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    Cryptocurrency trading: a comprehensive survey

    Cryptocurrencies have experienced broad market acceptance and fast development despite their recent conception. Many hedge funds and asset managers have begun to include cryptocurrency-related assets into their portfolios and trading strategies. The academic community has similarly spent considerable efforts in researching cryptocurrency trading. This paper seeks to provide a comprehensive survey of the research on cryptocurrency trading, by which we mean any study aimed at facilitating and building strategies to trade cryptocurrencies.

    As an emerging market and research direction, cryptocurrencies and cryptocurrency trading have seen considerable progress and a notable upturn in interest and activity (Farell 2015). From Fig. 1, we observe over 85% of papers have appeared since 2018, demonstrating the emergence of cryptocurrency trading as a new research area in financial trading. The sampling interval of this survey is from 2013 to June 2021.

    The literature is organised according to six distinct aspects of cryptocurrency trading:

    • Cryptocurrency trading software systems (i.e., real-time trading systems, turtle trading systems, arbitrage trading systems);

    • Systematic trading including technical analysis, pairs trading and other systematic trading methods;

    • Emergent trading technologies including econometric methods, machine learning technology and other emergent trading methods;

    • Portfolio and cryptocurrency assets including research among cryptocurrency co-movements and crypto-asset portfolio research;

    • Market condition research including bubbles (Flood et al. 1986) or crash analysis and extreme conditions;

    • Other Miscellaneous cryptocurrency trading research.

    In this survey we aim at compiling the most relevant research in these areas and extract a set of descriptive indicators that can give an idea of the level of maturity research in this area has achieved.

    We also summarise research distribution (among research properties and categories/research technologies). The distribution among properties defines the classification of research objectives and content. The distribution among technologies defines the classification of methods or technological approaches to the study of cryptocurrency trading. Specifically, we subdivide research distribution among categories/technologies into statistical methods and machine learning technologies. Moreover, We identify datasets and opportunities (potential research directions) that have appeared in the cryptocurrency trading area. To ensure that our survey is self-contained, we aim to provide sufficient material to adequately guide financial trading researchers who are interested in cryptocurrency trading.

    There has been related work that discussed or partially surveyed the literature related to cryptocurrency trading. Kyriazis (2019) investigated the efficiency and profitable trading opportunities in the cryptocurrency market. Ahamad et al. (2013) and Sharma et al. (2017) gave a brief survey on cryptocurrencies, merits of cryptocurrencies compared to fiat currencies and compared different cryptocurrencies that are proposed in the literature. Mukhopadhyay et al. (2016) gave a brief survey of cryptocurrency systems. Merediz-Solà and Bariviera (2019) performed a bibliometric analysis of bitcoin literature. The outcomes of this related work focused on specific area in cryptocurrency, including cryptocurrencies and cryptocurrency market introduction, cryptocurrency systems / platforms, bitcoin literature review, etc. To the best of our knowledge, no previous work has provided a comprehensive survey particularly focused on cryptocurrency trading.

    In summary, the paper makes the following contributions:

    • Definition This paper defines cryptocurrency trading and categorises it into: cryptocurrency markets, cryptocurrency trading models, and cryptocurrency trading strategies. The core content of this survey is trading strategies for cryptocurrencies while we cover all aspects of it.

    • Multidisciplinary survey The paper provides a comprehensive survey of 146 cryptocurrency trading papers, across different academic disciplines such as finance and economics, artificial intelligence and computer science. Some papers may cover multiple aspects and will be surveyed for each category.

    • Analysis The paper analyses the research distribution, datasets and trends that characterise the cryptocurrency trading literature.

    • Horizons The paper identifies challenges, promising research directions in cryptocurrency trading, aimed to promote and facilitate further research.

    Figure 2 depicts the paper structure, which is informed by the review schema adopted. More details about this can be found in “ Paper collection and review schema“ section.

    Find more: Survey developer interest blockchain apps cryptocurrencies – Krypto-NFTs

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