Gate Research Institute: The crypto market continues to fluctuate, and the SUI trend strategy returns over 285%.

Summary

• ETH outperforms BTC, showing stronger continuity and upside potential supported by both price structure and ETF capital inflows.
• The long-short ratio is synchronously declining, indicating a weakened willingness to chase long positions in the market, with a conservative sentiment prevailing. The short-term trend remains dominated by fluctuations.
• Contract positions and funding rates remain high and stable, with leverage participation not yet overheated, indicating a relatively healthy structure.
• The liquidation data did not show extreme clearing, and the rotation of long and short positions helps to shuffle emotions, providing a momentum basis for the next step in market development.
• In terms of quantitative strategies, the moving average dense breakout strategy achieved over 285% returns in the SUI cryptocurrency, demonstrating good short-term trading potential.

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 open interest, funding rates, and market liquidation data. These five indicators cover price trends, funding sentiment, and risk conditions, and can comprehensively reflect the current market's trading intensity and structural characteristics. The following will sequentially analyze the latest changes in each indicator since August 5:

1. Analysis of Price Volatility of Bitcoin and Ethereum

According to CoinGecko data, from August 5 to 18, the overall cryptocurrency market showed a pattern of high-level fluctuations. BTC and ETH, after reaching their respective stage highs in the previous phase, entered a period of sideways consolidation, with short-term momentum slowing down but the structure still leaning towards bullish.

In terms of price trends, BTC has been continuously hindered around 119,000 USDT since it reached a new high of 124,400 USDT on August 14, forming a clear high-level consolidation range. Figure 1 shows that its price has oscillated up and down around this position repeatedly, with multiple failed attempts to break through, and both momentum and trading volume have weakened, indicating insufficient market buying interest. In contrast, ETH has steadily risen from 4,300 USDT, with its price nearing the 4,800 USDT mark, gradually increasing along the short-term moving averages, showing a relatively more sustainable trend and a healthier technical structure.

From a fundamental perspective, ETH spot ETFs recorded a net inflow of $2.85 billion last week, setting a new historical high, with funds primarily concentrated in BlackRock and Fidelity products, indicating a significant increase in institutional willingness to allocate to ETH. In contrast, BTC ETFs remain overall stable but face net outflows in some products, exacerbating structural divergences. Overall, the continued inflows into ETFs reinforce institutional recognition and long-term allocation value of mainstream assets.【4】

In summary, the current cryptocurrency market is maintaining a high-level consolidation in the short term. BTC lacks a clear directional breakout, while ETH has a good technical structure with moderate momentum release. Additionally, the continuous influx of funds into spot ETFs provides strong support for ETH. If trading volume and volatility increase in tandem, ETH may have the potential to initiate a rally first. It is recommended to continuously monitor the changes in ETF fund flows and whether ETH can stabilize above the key level of 4,000 USDT to determine the timing for the next trend to begin.

Figure 1: BTC has been consistently blocked at 119,000 USDT after reaching a new high of 124,400 USDT on August 14, with weakening momentum.

In terms of volatility, BTC overall maintains a moderate fluctuation, only experiencing amplification on individual trading days, indicating a rather restrained pace of capital operation and a clear trend expectation. In contrast, ETH's volatility is notably active, with significant surges on multiple trading days, reflecting increased fluctuations in market sentiment and frequent short-term capital speculation.

Although the overall volatility remains at a medium-low level, the frequent warming of ETH indicates that it is more susceptible to news or liquidity-driven factors. If this is accompanied by an increase in volume, it is necessary to pay attention to whether it will translate into a substantial market movement.

Figure 2: BTC has mild fluctuations, while ETH experiences frequent and amplified fluctuations, indicating a more sensitive trading sentiment.

In the past two weeks, the cryptocurrency market has maintained a high-level consolidation pattern. BTC's short-term momentum has weakened and its direction remains unclear, while ETH continues its upward trend, showing relative advantages in both technical and funding aspects. In terms of volatility, ETH is more sensitive, with increased activity in short-term trading. If the subsequent trading volume supports this and ETF capital inflows continue, ETH is expected to be the first to welcome a breakthrough 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 for measuring the trading volume of long and short taker orders in the market, typically used to assess market sentiment and trend strength. When LSR is greater than 1, it indicates that the volume of active buying (long taker orders) exceeds that of active selling (short taker orders), suggesting that the market leans towards long positions with a bullish sentiment.

According to Coinglass data, the long-short trading scale ratio (LSR) of BTC has generally trended downward over the past two weeks. Although the price remains in a high consolidation range, the long-short ratio continues to decline, dropping significantly below 0.90 on August 17, reflecting a substantial weakening in market bullish sentiment. Short-term capital has shifted to a wait-and-see or bearish approach, indicating that while the BTC high structure remains stable, the momentum of emotional support is waning.

The ETH long-short ratio also shows a similar trend. Although the price has continued to rise and broke through 4,300 USDT since the beginning of August, the LSR has gradually fallen from its peak, recently maintaining around 0.90 for several days, indicating that capital operations during the upward process have clearly become more conservative. Some funds are inclined to position short positions to test the risk of a pullback. Although the market is rising, the sentiment has not completely turned strong, forming a divergence structure of price increase and weak sentiment.

Overall, under the backdrop of BTC and ETH fluctuating at high price levels, the long-short ratio is weakening simultaneously, indicating that the market has doubts about the sustainability of the subsequent upward trend. If the long-short ratio does not effectively rebound in the short term, it may limit further upward momentum; conversely, if LSR stabilizes and rises back above 1, it will become an important leading signal for the continuation of the market.

Figure 3: BTC price maintains a high consolidation range, but the long-short ratio continues to decline, reflecting a significant weakening of market bullish sentiment.

Figure 4: The ETH long-short ratio is declining simultaneously, and the sentiment has not followed the price to strengthen, indicating that short-term funds are becoming more cautious.

3. Analysis of Contract Holding Amount

According to Coinglass data, the total contract positions for BTC and ETH have remained at relatively high levels over the past two weeks, indicating that leveraged funds have not exited the market, and the atmosphere of market speculation still persists. The position amount for ETH has rapidly climbed since early August, reaching a peak of 65.7 billion USD around August 12, before slightly retreating, but the overall level remains higher than the previous average. The contract positions for BTC first fell and then rose, gradually increasing to 84.2 billion USD after August 10, showing a trend that is generally in sync with ETH, but with a relatively moderate increase.

Overall, the growth rate of ETH contract positions leads BTC, indicating that the market is more actively leveraging its outlook. This corresponds with the strong upward trend in spot prices. Although the current overall position level remains healthy, considering that both price and leverage are at high levels, one should be cautious of potential risks of concentrated liquidations or rapid corrections if unexpected fluctuations occur in the future.

Figure 5: BTC and ETH contract positions fluctuate at high levels, with ETH's growth rate leading and leveraged funds remaining active.

4. Funding Rate

In the past two weeks, the funding rates for BTC and ETH have fluctuated around the zero axis, indicating a stalemate in the market between bulls and bears, with a strong wait-and-see sentiment among leveraged funds. Although prices are at relatively high levels, the funding rates have not effectively turned positive, reflecting that this round of market movement is mainly driven by spot and low-leverage funds, with a relatively stable market structure.

ETH experienced several brief periods of negative funding rates in early to mid-August, indicating a slightly bearish sentiment during certain phases, but these were quickly corrected and did not trigger a significant reversal. BTC, on the other hand, exhibited smaller overall fluctuations and more stable funding rates, reflecting its stability as an asset for institutional allocation and its preferred advantages.

Overall, the current leverage momentum has not been significantly released. If the funding rate turns positive and stabilizes upward, coupled with an increase in volume, it may become an important signal for a secondary bullish attack in the market.

Figure 6: The funding rate oscillates around the zero axis, with the short-term market mainly in a wait-and-see mode, and the momentum still to be released.

5. Cryptocurrency Contract Liquidation Chart

According to Coinglass data, although the cryptocurrency market has been in a high consolidation phase over the past two weeks, it has still experienced occasional local market fluctuations that triggered contract liquidations, presenting a pattern of alternating bullish and bearish sentiments with a balanced tension.

On August 14 and August 18, the amount of long positions liquidated significantly increased, exceeding 800 million and 400 million dollars respectively. This reflects that during the market's pullback after a high rally, the funds chasing long positions faced reverse liquidation, indicating a slowdown in the bullish momentum and a rising cautious atmosphere in the market. On the other hand, the liquidation of short positions was concentrated on August 12 and 13, corresponding to the short-term rebound, where some shorts attempting to catch the top faced strong liquidations. [9]

Overall, the current pace of contract liquidations remains moderate and rotational, without a concentrated stampede-style chain liquidation. This indicates that the market maintains a healthy position structure amid fluctuations. The interplay of long and short positions releases liquidation tension, helping to cleanse short-term sentiment and floating chips, thus accumulating more stable momentum for future market movements.

Figure 7: The amount of long position liquidations on August 14 and August 18 significantly increased, reflecting that during the market's pullback after a high-level surge, the chasing long funds encountered reverse liquidations, indicating a slowdown in bullish momentum and a rising cautious atmosphere in the market.

In the current environment of high volatility and a structurally bullish market, the overall trading activity in the cryptocurrency market remains, but short-term capital sentiment has shown divergence, with leverage positioning becoming more cautious, resulting in a coexistence of trend continuity and volatility. Multiple indicators show that although BTC and ETH remain in a technically strong range, data such as the long-short trading ratio, funding rates, and contract liquidations all reflect a weakening willingness to chase prices, leading to a slowdown in bullish momentum in the short term. In the face of a complicated situation with long and short positions locked in and sensitive sentiments, investors need to rely more on systematic quantitative indicators to judge trend reversals and changes in capital structure.

Therefore, the following content will focus on the moving average in technical indicators, exploring its practical effects in identifying trend reversals and capturing entry and exit signals in high-level fluctuations and swing rotation markets. We will center on the "Dense Moving Average Breakthrough Strategy," backtesting its performance under different cryptocurrencies and market structures, and assessing the adaptability and stability of this strategy in following trends, controlling drawdowns, and amplifying mid-stage trend gains.

Quantitative Analysis - Moving Average Convergence 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 trends. Investors should fully consider risks and make cautious decisions when making relevant investments.)

1. Strategy Overview

The "Moving Average Convergence Breakout Strategy" is a momentum strategy that combines technical trend analysis. The strategy involves observing the convergence of multiple short to medium-term moving averages (such as 5-day, 10-day, 20-day, etc.) over a specific period to identify potential moments for directional volatility in the market. When multiple moving averages trend in unison and come closer together, it usually indicates that the market is in a consolidation phase, waiting for a breakout. If the price clearly breaks upward through the moving average area, it is considered a bullish signal; conversely, if the price breaks downward through the moving average band, it is seen as a bearish signal.

In order to enhance the practicality of the strategy and the effectiveness of risk control, this strategy also has a fixed ratio of take-profit and stop-loss mechanisms, ensuring timely entry and exit when a trend appears, balancing rewards and risk control. The overall strategy is suitable for capturing medium to short-term trend markets and possesses a certain level of discipline and operability.

2. Core Parameter Settings

3. Strategy Logic and Operational Mechanism

Entry Conditions

• Moving Average Convergence Judgment: Calculate the difference between the maximum and minimum values of the six moving averages: SMA20, SMA60, SMA120, EMA20, EMA60, and EMA120 (referred to as moving average distance). When the distance is below a set threshold (such as 1.5% of the price), it is considered moving average convergence.

• Price Breakthrough Judgment:

• When the current price crosses above the highest value of the six moving averages, it is considered a bullish breakout signal, triggering a buy operation.

• When the current price breaks below the lowest value of the six moving averages, it is considered a bearish breakout signal, triggering a sell operation.

Entry Conditions

• Long Position Exit:

• If the price falls below the lowest moving average at the time of opening, trigger the stop loss;

• Or if the price rises above "the distance between the opening price and the lowest moving average × the profit and loss ratio," it triggers a take profit.

• Short Position Exit:

• If the price rises above the highest moving average at the time of opening the position, trigger the stop loss;

• Or if the price drops more than "the distance between the opening price and the highest moving average × the profit-loss ratio", trigger take profit.

Practical Example Chart

• Trading signal triggered The chart below shows the TRX/USDT 1-hour candlestick chart at the most recent entry trigger on August 12, 2025. It can be seen that after the price broke upward following a highly concentrated level of six moving averages, it met the entry conditions set by the strategy. The system executed a buy operation at the price of the breakout, successfully capturing the starting point of the subsequent upward trend.

Figure 8: Schematic diagram of the actual entry position when the strategy conditions for TRX/USDT are triggered (August 12, 2025)

• Trading actions and results The system automatically exits based on a dynamic profit-taking mechanism after reaching the preset profit-loss ratio, effectively locking in the main segment gains. Although there is still potential for further upward movement that has not been included, the overall operation adheres to strategic discipline, demonstrating good risk control and execution stability. If combined with a trailing stop or trend-following mechanism in the future, it may further extend the profit space in a strong market.

Figure 9: TRX/USDT Strategy Exit Position Diagram (August 14, 2025)

Through the above practical examples, we intuitively present the entry logic and dynamic profit-taking mechanism of the strategy when the moving averages are dense and the price breakout conditions are triggered. The strategy captures the trend initiation points precisely through the interaction between price and moving average structure and automatically exits during subsequent fluctuations, locking in the main profit zone while controlling risk. This case not only verifies the practicality and execution discipline of the strategy but also reflects its stability and risk control ability in the real market, laying the foundation for subsequent parameter optimization and strategy summary.

4. Practical Application Examples

Parameter Backtest Settings To find the best combination of parameters, we conducted a systematic grid search within the following range:

• tp_sl_ratio: 3 to 14 (step size of 1)
• threshold: 1 to 19.9 (step size of 0.1)

Taking SUI/USDT as an example, in the backtesting data of the 1-hour K-line over the past year, the system tested a total of 2,280 parameter combinations and selected the top five with the best cumulative return performance. The evaluation criteria include annualized return rate, Sharpe ratio, maximum drawdown, and ROMAD (return to maximum drawdown ratio), used to comprehensively measure strategy performance.

Figure 10: Comparison Table of the Performance of Five Optimal Strategies

Strategy Logic Explanation When the system detects that the distance between the six moving averages converges to within 19.9%, and the price breaks above the upper edge of the moving averages from below, a buy signal is triggered. This structure aims to capture the moment when the price is about to initiate a breakout, entering at the current price and using the highest moving average at the time of the breakout as a reference benchmark for dynamic profit-taking, thereby enhancing the ability to control returns.

The settings used in this strategy are as follows:

• percentage_threshold = 19.9 (maximum gap limit for six moving averages)
• tp_sl_ratio = 14 (Dynamic Take Profit Margin Setting)
• short_period = 6, long_period = 14 (moving average observation period)

Performance and Results Analysis The backtesting period is from August 1, 2024, to August 18, 2025. This set of strategies has shown good performance across multiple currencies. Taking SUI as an example, the cumulative return rate reached 285.49%, with a maximum drawdown of 36.29% and a ROMAD of up to 7.25, demonstrating strong capital appreciation ability and moderate risk control. The XRP combination achieved a return of 101.86% despite a higher drawdown (48.87%), with a Sharpe Ratio of 1.46, indicating relatively stable performance in volatility control.

Figure 11: Comparison of the cumulative return rates of five sets of optimal parameter strategies over the past year

5. Summary of Trading Strategies

This study verifies that the trend strategy based on moving average convergence breakout has good practical potential in the medium to high volatility cryptocurrency market. Through clear entry and exit logic and robust risk control mechanisms, this strategy not only outperforms Buy and Hold overall but also demonstrates strong capital appreciation ability across multiple mainstream cryptocurrencies.

Especially in situations with low win rates, the strategy effectively controls losses and extends profit-holding time through an asymmetric profit and loss structure and strict trading discipline, successfully achieving the goals of risk control and profit accumulation, highlighting its adaptive advantages in unclear market trends. If future developments incorporate multi-factor signals, volume confirmation mechanisms, and dynamic parameter adjustment logic, it is expected to further enhance the strategy's stability and flexibility, and expand into multi-currency and multi-timeframe trading systems.

It is worth noting that the trading frequency of the five sets of parameters during this backtesting period is generally low, which may affect the stability of the statistical results and the generalization ability of the strategy. Some cryptocurrencies, such as BTC and SOL, have relatively weak win rates and return performances, possibly limited by the signal trigger thresholds or the volatility characteristics of the cryptocurrencies themselves. Therefore, it is recommended to further enhance the sample coverage in the future, such as extending the backtesting period, including more cryptocurrencies, or using different levels of time frames, to strengthen the robustness of the strategy and improve the reliability of live deployment.

Despite the aforementioned limitations, based on the current backtesting results, the five sets of optimal parameter combinations selected in this paper have achieved a relatively ideal balance between returns and stability in the current strategy, demonstrating practical application value. If factors such as trading volume and volatility can be further incorporated into the screening logic, and if the signal structure and capital management rules are continuously optimized, the strategy's adaptability in volatile markets is expected to improve continuously and show stable performance in a broader market environment.

Summary

From August 5 to August 18, 2025, the cryptocurrency market maintained a high-level fluctuation pattern overall, with the technical structure of mainstream assets showing strength. ETH performed relatively well, coupled with a record high in net inflows of spot ETF funds, providing medium-term support for the market. However, from the perspective of key indicators such as long-short trading ratios, funding rates, and liquidation structures, the market's willingness to chase long positions has weakened, and sentiment has become more conservative, showing a short-term pattern of structural fluctuations and chip redistribution.

Overall, the participation of leveraged funds has not yet overheated, with contract positions and funding rates remaining high but stable, indicating a healthy market structure; moderate liquidations under the rotation of long and short positions help to reshuffle sentiment and clear floating chips. If trading volume increases in the future and funding rates continue to turn positive and stabilize, multiple momentum factors may drive the market to break through the current consolidation range; conversely, if funds are hesitant and volatility contracts, mainstream coins may continue to exhibit weak consolidation in the short term.

In this context, the trend-based strategy constructed based on the dense moving average breakthrough logic has shown good practical potential in the medium to high volatility cryptocurrency market. Backtesting results indicate that the performance of the SUI and XRP strategies is particularly outstanding, with cumulative returns exceeding 100%.

It is important to note that during the backtesting period, the number of trades for the five sets of parameters was relatively low, which may affect the statistical robustness and generalization ability of the strategy. Some cryptocurrencies, such as BTC and SOL, also performed relatively conservatively due to their volatility characteristics and signal frequency limitations. Overall, this strategy achieves a good balance between returns, drawdown control, and execution efficiency, making it valuable for live deployment. In the future, integrating factors such as trading volume, volatility, or multi-period resonance, and introducing a more flexible risk control mechanism, is expected to further enhance the stability and adaptability of the strategy.
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. Sosovalue, https://sosovalue.com/assets/etf/us-btc-spot?from=moved
5. Coinglass, https://www.coinglass.com/LongShortRatio
6. Coinglass, https://www.coinglass.com/BitcoinOpenInterest?utm_source=chatgpt.com
7. Gate, https://www.gate.com/futures_market_info/BTC_USD/capital_rate_history
8. Gate, https://www.gate.com/futures/introduction/funding-rate-history?from=USDT-M&contract=ETH_USDT
9. Coinglass, https://www.coinglass.com/pro/futures/Liquidations

Disclaimer Investing in the cryptocurrency market involves high risk, and users are advised to conduct independent research and fully understand the nature of the assets and products being purchased before making any investment decisions. Gate does not take any responsibility for any losses or damages resulting from such investment decisions.