Gate Research: BTC and ETH Both Pull Back, Trend Strategies Become the Primary Source of Returns

Summary

• In June, BTC and ETH fell by 20.43% and 21.67% respectively. The market continued its weak adjustment, with the price center moving lower, and ETH underperforming BTC.

• The derivatives market continued to deleverage. Open interest for BTC and ETH perpetual contracts declined by 25.76% and 26.31% respectively. Long liquidations significantly exceeded short liquidations, and funding rates remained broadly neutral. The price decline primarily reflected weakened spot selling pressure and a simultaneous deterioration in risk appetite.

• June's market favored trend-following and breakout confirmation strategies. Parameter backtesting showed that the moving average confluence breakout strategy outperformed buy-and-hold overall, making it more suitable for capturing directional moves.

• Based on net returns, drawdown, and trade frequency, AAVE USDT was the best practical case for June. The strategy delivered a net return of 60.2%, compared to a 3.76% buy-and-hold return, with a maximum drawdown of 12.9%.

• In July, traders can continue tracking the moving average confluence breakout strategy, incorporating volume confirmation and a BTC trend filter to enhance signal quality and reduce the risk of false breakouts from counter-trend trading.

In June 2026, mainstream crypto assets continued their weak, downward-broadening consolidation. BTC opened the month at $73,684.1 and closed at $58,632.4, posting a monthly return of -20.43%. The intra-month high was $74,090.8 and the low was $58,106.9, resulting in an amplitude of 27.51%. ETH recorded a monthly return of -21.67% over the same period, with a maximum drawdown of -21.88%. Structurally, BTC rapidly declined in early June before entering a low-level recovery phase. A mid-month rebound failed to reopen upward space, and prices fell again at the end of the month. ETH's relative weakness was more pronounced, lacking price resilience and coming under pressure during periods of liquidity contraction.

On the derivatives front, open interest across major contracts failed to form a stable recovery. BTC USDT perpetual open interest fell from $5.19B to $3.85B, a monthly change of -25.76%. ETH's open interest saw a monthly change of -26.31%. In the liquidation structure, long liquidations significantly exceeded short liquidations, indicating that passive deleveraging during the downtrend remained the dominant force. Funding rates remained slightly positive or near neutral for most of the period. The price decline was not driven by extreme short crowding but rather by the trend impact of weakened spot selling pressure alongside deteriorating risk appetite.

On the quantitative strategy front, June favored trend-following and breakout confirmation approaches. This report used 4-hour candlesticks from Gate exchange to conduct a parameter grid backtest across 29 valid USDT spot trading pairs. The screening criteria were: monthly Gate spot trading volume exceeding $50 million, at least 2 trades, a maximum strategy drawdown not exceeding 20%, with one-way costs and slippage combined at 0.08%. Considering net returns, drawdown, and trade frequency, the best practical case for June was the AAVE USDT moving average confluence breakout strategy: a monthly net return of 60.2%, a buy-and-hold return of 3.76%, a maximum drawdown of -12.9%, 4 trades, a win rate of 75%, and a profit factor of 9.63.

1. Market Overview

The core characteristics of June's market were a downward-shifting price center, insufficient rebound persistence, and trading volume concentrating toward BTC and a few large-cap assets. BTC and ETH remained the most important bellwethers. BTC's monthly amplitude reached 27.51%, with an annualized realized volatility of approximately 43.55%. ETH's monthly amplitude was 34.29%, with an annualized realized volatility of about 65.43%. When major assets experience significant drawdowns simultaneously, cross-asset diversification offers limited protection for portfolio value in the short term. At the strategy level, strict adherence to position direction and exit discipline is essential.

In terms of trading volume, the samples with the highest June spot trading volume on Gate were concentrated in high-liquidity assets such as BTC, ETH, SOL, XRP, and DOGE. High trading volume carries two implications. First, backtest signals more closely reflect executable live trading conditions. Second, during periods of amplified intra-month volatility, rising volume is typically accompanied by both passive stop-losses and active position adjustments, allowing trend strategies to capture successive price ranges.

2. BTC and ETH Structural Observations

BTC's June price action can be divided into three phases. The first phase ran from June 1 to June 6, with prices rapidly declining from the month's opening range, daily candles weakening consecutively, and long liquidations in derivatives expanding simultaneously. The second phase spanned June 7 to June 18, during which BTC recovered within a low range. Local rebounds drove short-term short covering, but prices never reclaimed the early-month highs. In the third phase, during late June, BTC lost mid-month support again and closed near the low end of the range, indicating that capital continued to favor reducing risk exposure.

ETH underperformed BTC. ETH's June monthly return was -21.67%, a relative gap of -1.25% versus BTC. In weak months, ETH typically requires on-chain activity, ecosystem capital inflows, or an expansion in risk appetite for additional support. This month, none of these factors offset the pressures from macro risk and market deleveraging. From a strategic standpoint, ETH is better suited as a risk thermometer rather than a standalone offensive asset: when ETH fails to strengthen relative to BTC, the Beta risk of altcoin portfolios should be revised downward.

The relationship between volume and volatility is also noteworthy. BTC's trading volume expanded notably during the early decline and the late-month pullback, indicating that the downward move was not merely a low-liquidity slide but was accompanied by genuine turnover. If BTC re-enters a low-volatility consolidation phase, moving average confluence strategies will wait for the MA band to contract before determining breakout direction. If prices continue along a descending channel, short-cycle trend models may still outperform mean-reversion approaches.

3. Derivatives Market: Open Interest, Liquidations, and Funding Rates

Data from the derivatives market paints a relatively consistent picture, primarily reflecting passive risk reduction following the decline. BTC long liquidations totaled $329.4M, while short liquidations reached $144.9M. ETH long liquidations totaled $314.8M, with short liquidations at $193.4M. The high proportion of long liquidations means leveraged longs were forced to exit as prices fell, which also transmitted negative sentiment to spot prices.

Funding rates did not show extreme negative values, and the market was not experiencing one-sided excessive short positioning. For most of the period, funding rates were near neutral or slightly positive, suggesting that some capital was still attempting to buy dips or maintain long positions during the price weakness. If funding rates were to turn significantly negative while prices stopped making new lows, conditions would be closer to a short-term rebound. This month did not produce such a strong reflexive structure.

Periods when the account long/short ratio exceeds 1 do not necessarily indicate bullishness. In weak markets, a rising long/short ratio can sometimes result from retail traders taking contrarian long positions. Without OI expansion and upward price confirmation, this can instead become a source of future liquidation pressure. The account long/short ratios for BTC and DOGE were elevated on certain trading days, yet prices failed to sustain recovery. Such divergences should be incorporated into risk controls.

4. Quantitative Analysis: Moving Average Confluence Breakout Strategy

4.1 Strategy Logic

This report builds on the core concept of moving average confluence breakouts. When multiple short- and medium-term moving averages progressively converge, prices are in a compressed state ahead of a directional choice. When prices break above the upper band of the moving average envelope, it suggests bulls are regaining control. When prices break below the lower band, the probability of a continuing downtrend increases. This strategy does not predict turning points; it waits for the MA band to contract and then follows the direction prices reveal.

This report uses six moving averages to form the MA band, comprising three SMA and three EMA combinations. The parameter grid includes four period sets — (6,18,54), (8,24,72), (12,36,108), and (20,60,120) — with thresholds of 1.2%, 1.8%, 2.2%, 3%, and 4%, and dynamic take-profit multiples of 3, 4, 6, and 8. Using 4-hour candlesticks, data from May 1 to May 31 is used for indicator warm-up, and performance is calculated from June 1 to June 30.

Entry rules are as follows:

• MA band width = (highest of the six MAs - lowest of the six MAs) / closing price;

• When the MA band width falls below the threshold, the MAs are considered in confluence;

• When the closing price crosses above the upper band from below, a long position is opened at the open of the next 4H candle;

• When the closing price crosses below the lower band from above, a short position is opened at the open of the next 4H candle;

• After going long, a stop-loss is triggered if price falls below the lower band; after going short, a stop-loss is triggered if price rises above the upper band;

• When profit reaches "MA band width at entry × take-profit multiple", the position is closed at the open of the next 4H candle;

• Any open positions at month-end are force-closed at the closing price of the last 4H candle.

The backtest cost assumption is a 0.08% deduction per position change, covering trading costs and slippage. This assumption does not reflect actual Gate fees and is used solely for uniform comparison across different trading pairs and parameter combinations. The strategy does not use leverage, and capital utilization is calculated at 100%. Buy-and-hold returns are calculated from the first daily candle's open to the last daily candle's close for the same trading pair in June.

4.2 Sample and Screening

The candidate pool includes 29 valid Gate USDT trading pairs: BTC, ETH, SOL, XRP, DOGE, BNB, ADA, TRX, LINK, AVAX, BCH, LTC, DOT, NEAR, UNI, AAVE, ICP, ETC, ATOM, FIL, OP, ARB, SUI, WLD, INJ, PEPE, SHIB, ONDO, and HBAR.

To avoid a single incidental signal becoming the best sample, this report restricts practical cases to those with: monthly Gate spot trading volume exceeding $50 million, at least 2 trades in June, a maximum strategy drawdown not exceeding 20%, and position exposure not exceeding 95%. The purpose of these rules is not to chase theoretical maximum returns, but to identify strategy combinations that were executable in live trading during June.

4.3 Best Practical Case for June: AAVE USDT

Based on the screening rules above, the best case for June is AAVE USDT. This trading pair had a monthly spot trading volume of $108.2M, a monthly buy-and-hold return of 3.76%, an intra-month amplitude of 72.28%, and a maximum drawdown of -24.02%. The optimal strategy parameters were: MA period (8, 24, 72), MA confluence threshold of 4%, and a dynamic take-profit multiple of 8.

Backtest results show that the AAVE USDT equity curve exhibited a step-like pattern in June. The strategy did not predict direction at the start of the month but instead waited for breakout signals after the MA band contracted. This characteristic allowed it to avoid some ineffective oscillations while retaining positions when prices moved in sustained directions. Compared to buy-and-hold, the strategy's excess return was 56.44%, with the maximum drawdown contained at -12.9%. This indicates that June's returns primarily came from directional shifts and dynamic profit-taking. This sample is not merely a spot price replay; it also provides the foundation for expressing long/short directions via perpetual contracts.

From the trade details, the strategy's best-performing periods were concentrated after prices rapidly departed from the MA band. Short signals contributed more in the down-trending month, while long signals primarily served a rebound-confirmation function. If only spot long positions were allowed, the strategy's returns would have been significantly lower this month. If executed via perpetual contracts, additional attention must be paid to funding rates, liquidation prices, and position limits.

4.4 Strategy Return Sources

The effectiveness of the moving average confluence breakout strategy this month stems from three structural market characteristics.

First, prices repeatedly transitioned from narrow consolidation to directional expansion. The MA confluence condition divides market states into "waiting" and "executing," reducing frequent trading amid choppy conditions. The strategy only assumes directional risk when prices depart from the MA band.

Second, downtrends were more continuous in the weak market. Many high-Beta trading pairs in June did not immediately rebound after a single day of decline but instead moved down over several consecutive 4H candles. Trend strategies are more likely to achieve positive expectancy in this environment than mean-reversion approaches.

Third, dynamic take-profit reduced profit give-back. Fixed take-profit levels tend to exit too early when volatility expands, while pure MA-based stop-losses may return realized profits to the market. This strategy uses an "MA band width at entry × multiple" approach, allowing the take-profit target to vary with the degree of compression at entry. When MAs are tightly converged, the take-profit distance after a breakout is smaller; when the MA band is wider, the strategy allows for larger trend moves.

The strategy's limitations are equally clear. MA confirmation is inherently lagging and cannot capture the very beginning of a trend. When prices rapidly retrace, short positions may be stopped out near the upper band. If the market enters a directionless wide-range oscillation, the MA band will repeatedly contract and expand, and trading costs will erode returns. Therefore, this strategy is best suited as a trend enhancement module rather than a standalone all-weather allocation.

5. Portfolio Perspective: Combining Trend Enhancement with Neutral Strategies

June's sample demonstrates that trend strategies can play both defensive and offensive roles in down months. Short signals can hedge spot Beta, and long signals can capture low-level rebounds. However, the return distribution is not smooth. If the moving average confluence breakout strategy is used in portfolio management, it is better positioned as an enhancement module paired with low-correlation strategies.

A viable portfolio framework is as follows:

• Use BTC, ETH, or stablecoin yield strategies as a low-turnover core position;

• Activate the trend enhancement module only when breakouts occur after MA confluence, remaining in cash otherwise;

• Cap single trading pair risk budget at 10%-15% of portfolio equity;

• Set tighter per-trade loss limits for high-Beta altcoins;

• Reduce the weight of long signals when both BTC and ETH fall below their daily short- and medium-term MAs;

• Avoid chasing longs when funding rates are persistently and significantly positive while prices fail to make new highs;

• Increase the weight of rebound signals when funding rates turn negative, prices stop making new lows, and OI begins to recover steadily.

The key to this framework is placing strategy signals within a risk budget rather than directly extrapolating a single backtest result. June's best case is representative, but it does not guarantee the same returns can be replicated in July. The vitality of trend strategies comes from discipline: no trading when there is no MA confluence, exiting when stop-losses are triggered, and taking profits when dynamic take-profit targets are reached.

6. Risk Warning and Forward-Looking Observations

Three categories of indicators warrant close attention going forward.

First, whether BTC can reclaim its mid-June rebound range. If BTC can only consolidate at low levels, the sustainability of altcoin rebounds will be limited. If BTC breaks upward on volume and drives an ETH/BTC recovery, the quality of long signals in trend models will improve.

Second, whether derivatives OI grows in tandem with price rebounds. Price rebounds without OI growth often indicate mere