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Kryptowährungen in der Asset-Allokation: Eine empirische Untersuchung auf Basis eines beispielhaften deutschen Multi-Asset-Portfolios

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  2. Economics, Finance, Business & Management
  3. Vierteljahrshefte zur Wirtschaftsforschung
  4. Vol. 87, Issue 3
  5. pp. 107–128

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Glas, T., Poddig, T. Kryptowährungen in der Asset-Allokation: Eine empirische Untersuchung auf Basis eines beispielhaften deutschen Multi-Asset-Portfolios. Vierteljahrshefte zur Wirtschaftsforschung, 87(3), 107-128. https://doi.org/10.3790/vjh.87.3.107
Glas, Tobias N. and Poddig, Thorsten "Kryptowährungen in der Asset-Allokation: Eine empirische Untersuchung auf Basis eines beispielhaften deutschen Multi-Asset-Portfolios" Vierteljahrshefte zur Wirtschaftsforschung 87.3, 2018, 107-128. https://doi.org/10.3790/vjh.87.3.107
Glas, Tobias N./Poddig, Thorsten (2018): Kryptowährungen in der Asset-Allokation: Eine empirische Untersuchung auf Basis eines beispielhaften deutschen Multi-Asset-Portfolios, in: Vierteljahrshefte zur Wirtschaftsforschung, vol. 87, iss. 3, 107-128, [online] https://doi.org/10.3790/vjh.87.3.107
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Kryptowährungen in der Asset-Allokation: Eine empirische Untersuchung auf Basis eines beispielhaften deutschen Multi-Asset-Portfolios

Glas, Tobias N. | Poddig, Thorsten

Vierteljahrshefte zur Wirtschaftsforschung, Vol. 87(2018), Iss. 3 : pp. 107–128

5 Citations (CrossRef)

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Article Details

Publisher Name
Duncker & Humblot GmbH
DOI
https://doi.org/10.3790/vjh.87.3.107
Language
German
Pages
22
License
closed-access
Keywords

Author Details

Tobias N. Glas, Lehrstuhl für ABWL, Universität Bremen.

Thorsten Poddig, Lehrstuhl für ABWL, Universität Bremen.

Cited By

  1. The Cross-Section of Cryptocurrency Risk and Return

    Günther, Steffen | Fieberg, Christian | Poddig, Thorsten

    Vierteljahrshefte zur Wirtschaftsforschung, Vol. 89(2020), Iss. 4 P.7

    https://doi.org/10.3790/vjh.89.4.7 [Citations: 2]

  2. Asset Pricing and Investment Styles in Digital Assets

    Digital Assets

    Glas, Tobias

    2022

    https://doi.org/10.1007/978-3-030-95695-0_5 [Citations: 0]

  3. Diginomics Research Perspectives

    Asset Pricing in Digital Assets

    Günther, Steffen | Glas, Tobias | Poddig, Thorsten

    2022

    https://doi.org/10.1007/978-3-031-04063-4_7 [Citations: 0]

  4. Banking & Innovation 2022/2023

    Einfluss der Inflationspolitik der Europäischen Zentralbank auf das Anlegerverhalten

    Dückerhoff, Fabian | Dill, Arthur

    2023

    https://doi.org/10.1007/978-3-658-39388-5_12 [Citations: 0]

  5. Asset Pricing and Investment Styles in Digital Assets

    Digital Assets in a Multi-asset Context

    Glas, Tobias

    2022

    https://doi.org/10.1007/978-3-030-95695-0_6 [Citations: 0]

References

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  3. Cao, J., R. Fu und Y. Jin (2017): International diversification through iShares and their rivals. Journal of Risk, 19 (3), 25–55.  Google Scholar
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  28. Huberman, G.und S. Kandel (1987): Mean-variance spanning. The Journal of Finance, 42 (4), 873–888.  Google Scholar
  29. Hubrich, S. (2017): Know when to Hodl Em, know when to Fodl Em: An investigation of factor based investing in the cryptocurrency space. Working Paper.  Google Scholar
  30. Varmaz, A. und S. Abée (2018): Sind digitale Währungen gewöhnliche Investitionsobjekte? Vierteljahrshefte zur Wirtschaftsforschung, 87 (3), 83–105.  Google Scholar
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  32. Colianni, S., S. Rosales und M. Signorotti (2015): Algorithmic trading of cryptocurrency based on twitter sentiment analysis. Working Paper.  Google Scholar
  33. Glaser, F., K. Zimmermann, M. Haferkorn, M. C. Weber und M. Siering (2014): Bitcoin – asset or currency? Revealing users' hidden Intentions. ECIS 2014. Tel Aviv.  Google Scholar
  34. Varmaz, A. und N. Varmaz (2018): Eine empirische Analyse von Initial Coin Offerings (ICO). Vierteljahrshefte zur Wirtschaftsforschung, 87 (3), 129–150.  Google Scholar
  35. Trimborn, S. und W. K. Härdle (2016): CRIX an Index for Blockchain Based Currencies. Working Paper.  Google Scholar
  36. Edwards, F. R. und J. Liew (1999): Hedge funds versus managed futures as asset classes. The Journal of Derivatives, 45–64.  Google Scholar
  37. El Bahrawy, A., L. Alessandretti, A. Kandler, R. Pastor-Satorras und A. Baronchelli (2017): Evolutionary dynamics of the cryptocurrency market. Royal Society Open Science, 4.  Google Scholar
  38. Ferson, W. E., S. R. Foerster und D. B. Keim (1993): General tests of latent variable models and mean-variance spanning. The Journal of Finance, 48 (1), 131–156.  Google Scholar
  39. Ince, O.S. und R.B. Porter (2006): Individual equity return data from Thomson Datastream: Handle with care! The Journal of Financial Research, 29 (4), 463–479.  Google Scholar
  40. Kan, R. und G. Zhou (2012): Tests of mean-variance spanning. Annals of Economics and Finance, 13 (1), 145–193.  Google Scholar
  41. Bekaert, G. und M. S. Urias (1996): Diversification, integration and emerging market closed-end funds. The Journal of Finance, 51(3), S. 835-869.  Google Scholar
  42. Rohrbach, J., S. Suremann und J. Osterrieder (2017): Momentum and trend following trading strategies for currencies revisited – combining academia and industry. Working Paper.  Google Scholar
  43. Hansen, L. P. (1982): Large Sample Properties of Generalized Method of Moments Estimators. Econometrica, 50 (4), 1029–1054.  Google Scholar
  44. Agarwal, V. und N. Y. Naik (2000): On taking the „alternative“ route: Risks, rewards, style and performance persistence of hedge funds. Journal of Alternative Investments, 2 (4), 6–23.  Google Scholar
  45. Cao, J., R. Fu und Y. Jin (2017): International diversification through iShares and their rivals. Journal of Risk, 19 (3), 25–55.  Google Scholar
  46. Schneeweis, T. und G. Martin (2001): The benefits of hedge funds: Asset allocation for the institutional investor. Journal of Alternative Investments, 4 (3), 7–26.  Google Scholar
  47. Rosenfeld, M. (2011): Analysis of bitcoin pooled mining reward systems. Working Paper.  Google Scholar
  48. Chuen, D. L., L. Guo und Y. Wang (2018): Cryptocurrency: A new investment opportunity? Journal of Alternative Investments, 20 (3), 16–40.  Google Scholar
  49. Nakamato, S. (2008): Bitcoin: A peer-to-peer electronic cash system. Working Paper.  Google Scholar
  50. Markowitz, H. (1952): Portfolio selection. The Journal of Finance, 7 (1), 77–91.  Google Scholar
  51. Maillard, S., T. Roncalli und J. Teïletche (2010): The properties of equally weighted risk contribution portfolios. Journal of Portfolio Management, 36 (4), 60–70.  Google Scholar
  52. Karavas, V. N. (2000): Alternative investments in the institutional portfolio. Journal of Alternative Investments, 3 (3), 11–25.  Google Scholar
  53. Hansen, L.P. und R. Jagannathan (1991): Implications of security market data for models of dynamic economies. Journal of Political Economy, 99 (2), 225–262.  Google Scholar
  54. Huberman, G.und S. Kandel (1987): Mean-variance spanning. The Journal of Finance, 42 (4), 873–888.  Google Scholar
  55. Hubrich, S. (2017): Know when to Hodl Em, know when to Fodl Em: An investigation of factor based investing in the cryptocurrency space. Working Paper.  Google Scholar
  56. Varmaz, A. und S. Abée (2018): Sind digitale Währungen gewöhnliche Investitionsobjekte? Vierteljahrshefte zur Wirtschaftsforschung, 87 (3), 83–105.  Google Scholar
  57. Glas, T. N. (2019): Investments in cryptocurrencies: Handle with care! Journal of Alternative Investments (im Erscheinen).  Google Scholar
  58. Colianni, S., S. Rosales und M. Signorotti (2015): Algorithmic trading of cryptocurrency based on twitter sentiment analysis. Working Paper.  Google Scholar
  59. Glaser, F., K. Zimmermann, M. Haferkorn, M. C. Weber und M. Siering (2014): Bitcoin – asset or currency? Revealing users' hidden Intentions. ECIS 2014. Tel Aviv.  Google Scholar
  60. Varmaz, A. und N. Varmaz (2018): Eine empirische Analyse von Initial Coin Offerings (ICO). Vierteljahrshefte zur Wirtschaftsforschung, 87 (3), 129–150.  Google Scholar
  61. Trimborn, S. und W. K. Härdle (2016): CRIX an Index for Blockchain Based Currencies. Working Paper.  Google Scholar
  62. Edwards, F. R. und J. Liew (1999): Hedge funds versus managed futures as asset classes. The Journal of Derivatives, 45–64.  Google Scholar
  63. El Bahrawy, A., L. Alessandretti, A. Kandler, R. Pastor-Satorras und A. Baronchelli (2017): Evolutionary dynamics of the cryptocurrency market. Royal Society Open Science, 4.  Google Scholar
  64. Ferson, W. E., S. R. Foerster und D. B. Keim (1993): General tests of latent variable models and mean-variance spanning. The Journal of Finance, 48 (1), 131–156.  Google Scholar
  65. Ince, O.S. und R.B. Porter (2006): Individual equity return data from Thomson Datastream: Handle with care! The Journal of Financial Research, 29 (4), 463–479.  Google Scholar
  66. Kan, R. und G. Zhou (2012): Tests of mean-variance spanning. Annals of Economics and Finance, 13 (1), 145–193.  Google Scholar
  67. Bekaert, G. und M. S. Urias (1996): Diversification, integration and emerging market closed-end funds. The Journal of Finance, 51(3), S. 835-869.  Google Scholar
  68. Rohrbach, J., S. Suremann und J. Osterrieder (2017): Momentum and trend following trading strategies for currencies revisited – combining academia and industry. Working Paper.  Google Scholar
  69. Hansen, L. P. (1982): Large Sample Properties of Generalized Method of Moments Estimators. Econometrica, 50 (4), 1029–1054.  Google Scholar
  70. Agarwal, V. und N. Y. Naik (2000): On taking the „alternative“ route: Risks, rewards, style and performance persistence of hedge funds. Journal of Alternative Investments, 2 (4), 6–23.  Google Scholar
  71. Cao, J., R. Fu und Y. Jin (2017): International diversification through iShares and their rivals. Journal of Risk, 19 (3), 25–55.  Google Scholar
  72. Schneeweis, T. und G. Martin (2001): The benefits of hedge funds: Asset allocation for the institutional investor. Journal of Alternative Investments, 4 (3), 7–26.  Google Scholar
  73. Rosenfeld, M. (2011): Analysis of bitcoin pooled mining reward systems. Working Paper.  Google Scholar
  74. Chuen, D. L., L. Guo und Y. Wang (2018): Cryptocurrency: A new investment opportunity? Journal of Alternative Investments, 20 (3), 16–40.  Google Scholar
  75. Nakamato, S. (2008): Bitcoin: A peer-to-peer electronic cash system. Working Paper.  Google Scholar
  76. Markowitz, H. (1952): Portfolio selection. The Journal of Finance, 7 (1), 77–91.  Google Scholar
  77. Maillard, S., T. Roncalli und J. Teïletche (2010): The properties of equally weighted risk contribution portfolios. Journal of Portfolio Management, 36 (4), 60–70.  Google Scholar
  78. Karavas, V. N. (2000): Alternative investments in the institutional portfolio. Journal of Alternative Investments, 3 (3), 11–25.  Google Scholar

Abstract

This article shows that the inclusion of cryptocurrencies to a portfolio consisting of several German asset classes should be viewed with caution. Due to a high realized volatility, cryptocurrencies are only marginally included in a reference portfolio constructed by using a Markowitz and a risk-parity approach. At the same time, the inclusion of cryptocurrencies is not supported by mean-variance-spanning tests. Furthermore, the tradability of this new asset class and its data availability pose additional problems such that our disappointing results may be even biased in favor of cryptocurriencies.

Table of Contents

Section Title Page Action Price
Tobias N. Glas / Thorsten Poddig: Kryptowährungen in der Asset-Allokation: Eine empirische Untersuchung auf Basis eines beispielhaften deutschen Multi-Asset-Portfolios 1
Zusammenfassung 1
Summary 1
1 Der Aufstieg einer neuen Asset-Klasse 2
1.1 Erster Überblick 2
1.2 Eine Einführung in Kryptowährungen 3
2 Verwandte Literatur 4
3 Daten 6
3.1 Kryptowährungen 6
3.2 Referenz-Assets 8
4 Bildung des Referenzportfolios 9
5 Allokation von Kryptowährungen zum Referenzportfolio 1
6 Mean-Variance-Spanning-Tests 1
7 Risk-Parity 1
8 Schlussfolgerung 2
Literaturverzeichnis 2

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