## 5 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline
**60** & 0.47\% & 1.32\% & 8.67\% & 10.18\% & 10.67\% & 17.58\% & 4.92\% & 6.46\% & 2.60\% & 8.15\% \\ \hline
**55** & \(-\)0.03\% & 10.52\% & 4.69\% & 7.85\% & 9.66\% & 15.78\% & 4.35\% & 0.34\% & 2.60\% & 8.15\% \\ \hline
**50** & \(-\)0.04\% & 3.41\% & 0.83\% & 8.82\% & 11.54\% & 8.51\% & 3.92\% & 0.65\% & 2.27\% & 8.15\% \\ \hline
**45** & 11.58\% & 3.85\% & 4.51\% & 7.04\% & 10.35\% & 7.68\% & 14.22\% & 6.46\% & 7.90\% & 15.05\% \\ \hline
**40** & 2.93\% & 3.11\% & 6.05\% & 7.14\% & 14.30\% & 7.73\% & 9.79\% & 19.49\% & 20.79\% & **31.73\%** \\ \hline
**35** & 2.54\% & 0.91\% & 7.20\% & 2.33\% & 6.04\% & 9.21\% & 11.67\% & 16.70\% & 20.61\% & 26.84\% \\ \hline
**30** & 2.67\% & 4.21\% & 5.64\% & 3.84\% & 4.55\% & 9.91\% & 11.55\% & 16.00\% & 20.61\% & 29.41\% \\ \hline
**25** & 4.05\% & 4.56\% & 2.41\% & 3.31\% & 6.29\% & 10.24\% & 8.32\% & 12.19\% & 15.82\% & 23.22\% \\ \hline
**20** & 2.14\% & 2.02\% & 3.22\% & 4.51\% & 5.08\% & 5.33\% & 6.68\% & 10.68\% & 12.58\% & 24.29\% \\ \hline
**15** & 6.33\% & 7.02\% & 3.44\% & 5.39\% & 5.27\% & 4.22\% & 8.13\% & 12.28\% & 3.71\% & 2.61\% \\ \hline
**10** & 5.48\% & 5.62\% & 5.77\% & 6.45\% & 2.20\% & 2.56\% & 3.20\% & 7.88\% & 4.86\% & \(-\)9.79\% \\ \hline
**5** & 3.85\% & 3.87\% & 3.68\% & 3.93\% & 5.34\% & 8.15\% & \(-\)27.09\% & 0.00\% & 0.00\% & 0.00\% \\ \hline
**n1/n2** & **0.25** & **0.5** & **0.75** & **1** & **1.25** & **1.5** & **1.75** & **2** & **2.25** & **2.5** \\ \hline \end{tabular} Note: The first column refers to n1 from the 5-day MA at the bottom to the 60-day MA at the top, and the last row refers to n2 from 0.25 SD at the leftmost to 2.5 SDs at the rightmost. The AHP in blue is the highest AHP in this table.  
\end{table} 
Table 6: Heatmap Matrix results of trading ETH spot with exits after holding a fixed period. This table shows the AHR results using BBTS (n1, n2), where n1 (moving average lengths) ranges from 5 to 60 days with a 5-day interval and n2 (standard deviations) ranges from 0.25 SD to 2.5 SD interval. Additionally, each cell in the heatmap matrix displays AHR obtained from one of the BBTS (n1, n2) with exits of 60 days for trading ETH spots. models in accuracy, and [PERSON] et al. [86] investigated Bitcoin volatility, predicting trends using on-chain data and whale-alert tweets. Q-learning produces accurate predictions, providing useful information for informed Bitcoin investment decisions and risk management. These studies offer novel approaches for forecasting cryptocurrency movement and potentially profiting from cryptocurrency trading. Furthermore, there are two ways to exit the market following BBTS: the first is to exit once BBTS emits selling signals, and the second is to exit after holding for a specific period. However, since there is no uniramous fixed period, we then use 60 days as exit after referring to the average duration day and the maximum MA day employed in diverse BBTS. Following that, we test H4 by examining whether exiting the market once BBTS triggers selling signals would outperform exiting the market after holding a special period (e.g., 60 days). Comparably, the heatmap matrix results shown in Tables 3 and 4 are better than those shown in Tables 5 and 6, indicating that better performance is shown in following BBTS as exiting the market as the trading signal emitted by BBTS instead of exiting the market after holding a special period, thus accepting H4. Such findings are somewhat similar in that the results using variable moving average (VMA) trading regulation are better than those using fixed moving average (FMA) trading regulation in the relevant studies [87; 88]. Instead of cryptocurrency markets, [PERSON] et al. [89] apply VMA trading rules to US stock markets, showing that the NASDAQ 100 index outperforms the DJ30 index, providing useful information for those who purchase stocks that track the NASDAQ 100 and DJ30 (i.e., index ETF traders).