Identifying and evaluating the profitable technical trading rules in the cryptocurrency market using a hybrid qualitative-quantitative method

Objective: The purpose of this paper is to select the best technical indicators in the cryptocurrency market from the point of view of the market experts, optimize the performance of the indicators by optimization algorithms and finally compare the performance of the selected trading rules with each other as well as with the buy and hold strategy.

Method: In this research, technical trading rules are extracted and optimized for trading two cryptocurrencies, i.e. Bitcoin and Ethereum, using a hybrid qualitative-quantitative method. The efficiency of the extracted rules is evaluated and compared with the buy and hold strategy. In the qualitative part, the most important technical indicators are selected and ranked based on the cryptocurrency experts’ view using the fuzzy TOPSIS technique. In the quantitative part, the selected trading rules are implemented for a certain period and the parameters of the indicators are optimized using the grid search and particle swarm optimization algorithm. Finally, the performance of the selected trading strategies by the experts and optimized with the metaheuristic algorithms are evaluated and compared.

Result: In the qualitative part of the research, eighteen technical indicators were selected as the candidate indicators in the cryptocurrency trading, using the results of the related studies. The selected indicators are ranked based on the survey of thirteen cryptocurrency market experts using snowball sampling method. Finally, four technical indicators were selected as the superior indicators with a significant difference compared to the other technical indicators. The selected indicators were exponential moving average, relative strength index, ICHIMOKU and moving average convergence-divergence. In the quantitative part of the research, the expert based trading rules were implemented for Bitcoin and Ethereum markets in the period of 2018/06/30 to 2020/06/30. According to our numerical results, most of the expert based trading strategies are more profitable than the buy and hold strategy. Then, the parameters of the expert based trading rules were optimized using two metaheuristic algorithms, namely grid search and particle swarm optimization. The implementation results showed, the trading strategies optimized by these algorithms outperform the expert-based as well as the buy and hold strategies.

Conclusion: Based on the experimental results of this research, exponential moving average, relative strength index, ICHIMOKU and moving average convergence-divergence trading rules are commonly used and proposed by the cryptocurrency market experts. Moreover, the profitability of the well-known technical trading rules could be significantly improved using the grid search and particle swarm optimization algorithms. Also, the trading strategies using the combination of several technical indicators always perform better than the trading strategies with a single indicator. However, all technical analysis strategies are not necessarily more profitable compared to the buy and hold strategy. Using inappropriate technical strategies may not only be better than the buy and hold strategy, but sometimes it causes losses in cryptocurrency trading.