As of the end of the first quarter of 2026, in the East Eight Time Zone, the paper losses of large Bitcoin holders were quickly realized as actual losses. Shark and whale addresses recorded a total of approximately 30.9 billion dollars in realized losses during this quarter, averaging about 337 million dollars per day, a figure that is extremely prominent in historical cycles. Statistics from Glassnode and several media outlets show that this intensity of loss has approached extreme levels seen during the 2022 bear market, implying that some funds chose to "cut losses and exit" amidst significant pain. In this round of selling pressure, the capitulation-style selling by large addresses intertwined with rising macro risks became a key clue driving market sentiment from high optimism to caution and wait-and-see.

Daily losses of 337 million dollars: large holders collectively press the stop-loss button

In the first quarter of 2026, the most influential fund group on the Bitcoin chain—holders of 100–1,000 BTC "sharks" and 1,000–10,000 BTC "whales"—rarely synchronized to enter a phase of realized losses. Statistics show these two groups had average realized losses of approximately 188.5 million dollars and 147.5 million dollars per day, respectively, totaling nearly 337 million dollars per day, indicating that the sell-off was both concentrated and sustained, rather than isolated actions by individual large holders.

Glassnode provided more representative chain observations in early April, East Eight Time Zone: Addresses holding 0.1K–10K BTC had a 7-day moving average of realized losses exceeding 200 million dollars per day, clearly defined as a typical characteristic of "capitulation-style selling." This indicates that a considerable portion of funds chose to passively or actively stop losses under significant losses, rather than calmly adjusting positions or taking profits at high levels.

From a longer time dimension, the 30.9 billion dollars in cumulative realized losses for the quarter concentrated in the first quarter of 2026, rather than being a result of a few days' “black swan” shocks. The magnification of losses shows a clear phase: first, the marginal deterioration of macro conditions and sentiment led to increased daily losses, followed by a period of sustained high levels, which then gradually converged. This structure of "continuous high losses over several weeks" illustrates that the selling pressure did not occur instantaneously but rather represents a genuine clearing process.

Loss scale approaches the low point of the 2022 bear market

When referring to historical cycles, the current round of paper losses for large holders has approached the intensity of the last deep winter. Research data indicates that the 30.9 billion dollars of realized losses in the first quarter of 2026 is comparable to peak ranges during the 2022 bear market, with several institutions and media describing it as "close to 2022 bear market levels." Despite prices not necessarily returning to historical lows, similar loss amounts to those seen in deep bear phases highlight the extremity of current market pressures.

This also means that the current position of Bitcoin is not simply a "new price low replication," but rather a loss concentration release resulting from the "resetting of profit structures and chip structures." The last deep bear market often appeared during periods of continuous price breakdown and universally pessimistic market expectations, while this round is more of a result of repeated corrections of high-level optimism and the gradual accumulation of trapped positions, triggered by a more severe adjustment leading to massive loss clearing.

Historically, large holders near cycle turning points are often not the first to exit but rather tend to concentrate their losses during extreme panic, liquidity tightness, or passive clearances due to risk control. The 2022 bear market followed this pattern, and this round has similar shadows: the "strong hands" that persisted in holding over a longer period ultimately chose to exit with significant losses under the dual pressures of sentiment and macro conditions.

However, unlike in the past, this round of losses has a more "compressed" rhythm—quickly accumulating to levels close to the losses of the previous bear market within a quarter, rather than consuming slowly over a long time. This difference in intensity and rhythm lays more complex variables for the subsequent price and sentiment recovery path: on one hand, a large amount of historical costs is quickly reset; on the other hand, the collapse of market confidence is also more sudden and profound.

Macro risks heating up: from inflation expectations to crowded AI trading

The driving force behind this round of massive losses is not solely the chip structure on-chain but rather the resonance with the external macro environment. After entering 2026, global market worries about rising inflation resurfaced, and interest rate path expectations fluctuated repeatedly. The possibility of prolonged high interest rates and interest rate cuts not meeting expectations are suppressing the pricing of risk assets, including crypto assets, causing "high volatility, high risk" assets to become priority candidates for reduction.

At the same time, the penetration of AI-related quantitative and programmatic strategies in the crypto market has significantly increased. A large number of strategies became highly crowded under similar macro signals and price thresholds: when volatility intensified and trend signals were triggered, models might collectively reduce long positions or amplify short positions. This combination of "homogeneous logic + automated execution" has magnified what could have been a slow clearance into a panic-style sell-off within a short period.

In this context, the massive stop-loss by whales and sharks is likely not entirely due to "subjective pessimism," but rather a result of overlapping macro risk aversion sentiments and programmatic selling rules. When inflation expectations rise and the relative returns of safe-haven assets increase, risk control models tend to reduce the weight of high-beta assets; once Bitcoin's volatility and declines trigger model thresholds, most strategies will execute selling or stop-loss instructions indiscriminately, directly pulling on-chain realized losses to magnify.

This also indicates that this round of large losses cannot simply be viewed as "isolated on-chain events beyond macro." Macro variables, through institutional risk control, quantitative models, and funding costs, transmit to the decision-making of large holders, ultimately reflected in the 30.9 billion dollars of quarterly loss data on-chain. Macro is not a static backdrop but one of the important driving forces behind this round of selling pressure.

Emotion and chip migration: who is taking over from the whales

From the perspective of realized losses, the profile of the selling party in this round is relatively clear: high-cost, large position older funds are forced to cut losses and exit. These funds continuously increased their positions or held during the earlier price uptrend, once realizing considerable paper profits, but were gradually eroded in subsequent volatility and macro headwinds. When prices retreated to a certain threshold, some whales and sharks chose to take losses and exit, leaving visible marks of huge losses on-chain.

Corresponding to this is a more decentralized takeover structure. On-chain data and market microstructure simulation show that new chips are more likely to flow to small and medium investors and short-term traders, including funds moving through spot purchase, short-term operations, or even high-frequency strategies. This means that the chips originally concentrated in a few large addresses are gradually migrating into the hands of a broader, more decentralized group, resulting in a decrease in chip concentration.

This redistribution of chips has important implications for subsequent volatility. On one hand, in the short term, due to the limited risk tolerance and faster trading rhythm of new inflows, price fluctuations may be amplified: when faced with adverse news again, small and medium investors are more likely to exit in panic. On the other hand, from a longer cycle perspective, a large portion of potential selling pressure has been released through realized losses, and the "historical high-position chips" from a macro perspective are gradually decreasing, meaning the selling pressure the market encounters in future equal decline periods may be relatively less.

Emotionally, a clear turning point has emerged. Previously, a considerable number of large holders and retail investors built an optimistic expectation based on "long-term bullish logic," but following this round of massive losses and macro uncertainties, the main melody is shifting to "survival first." Fund management, risk control, and leveraged contraction are prioritized, leading to a significant increase in market uncertainty about the future, making it difficult to return to the previous one-sided optimistic atmosphere in the short term.

Price path projection: three possibilities after capitulation-style selling

Combining similar scales of realized loss phases in history, several scenario projections for subsequent price developments can be made without assuming specific price levels. It is important to emphasize that the 30.9 billion dollars in quarterly losses more reflects "behavioral intensity" rather than "absolute price positions," so the focus of interpretation is on rhythm and structure, rather than predicting single points.

Scenario one is a phase rebound after concentrated selling pressure release. In previous cycles, when on-chain realized losses spiked in a short time and then started to significantly decline, it often indicated that active or passive selling had come to an end, and the market entered a "vacuum zone." If marginal improvements occur in the macro environment, alongside whales' addresses halting declines and some slightly increasing their holdings again, prices may have the opportunity to build a short-term rebound on this basis. Observable on-chain signals include: a slowdown in net outflows from large addresses or even a transition to net inflows; daily realized losses converging toward the breakeven zone, etc.

Scenario two is high-level consolidation and weak fluctuations under sustained macro tightening. If the interest rate path remains unfriendly and risk appetites are difficult to restore, Bitcoin may not immediately welcome a strong rebound after completing a round of capitulation-style selling but rather oscillate in a wide range for a long time. At this point, realized loss data will decrease from high levels but will not significantly turn positive, and the market will maintain a state of low trading and repeated testing of support levels.

Scenario three involves another drop amid further deteriorating emotions and external shocks. In this path, this round of capitulation-style selling proves to be just the first phase of clearing; if new macro headwinds or liquidity events arise subsequently, remaining high-cost chips may be forced to exit again, forming a second wave of but relatively smaller realized loss peaks. In this situation, price ranges may be readjusted downward, and the emotional recovery cycle further extended.

Regardless of which of the three paths eventually dominates, key indicators that investors should pay attention to are: whether on-chain losses continue to converge, whether whale and shark addresses shift from net reduction to net increase, and the marginal changes of macro variables (such as interest rate expectations and inflation data). A one-time massive loss does not automatically correspond to the extremes of "bottoming" or "collapse"; what truly holds guiding significance is the combination evolution of fund behaviors and macro environments following the losses.

After whales take losses and exit, how much imagination does Bitcoin still have?

From the data above, we can see that this round of massive realized losses results from the interweaving of three main lines: macro pressures, emotional turning points, and chip migration. On one hand, the uncertainty of inflation expectations and interest rate paths raises holding costs and risk aversion; on the other hand, AI-driven programmatic trading amplifies micro volatility, prompting large funds to clear out amid risk control triggers; ultimately, these factors collectively shaped the approximately 30.9 billion dollars of losses in the first quarter of 2026 and shifted the chips from high-cost large holders to more decentralized new inflows.

In the short term, the panic and intense volatility arising from this clear-out are difficult to avoid; market sentiment often goes through a more cautious and even pessimistic phase following capitulation-style selling. However, structurally, a large amount of realized losses also means that some historical holding costs have been reset, and potential selling pressure has been digested in terms of price and time to a considerable extent. The key for the next stage lies in whether there is new incremental capital and narrative fundamentals to take over, rather than relying simply on "previous high-level liquidity returning."

In such an environment, a more rational approach is to: continuously monitor on-chain large address position changes, directional shifts in realized profit and loss indicators, and macro-level inflation, interest rate, and liquidity signals, rather than being swayed by one-time loss data to make extreme decisions. For medium to long-term participants, what matters is not "how much was lost on a particular day," but "who is exiting, who is entering, and whether their pricing logic for the future has fundamentally changed."

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