OG-CAT: A Novel Algorithmic Trading Alternative to Investment in Crypto Market
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Date
2023-03-28T00:00:00
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Springer
Abstract
Cryptocurrencies have emerged as a good tool for investment/trading in the last decade. The investors have achieved promising gains with the long-term investments made at reasonably good price/time. However, investment in cryptocurrencies is also exposed to extremely high volatility. Due to this, the investment may suffer from a high drawdown as the price may fall. In this work, we proposed optimized Greedy-cost averaging based trading (OG-CAT) a novel trading framework as an alternative to long-term investment in cryptocurrencies. The approach exploits the wavy structure of the price movement of cryptocurrencies, the high volatility of price, and the concept of cost averaging. Furthermore, the parameters of the approach are optimized with the simulated annealing algorithm. The approach is evaluated on the two prominent cryptocurrencies: bitcoin and ethereum. During the evaluation, OG-CAT not only outperformed the buy-and-hold investment approach in terms of profit but also demonstrated a lower drawdown. The profit percentage in the case of trading BTC with OG-CAT is 1.63 times more and the max drawdown is 1.62 times less than compared to the buy-and-hold strategy. � 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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Keywords
Algorithmic trading, Bitcoin, Blockchain, Cryptocurrency, Dollar cost averaging, Ethereum, Optimization, Trading strategy