Overview

This biweekly quantitative report (Mar 12 - 26, 2025) provides an in-depth analysis of recent trends and dynamics in the cryptocurrency market through multidimensional data analysis. The report focuses on key indicators for Bitcoin and Ethereum and contract liquidation events while also providing in-depth analysis and backtesting of the TD Sequential indicator.

Abstract

• Over the past two weeks, the Bitcoin (BTC) market has become increasingly sensitive, while Ethereum (ETH) has shown weak price action and lacks upward momentum, though its volatility remains relatively low.
• The BTC long/short trading ratio has stayed between 0.95 and 1.10, suggesting that traders still have a strong appetite for long positions during the price rebound.
• The average daily liquidations in the derivatives market have dropped to $200 million, a 74% decrease compared to earlier periods.
• Bitcoin’s realized market cap growth rate for the month is just 0.67%, indicating that new capital inflows have nearly stalled.
• Using the TD Sequential indicator to forecast price reversals, returns reached as high as 178% under optimal parameter settings.

Market Overview

1. Bitcoin & Ethereum Volatility Analysis

Over the past two weeks, Bitcoin (BTC) has rebounded steadily after forming a short-term bottom around the $80,000 level in mid-March, climbing back to $87,000 by March 26. In contrast, Ethereum (ETH) has seen more modest gains, gradually rising from around $2,000 to $2,100. The overall price increase for ETH has lagged behind BTC, signaling weaker bullish sentiment toward Ethereum.

Chart 1: BTC has rebounded to $87,000, while ETH remains near $2,100, showing relatively weaker performance.

Regarding volatility, BTC has generally exhibited greater fluctuations than ETH, indicating that market participants are more reactive to Bitcoin’s price movements. Short-term trading sentiment remains dominant. Compared to the heightened volatility seen at the beginning of March, BTC and ETH have now entered a more stable phase, suggesting that extreme emotions are fading and market sentiment is becoming more rational.

Chart 2: BTC shows higher volatility than ETH, reflecting stronger price swings.

Overall, the market appears to be entering a phase of volatility compression, with BTC showing stronger momentum than ETH. If low volatility persists, it may signal an upcoming trend confirmation. However, a sudden rise in volatility could indicate a directional breakout—investors should be mindful of the risks associated with short-term market swings. In the short term, keeping an eye on BTC’s capital flow and volatility trends can be a key indicator of market risk appetite. [1][2]

2. Bitcoin and Ethereum Long/Short Taker Size Ratio (LSR) Analysis

The Long/Short Taker Size Ratio (LSR) measures the volume of aggressive buying versus selling and is a key metric to gauge market sentiment and trend strength. An LSR above 1 indicates more aggressive buying (longs), suggesting a bullish sentiment in the market.

According to data from Coinglass, BTC’s LSR has shown a mildly upward trend over the past two weeks, fluctuating between 0.95 and 1.10. Even as BTC stabilized and rebounded, the LSR didn’t decline significantly—indicating continued bullish sentiment and a relatively optimistic market tone. By comparison, ETH’s LSR remained between 0.90 and 1.05 during the same period, but with slower fluctuations. During ETH’s mild price recovery, the LSR did not strengthen noticeably, suggesting that market participants remain cautious about Ethereum’s upside. While prices have rebounded slightly from the bottom, the momentum appears weak, reflecting conservative capital inflows.

Overall, BTC’s LSR has moved in sync with its price trend, suggesting growing confidence in its upward potential. ETH, on the other hand, lacks strong long-side support during its recovery phase, and may continue to trade sideways in the near term. Investors are advised to keep a close watch on LSR movements, as it remains a crucial signal for shifts in market sentiment. [3]

Chart 3: BTC’s LSR stays between 0.95 and 1.10, showing continued buying interest during the rebound.

Chart 4: ETH’s LSR shows slower movements, holding steady between 0.95 and 1.05.

3.Open Interest Analysis

According to Coinglass data, since March 12, Bitcoin (BTC) open interest has shown a clear rebound, rising sharply from a low of around $49 billion to nearly $58 billion. This suggests a notable return of capital to the market, with short-term trading sentiment turning increasingly positive. The recent price recovery may drive the surge, improved risk appetite, or a rebuilding of leveraged positions—indicating growing short-term bullish expectations for BTC.

By contrast, Ethereum (ETH) open interest has also ticked slightly during the same period but with much less intensity, rising modestly from around $19 billion to $21 billion. This more muted increase reflects continued caution among leveraged traders toward ETH, and suggests that confidence in ETH’s rebound remains weaker than for BTC.

Overall, BTC’s stronger open interest recovery signals a market sentiment leaning more toward Bitcoin in the short term, with investors’ risk appetite gradually improving. However, if open interest fails to continue rising, BTC could slip back into a consolidation phase. Whether capital continues to flow in will be a key factor in determining the market’s next direction. [4]

Chart 5: BTC open interest shows strong momentum, while ETH’s recovery is limited, reflecting weaker confidence in its rebound.

4. Funding Rates Analysis

Over the past two weeks, funding rates for BTC and ETH have fluctuated sharply, with frequent up-and-down swings, highlighting the market’s choppy leverage sentiment and uncertain short-term direction. BTC’s funding rate dipped into negative territory at several points, reaching as low as -0.01%. This indicates that short sellers briefly gained the upper hand, suggesting lingering bearish expectations around BTC’s short-term movement.

While ETH’s funding rates also showed frequent swings, the magnitude was slightly lower than BTC’s, reflecting a relatively milder speculative environment and less aggressive leverage activity around Ethereum.

Notably, even though BTC and ETH prices have rebounded over the past week, funding rates haven’t followed suit—instead, they quickly retreated after local peaks. This disconnect suggests the current rally lacks strong support from leveraged capital. The repeated shifts in funding rates imply the market remains in a tug-of-war between bulls and bears, with no clear capital flow trend yet. [5][6]

Chart 6: BTC funding rates repeatedly fell into negative territory, indicating that bearish capital briefly dominated the market.

5. Cryptocurrency Contract Liquidation Trends

Data from Coinglass shows that since March 12, liquidation activity in the crypto derivatives market has significantly declined. Compared to the heavy liquidations seen in early March, recent volatility has been much more subdued, and leverage adjustments are now more controlled. This suggests the market is entering a consolidation phase.

Interestingly, average liquidation amounts for short positions were slightly higher than for longs, indicating that some bearish traders were forcefully liquidated during the price rebound. Meanwhile, long liquidations have returned to normal levels, reflecting a partial recovery in bullish sentiment, though still cautious.

Overall, liquidation data shows the market has cooled notably from the high-volatility phase in late February to early March. The current average daily liquidation amount is around $200 million—a 74% drop from prior levels—suggesting that short-term market risk has been largely digested. If prices continue rising steadily and liquidation levels remain low, investor confidence could improve further. [7]

Chart 7: From March 12 to March 25, average daily liquidations in the contract market fell to $200 million, down 74% from earlier highs

6. Bitcoin Realized Cap Growth Rate at Just 0.67%

According to data from Glassnode, Bitcoin’s monthly growth rate in realized market cap is just 0.67%. The realized cap is calculated based on the price at which each BTC last moved on-chain, providing a clearer picture of actual capital cost. This slow growth indicates a lack of fresh capital inflows, suggesting that the buying pressure needed to support higher prices is weakening.

BTC has dropped over 10% from its February high of $97,000 to the current level of $87,000. This decline is not just a technical correction—it reflects deeper issues such as shrinking liquidity and cooling trader enthusiasm.

The market may face further downside risks without strong support from fundamentals or new capital. At this stage, investors should pay close attention to capital flows—including ETF inflows/outflows, stablecoin market cap trends, and on-chain activity like active addresses. These, combined with shifts in the macroeconomic environment, will be critical for assessing risk. Blind chasing or heavy positions should be avoided in the current climate. [8]

Chart 8: Bitcoin’s realized cap growth rate is only 0.67%, indicating that new capital inflows have nearly come to a halt

Quantitative Analysis – TD Sequential: An Early Warning System for Market Turning Points

（Disclaimer: All forecasts in this article are based on historical data and market trends. They are for reference only and should not be considered investment advice or guarantees of future market performance. Investors should fully assess risks and make cautious decisions when engaging in related investments.）

1. Overview of the Indicator

The TD Sequential is a counting-based system developed by technical analyst Tom DeMark, widely used across equities, futures, and cryptocurrency markets to identify potential trend reversals. The core idea is simple: after a sustained price move—either upward or downward—the trend may begin to show signs of “exhaustion,” indicating a possible reversal or at least a pause. This analysis backtests the indicator to evaluate its practical effectiveness in real trading scenarios.

2. Core Calculation Logic

The core calculation of the TD Sequential indicator is based on a price comparison mechanism. It evaluates the relative position and magnitude of the current price by comparing it to the price from a specified number of periods ago (denoted as LAG_N). The TD count starts at an initial value of 0 and is updated continuously based on these comparisons:

• If the current price is higher than the price LAG_N periods ago, the TD count increases by 1, up to a maximum of 13.
• If the current price is lower, the TD count decreases by 1, down to a minimum of 13.
• If the prices are equal, the TD count resets to 0.

This method produces TD values within a range of -13 to 13, allowing traders to gauge current price levels’ relative strength or weakness and identify potential reversal zones.

3. Trading Strategy Application

Trading Logic:

• In an uptrend, when the TD value declines from a higher number (e.g., 10) to a specific threshold (e.g., 9), it could signal an upcoming price drop, suggesting a potential short trade.
• In a downtrend, when the TD value rises from a lower number (e.g., -10) to a less negative value (e.g., -9), it may indicate an upcoming rebound—suggesting a potential long trade.

Trading Example:

Here’s an example using BTC 15-minute perpetual contracts on January 3, 2025:

The TD value is used to determine the relative position of the current price. BTC_Close refers to the 15-minute candlestick closing price of Bitcoin. Diff represents the difference between the current period’s price and the previous period’s price. Signals indicate entry signals, where 1 means the conditions for entry are met, and 0 means no action is taken.

We assume the price comparison baseline is the previous period (though this can be adjusted to other intervals). Starting from a TD value of 7, if the current price continues to fall compared to the previous period (with Diff shown in green), the TD value will decrease by 1 for each decline. Conversely, when the price rises (with Diff shown in blue), indicating that the current price is higher than the previous one, the TD value increases by 1. This mechanism is used to determine the relative position of the price.

Assuming the entry condition is defined as the current TD value equals 1 and the previous TD value is greater than the current value, this suggests a downward trend nearing the center point (0), indicating a possible reversal. When these conditions are met, a buy order is triggered at the closing price—for example, at 2025-01-03 05:15:00, when the Signal equals 1.

Strategy Parameter Description:

This strategy uses two parameters—LAG_N and N_SIGNAL—to determine the conditions for triggering trading signals.

1. LAG_N (Lag Period)

LAG_N defines how many periods back the current price is compared against to assess trend changes.

If LAG_N = 1, each closing price is compared to the previous period’s closing price. For example, when the BTC price drops from 97,019.1 to 96,930.5, the TD value decreases from 7 to 6. If LAG_N = 4, the current price is compared to the price four periods earlier, which helps smooth out short-term market noise and allows for more stable trend identification.

2. N_SIGNAL (Signal Trigger Threshold)
N_SIGNAL defines the TD value at which a trade signal is triggered, with the condition that the previous TD value must be greater than the current one. If the previous TD = 13 and N_SIGNAL = 13, then the condition changes slightly: the previous TD must be greater than or equal to the current TD, in line with the TD value’s upper limit.

If N_SIGNAL = 1, a buy signal is triggered when the current TD = 1 and the previous TD > current TD. For example, on 2025-01-03 at 05:15:00, when the TD value drops from 2 to 1, a buy signal is generated. This suggests the recent downtrend may be nearing exhaustion, and a rebound is likely.

Adjusting these two parameters allows the strategy to be fine-tuned for different market conditions, enhancing precision while reducing risk.

4.Parameter Optimization and Backtesting Validation

The core logic of this trading strategy is based on evaluating the relative position of price movements using the TD Sequential indicator. By identifying the price’s position relative to historical data—and combining it with trend direction and exhaustion signals—we aim to pinpoint potential turning points. A reversal may occur when prices become excessively high, low, or revert toward the mean. The TD value is constrained within a range of -13 to 13 to capture such scenarios. For this backtest, the holding period is fixed at N candlestick intervals, using 15-minute BTC_USDT perpetual contracts. The backtest period spans from March 24, 2024, to March 24, 2025. Transaction costs, such as fees or slippage, were not considered.

To identify the optimal parameter combination, we conducted backtesting across the following ranges:

• LAG_N: 0 ~13
• N_SIGNAL: -13~13

This results in a total of 14 × 27 = 378 unique parameter combinations.

Since each parameter set generated over 750 trades, the sample size meets statistical validity requirements. Therefore, we did not filter based on trade count and instead selected the top five combinations with the highest average returns. The five best-performing parameter combinations are as follows:

• LAG_N: 3, N_SIGNAL: 8
• LAG_N: 2, N_SIGNAL: 8
• LAG_N: 4, N_SIGNAL: 8
• LAG_N: 4, N_SIGNAL: 7
• LAG_N: 11, N_SIGNAL: 5

After identifying the top five strategies, we applied equal weighting to combine them and plotted the cumulative returns, Sharpe ratios, and overall profitability for analysis.

Chart: Cumulative return curves for the five strategies under equal weighting (each interval represents 15 minutes)

Chart: The highest Sharpe ratio of 3.72 occurred at the 4th holding interval

Chart: The maximum return of 178% was achieved at the 61st holding interval

5. Trading Strategy Summary

Using equal weighting, we combined the five best-performing parameter sets into a single composite strategy. The results show that the risk-adjusted return (Sharpe ratio) peaked at 3.72 when holding positions for four intervals. However, the total return at that point was only 77%, suggesting that the LAG_4 strategy, while relatively conservative and lower in volatility, is effective at controlling risk but may underperform in terms of absolute return compared to longer holding periods that take on more volatility for potentially higher gains. Regarding total return, we observed that as the holding period increased, returns continued to rise, reaching a maximum of 178% at the 61st interval. After this point, returns began to decline. The strategy delivered a significantly enhanced performance compared to simply holding BTC—which yielded about 35% during the same period.

Analyzing the optimal parameter combinations reveals that most of the best-performing LAG_N values fall between 2 and 4 (with only one outlier at 11). This indicates the strategy is primarily focused on short-term price fluctuations, using recent price movements to identify reversal signals and capture medium-to-short-term opportunities. Additionally, the N_SIGNAL values are mostly clustered around 7 to 8, which suggests that the best signals tend to occur when the TD indicator reaches relatively high values, indicating clearer confirmation of market reversals. This also reflects the strategy’s tendency to enter trades after a noticeable price decline. Overall, these findings suggest that the strategy is best suited for medium- to short-term reversal trading. It relies on short-term price comparisons and a relatively high threshold for signal activation to capture reversal opportunities within shorter holding periods. This approach aims to generate more stable, risk-adjusted returns, while holding positions for too long may diminish performance.

While the backtest results are promising, it’s important to remember that reversal strategies inherently seek turning points. Misjudging the trend direction could lead to significant losses. Therefore, downside risk must still be carefully controlled.

Conclusion

Between March 12 and March 26, the cryptocurrency market exhibited a structural pattern of “price rebound amid cautious sentiment.” Volatility in both BTC and ETH declined, indicating a cooling of short-term extreme emotions. Although market sentiment around BTC showed a modest improvement compared to ETH, overall leveraged momentum remained weak. On-chain and derivatives data revealed a recovery in open interest and a sharp decline in liquidations, suggesting that the deleveraging process is largely complete. However, the slowdown in Bitcoin’s realized market cap growth points to a lack of fresh capital inflows, and trading activity declines.

In the quantitative analysis section, we conducted backtesting using the TD Sequential indicator, which aims to forecast market price reversals. Under optimal parameter settings, the strategy achieved a return of up to 178%. However, it’s important to note that the TD Sequential is not a foolproof predictive tool. In real-market conditions, its effectiveness can be impacted by sharp volatility and false signals. We recommend that investors complement the TD strategy with multi-dimensional data analysis and robust risk management, making rational, well-informed trading decisions with a cautious approach.


References:

1. Gate.io,https://www.gate.io/trade/BTC_USDT
2. Gate.io,https://www.gate.io/trade/ETH_USDT
3. Coinglass,https://www.coinglass.com/LongShortRatio
4. Coinglass,https://www.coinglass.com/BitcoinOpenInterest?utm_source=chatgpt.com
5. Gate.io,https://www.gate.io/futures_market_info/BTC_USD/capital_rate_history
6. Gate.io,https://www.gate.io/futures/introduction/funding-rate-history?from=USDT-M&contract=ETH_USDT
7. Coinglass,https://www.coinglass.com/pro/futures/Liquidations
8. Glassnode,https://studio.glassnode.com/charts/ba1ec93d-85f4-41fe-5606-798a2f30013a?s=1679144783&u=1742303183

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Disclaimer
Investing in the cryptocurrency market involves high risk, and it is recommended that users conduct independent research and fully understand the nature of the assets and products they are purchasing before making any investment decisions. Gate.io is not responsible for any losses or damages caused by such investment decisions.