1. The failure of historical predictive logic: the paradigm shift from “retail dominance” to “institutional pricing.”
In the past decade, Bitcoin's price fluctuations in the fourth quarter have been mainly driven by retail investment, combined with the scarcity expectations brought by the “halving cycle” (the block reward is halved every four years), resulting in a regular characteristic of “year-end surges.” For example, in Q4 2017, a retail speculative frenzy drove Bitcoin from $6,000 to nearly $20,000; in Q4 2020, under the liquidity easing after the pandemic, retail funds once again dominated the price, rising from $10,000 to $29,000. This historical pattern has led analysts to habitually consider “time points” as the core basis for predictions, while ignoring the fundamental shift in the core driving forces of the current market.
Today, institutional funds have replaced retail investors as the dominant force in Bitcoin pricing, directly rewriting the logic of seasonal volatility. According to data disclosed by institutions such as CoinShares and Grayscale, as of the third quarter of 2024, the cumulative net inflow of global Bitcoin ETFs (exchange-traded funds) has reached $54.75 billion, with the U.S. spot Bitcoin ETF contributing over 80% of the capital — a single product from BlackRock, IBIT, has seen net inflows surpassing $20 billion. The large-scale entry of institutional funds has not only changed the holder structure of Bitcoin (currently, institutions hold 31% of Bitcoin supply, up 24 percentage points from 2020) but has also significantly reduced market volatility: data shows that the average daily volatility of Bitcoin in 2024 has dropped from 4.2% in 2020 to 1.8%, and the trading range has shrunk from 'thousands of dollars of fluctuation' to 'oscillation within thousands of dollars', making the volatility environment required for traditional 'year-end peaks' no longer exist.
Second, the core error assumption of peak forecasting: Ignoring 'structural changes'
Currently, some analysts still use the 'historical cycle timing bet' model (such as 'peaks reached 12-18 months after halving', 'Q4 seasonal rises'), but overlook three key structural changes, resulting in deviations between forecasts and market reality:
Error assumption 1: The funding-driven logic remains unchanged
Traditional forecasts believe that 'retail fund inflow is the core driving force of prices', but the current increase in Bitcoin's funds mainly comes from institutional allocation demand — for example, pensions and family offices are allocating Bitcoin as an 'anti-inflation asset', which has characteristics of 'long-term holding, low-frequency trading', and will not enter and exit due to seasonal emotional concentration like retail funds, making it naturally difficult to form 'Q4 short-term peaks'. For example, in Q3 2024, despite being in the traditional 'pre-heating period', the net inflow of institutional funds grew only 3% quarter-on-quarter, far below the 25% growth rate of the same period in 2020, and the price remained within the range of $45,000 - $50,000, without the expected 'pre-heating rise'.
Error assumption 2: The disconnection between macro factors and Bitcoin
Past predictions often viewed Bitcoin as an 'asset independent of macroeconomic factors', but the correlation between Bitcoin and macroeconomic policy has significantly increased. The Federal Reserve's interest rate policy and the global liquidity environment directly affect institutional allocation willingness: during the Federal Reserve's rate hike cycle in 2023, net inflows into Bitcoin ETFs decreased by 18% quarter-on-quarter; after expectations of rate cuts rose in 2024, net inflows began to recover. This means that 'Q4 peaks' are no longer solely determined by Bitcoin's own cycle but also rely on the macro policy window — if the Federal Reserve maintains high interest rates at the end of the year, even if it is in the traditional 'peak season', institutional funds may still take a wait-and-see attitude, thus rendering peak forecasts ineffective.
Error assumption 3: Static understanding of scarcity logic
Traditional forecasts regard 'scarcity brought about by halving' as the core logic for price increases, but the current scarcity has shifted from 'fixed total supply' to 'reduced circulation caused by institutional locking'. According to Glassnode data, among the Bitcoin held by institutions, 90% of the holdings have exceeded 6 months, remaining in a 'long-term locked' state, resulting in the actual circulating Bitcoin supply decreasing by 15% compared to 2020. This 'passive scarcity' differs from traditional 'halving scarcity': the former is caused by long-term allocation behavior leading to reduced circulation, which will not trigger 'scarcity speculation' at specific time points like the latter, thus making it difficult to create 'short-term peaks' and more likely to drive prices to 'rise slowly over the long term'.
Third, reinterpreting Bitcoin price predictions: from 'timing bets' to 'logical deductions'
A more reasonable predictive logic should be based on the dynamic deduction of 'macroeconomic policy + institutional behavior + scarcity', rather than rigid historical timing bets. For example, some institutional analysts predict that 'Bitcoin prices will exceed $200,000 in 2025'; their core basis is not 'Q4 seasonality', but rather three long-term logics:
First, after the Federal Reserve enters a rate-cutting cycle, global liquidity easing will enhance institutions' allocation to alternative assets; second, the size of Bitcoin ETFs is expected to exceed $100 billion in 2025, further tightening circulation; third, the application of blockchain technology in areas such as cross-border payments and supply chain finance will enhance the actual value support of Bitcoin. These logics point to a 'long-term trend', rather than a 'short-term quarterly peak', and indirectly verify the limitations of traditional Q4 peak forecasts.
In summary, the errors in predicting Bitcoin peaks in the fourth quarter fundamentally stem from the neglect of the structural transformation of the market from 'retail dominance to institutional dominance'. In the future, if historical cycle models are still used for timing bets, it will not only be difficult to capture price trends but may also lead to investment decision errors due to misjudgment of market logic. Understanding institutional fund behavior, the relationship with macroeconomic policy, and the new form of scarcity is the core premise for grasping Bitcoin's price direction.#etf以太坊
