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Trading Cryptocurrencies Using Second Order Stochastic Dominance

Author

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  • Gil Cohen

    (Department of Management, Western Galilee Academic College, Acre 2412101, Israel)

Abstract

This research is the first attempt to customize a trading system that is based on second order stochastic dominance (SSD) to five known cryptocurrencies’ daily data: Bitcoin, Ethereum, XRP, Binance Coin, and Cardano. Results show that our system can predict price trends of cryptocurrencies, trade them profitably, and in most cases outperform the buy and hold (B&H) simple strategy. Our system’s best performance was achieved trading XRP, Binance Coin, Ethereum, and Bitcoin. Although our system has also generated a positive net profit (NP) for Cardano, it failed to outperform the B&H strategy. For all currencies, the system better predicted long trends than short trends.

Suggested Citation

  • Gil Cohen, 2021. "Trading Cryptocurrencies Using Second Order Stochastic Dominance," Mathematics, MDPI, vol. 9(22), pages 1-10, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2861-:d:676689
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    References listed on IDEAS

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    7. Marco Ortu & Nicola Uras & Claudio Conversano & Giuseppe Destefanis & Silvia Bartolucci, 2021. "On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning," Papers 2102.08189, arXiv.org, revised Feb 2021.
    8. Gil Cohen, 2021. "Optimizing candlesticks patterns for Bitcoin's trading systems," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1155-1167, October.
    9. Brandvold, Morten & Molnár, Peter & Vagstad, Kristian & Andreas Valstad, Ole Christian, 2015. "Price discovery on Bitcoin exchanges," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 36(C), pages 18-35.
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    11. Yue Liu & Aijun Yang & Jijian Zhang & Jingjing Yao, 2020. "An Optimal Stopping Problem of Detecting Entry Points for Trading Modeled by Geometric Brownian Motion," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 827-843, March.
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    Cited by:

    1. Rolando Rubilar-Torrealba & Karime Chahuán-Jiménez & Hanns de la Fuente-Mella, 2023. "A Stochastic Analysis of the Effect of Trading Parameters on the Stability of the Financial Markets Using a Bayesian Approach," Mathematics, MDPI, vol. 11(11), pages 1-14, May.
    2. José Luis Miralles-Quirós & María Mar Miralles-Quirós, 2022. "Mathematics, Cryptocurrencies and Blockchain Technology," Mathematics, MDPI, vol. 10(12), pages 1-2, June.
    3. David Cerezo S'anchez, 2022. "Zero-Knowledge Optimal Monetary Policy under Stochastic Dominance," Papers 2210.06139, arXiv.org.

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