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The Decision to Produce Altcoins: Miners' Arbitrage in Cryptocurrency Markets

Author

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  • Adam Hayes

    (Department of Economics, New School for Social Research)

Abstract

Bitcoin has become the de facto 'gold' standard among cryptocurrencies as it is the most widely accepted in commerce, has the largest mining network, and greatest volume of transactions. Because of this, miners of other SHA-256 cryptocurrencies will tend to convert those altcoins into bitcoin in order to transact in a meaningful way with the real economy. The result is that bitcoin mining regulates that of all other SHA-256 blockchains. Specifically, what matters is the expected number of bitcoins produced per day given a unit of hashing (mining) power, whatever the equivalence in the coin being mined. If mining for a different coin would yield a greater return in bitcoins at the margin (per day) for a miner, an apparent arbitrage opportunity will exist to direct mining effort at that cryptocurrency and subsequently exchange those for bitcoin. These opportunities, once taken, quickly eliminate the profitable arbitrage and appear to operate in a fairly efficient and predictable manner. A model is developed in this paper to formalize this process where cryptocurrency miners seeking to maximize production in terms of bitcoins earned in a day will exploit any such opportunities. If no such opportunities exist, they will simply revert to mining bitcoins directly. There are some important implications to this process, such as a tendency for cryptocurrencies to fall in price relative to bitcoin over time, and for changes in bitcoin mining difficulty to indirectly influence the market prices of altcoins. Finally, it seems that those undertaking this process of miners' arbitrage do so at the expense of speculators and noise traders who make decisions regarding buy and sell trades without the use of fundamental data. These participants generally have poor timing, follow trends, and over-react to good and bad news. Altcoins are produced by miners and subsequently offered for sale in the market in order to obtain bitcoins; meanwhile noise traders serve as the only bid-side to the market, on average.

Suggested Citation

  • Adam Hayes, 2015. "The Decision to Produce Altcoins: Miners' Arbitrage in Cryptocurrency Markets," Working Papers 1504, New School for Social Research, Department of Economics.
    • Handle: RePEc:new:wpaper:1504
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    File URL: http://www.economicpolicyresearch.org/econ/2015/NSSR_WP_042015.pdf
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    References listed on IDEAS

    as
    1. Adam Hayes, 2014. "What Factors Give Cryptocurrencies Their Value: An Empirical Analysis," Working Papers 1406, New School for Social Research, Department of Economics, revised Mar 2015.
    2. Neil Gandal & Hanna Halaburda, 2014. "Competition in the Cryptocurrency Market," Staff Working Papers 14-33, Bank of Canada.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2016. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. I," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 44, pages 5-24.
    2. Mark Mizraki, 2015. "Conversation with Mark Mizruchi:“There is Very Little Organizational Theory Left in Sociology Departments”," Journal of Economic Sociology, National Research University Higher School of Economics, vol. 16(3), pages 14-25.
    3. Pavković Ana & Anđelinović Mihovil & Pavković Ivan, 2019. "Achieving Portfolio Diversification through Cryptocurrencies in European Markets," Business Systems Research, Sciendo, vol. 10(2), pages 85-107, September.
    4. Sondes Mbarek & Donia Trabelsi & Michel Berne, 2020. "Are virtual currencies virtuous? Ethical and environmental issues," Post-Print hal-02434877, HAL.
    5. Adam Hayes, 2015. "A Cost of Production Model for Bitcoin," Working Papers 1505, New School for Social Research, Department of Economics.
    6. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2017. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. Part 2," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 45, pages 5-28.
    7. Lars Steinert & Christian Herff, 2018. "Predicting altcoin returns using social media," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-12, December.

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    More about this item

    Keywords

    Bitcoin; cryptocurrency; altcoins; arbitrage; equilibrium models; currency exchanges;
    All these keywords.

    JEL classification:

    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G1 - Financial Economics - - General Financial Markets
    • L17 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Open Source Products and Markets
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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