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The Cross-Section of Cryptocurrency Risk and Return

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  2. Economics, Finance, Business & Management
  3. Vierteljahrshefte zur Wirtschaftsforschung
  4. Vol. 89, Issue 4
  5. pp. 7–28

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Günther, S., Fieberg, C., Poddig, T. The Cross-Section of Cryptocurrency Risk and Return. Vierteljahrshefte zur Wirtschaftsforschung, 89(4), 7-28. https://doi.org/10.3790/vjh.89.4.7
Günther, Steffen; Fieberg, Christian and Poddig, Thorsten "The Cross-Section of Cryptocurrency Risk and Return" Vierteljahrshefte zur Wirtschaftsforschung 89.4, , 7-28. https://doi.org/10.3790/vjh.89.4.7
Günther, Steffen/Fieberg, Christian/Poddig, Thorsten: The Cross-Section of Cryptocurrency Risk and Return, in: Vierteljahrshefte zur Wirtschaftsforschung, vol. 89, iss. 4, 7-28, [online] https://doi.org/10.3790/vjh.89.4.7
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The Cross-Section of Cryptocurrency Risk and Return

Günther, Steffen | Fieberg, Christian | Poddig, Thorsten

Vierteljahrshefte zur Wirtschaftsforschung, Vol. 89 (2020), Iss. 4 : pp. 7–28

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Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/vjh.89.4.7
Language
English
Pages
22
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Author Details

Steffen Günther, University of Bremen, Chair of Finance

  • Steffen Günther is a PhD student at the chair of finance, University of Bremen. He holds a degree in economics from the TU Dresden. His current research focusses on cryptocurrencies as a new and emerging financial asset class and in particular on asset pricing. He furthermore develops open source software applications for empirical capital market research.
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Christian Fieberg, University of Bremen, Empirical Capital Market Research and Derivatives

  • Christian Fieberg is researcher at the University of Bremen, with a special focus on empirical capital market research and derivatives and research fellow at Hamburg University. He conducted research and taught at Jacobs University, Concordia University (Montreal), University of the Free State (Bloemfontein), University of Oldenburg and Bremen University of Applied Sciences. He worked as a fund manager at Bremer Landesbank, NordLB and Solvecon Invest.
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Thorsten Poddig, University of Bremen, Chair of Finance

  • Thorsten Poddig holds the chair of finance at the University of Bremen and is head of CARMA – Center for Asset and Risk Management Applications. He studied economics and computer science at the Universities Hamburg and Bremen. His research focusses on the analysis, modelling and prediction of financial markets with modern quantitative methods. He is in the german community among the first using machine learning applications in financial markets research and published several articles on that topic since 1991.
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Cited By

  1. 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]

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Abstract

Summary: We analyze the cross-section of more than 1200 cryptocurrencies derived from 350 exchanges in the time period from January 2014 to June 2020. Specifically, we investigate whether well-known cross-sectional characteristics like beta (Fama/MacBeth (1973)), size (Banz (1981)) or momentum (Jegadeesh/Titman (1993)) – which have been intensively investigated in the equities literature – explain the cross-section of cryptocurrency returns. We apply the monotonic relationship (Mr.) test developed by Patton and Timmermann (2010) to test for dependencies between characteristics and average portfolio returns and standard deviations. We extend the existing literature on cryptocurrencies showing that there are various characteristics which are able to explain cryptocurrency risk and return.

Zusammenfassung: Wir untersuchen den Querschnitt von über 1200 Kryptowährungen, gesammelt von 350 Handelsplätzen, in der Zeitspanne von Januar 2014 bis Juni 2020. Im speziellen untersuchen wir, ob weit verbreitete Charakteristika, wie Beta (Fama/MacBeth (1973)), Size (Banz (1981)) oder Momentum (Jegade‍esh/Titman (1993)) – die bereits intensiv in der Aktienliteratur untersucht werden – den Querschnitt der Kryptowährungsrenditen erklären können. Wir verwenden den Monotonic Relationship (MR) Test von Patton und Timmermann (2010) um auf Abhängigkeiten zwischen Charakteristika und durchschnittlichen Portfoliorenditen sowie Standardabweichungen zu testen. Wir erweitern die bestehende Literatur, indem wir zahlreiche Charakteristika identifizieren, die Risiko und Renditen von Kryptowährungen erklären können.

Table of Contents

Section Title Page Action Price
Steffen Günther, Christian Fieberg and Thorsten Poddig: 7
 The Cross-Section of Cryptocurrency Risk and Return 7
1 Introduction 8
2 Literature Review 9
3 Data and Methodology 11
4 Results 7
4.1 Returns 7
4.2 Risk 7
4.3 Reversal and Momentum in Cryptocurrencies – a closer look 7
4.4 Double Sorts 7
4.5 Transaction Costs 7
5 Conclusion 7
References 7

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