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Cryptocurrency trading: a comprehensive survey

DOI: 10.1186/s40854-021-00321-6 ABSTRACT: Abstract In recent years, the tendency of the number of financial institutions to include cryptocurrencies in their portfolios has accelerated. Cryptocurrencies are the first pure digital assets to be included by asset managers. Although they have some commonalities with more traditional assets, they have their own separate nature and their behaviour as an asset is still in the process of being understood. It is therefore important to summarise existing research papers and results on cryptocurrency trading, including…

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The rapid growth of cryptocurrencies: How profitable is trading in digital money?

DOI: 10.1002/ijfe.2778 ABSTRACT: There has been a tremendous growth in cryptocurrencies, which has challenged policy makers around the globe. We obtain millisecond data of some of the most frequently traded cryptocurrencies – bitcoin, ethereum, ripple, litecoin and dash – and two cryptocurrency indices – CRIX and CCI30 – to examine their profitability. Our profitability findings suggest that cryptocurrency traders generate significant profits after considering reasonable transaction costs. We also observe that cryptocurrency market participants can expand and sustain the levels…

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Cryptocurrency investment: A safe venture or a new type of gambling?

DOI: 10.4309/JGI.2021.47.8 ABSTRACT: Investment behaviour and gambling overlap from time to time. It is stated that there is a spectrum between gambling and investment behaviour, and there are “speculative” investment tools in the middle of the spectrum. Considering that it presents a higher risk because of its high volatility compared to traditional investment instruments, trading cryptocurrencies can become pathological and gambling-like. This study aims to investigate the pathological trading behaviour and frequency among cryptocurrency investors, to investigate additional gambling disorders,…

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Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting

DOI: 10.48550/arxiv.2209.05559 ABSTRACT: Designing profitable and reliable trading strategies is challenging in the highly volatile cryptocurrency market. Existing works applied deep reinforcement learning methods and optimistically reported increased profits in backtesting, which may suffer from the false positive issue due to overfitting. In this paper, we propose a practical approach to address backtest overfitting for cryptocurrency trading using deep reinforcement learning. First, we formulate the detection of backtest overfitting as a hypothesis test. Then, we train the DRL agents, estimate…

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