Gate Research Institute: ETH's price chasing lacks strength, trend breakout strategy yields over 240%

Introduction

The quantitative bi-weekly report (from May 27, 2025, to June 9, 2025) focuses on the market performance of Bitcoin and Ethereum, systematically analyzing key indicators such as long-short ratios, contract open interest, and funding rates to provide a quantitative interpretation of the overall market. This issue's quantitative strategy module emphasizes the practical application of the "Moving Average Trend Breakout Strategy" among the top ten projects by market capitalization in the cryptocurrency space (excluding stablecoins), systematically elaborating on its strategic logic, signal determination mechanism, and execution process. Through parameter optimization and historical backtesting validation, the strategy demonstrates good stability and execution discipline in trend identification and risk control. Compared to simply holding BTC and ETH, this strategy performs exceptionally well in terms of enhancing returns and controlling drawdowns, offering a practical quantitative trading reference framework.

Abstract

• In the past two weeks, BTC has fluctuated in the range of 100,000 to 110,000 USDT with mild volatility; during the same period, ETH has repeatedly tested 2,600 USDT before retreating, showing an overall mixed trend that indicates insufficient market enthusiasm for chasing highs and a cautious sentiment.
• The BTC contract position amount has slightly retreated from its high point, while ETH remains at a relatively high level, indicating a divergence in the allocation of funds between the two.
• In terms of funding rates, BTC is more volatile, frequently switching between the positive and negative 0.01% range, indicating significant market disagreement on its short-term direction.
• Musk and Trump had a fierce argument on social media, triggering short-term panic in the market, with the total liquidation amount across the internet approaching 1 billion dollars within 24 hours.
• The quantitative analysis uses the "Moving Average Trend Breakthrough Strategy", and under optimal parameter selection, the XRP strategy yield exceeds 240%.

Market Overview

In order to systematically present the funding behavior and trading structure changes in the current cryptocurrency market, this report analyzes from five key dimensions: the price volatility of Bitcoin and Ethereum, long-short trading ratio (LSR), contract holding amount, funding rate, and market liquidation data. These five indicators cover price trends, funding sentiment, and risk conditions, providing a relatively comprehensive reflection of the current market's trading intensity and structural characteristics. The following will sequentially analyze the latest changes in each indicator since May 27.

1. Analysis of Price Volatility of Bitcoin and Ethereum

According to CoinGecko data, BTC has been steadily fluctuating in the range of 100,000 to 110,000 USDT over the past two weeks, with small volatility and a stable price structure, showing strong bearish resistance; on the other hand, ETH has repeatedly surged past 2,600 USDT only to quickly pull back, with insufficient momentum for chasing highs, exhibiting a fluctuating trend and a cautious attitude from investors. Since BTC successfully maintained above 105,000 USDT at the end of May, there have been pullbacks but it has not broken through key support, maintaining an upward structure with good continuity of overall momentum; in contrast, ETH lacks the support of trading volume, facing repeated sell pressures after surging, with clear divergence in MACD momentum, and a pronounced tug-of-war between bulls and bears in the short term.

The FOMC meeting minutes released by the Federal Reserve on May 28 sent hawkish signals. Despite pausing interest rate hikes for the third consecutive time, officials are generally concerned about stubborn inflation, with core PCE at 2.6%, and inflation may not gradually decline until 2027. At the same time, the GDP growth forecast has been lowered and the unemployment rate has been raised, reflecting an increased risk of economic recession, leading to a clear cooling of market expectations for short-term rate cuts.

Overall, BTC has received more funding favor and has shown greater resilience in structural adjustments; ETH, on the other hand, is limited by insufficient themes and momentum, leading to a relatively weak performance. It is recommended to continue monitoring the Federal Reserve's June interest rate meeting, the inflow situation of Bitcoin spot ETFs, and whether the Ethereum Layer 2 ecosystem can reactivate market enthusiasm.

Figure 1: BTC fluctuates in the range of 100,000 to 110,000 USDT, with relatively mild volatility; in contrast, ETH lacks upward momentum, showing erratic trends, and market sentiment is becoming cautious. !

In terms of volatility, the volatility of ETH is significantly higher than that of BTC, indicating that its price is more susceptible to short-term capital drives and emotional influences. ETH has experienced drastic fluctuations on multiple trading days, especially during phases of local market rebounds and pullbacks, where the volatility rapidly escalates, reflecting intense market speculation and frequent capital inflows and outflows.

In contrast, the volatility distribution of BTC is more balanced, lacking significant peaks, demonstrating stronger price stability and structural support. In the context of a market lacking a clear trend, BTC's low volatility characteristics indicate a more robust capital allocation, while ETH, due to the lack of continuous thematic support, experiences concentrated short-term fluctuations that are easily driven by news.

Figure 2: The overall volatility of ETH is significantly higher than that of BTC, indicating that its price is more susceptible to short-term capital movements and emotional influences.

In the past two weeks, BTC and ETH have shown a clear divergence. BTC has been steadily oscillating with mild volatility, demonstrating strong resistance to decline and capital support; on the other hand, ETH lacks sustained momentum, struggles to rise, and exhibits a fluctuating trend, with a cautious stance from capital. On the macro front, the Federal Reserve's meeting minutes are hawkish, suppressing market expectations for short-term easing and further strengthening capital's preference for core assets. In terms of volatility, ETH is significantly higher than BTC, reflecting that its short-term performance is heavily influenced by sentiment and news, while market risk appetite is more inclined towards prudent allocation during structural adjustments. Overall, BTC shows stronger resilience within the current range, and future attention should be paid to the marginal effects of policy direction and capital flow on the market.

2. Analysis of the Long-Short Ratio (LSR) of Bitcoin and Ethereum Trading Volume

The Long/Short Taker Size Ratio (LSR) is a key indicator that measures the trading volume of long versus short orders in the market, often used to gauge market sentiment and trend strength. When LSR is greater than 1, it indicates that the volume of proactive buying (taking long orders) exceeds that of proactive selling (taking short orders), suggesting that the market is more inclined to go long, with sentiment leaning bullish.

According to Coinglass data, the long-short ratio (LSR) of BTC and ETH has not synchronized with price trends overall, reflecting a lack of consistent expectations from the market regarding current price fluctuations, with a neutral funding sentiment and significant hedging behavior. For BTC, the price has corrected since the end of May, falling from a peak to around 102,000 USDT. Although there was a slight rebound in the short term after June 7, the overall structure is still in a correction phase. Meanwhile, the LSR has not shown a significant decline, only retreating to around 0.85, and instead quickly rebounded when prices corrected, even reaching as high as 1.1, indicating short sellers covering their positions or short-term long positions testing the waters. However, this ratio has not formed a sustained trend, remaining in a range of 0.9 to 1.1, suggesting a lack of clear directional consensus in the market and a neutral funding sentiment.

The price of ETH fell from a high of around 2,600 USDT at the beginning of June, retracing to 2,400 USDT before consolidating in a range. LSR also fluctuated significantly, repeatedly dropping below 0.9, reflecting that bearish pressure remains strong during the upward movement. Even though the price rebounded, LSR has not stabilized back above 1, indicating insufficient bullish dominance and increasing market contention.

Overall, although BTC and ETH have experienced a short-term technical rebound, the long-short trading ratio has not formed a synchronous structural enhancement, indicating that funds remain uncertain about the future direction. The recent fluctuations in LSR are more likely to reflect short sellers taking profits or short-term fund repositioning, rather than a clear trend reversal. If LSR can continue to hold above 1, it may support the price to develop a more sustainable upward structure.

Figure 3: BTC price has been retracing since the end of May, and is still in a correction structure overall. The LSR is oscillating between 0.9 and 1.1, indicating a lack of clear directional consensus in the market, with overall funding sentiment being neutral.

Figure 4: Even though the ETH price rebounded, LSR has not stabilized above 1, indicating insufficient bullish dominance and intensified market speculation.

3. Contract Position Amount Analysis

According to Coinglass data, the contract holding amounts of BTC and ETH have shown divergence. The BTC contract holding amount gradually declined after reaching a peak of about 82 billion USD around May 20, stabilizing in the range of 72 billion to 74 billion USD over the past two weeks, reflecting a withdrawal of leveraged funds during the price correction phase and a cooling market sentiment. In contrast, the ETH contract holding amount has remained relatively high since mid to late May, fluctuating around 35 billion USD, indicating that despite significant price volatility, the funding layout on the contract side has remained relatively stable, with no signs of large-scale position reduction, and participation willingness still maintained at a medium to high level.

Overall, the leverage structure of BTC has shown a significant cooling after the market correction at the end of May, while ETH has demonstrated stronger holding resilience. Although funds have not significantly withdrawn from the ETH market, the combination of the continuously low LSR and the price fluctuations indicates a cautious market sentiment, primarily focusing on short-term speculation, and a structural trend has not yet formed. If the contract open interest of BTC and ETH can synchronously increase in volume afterwards, it will be an important signal for the market to restart the trend.

Figure 5: The BTC contract position amount has slightly retreated from its high, while ETH remains at a relatively high level, indicating a divergence in capital layout between the two.

4. Funding Rate

The funding rates for BTC and ETH have been fluctuating slightly around 0%, frequently switching between positive and negative, reflecting the tug-of-war between bullish and bearish forces in the market, with sentiment leaning towards a wait-and-see approach. In particular, the BTC funding rate has seen more drastic fluctuations over the past week, frequently switching between the positive and negative 0.01% range, indicating significant disagreement in the market regarding its short-term direction, with leveraged funds entering and exiting more aggressively, leading to relatively weak structural stability. In contrast, although the ETH funding rate also experiences fluctuations, the amplitude is slightly smaller, and the trend is relatively convergent, reflecting a more cautious capital allocation and a relatively mild leveraged sentiment.

Overall, although BTC and ETH have shown positive rates on some trading days, indicating that bulls are attempting short-term entries, no sustainable trend has formed. The current market still lacks clear directional expectations, with a restrained pace of capital accumulation, and the market is in a phase of fluctuation and consolidation. The funding rates also reflect a market sentiment that is neutral and cautious.

Figure 6: The funding rate of BTC fluctuates more violently, frequently switching between the positive and negative 0.01% range, indicating a significant divergence in the market regarding its short-term direction.

5. Cryptocurrency Contract Liquidation Chart

According to Coinglass data, in the past two weeks, long liquidations have consistently exceeded short liquidations on most trading days, indicating a strong bullish sentiment in the market during high volatility periods, with funds generally inclined to increase positions during the upward trend. However, against the backdrop of market pullbacks or intensified fluctuations, long positions have frequently faced liquidation, with liquidation amounts repeatedly exceeding $500 million, reaching a peak of $875 million on June 5. That evening, a heated dispute erupted between Musk and Trump on social media, triggering short-term panic in the market, with Tesla's stock price and Bitcoin dropping in sync, exacerbating overall market volatility. This event led to a large number of long positions being liquidated, with the total liquidation amount across the network approaching $1 billion within 24 hours, making it one of the largest liquidation peaks in the recent contract market.

In contrast, the overall scale of short positions being liquidated is relatively low. Although it has expanded during some short-term rebounds, it has not formed a sustained dominant pattern. June 9 was one of the few days when short positions exceeded long positions, mainly due to positive news released from the Sino-U.S. talks, with the White House hinting at easing export controls, which improved market sentiment and triggered a price rebound, leading to concentrated short position buybacks and resulting in liquidations.

Overall, the current market liquidation structure presents a "bullish-dominated liquidation" pattern, reflecting a significant misjudgment of funds regarding short-term market conditions in an environment characterized by high leverage and high volatility, intensifying the risks of chasing highs. Combining data such as LSR and funding rates, although the current market has active trading support, it is still in a stage of structural divergence and has not yet formed a clear unilateral trend. In operations, one must be wary of the severe volatility and irrational pullback risks brought by the magnification of liquidations.

Figure 7: Long positions frequently faced liquidation, with the scale of liquidations repeatedly exceeding $500 million, especially reaching a peak of $875 million on June 5.

Quantitative Analysis - Moving Average Trend Breakthrough Strategy

(Disclaimer: All predictions in this article are based on historical data and market trends, and are for reference only. They should not be considered as investment advice or guarantees of future market movements. Investors should fully consider the risks and make cautious decisions when engaging in relevant investments.)

1. Strategy Overview

The moving average trend breakthrough strategy is a medium to short-term trading strategy based on trend judgment through moving average crossovers and price fluctuations. By combining the Simple Moving Average (SMA) and the Exponential Moving Average (EMA), it monitors the directional changes of price trends, using the short-term moving average crossing above or below the long-term moving average as buy or sell signals. At the same time, the strategy introduces a dynamic stop-loss and take-profit mechanism to lock in profits or limit losses, making it suitable for application in a trending market environment with fluctuations.

2. Core parameter settings

3. Strategy Logic and Operation Mechanism

Entry Conditions

• When the short-term moving average crosses above the long-term moving average in a no position state, the strategy triggers a buy operation.

Entrance requirements:

• Short-term moving average crosses below long-term moving average: When the short-term moving average falls below the long-term moving average, it is considered a sign of weakening market conditions, triggering a closing signal.
• Stop Loss Close Position: If the price falls back to the purchase price * (1 - stop_loss_percent), a forced stop loss will be triggered.
• Take Profit Close: If the price rises to the buy price * (1 + take_profit_percent), trigger the take profit close.

Practical Example Diagram

• Trading signal triggered

The chart below shows the XRP/USDT 4-hour candlestick chart at the most recent entry point triggered by the strategy on June 3, 2025. After a brief price correction, a technical reversal signal appeared in the early hours of June 3: the short-term moving average MA5 began to cross above the medium to long-term moving average MA10, the MACD fast line and slow line formed a golden cross, and the trading volume increased simultaneously, indicating enhanced bullish momentum. The strategy triggered a buy at this position, successfully capturing a subsequent significant rebound, which overall aligns with the positioning logic of a trend-following bullish strategy.

Figure 8: Schematic diagram of the actual entry position when the strategy conditions for XRP/USDT are triggered (June 3, 2025)

• Trading Actions and Results XRP shows signs of short-term weakness after a continuous rise, with a MACD death cross forming and short-term moving averages starting to press down. A sell operation is executed at this position, successfully locking in profits from the previous rebound. Although the price only slightly retraced afterwards, this exit aligns with the risk control logic of the trend strategy, "exit when momentum weakens," demonstrating good discipline in swing trading. In the future, if dynamic profit-taking or trend-following mechanisms can be combined, it is expected to further enhance overall profit retention efficiency and profit margins.

Figure 9: XRP/USDT Strategy Exit Position Diagram (June 5, 2025)

Through the above practical example, we intuitively demonstrated the entry and exit logic and dynamic risk control mechanisms of the trend strategy during the price momentum change process. The strategy judges the trend direction based on the crossover of short-term and long-term moving averages, and enters the market when the short-term moving average crosses above, capturing upward momentum; when the short-term moving average crosses below or the momentum indicator weakens, it exits in a timely manner to effectively avoid drawdown risks. While controlling profit and loss fluctuations, the strategy successfully locks in the profits of major waves. This case not only verifies the operability and disciplined execution of the trend strategy in actual market conditions but also reflects its good profit retention ability and defensiveness in a highly volatile market environment, providing a reliable empirical basis for subsequent parameter optimization and cross-product applications.

4. Practical Application Examples

Parameter Backtesting Settings

To find the best parameter combination, we conduct a systematic grid search over the following range:

• short_period: 2 to 10 (step size of 1)
• long_period: 10 to 20 (step size is 1)
• stop_loss_percent: 1% to 2% (step size of 0.5%)
• take_profit_percent: 10% to 16% (step size of 5%)

Taking the top ten projects by cryptocurrency market capitalization (excluding stablecoins) as an example, this article backtested the 4-hour K-line data from May 2024 to June 2025, testing a total of 891 parameter combinations and selecting the ten with the best annualized return performance. Evaluation criteria include annualized return, Sharpe ratio, maximum drawdown, and ROMAD (return to maximum drawdown ratio), to comprehensively assess the strategy's stability and risk-adjusted performance in different market environments.

Figure 10: Performance Comparison Table of Ten Optimal Strategy Groups

Strategy Logic Description When the program detects that the short-term moving average crosses above the long-term moving average, it is considered a trend initiation signal, and the strategy will immediately trigger a buy operation. This structure aims to capture the initial strengthening phase of the market by identifying the price trend direction through moving average crossovers, combined with a dynamic take-profit and stop-loss mechanism for risk control. If the subsequent short-term moving average crosses below the long-term moving average, or if the price reaches the preset stop-loss or take-profit ratio, the system will automatically execute an exit operation to achieve robust profit locking and risk prevention.

Taking XRP as an example, the settings used in this strategy are as follows:

• short_period= 2 (short-term moving average period, used to track price changes)
• long_period = 19 (long-term moving average period, used to determine trend direction)
• stop_loss_percent = 1.5%
• take_profit_percent = 10%

This logic combines trend breakout signals with fixed ratio risk control rules, suitable for trading environments where market direction is clear and wave structures are distinct, effectively controlling drawdowns while following trends, thus enhancing trading stability and overall yield quality.

Performance and Results Analysis The backtesting period is from May 2024 to June 2025. The cumulative return performance of the top ten cryptocurrency projects by market capitalization (excluding stablecoins) using trend strategies is overall robust, with most cryptocurrencies clearly outperforming the Buy and Hold strategy of BTC and ETH. Among them, XRP and DOGE performed particularly well, with cumulative returns of 243% and 234%, respectively. In contrast, the spot holding strategy for BTC and ETH has been in a long-term oscillating or downward trend, with ETH even retracing more than 50% at one point. The trend strategy effectively avoided downside risks and captured multiple swing opportunities, demonstrating excellent risk control and asset appreciation capabilities.

On the whole, the trend strategy has shown good adaptability in multi-currency, which can effectively control drawdowns in sharp fluctuations while steadily accumulating returns. The current strategy portfolio has achieved a good balance between reward and robustness, and has the value of real-world deployment. In the future, dynamic Bollinger parameters, volume factors or volatility screening mechanisms can be further introduced to optimize the performance of the strategy in different market environments, and be extended to a multi-currency and multi-period quantitative trading framework to improve the overall adaptability and trading efficiency.

Figure 11: Comparison of cumulative return rates over the past year between ten sets of optimal parameter strategies and BTC, ETH holding strategies.

5. Trading Strategy Summary

The moving average trend breakthrough strategy uses moving average crossovers as the core entry and exit logic, combined with dynamic stop-loss and take-profit mechanisms, demonstrating robust risk control capabilities and good performance across multiple mainstream crypto assets. During the backtesting period, the strategy effectively captured multiple rounds of short- to medium-term trend movements, especially performing outstandingly in volatile and reversal market conditions, significantly outperforming the traditional Buy and Hold strategy.

From the results of the multi-currency backtesting, the strategy combinations of projects such as XRP, DOGE, and ADA have achieved impressive results, with the highest cumulative returns exceeding 240%, effectively avoiding the deep drawdown risks encountered when holding spot assets like ETH, thereby validating the applicability and robustness of the strategy in practical situations.

It is worth noting that although the win rate of most strategies is below 50%, through a well-designed risk-reward ratio (profit-loss ratio), it is still possible to achieve a positive return overall, even with a lower win rate, demonstrating the effectiveness of the strategy in controlling profits and losses as well as position management.

Overall, this strategy has a good balance in controlling drawdowns, improving return efficiency, and enhancing capital utilization, making it suitable for deployment in high-volatility market environments. In the future, technical factors such as Bollinger Bands, volume filtering, and volatility screening can be further introduced to optimize signal quality and improve performance within a multi-period and multi-asset framework, laying the foundation for establishing a robust quantitative trading system.

Summary

From May 27 to June 9, 2025, the cryptocurrency market experienced a phase of high volatility and structural adjustment. BTC and ETH repeatedly switched between high-level fluctuations and range corrections, with overall market sentiment being cautious. Although the contract open interest remained high and funds continued to flow in, both the long-short ratio (LSR) and funding rates did not show a clear unilateral tendency, indicating that the main capital was still focused on hedging and short-term trading, with high leverage and high liquidation risks coexisting. During this period, long liquidation events occurred frequently, especially on June 5 when Musk and Trump had a heated exchange on social media, triggering market panic, which led to a simultaneous decline in Tesla and Bitcoin. Nearly 1 billion dollars were liquidated across the network within 24 hours, highlighting the lack of stable confidence in high positions under the current market conditions, with the risk of leverage usage significantly increasing.

In this context, this quantitative analysis focuses on the "Moving Average Trend Breakout Strategy," verifying its adaptability and practicality under different market conditions. The strategy identifies trend initiation through the short-term moving average crossing above the long-term moving average, and combines a fixed ratio take-profit and stop-loss mechanism to control risk. Backtesting results show that the strategy performs outstandingly among cryptocurrencies such as XRP, DOGE, and ADA, with the highest cumulative return exceeding 240%, and it demonstrates good drawdown control capability.

It is worth noting that although the overall win rate of the strategy is relatively low (below 50%), it can still achieve long-term positive returns by relying on a high profit-loss ratio and a clear disciplined exit mechanism. This reflects the effectiveness of the strategy in capital management and risk control. The current strategy strikes a good balance between returns, robustness, and execution simplicity, making it suitable for live deployment. However, in practice, it may still be affected by market fluctuations, extreme conditions, or signal failure. It is recommended to combine other quantitative factors and risk control mechanisms to enhance the strategy's stability and adaptability, and to make rational judgments and respond cautiously.
Reference Material:

1. CoinGecko, https://www.coingecko.com/
2. Gate, https://www.gate.com/trade/BTC_USDT
3. Gate, https://www.gate.com/trade/ETH_USDT
4. Coinglass, https://www.coinglass.com/LongShortRatio
5. Coinglass, https://www.coinglass.com/BitcoinOpenInterest?utm_source=chatgpt.com
6. Gate, https://www.gate.com/futures_market_info/BTC_USD/capital_rate_history
7. Gate, https://www.gate.com/futures/introduction/funding-rate-history?from=USDT-M&contract=ETH_USDT
8. Coinglass, https://www.coinglass.com/pro/futures/Liquidations

Disclaimer Investing in the cryptocurrency market involves high risks, and it is recommended that users conduct independent research and fully understand the nature of the assets and products being purchased before making any investment decisions. Gate does not bear any responsibility for any losses or damages resulting from such investment decisions.