When the "Old Map" No Longer Applies: A Review of 8 "Failing Classic Cryptocurrency Indicators"

Author: Frank, PANews

At the beginning of 2026, the cryptocurrency market is filled with a sense of frustration and confusion.
Bitcoin has retraced approximately 36% from its all-time high set in October 2025, and the market swings back and forth between bulls and bears. But what unsettles many crypto investors even more than the price itself is that their previously relied-upon indicator systems for market judgment have almost all become ineffective.
The S2F model’s prediction of $500,000 has deviated more than threefold from reality; the four-year cycle, after the halving, has yet to produce explosive rallies; the Pi Cycle Top indicator remains silent throughout the entire cycle; the fixed threshold of the MVRV Z-Score no longer triggers signals; and the top region of the rainbow chart has become unreachable. Meanwhile, the contrarian signals from the Fear and Greed Index repeatedly fail, and the highly anticipated “altcoin season” has yet to arrive.
Why have these indicators collectively failed? Is it due to temporary deviations, or has the market structure undergone a fundamental change? PANews has systematically analyzed the eight widely discussed failed indicators.

Four-Year Cycle Theory: The Halving Supply Shock Is Becoming Insignificant
The four-year cycle is the most widely accepted rule in the crypto market, suggesting Bitcoin follows a fixed rhythm driven by halving events: accumulation before halving, explosive growth 12-18 months after, a peak with 75%-90% decline, and then a bottoming out before restarting. The halvings in 2012, 2016, and 2020 have validated this pattern well.
However, after the April 2024 halving, the market did not experience the typical explosive rally seen in previous cycles. Bitcoin’s annualized volatility has dropped from over 100% historically to about 50%, showing more “slow bull” characteristics. The decline in bear markets has also narrowed: in 2022, the drop from peak to trough was 77%, less than 86% in 2014 and 84% in 2018.
Discussions about the failure of the four-year cycle are widespread on social media. The mainstream view is that the entry of institutional funds has fundamentally changed the microstructure of the market.
First, Bitcoin spot ETFs in the US have continuously absorbed capital, creating sustained demand and breaking the simple narrative driven solely by halving.
Second, on the supply side, the 2024 halving reduced block rewards to 3.125 BTC, decreasing daily new supply from about 900 BTC to 450 BTC, with an annual supply reduction of approximately 164,000 coins. This halving lowered Bitcoin’s annual inflation rate (supply growth) from 1.7% to about 0.85%, with the reduced supply amounting to only 0.78% of the total 21 million coins. Compared to the market cap of trillions of dollars, this supply reduction’s actual impact is negligible.

Pi Cycle Top: Lower Volatility Makes Moving Averages Cross Less Likely
Developed by Philip Swift, the Pi Cycle Top indicator identifies market tops by observing when the 111-day moving average crosses above twice the 350-day moving average. This indicator accurately signaled tops in 2013, 2017, and April 2021.

In the 2025 bull cycle, the two moving averages never produced a valid crossover, and the indicator remained “silent.” Yet, the downward trend in the market was already quite clear.
The reason for this failure may be that Pi Cycle Top relies on significant price volatility to generate crossovers—when short-term moving averages diverge sharply from long-term ones. As Bitcoin’s volatility structurally declines, especially with ETF and institutional participation, price movements have become smoother. The parabolic rises driven by retail investors have diminished, making the conditions for moving average crossovers less likely. Additionally, this indicator is essentially a curve fit based on early adoption phases (2013–2021). After structural changes in market participation, the parameters fitted in early periods may no longer be applicable.

MVRV Z-Score: Changes in Market Size and Holding Patterns Alter the Basis of Calculation
The MVRV Z-Score is an on-chain valuation metric comparing Bitcoin’s market value (current market cap) with realized value (the total value based on the last on-chain movement price per coin). Traditionally, a Z-Score above 7 signals overbought conditions, while below 0 indicates extreme undervaluation.

In practice, even at the 2021 cycle top, the Z-Score did not reach previous cycle highs; the fixed threshold (>7) was not triggered. By 2025, although Bitcoin topped out, the highest Z-Score was only 2.69.
Possible reasons include:

1. Institutional high-cost buying and long-term holding have systematically elevated the realized value close to the market value, compressing the Z-Score’s volatility range.
2. Short-term active traders’ high-frequency movements continually “refresh” the realized value near current prices, further narrowing the gap between market cap and realized value.
3. As the market cap expands, generating the same extreme Z-Score as in early cycles requires exponentially larger capital.

The combined effect is that the Z-Score’s ceiling has been structurally lowered, making the original “7 = overbought” threshold impossible to reach.

Rainbow Chart: The Logarithmic Growth Assumption Is Being Broken
The Bitcoin Rainbow Chart uses a logarithmic growth curve to fit long-term price trends, dividing price ranges into color bands from “extremely undervalued” to “bubble peak,” helping investors identify buy and sell signals. In 2017 and 2021, when prices reached high color bands, they indeed corresponded to cycle tops.

However, during the entire 2024–2025 bull cycle, Bitcoin’s price only stayed within the neutral “HODL!” zone, never approaching the deep red “bubble” zone. The chart’s top prediction function has almost no effect.
For the rainbow indicator, the model treats price as a function of time, ignoring halving, ETFs, institutional funds, macro policies, or other variables. Additionally, the decline in volatility brought by institutional participation reduces the deviation of prices from the trend line, making the fixed-width color bands less reachable. Furthermore, Bitcoin’s growth is transitioning from the “steep segment of the S-curve” of adoption to the “slow growth phase of a mature asset.” The exponential extrapolation of the logarithmic function overestimates actual growth, causing prices to long remain below the centerline.

Altcoin Season Index and BTC Dominance: The Premise of Capital Rotation Has Changed
The Altcoin Season Index measures the proportion of the top 100 altcoins outperforming BTC over the past 90 days; a value above 75 indicates “altcoin season.” BTC Dominance (Bitcoin’s market cap share) falling below 50% or 40% signals capital flowing from BTC to altcoins. In 2017, BTC dominance dropped from 85% to 33%, and in 2021 from 70% to 40%, corresponding to major altcoin rallies.

However, throughout 2025, the Altcoin Season Index remained below 30, staying in a “Bitcoin season” zone. BTC dominance peaked at 64.34% and never fell below 50%. Early 2026, the so-called “altcoin season” is more about precise narrative-driven rotations, benefiting only specific sectors like AI and RWA, rather than broad rallies like in previous cycles.
The deeper reason for these indicators’ failure is that, with institutional and ETF funds dominating, these funds’ risk appetite for Bitcoin remains significantly higher than for altcoins. Additionally, large capital inflows have been siphoned into AI and precious metals markets amid market frenzy, reducing overall crypto inflows. The incremental capital attracted by Bitcoin ETFs flows directly into BTC, and these funds are structured as financial products, not entry tickets into the crypto ecosystem. Moreover, the narrative exhaustion in the altcoin ecosystem and weakening liquidity support for new projects are also key reasons why altcoin season has not materialized.

Fear and Greed Index: Retail Sentiment Is No Longer the Price Driver
The Crypto Fear and Greed Index combines factors like volatility, market momentum, social media sentiment, and Google Trends into a 0–100 score. The classic approach is to buy when extremely fearful and sell when extremely greedy.

In April 2025, the index dropped below 10, lower than during the FTX collapse, but Bitcoin did not experience the expected sharp rebound afterward. The 30-day average for the year was only 32, with 27 days in fear or extreme fear zones. As a top indicator, it is also unreliable. At the market high in October 2025, the index was only around 70.
The core reason for the failure of the Fear and Greed Index is that the transmission mechanism between sentiment and price has been broken by institutional funds. When retail investors are fearful, institutions may be buying the dip; when retail investors are greedy, institutions might be hedging with derivatives. This disconnect means retail sentiment no longer drives price movements.

NVT Ratio: On-Chain Transaction Volume No Longer Reflects True Economic Activity
The NVT ratio, called the “Crypto Price-to-Earnings ratio,” divides network value (market cap) by daily on-chain transaction volume. A high NVT may indicate overvaluation; a low NVT suggests undervaluation.

In 2025, the indicator showed contradictory signals: in April, before a large price increase, the NVT Golden Cross reached 58; by October, when prices hit around $120,000, it indicated undervaluation.
The fundamental reason for NVT’s failure is that the on-chain transaction volume, the denominator, no longer accurately represents Bitcoin’s real economic activity.

S2F Model: Only Looks at Supply, Not Demand
The Stock-to-Flow (S2F) model was proposed by anonymous analyst PlanB in 2019, borrowing precious metals valuation logic. It measures scarcity by the ratio of Bitcoin’s stock (total supply) to its annual production (flow), fitting a price prediction curve via logarithmic regression. The core assumption is that after each halving, the S2F ratio doubles, leading to exponential price increases.

In terms of failure, in December 2021, the model predicted Bitcoin should reach about $100,000, but the actual price was around $47,000—more than 50% off. In 2025, the target was $500,000, but the actual price was only about $120,000, with a deviation exceeding three times.
The fundamental reason for S2F’s failure is that it is purely a supply-side model, ignoring demand-side variables. Moreover, as Bitcoin’s market cap reaches trillions, exponential growth becomes physically harder to sustain, and diminishing marginal effects are unavoidable.

The Real Issue Is Not a Single Indicator, but the Shared Market Assumptions
Viewing these indicators collectively reveals that their failures are not isolated incidents but point to the same structural changes:

• Institutional shifts have altered the microstructure: Bitcoin ETFs, corporate treasury allocations, CME derivatives, and pension fund entries have fundamentally changed capital structures and price discovery mechanisms. Institutions tend to buy on dips and hold long-term, smoothing out volatility previously driven by retail sentiment. This makes all indicators relying on extreme volatility or sentiment signals less effective.
• The siphoning of funds into AI and precious metals markets, along with declining market liquidity, has reduced overall crypto inflows.
• Structural decline in volatility is a direct technical reason for many indicators’ failure: Pi Cycle Top and rainbow charts require extreme price moves to trigger signals; MVRV needs large deviations between market cap and cost basis; funding rate indicators need extreme leverage imbalances. As volatility drops from 100% to 50%, these conditions become harder to satisfy.
• Bitcoin’s “asset type” is shifting: from a digital commodity to a macro financial asset. Its price drivers are moving from on-chain variables (halving, on-chain activity) to macro factors like Federal Reserve policies, global liquidity, and geopolitical risks. Indicators focused on on-chain data face a market increasingly dominated by off-chain factors.
• The representativeness of on-chain data itself is declining: Layer 2 transactions, exchange settlements, ETF custody modes—all these trends erode the data foundation of on-chain indicators like NVT and MVRV, making it harder to capture the full picture.
• Many classic indicators are based on curve fitting over just 3-4 halving cycles, with very small sample sizes. After market regime changes, they tend to fail.

For individual investors, the collective failure of these indicators may convey a simpler message: understanding each indicator’s assumptions and boundaries is more important than seeking a universal predictive tool. Over-reliance on any single indicator can lead to misjudgments. During a period when fundamental rules are being rewritten, maintaining cognitive flexibility may be more pragmatic than chasing the next “all-in-one” indicator.