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ISSN:
2049-5404 (print)
2049-5412 (online)
Editor-in-chief: Manmohan Singh
Impact Factor: 0.2
First Published: September 2012
Pages:
37-65
DOI:
10.21314/JFMI.2023.006
First published:
Oluwasegun Bewaji, Sania Hamid, Timothy Aerts, Shaun Byck, Ronald Heijmans and Ellen van der Woerd
This paper identifies triangular arbitrage trading opportunities using a branch of evolutionary algorithms known as genetic algorithms in an effort to derive insights into the volatility of cryptocurrencies and stablecoins with the largest market cap. The triangular trades are carried out as an arbitrage play consisting of two or more cryptocurrencies as well as a fiat currency (the US dollar) used to enter and exit the trades. Our results show persistent tradable arbitrage profits per trade for digital currencies of US$2 for stablecoins, US$5 for cryptocurrencies and US$25 for a strategy using both stablecoins and cryptocurrencies. As expected, employing the same strategy using strictly fiat currencies did not yield arbitrage profits, highlighting the relative volatility of both cryptocurrencies and, perhaps more surprisingly, stablecoins.
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Are cryptocurrencies cryptic or a source of arbitrage? A genetic algorithm approach – Risk.net
