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Optimal and Naive Diversification in Currency Markets

Author

Listed:
  • Fabian Ackermann

    (Zurcher Kantonalbank)

  • Walt Pohl

    (University of Zurich)

  • Karl Schmedders

    (University of Zurich)

Abstract

DeMiguel, Garlappi, and Uppal (Review of Financial Studies, 22 (2009), 1915-1953) showed that in the stock market, it is difficult for an optimized portfolio constructed using mean-variance analysis to outperform a simple equally-weighted portfolio because of estimation error. In this paper, we demonstrate that portfolio optimization can be made to work in currency markets. The key difference between the two settings is that in currency markets interest rates provide a predictor of future returns that is free of estimation error, which permits the application of mean-variance analysis. We show that over the last 26 years, a mean-variance efficient portfolio constructed in this fashion has a Sharpe ratio of 0.91, versus only 0.15 for the equally-weighted portfolio. We also consider the practical implementation of this strategy.

Suggested Citation

  • Fabian Ackermann & Walt Pohl & Karl Schmedders, 2012. "Optimal and Naive Diversification in Currency Markets," Swiss Finance Institute Research Paper Series 12-36, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1236
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    Cited by:

    1. Cheng Yan & Ji Yan, 2021. "Optimal and naive diversification in an emerging market: Evidence from China's A‐shares market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3740-3758, July.
    2. Gelmini, Matteo & Uberti, Pierpaolo, 2024. "The equally weighted portfolio still remains a challenging benchmark," International Economics, Elsevier, vol. 179(C).
    3. Heming Chen & Xiaojing Cai, 2025. "Optimal vs. Naive Diversification in the Cryptocurrencies Market: The Role of Time-Varying Moments and Transaction Costs," Papers 2501.12841, arXiv.org, revised Nov 2025.
    4. Walter Bazán-Palomino & Diego Winkelried, 2021. "FX markets’ reactions to COVID-19: Are they different?," International Economics, CEPII research center, issue 167, pages 50-58.
    5. Mikhail Chernov & Magnus Dahlquist & Lars Lochstoer, 2023. "Pricing Currency Risks," Journal of Finance, American Finance Association, vol. 78(2), pages 693-730, April.
    6. Platanakis, Emmanouil & Sutcliffe, Charles & Urquhart, Andrew, 2018. "Optimal vs naïve diversification in cryptocurrencies," Economics Letters, Elsevier, vol. 171(C), pages 93-96.
    7. Hafner, Christian & Herwartz, Helmut, 2020. "Dynamic score driven independent component analysis," LIDAM Discussion Papers ISBA 2020031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Joscha Beckmann & Gary Koop & Dimitris Korobilis & Rainer Alexander Schüssler, 2020. "Exchange rate predictability and dynamic Bayesian learning," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 410-421, June.
    9. Lawrence Kryzanowski & Jie Zhang & Rui Zhong, 2021. "Currency hedging and quantitative easing: Evidence from global bond markets," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 555-597, June.
    10. Fan, Zhenzhen & Paseka, Alexander & Qi, Zhen & Zhang, Qi, 2022. "Currency carry trade: The decline in performance after the 2008 Global Financial Crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    11. Alexakis, Christos & Kenourgios, Dimitris & Pappas, Vasileios & Petropoulou, Athina, 2021. "From dotcom to Covid-19: A convergence analysis of Islamic investments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    12. Yuta Hibiki & Takuya Kiriu & Norio Hibiki, 2024. "Optimal Currency Portfolio with Implied Return Distribution in the Mean-Variance Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(2), pages 251-283, June.
    13. Kharrat, Sabrine & Hammami, Yacine & Fatnassi, Ibrahim, 2020. "On the cross-sectional relation between exchange rates and future fundamentals," Economic Modelling, Elsevier, vol. 89(C), pages 484-501.
    14. Alla Petukhina & Simon Trimborn & Wolfgang Karl Härdle & Hermann Elendner, 2021. "Investing with cryptocurrencies – evaluating their potential for portfolio allocation strategies," Quantitative Finance, Taylor & Francis Journals, vol. 21(11), pages 1825-1853, November.

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    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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