In 2020 and 2021, the cryptocurrency market attracted millions of new traders and investors. Lack of regulation, high liquidity, and modern exchanges significantly lowered the entry threshold for new market participants. In 2021, over 5 million Americans were regularly involved in cryptocurrency trading. At that time, the interest in market indicators and trading strategies remained low, leading to the conclusion that most investors did not use decision-support indicators. The correct and backtested use of technical analysis signals can give the trader a significant advantage over most market participants. This work introduces an algorithmic approach to examining the effectiveness of the signals generated by one of the most popular market indicators, the Relative Strength Index (RSI). A model corresponding to an actual cryptocurrency exchange was used to backtest the strategies. The results show that the RSI as a momentum indicator in the cryptocurrency market involves high risk. Using alternative RSI applications can allow traders to gain an advantage in the cryptocurrency market. Comparing the results with the traditional buy and hold strategy shows the credible potential of the indicated method and the usage of signals generated by the technical analysis indicators.

The cryptocurrency landscape underwent significant changes in 2024 with the regulatory approval of spot Bitcoin ETFs, opening the market to institutional investors and millions of new clients. As Bitcoin reached new price peaks, the market attracted many retail traders using speculative approaches, evidenced by the surge in meme coins at the end of 2024. In such an environment, properly examining trading strategies can offer substantial advantages over the majority of market participants. Many traders, however, fail to test their strategies adequately, limiting evaluations to selected time periods and risking overfitting. This paper introduces the Rolling Strategy–Hold Ratio (RSHR), which uses a rolling-window approach to evaluate how strategies would perform from thousands of different starting points. This method helps mitigate recency bias and provides a more comprehensive understanding of strategy performance across diverse market conditions and cycles. By comparing strategies results against buy-and-hold results, traders can make informed decisions about whether to refine their strategies further or opt for index-based investing or alternative analytical methods. This study demonstrates the RSHR’s applications across technical, on-chain, sentiment analysis, and dollar cost averaging strategies, with initial research suggesting potential applications in traditional markets.