As of March 31, in the time zone of UTC+8, the price of Bitcoin is oscillating at a high level, with the Bitcoin spot ETF recording a slight net inflow of approximately 1,090 BTC (about $7.324 million) for the day, but its 7-day moving average has remained in a net outflow range, making the divergence between short-term "blood return" and medium-term "blood loss" increasingly apparent. At the same time, both Ethereum and SOL-related ETFs have also seen net outflows, combined with approximately $306 million in liquidations in a single day according to CoinGlass statistics, the market is in a sensitive phase of simultaneously contracting high leverage and risk appetite. In the context of significantly reduced institutional demand, where is the capital coming from and where is it flowing to? The reduction in holdings by mining companies, movements of large whales to exchanges, and the game of short-term leveraged positions have become key clues to understanding the current market structure.

Single-day recovery but unable to halt weekly blood loss

On March 31, Lookonchain data showed that the U.S. Bitcoin spot ETF had a total net inflow of approximately 1,090 BTC in a single day, corresponding to about $7.324 million, providing some support to the price. From a single-day perspective, the marginal warming of ETF capital corresponds to Bitcoin stabilizing near a key support level, indicating that some funds are still willing to attempt left-side positioning after a pullback.

However, when viewed over a week-long perspective, according to Glassnode's monitoring, the 7-day simple moving average (7D-SMA) of Bitcoin ETF has been continuously net outflowing for several days, with daily outflows roughly in the range of 200-500 BTC, marking the first time since the approval of the spot ETF in January that such a persistent and clearly directional net outflow phase has appeared. Glassnode points out that 7D-SMA turning negative indicates that institutions are showing obvious hesitation at the current price level, leaning more towards reducing positions or rotation rather than continuing large-scale accumulation.

This dislocation of "daily net inflow and weekly net outflow" reflects that the structure of capital is becoming polarized: on one hand, short-term capital is utilizing a retreat in sentiment and technical support levels to enter the market and play for rebounds, pushing single-day data into positive territory; on the other hand, medium-term allocation funds are continuously reducing holdings over a longer time dimension, transferring chips to trading subjects with a higher risk appetite. Rebound buying pressure coexists with trend-based reduction, meaning that behind the apparent price stability lies a process of institutional rotation and risk transfer.

Ethereum and SOL funds retreat, overall risk appetite downgrades

In contrast to the slight net inflow of the Bitcoin ETF for the day, Lookonchain data showed that Ethereum ETF had a net outflow of approximately 4,079 ETH on March 31, with a capital scale of about $8.44 million; SOL ETF simultaneously net outflowed about 72,525 SOL, equivalent to $5.95 million. In the absence of major systemic negative factors, this synchronized outflow appears more like a withdrawal of risk appetite targeting high beta assets.

In context, some opinions suggest that the outflow of ETH funds may be somewhat associated with the decline in on-chain staking and related strategy yields following the Dencun upgrade, with some funds that previously participated in ETH long positions through the ETF choosing to reduce leverage and exposure after adjusting their yield expectations. However, it should be emphasized that this association is currently merely a correlation hypothesis rather than a validated direct causation, and specific motivations still require more on-chain and holding data corroboration.

Regardless of the specific drivers, capital behavior has already signaled: while BTC still has a slight net inflow, ETFs for high-elasticity assets like ETH and SOL have shown more obvious net outflows, indicating that institutions and large funds are collectively downgrading risk settings, retreating from high beta to "relatively safer" targets. For the broader altcoin sector, such capital outflows at the ETF level often influence through two main paths: one, compressing passive and active allocation demand related to high beta assets and weakening liquidity support during subsequent upward movements; two, during overall risk appetite declines, creating suppression on altcoin sectors' beta trading and leveraged games, widening the extent of chasing rallies and liquidity withdrawal.

$300 million in liquidations and stubborn leveraged longs

The changes in leveraged positions also deserve attention. CoinGlass data shows that as of March 31, the entire market saw total liquidations of approximately $306 million in a single day, with BTC-related positions liquidated at around $123 million and ETH at about $91.11 million, with the rest being other assets. The volume of such liquidations indicates that a considerable portion of high-leverage capital has been passively forced out during the previous declines and oscillations.

More noteworthy is the long-short structure. According to CoinGlass statistics, the day's long-short liquidation ratio was about 1.6:1, with the long liquidation scale significantly exceeding that of the shorts, indicating that even after experiencing a round of concentrated liquidations, the market's leveraged structure still clearly leans towards the bullish side, as long leverage has not been completely cleared. In other words, there remains a considerable amount of aggressive capital betting on a continuation of price strength or even rapid rebounds.

Contrasting this with the cooling of ETF funds, a typical risk mismatch emerges: while institutions are continuing to net out through ETFs and reducing exposure, some in-market traders choose to "counter-trend leverage" and play for rebounds. This structure of "long positions reducing while short-term plays are all-in" makes it so that the market has already buried potential liquidation chains before a significant price breakdown occurs. If subsequent ETF fund outflows continue, and price momentum fails while spot support is weakened, the remaining long leverage could trigger a second round of concentrated liquidation pressure, resulting in more intense volatility to clear risks.

Mining companies' sell-offs and AI transitions change the supply side

Changes on the supply side are also happening. According to a single source disclosure, the Bitcoin mining company Bitfarms has realized approximately $28.2 million in profits by selling part of its BTC holdings. It is important to note that the public information does not disclose the specific amount of BTC sold or its proportion of total holdings, so any precise estimation of the sell-off scale falls within the realm of informational deficiencies, making it impossible to derive detailed changes in holding structures from this.

More structurally significant is the directional choice: Bitfarms' announcement to enter the AI computing business is seen as a reflection of the broader trend of mining companies collectively transitioning to AI around 2026. During the halving cycle, the traditional model relies on "stockpiling coins and waiting for price increases" to hedge against production decline risks, while transitioning to "selling coins for cash and investing in AI computing or data centers," indicates that mining companies are becoming more inclined to secure real profits and diffuse risks from single asset price fluctuations in their asset liability management and cash flow.

Such behavior has two layers of impact on the market: in the short term, shifting from "increasing inventory" to "selling coins for cash" will increase the selling pressure on the spot market, enhancing on-chain circulating supply, particularly when prices are high or in oscillation ranges, as mining companies tend to sell at highs to retrieve funds; in the long term, as BTC output declines post-halving, and some computing power and capital flow towards AI fields, mining companies' structural selling capacity and willingness for BTC might marginally decrease, presenting an opportunity for supply tightening over a longer cycle.

If more mining companies follow Bitfarms' lead to concentrate on selling BTC within the same time window to support AI expansion or other capital expenditures, then in the short term, BTC's on-chain net supply will show a phase increase, and the pace of selling will further distance itself from the traditional logic of "producing means selling." Investors need to pay attention to whether the selling pressure from mining companies is amplifying in resonance with ETF fund outflows, forming a response in sensitive market areas that exaggerates the price's reaction to negative capital flows.

Large whales transferring to exchanges: Real sell-off or speculation?

Outside of institutions and mining companies, the movements of whales provide another clue for market observation. Single-source information indicates that a certain whale transferred approximately 600 BTC to Binance around March 31, worth about $40.41 million at the time. Since this data is currently only reported in a single channel, credibility and completeness must be approached with caution and cannot be viewed as a comprehensive reflection of overall whale behavior.

Traditionally in on-chain analysis, "large BTC transfers to exchanges = potential selling pressure" is a common conclusion, but it is important to emphasize: transferring to exchanges merely represents assets entering a tradeable state and should not be directly equated with an actual sale that has occurred or is inevitable. Whales may choose to place orders to reduce positions, or may only use transfers for hedging, staking, market making, or preparing for future trades; the specific intention needs to be verified with subsequent transaction volumes and on-chain capital trajectories.

When looking at the behaviors of large whales alongside ETF fund outflows, there are generally two possible paths: one is that whales actively take on positions during the phase of ETF institutions reducing their positions, achieving medium to long-term layouts at lower premiums or better prices; the other is that in a context where leveraged long sentiment remains strong and prices are relatively firm, they choose to transfer their chips to exchanges for selling at highs, possibly driving partial upward movements and then selling at peak. These two paths have completely different directional impacts on price and liquidity, and therefore cannot be concluded lightly.

A more cautious approach is to continuously monitor whether these whale addresses subsequently exhibit large sell orders, spot outflows, or further capital interactions with other exchanges or wallets, and correlate this with actual transaction volumes, order book depth, and ETF net inflow and outflow data to judge the nature of their selling pressure or support, thus more accurately grasping the true impact of whales on market structure.

Short-term rebounds and medium-term retreats pulling against each other

In summary of the above dimensions, the current market presents a pattern of coexisting short-term rebounds and medium-term retreats: on March 31, the Bitcoin spot ETF recorded a slight net inflow of approximately 1,090 BTC, but the 7-day moving average continues to show net outflows; ETFs for Ethereum and SOL showed more obvious single-day net outflows, reflecting a contraction in risk appetite towards lower beta assets; the leveraged market, after experiencing approximately $306 million in total liquidations, with long liquidations being about 1.6 times that of shorts, still leans bullish structurally. These fragmented signals collectively point to the fact that while prices have not yet exhibited extreme trends, the internal structures of funds and leverage are already in adjustment.

In causal judgments, it is necessary to maintain sufficient restraint. The flow of ETF funds, mining companies' selling and transitioning behaviors, and large whales transferring to exchanges can only be described as "concurrent events" occurring within the same time window; their mutual influences and whether one drives the other lacks sufficient data to support linear, singular causal chain assertions. Simply attributing price fluctuations to a single action from one party is neither rigorous nor does it help to mitigate noise.

For investors, a more actionable approach is to establish a quantifiable tracking observation framework:

● On the ETF side: Continuously focus on the net inflow/outflow changes of the 7D-SMA of Bitcoin spot ETF, observing points of convergence or even reversal from continuous net outflows; simultaneously observe whether there are any capital inflows for mainstream asset ETFs like ETH and SOL to determine if risk appetite stabilizes.

● On the supply side and on-chain behavior: Track the overall holding trends and selling rhythm of mining companies, observing if there is a gathering of more "selling coins for cash + investing in AI" behaviors; alongside monitoring BTC's net inflow/outflow from exchanges and large whale addresses' capital transfer situations to gauge the dynamic balance of spot selling pressure and support.

● On leverage and liquidation structures: Combine data from CoinGlass and others to monitor long-short position ratios and liquidation distributions, and raise risk caution during stages where long leverage becomes too concentrated and ETFs are still net outflowing, being alert to the possibility of secondary liquidations amplifying volatility.

Under the current conditions, a relatively neutral judgment is: if the net outflow trend of institutions through ETFs continues while in-market leveraged longs do not significantly cool off, it is more likely that the market does not directly enter unilateral declines or straight line increases, but rather goes through a period dominated by range oscillations and phase liquidations for repricing. In such an environment, compared to chasing short-term extreme scenarios, data-driven, rhythm-based position management and risk control are often more critical.

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