeMiguel, V., Garlappi, L., & Uppal, R. (2009). Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy? The Review of Financial Studies, 22(5), 1915–1953. https://doi.org/10.1093/rfs/hhm075

Eling, M., & Schuhmacher, F. (2007). Does the choice of performance measure influence the evaluation of hedge funds? Journal of Banking & Finance, 31(9), 2632-2647. https://doi.org/10.1016/j.jbankfin.2006.09.015

Elton, E. J., Gruber, M. J., & Blake, C. R. (1996). The persistence of risk-adjusted mutual fund performance. The Journal of Business, 69(2), 133–157.

ETFGI. (2025, December 31). Crypto ETFs listed globally suffered net outflows of US$2.95 billion in November according to new research by ETFGI [Internet]. ETFGI. Retrieved from: https://etfgi.com/news/press-releases/2025/12/crypto-etfs-listed-globally-suffered-net-outflows-us295-billion

FASB. (2023). Accounting Standards Update No. 2023-08—Intangibles—Goodwill and Other—Crypto Assets (Subtopic 350-60): Accounting for and disclosure of crypto assets. Financial Accounting Standards Board.

Han, W., Newton, D., Platanakis, E., Wu, H., & Xiao, L. (2024). The diversification benefits of cryptocurrency factor portfolios: Are they there? Review of Quantitative Finance and Accounting, 63(2), 469-518. https://doi.org/10.1007/s11156-024-01260-w

IFRS Interpretations Committee. (2019). Holdings of cryptocurrencies—Agenda decision. IFRS Foundation.

Jorion, P. (2001). Value at risk: The new benchmark for managing financial risk (2nd ed.). McGraw-Hill.

Keating, C., & Shadwick, W. F. (2002). A universal performance measure. Journal of Performance Measurement, 6(3), 59-84.

Krückeberg, S., & Scholz, P. (2019). Cryptocurrencies as an asset class. In S. Goutte, K. Guesmi, & S. Saadi (Eds.), Cryptofinance and mechanisms of exchange: The making of virtual currency. Springer. https://doi.org/10.1007/978-3-030-30738-7_1

Liu, Y., Tsyvinski, A., & Wu, X. (2022). Common risk factors in cryptocurrency. The Journal of Finance, 77(2), 1133-1177. https://doi.org/10.1111/jofi.13119

Magdon-Ismail, M., Atiya, A. F., Pratap, A., & Abu-Mostafa, Y. S. (2004). On the maximum drawdown of a Brownian motion. Journal of Applied Probability, 41(1), 147-161. https://doi.org/10.1239/jap/1077134674

Malhotra, D. K. (2025). Deciphering digital assets exchange-traded funds: Correlations, contradictions, and systematic influences. Journal of Asset Management, 26(6), 567-578. https://doi.org/10.1057/s41260-025-00426-y

Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x

Muvunza, T. (2020). An alpha-stable approach to modelling highly speculative assets and cryptocurrencies. ArXiv. https://doi.org/10.48550/arXiv.2002.09881

Newey, W. K., & West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–708. https://doi.org/10.2307/1913610

Rockafellar, R. T., & Uryasev, S. (2002). Conditional value-at-risk for general loss distributions. Journal of Banking & Finance, 26(7), 1443-1471. https://doi.org/10.1016/S0378-4266(02)00271-6

S&P Dow Jones Indices. (2025). S&P cryptocurrency Broad Digital Asset (BDA) index. S&P Global.

Sharpe, W. F. (1994). The Sharpe ratio. The Journal of Portfolio Management, 21(1), 49–58. https://doi.org/10.3905/jpm.1994.409501

SIX. (2025, April 2). No crypto ETFs in Europe? Why Swiss ETPs are the solution [Internet]. SIX. Retrieved from: https://www.six-group.com/en/blog/etps-on-crypto.html

Sortino, F. A., & van der Meer, R. (1991). Downside risk. The Journal of Portfolio Management, 17(4), 27–31. https://doi.org/10.3905/jpm.1991.409343

Tang, H., Xie, K., & Xu, X. E. (2025). Cryptocurrency ETFs vs. nonredeemable investment trusts: An in-depth analysis. International Review of Economics & Finance, 102, 104264. https://doi.org/10.1016/j.iref.2025.104264

Tsay, R. S. (2010). Analysis of Financial Time Series (3rd ed.). John Wiley & Sons.

Additional Files

Published

2026-09-18

How to Cite

Putra, G. K., & Adi Ekaputra, I. (2026). Risk-adjusted performance, performance persistence, and portfolio diversification of multi-crypto exchange-traded products. AFRE (Accounting and Financial Review), 9(2), 249–273. https://doi.org/10.26905/afr.v9i2.17399

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