Improving the mechanical approach using bitcoin market volume data

DOI: 10.31673/2412-9070.2025.026142

Abstract

The subject of this study is the improvement of the mechanistic approach to the analysis of market volumes of cryptocurrencies, in particular Bitcoin, using indicators of market purchases, sales and their difference. The purpose of the work is to determine the effectiveness of the improved mechanistic approach by using market volumes of purchases, sales and their difference in predicting market trends and its impact on the profitability of Bitcoin trading strategies. The objectives of the study include: to expand the mechanistic approach by using market volumes (purchases, sales, the difference between them); to test the improved approach on historical BTC/USDT trading data using the moving average strategy; to compare the effectiveness of the new approach with the traditional mechanistic analysis of total volume; to assess the dependence of profitability and win rate on the selected method and time intervals (1 day, 4 hours, 30 minutes). The results obtained indicate that the impulse of market purchases (GMI Volume Buy) demonstrates the highest profitability and accuracy among all analyzed indicators, while the impulse of volume difference (GMI Volume Delta) has the lowest efficiency and higher volatility. It was found that shortening the time interval reduces the profitability and stability of all methods, and also increases their sensitivity to the choice of parameters. Thus, the study confirms the prospects of the mechanistic approach, especially taking into account the market volumes of purchases and sales. The results can be used to improve algorithmic trading strategies, aswell as in further research related to the application of machine learning algorithms and optimization of mechanistic analysis parameters.

Keywords: mechanistic approach; cryptocurrency; moving average; trading volumes; backtesting; bitcoin, trading strategy; forecasting; dependence; data.