Introduction
Since the beginning of this year, the BTC market has exhibited a notable phenomenon: price, open interest (OI), funding rates, and liquidation volumes have repeatedly moved out of sync or even diverged significantly. Under conventional market logic, a trending rally is typically accompanied by rising prices, expanding OI, and positive or increasing funding rates, reflecting continued inflows of leveraged long positions. During market declines, falling prices are generally associated with contracting OI, weaker funding rates, and larger long liquidations. However, this relationship has not consistently held across multiple market cycles this year.
Particularly noteworthy is that during several sharp sell-offs, BTC prices continued to fall even after OI had already declined substantially, funding rates had dropped rapidly or turned negative, and concentrated liquidations had occurred. Prices subsequently stabilized or rebounded. In other words, deleveraging in the derivatives market sometimes appeared to complete the process of risk reduction before spot prices reached a bottom.
This raises a more trading-relevant question: Can deleveraging predict BTC rebounds?
Accordingly, this report examines whether stable relationships exist between BTC price, open interest, actual long and short liquidation volumes, and funding rates. We test whether sharp declines in OI, elevated liquidation intensity, and negative funding rates can predict BTC rebounds or lower volatility over the subsequent 1–14 days.
The test period begins in 2025. We find that among the 13 events in which the daily decline in OI fell into the lowest 10% of its own trailing 90-day distribution while BTC closed higher on the same day, average forward returns over 1, 3, 7, and 14 days were +0.38%, +2.00%, +1.45%, and +2.10%, respectively. Among the 22 events in which funding recovered from negative to non-negative while BTC closed higher, corresponding returns were +0.63%, +0.35%, +0.86%, and +1.04%. In the 21 events where elevated long liquidations occurred alongside a price decline on the previous day and BTC turned positive the following day, subsequent returns were +0.39%, +0.24%, +1.05%, and +0.91%.
Overall, deleveraging pressure is not unconditionally positively correlated with subsequent rebounds. Only when OI contraction, funding recovery, or long liquidations are followed by confirmation that prices have stopped falling do forward 1–14 day returns become more likely to turn positive.
1. Backtesting the Four Indicators in 2026
1.1 What Does Each of the Four Indicators Tell Us?
1.1.1 Price: The Final Outcome, Not the Source of Positioning
- Price reflects the combined outcome of all spot and derivatives trading activity. A price increase may be driven by spot buying, newly opened futures longs, short stop-losses, or short covering. A price decline may result from spot selling, newly established short positions, long stop-losses, or forced liquidations. Price alone therefore cannot identify the source of the underlying positioning.
1.1.2 OI: How Much Contractual Risk Remains in the Market
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OI measures the total amount of outstanding contracts. Rising OI indicates that new risk positions are entering the market, while falling OI indicates that positions are being closed. However, OI itself does not reveal whether long or short positions are being closed.
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A price decline accompanied by falling OI may reflect long stop-losses, forced liquidations, or voluntary deleveraging. A price increase accompanied by falling OI may instead reflect short covering. These two situations can have completely different implications for future returns.
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Therefore, neither “rising OI = bullish” nor “falling OI = bearish” is valid by definition. In this report, we use total open interest measured in BTC rather than in U.S. dollar value, because the BTC-denominated measure more closely captures whether the number of contract-risk units remaining in the market is increasing or decreasing.
1.1.3 Funding: The Cash Flow That Corrects the Premium Between Perpetual Futures and Spot Prices
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Funding is a periodic cash flow exchanged between long and short positions. Positive funding is generally paid by longs to shorts, and vice versa. Funding is also influenced by basis, interest rates, trading costs, and arbitrage constraints.
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In this report, actual funding settlements within each day are aggregated and converted into basis points per day.
1.1.4 Liquidation Volume: Forced Deleveraging That Has Already Occurred
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The key difference between liquidations and OI or funding is that liquidation data capture the point at which risk moves from being “potential” to “realized.”
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Long liquidations typically occur during rapid price declines, while short liquidations usually occur during sharp rallies. We use daily liquidation amounts from Gate’s publicly available derivatives statistics and divide them by USD-denominated OI from the same source to calculate liquidation intensity, avoiding direct comparisons of absolute liquidation amounts across markets of different sizes.
1.2 Backtest Results
Underlying: BTCUSDT Perpetual Contract
Full test period: January 1, 2025–August 24, 2026, covering 601 UTC daily observations
Year-to-date observation period: January 1, 2026–August 24, 2026, covering 236 observations
In the chart above, the blue line represents BTC perpetual futures prices, while the orange line represents BTC-denominated OI. The middle-panel bars show cumulative daily funding, with the black line representing its 14-day moving average. The lower panel shows actual long and short liquidation amounts on Gate, together with the 14-day moving average of total liquidations. Purple triangles indicate confirmation days when BTC turned positive following long liquidations. Liquidation data begin on March 1.
1.2.1 January–February: From “Price Down, OI Unchanged” to Concentrated Deleveraging
BTC fell 11.4% in January, while OI declined by only 0.4% and average daily funding remained as high as +1.48 basis points. In other words, although prices had already weakened materially, the number of outstanding perpetual contracts and the cost of holding long positions had not contracted accordingly.
January 20 and January 29 were particularly representative. BTC fell 4.5% and 5.2% on those dates, respectively, while OI increased by 5.2% and 4.9%. This phase therefore resembled “continued position building during a decline,” with risk being postponed rather than removed.
January 31 marked the first major deleveraging point: BTC fell 6.5% in a single day, OI declined 8.4%, and more than $2.4 billion in long positions were liquidated.
In February, BTC fell another 13.0% during the month, OI declined 13.6%, and average funding turned negative to −0.23 basis points. The market shifted from the earlier regime of “falling prices with resilient positioning” to one in which price, positioning, and holding costs contracted simultaneously.
February 5–6 best illustrates the “pressure–confirmation” framework among the four indicators. BTC plunged 14.0% on February 5. On February 6, BTC rebounded 12.2%, while OI continued to fall by 8.2% and funding dropped to −2.88 basis points.
This rebound was not driven by an aggressive influx of newly leveraged longs. Instead, it more closely resembled a deleveraging rebound following the exit of existing positions and increasingly crowded short exposure. Price, OI, and funding collectively indicated a clear washout inflection point.
1.2.2 March–April: Price and OI Recover in a Negative-Funding Environment
In March, the market transitioned from deleveraging to position rebuilding. BTC rose 3.8% during the month and OI increased sharply by 14.6%, while average daily funding remained negative at −0.30 basis points. Funding was negative on 61.3% of trading days.
Prices and OI had already recovered, while the cost of perpetual positioning still leaned toward shorts. This indicates that the rally was not accompanied by typical long-side overheating and instead retained some potential fuel from short covering.
March 4 was the first key inflection point during this phase. BTC rose 6.4% in one day, while OI increased 15.5%. Total liquidations reached $32.31 million, of which $30.18 million—or 93.4%—came from shorts.
This represented a rally driven simultaneously by short liquidations and new position formation. Total March liquidations reached $304 million, indicating that the recovery was not smooth but instead took place through repeated compression of both long and short leverage.
In April, BTC rose 12.1% and OI increased 6.9%, extending the co-movement between price and positioning. Meanwhile, average daily funding declined further to −0.59 basis points, with negative funding recorded on two-thirds of all days. Of the $174 million in monthly liquidations, $116 million came from shorts.
Overall, the main driver of the March–April rally was not long-side funding. Rather, the market advanced against a backdrop of negative funding through a combination of short covering, short liquidations, and position rebuilding.
1.2.3 May–June: Price Weakens While OI Remains Elevated, and Long Liquidations Shift from Isolated Events to Concentrated Waves
The relationship among the four indicators began to reverse in May.
BTC fell 5.8% during the month, while OI still increased 1.1% and average funding turned positive to +0.75 basis points. Falling prices, stable or rising contract exposure, and higher costs for long positioning indicated that risk was increasingly concentrating on the long side.
Monthly liquidations increased to $247 million, including $149 million in long liquidations. On May 17, total liquidations reached $28.08 million, with longs accounting for 94.1%. This marked a clear point at which leveraged longs began to exit involuntarily. However, OI did not continue to decline during the month, suggesting that exited positions were quickly replaced by newly opened positions.
June was the clearest long-side capitulation period of the year. BTC fell 17.9% during the month, while total liquidations rose to $475 million, the highest monthly level between March and August. Long liquidations amounted to $330 million, accounting for 69.5%.
A concentrated liquidation cluster emerged from June 1–5. On June 2, BTC fell 6.5%, while long liquidations reached $53.70 million, accounting for 93.4% of the total. Long liquidations of $38.94 million and $31.29 million followed on June 3 and June 4, respectively. On June 5, BTC fell another 4.4%, with long liquidations reaching $51.21 million and accounting for 85.7% of the total.
Notably, OI actually increased by 3.0% over the month. This shows that June was not a complete, one-directional deleveraging event. Instead, it consisted of a cycle of “old longs liquidated—new positions rebuilt—prices remaining under pressure.”
Despite substantial liquidation volumes, a sustainable rebound did not immediately follow. This helps explain why a raw liquidation spike is not a sufficient bottoming signal: as long as OI continues to rebuild and prices have not confirmed stabilization, forced liquidations can occur repeatedly.
1.2.4 July–August: From a Re-Leveraging Rally to a Short-Liquidation-Driven Deleveraging Rally
In July, BTC rose 4.8%, OI increased 5.8%, and average daily funding climbed to +1.83 basis points, reflecting a trend-expansion regime in which price, positioning, and long-side holding costs increased simultaneously.
The monthly liquidation structure shifted back toward short liquidations. Total liquidations reached $178 million, including $108 million from shorts.
The market structure from August 1–26 was markedly different. BTC rose 25.8%, while OI declined 2.7% and funding remained at +1.89 basis points. Of the $315 million in total liquidations, $246 million came from shorts, accounting for 78.0%.
The combination of strong price appreciation without corresponding OI expansion represented the clearest monthly “price up, OI down” divergence of the year. This suggests that forced short covering, rather than continued growth in perpetual long positions, was an important driver of the rally.
Key inflection points were concentrated between August 19 and 21. Over these three days, BTC prices rose rapidly, short liquidations expanded repeatedly, and OI failed to increase proportionally, forming a typical short squeeze and deleveraging-driven rally.
1.3 Interim Conclusions
From the monthly and event-level evolution, the four indicators do not maintain fixed relationships. Instead, the market sequentially passed through four distinct regimes:
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In January, prices declined but leverage resisted exiting.
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In February, prices and OI underwent a joint washout.
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In March and April, the market recovered with negative funding and short liquidations providing support.
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In May and June, prices weakened while OI continued to rebuild, triggering repeated long liquidations.
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In July, the market resumed a leveraged rally.
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In August, large-scale short liquidations accelerated price gains.
Accordingly, shifts in combinations of the four indicators can be summarized as follows:
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Price down + OI up + positive funding usually indicates that risk is still accumulating.
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Price down + OI down + rising long liquidations indicates that deleveraging is occurring.
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Only when prices subsequently turn positive while OI stops expanding or continues to decline do liquidations become more likely to shift from a trend-continuation signal to a rebound-confirmation signal.
2. Data and Testing Methodology: Can Deleveraging Predict a Rebound?
How can the question “Can deleveraging predict a rebound?” be translated into testable indicators?
From a market-behavior perspective, deleveraging may result from forced liquidation after long-side crowding or from voluntary position reductions by investors. Its most direct price manifestation is usually downward pressure on BTC.
In derivatives markets, the process is often accompanied by several typical characteristics: sharply higher liquidation volume, funding turning negative or falling rapidly, and substantial OI contraction. These three variables can therefore serve as basic indicators for identifying whether the market is experiencing concentrated deleveraging.
Likewise, rebound confirmation can be observed through signals such as a sharp decline in OI accompanied by a positive BTC close, or funding recovering from negative to positive.
Specifically, “rebound” is measured using two reproducible criteria:
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Whether cumulative return after the event is greater than zero, defined as the rebound win rate.
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Whether average cumulative return after the event is positive and how it compares with non-event days.
Because confirmation-type signals can only be identified after the confirmation day closes, the earliest executable entry point is the following trading day.
Based on this framework, we use BTC price, OI, funding, and liquidation data since the beginning of this year as underlying variables and divide deleveraging events into three levels:
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Baseline deleveraging signals: Identify whether derivatives markets are undergoing significant leverage contraction, such as a sharp OI decline, extreme funding deterioration, or abnormal liquidation spikes, without imposing any price-direction restriction. These serve as the baseline control group.
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Directional deleveraging signals: Add a price-direction condition to the baseline signal—for example, BTC falling while OI drops sharply—to identify typical episodes in which “price decline + leverage exit” occur simultaneously.
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Price-confirmation signals: Deleveraging remains in progress, but prices begin showing resilience or reversal—for example, OI falling sharply while BTC closes higher—to determine whether the market has moved from “leverage washout” into a “price absorption” phase.
To avoid arbitrarily setting fixed thresholds or selecting ex-post optimal parameters, all abnormal indicators are identified using rolling percentiles. The baseline deleveraging group is retained as a benchmark, while economically meaningful directional and price-confirmation conditions are added step by step to compare the explanatory and predictive power of different signals for subsequent BTC rebounds.
Note: The liquidation-confirmation signal uses the 60th percentile rather than only the most extreme 90th percentile because BTC rebounds often occur near inflection points during sustained liquidation episodes, rather than necessarily at the absolute liquidation peak.
3. Event Results: Positive Relationships Come from Confirmation, Not from Pressure Itself
3.1 Baseline Deleveraging
Neither sharp OI declines nor liquidation spikes produced consistent V-shaped rebounds. Total liquidation spikes were particularly weak as predictive signals because they combine both long liquidations during market declines and short squeezes during rallies, weakening their aggregated directional meaning.
Funding turning negative produced positive average returns across all four horizons and was the raw variable most closely associated with positive forward performance. However, after controlling for same-day returns, momentum, volatility, and trading volume, only the 14-day coefficient reached +2.21 percentage points, with a nominal p-value of 0.100. This still does not meet the threshold for robust statistical significance.
3.2 Returns After Adding Price Confirmation
Average returns were positive across all four horizons for all three confirmation events. None of the 12 results was negative. This represents the main empirical evidence supporting the conclusions of this report.
The economic interpretation is also consistent across signals: deleveraging has already occurred, but prices remain able to close higher despite position exits. This indicates that selling pressure is no longer pushing the market lower and that risk reduction is more likely to transition into a short-term recovery.
After controlling for additional variables, the 3-day and 14-day excess-return coefficients for OI Flush Confirmation were +2.55 and +3.64 percentage points, with nominal p-values of 0.016 and 0.045, respectively. Funding Recovery Confirmation retained positive coefficients across all four horizons, while the 14-day coefficient for Liquidation Rebound Confirmation was +1.45 percentage points.
However, after applying multiple-testing adjustments within the same sample, none of the results remained significant under commonly used thresholds. This means that while the positive relationship is clear in conditional averages, it remains exploratory under stricter standards for independent predictive power.
4. Four Regimes for Assessing BTC Market Conditions
4.1 Scenario A: Price Down, OI Up, Funding Positive, Long Liquidations Still Limited
This is a state in which risk is still accumulating and has not yet been fully released.
Prices are weakening while positioning remains elevated. This may reflect newly opened shorts or longs attempting to buy the dip. Positive funding indicates that the cost of holding long positions remains high.
At this stage, it is inappropriate to interpret “potential deleveraging” as a rebound signal in advance.
4.2 Scenario B: Price Down, OI Down, Long Liquidations Rising, Funding Turns Negative
This represents the most typical form of long-side deleveraging.
All four pieces of evidence indicate that forced selling pressure has already emerged. However, baseline event results show that the impact can still persist.
Therefore, this state should be viewed as an observation zone, rather than an immediate buy signal.
4.3 Scenario C: Long Liquidations on the Previous Day, Price Turns Positive the Next Day, and OI No Longer Expands Rapidly
Liquidations have removed fragile long positions, while prices subsequently refuse to continue falling. Conditional average returns over the next 1–14 days tend to be positive.
If funding simultaneously recovers from negative levels, this suggests that the shorts’ advantage is also weakening, improving signal quality.
Actual execution must take place after the confirmation-day close; the intraday low cannot be assumed as an achievable entry price.
4.4 Scenario D: Price Up, OI Down, Short Liquidations Rising
This typically reflects a short-covering or short-squeeze rally.
Short liquidations show a mild positive correlation with returns over the following 1–2 days, suggesting that the squeeze may continue temporarily.
However, if OI subsequently rebuilds rapidly and funding becomes overheated, the rally can transition from a deleveraging-driven move into a crowded long market, changing the underlying risk structure.
5. Conclusion
There is no stable long-term positive relationship among BTC price, OI, funding, and liquidation volumes. OI can diverge from price on many trading days; funding primarily reflects positioning crowding and leverage costs; and liquidation direction has the most direct relationship with same-day price movements.
Empirical results show that using sharp OI declines, negative funding, or liquidation spikes as standalone deleveraging signals does not generate consistent subsequent rebound returns. Particularly after large-scale liquidations, price shocks often remain incomplete and the prevailing downtrend may continue in the short term.
However, once the analysis shifts from “Has deleveraging pressure appeared?” to “Has price begun to absorb selling pressure after deleveraging?”, the results change materially.
When OI drops sharply while BTC closes higher, when funding recovers from negative to non-negative while BTC closes higher, or when BTC turns positive the day after concentrated long liquidations, average cumulative returns over the subsequent 1–14 days are all positive. Among these signals, liquidation rebound confirmation also remains positive across both earlier and later subsamples, suggesting relatively better stability.
This means that a more accurate answer to the question “Can deleveraging predict a rebound?” is not that deleveraging inevitably leads to a rebound. Instead, deleveraging removes fragile positions, while price confirmation determines whether selling pressure has been absorbed by the market.
Only when pressure release is followed by price confirmation does the distribution of subsequent BTC returns shift more clearly toward positive outcomes.
Accordingly, compared with directly buying the dip when OI, funding, or liquidation volumes reach extreme thresholds, a two-stage framework of pressure release + price confirmation is more consistent with the observed data.
Current evidence suggests that this framework may serve as a candidate indicator for identifying potential BTC rebound windows, but it is not yet sufficient to establish an independent, stable, and universally tradable causal signal.
Further research should incorporate longer time periods, hourly OI, funding, and liquidation data across multiple exchanges, and rigorous rolling out-of-sample testing to evaluate the stability and practical trading value of these signals across different market regimes.
Data Source:
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