Has the Bitcoin's "highest indicator" failed?

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In the recent bull market, many of the most popular Bitcoin top indicators failed to trigger, leading observers to question whether the underlying data has “failed.” This article analyzes some widely used tools, explores the reasons for their poor performance in this cycle, and outlines how to adjust them based on Bitcoin's constantly evolving market structure.

Price Tool Prediction

On the price prediction tool indicators of Bitcoin Magazine Pro, the recent bull market has never reached several historically reliable top models, such as Delta Top, Terminal Price, and Top Cap (not even during the previous cycle). The Bitcoin Investor Tool, which uses two moving averages multiplied by 5, has also not been tested, and the Pi Cycle Top indicator, although closely monitored by many traders, has failed to provide accurate timing or price signals. This has led to understandable questions: Have these models stopped working, or has Bitcoin outgrown them?

Figure 1: Historically reliable top models, such as Top Cap, Delta Top, and Terminal Price, have not been reached in this bull market cycle.

Bitcoin is an evolving asset, with its market structure, liquidity, and participant engagement all changing. Assuming data has taken effect, it is better to adjust these metrics more appropriately from different perspectives and time frames. The goal is not to abandon these tools, but to make them more robust and responsive to a market that no longer offers the same exponential rises early on and cyclical peaks as it did in previous years.

From fixed to dynamic

MVRV Z-Score 2-Year Rolling Indicator has always been a core tool for identifying overheated market conditions, but in this cycle, it has not effectively led to the peak of the bull market. When Bitcoin first broke through the $73,000–$74,000 range, the indicator experienced a significant surge, but failed to provide a clear exit signal for the subsequent rise. Currently, the indicator is at the most oversold reading on record.

Figure 2: The typically reliable MVRV Z-Score 2-year rolling indicator failed to trigger an exit signal during the cycle.

To address this flaw, the MVRV Z-Score can be restructured on a rolling 6-month basis, rather than two years, making it more sensitive to recent conditions while still based on the dynamics of realized value. In addition to the weekly lookback period, abandoning fixed thresholds in favor of dynamic distribution-based ranges is also helpful. By sparsely marking the proportion of days spent above or below different Z-Score levels, areas such as the top 5% can be identified, as well as the bottom 5%. In this cycle, when Bitcoin first broke through $100,000, this metric indeed signaled in the upper range, and historically, the trend of entering the top 5% region has correlated quite well with cycle recovery, even if they did not capture the ideal peak.

Figure 3: The adjusted 6-month MVRV Z-Score, with targeted upper and lower percentages, provides more timely buy/sell signals.

reacts faster

In addition to valuation tools, activity-based indicators like Coin Days Destroyed ( Coin Days Analyst ) can enhance their utility through the entire period of its retrospective. The 90-day moving average of coin days analyst volume has historically tracked large sell-offs by long-term holders, but due to the more cautious trend and increased volatility of the current cycle, the 30-day moving average typically provides more valuable reference information. As Bitcoin no longer offers the same parabolic rise, indicators need to react faster to reflect shallower, yet still significant, profit-taking and investor rotation waves.

Figure 4: It has been proven that the 30-day moving average's coin-day conjecture reacts faster to on-chain dynamics.

Fix recent readings, and the potential rise before reaching a new high in this cycle's history, the 30-day coin Tianyu indicator almost triggered at the peak of the cycle. It was triggered when Bitcoin first crossed around $73,000–$74,000 and when the price broke $100,000, effectively marking all key selling waves. While this is easy to observe in hindsight, it reinforces a point: on-chain supply and demand signals remain relevant; the task is to infer them based on current volatility and market depth.

Spent Output Profit Ratio (SOPR)

Spent Output Profit Ratio (SOPR) provides another perspective on realized profits and losses, but the raw data series can be quite chaotic, with fluctuating spikes, mean reversion of profits and losses, and significant volatility during mid-surrender in uptrends and bull markets. To extract more actionable information, the SOPR changes can be adjusted using a 28-day (monthly) period. This smoothed alternative emphasizes that within short-term windows, the ultimate realization trend reaches extreme levels, leading to volatility in cyclical fluctuations.

Figure 5: Applying the 28-day moving average to the SOPR indicator can smooth the data, reducing unnecessary “noise” and accurately identifying local tops.

Evaluating the recent cycles, the monthly SOPR changes produced significant peaks when Bitcoin first broke through the $73,000–$74,000 range, again when it surpassed $100,000, and around the $120,000 area. Although these did not perfectly capture the ultimate peaks, they strongly coincided with the cycle fatigue that promoted the end of the pressure phase. Utilizing monthly changes instead of raw indicators has made the signals clearer, especially when observing Bitcoin's purchasing power against stocks and gold across assets.

Conclusion

In hindsight, the top indicators that were popular throughout the bull market, if simplified through the right perspective and appropriate time frames, did indeed play a role. The key principle remains: react to the data, do not try to predict. Waiting for any single indicator to perfectly predict the top is less effective than using a basket of adjusted indicators and interpreting them through the lens of strength and the ever-changing market dynamics, which can increase the probability of identifying when Bitcoin is overheating and when it transitions into a more favorable accumulation phase. The focus in the coming months will be on refining these models to ensure they are not only historically effective but also maintain integrity in accuracy for the future.

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