GateAI Bear Market Parameter Guide: How to Set a Buy Low, Sell High Strategy to Survive Long-Term Downtrends

“Money is made in a bear market; you just didn’t realize it at the time.” This classic insight from the crypto community precisely captures the essence of strategic positioning during market downturns.

When Bitcoin’s price has fallen over 22% in the past 30 days and Ethereum has dropped more than 32%, this prolonged downward trend is quietly changing the fundamental logic of crypto trading.

Traditional “hold” strategies are being tested in this environment, while the value of grid trading strategies aimed at “buying low and selling high” is gradually emerging. The core challenge in implementing such strategies lies in parameter settings; the combination of key parameters like price range and grid spacing directly determines the strategy’s profitability and risk level.

Market Dilemma

By early 2026, the crypto market shows a clear downward trend. Bitcoin’s price once broke above $95,000 in January but then entered a wide-ranging oscillation pattern. As of February 10, Bitcoin’s price is $70,108, a significant retracement from its all-time high.

In an environment dominated by macro policy-driven market sentiment, the behavior patterns of market participants are undergoing fundamental changes. Industry data shows that the total trading volume in the crypto market in 2025 has significantly slowed, and participant behavior is shifting accordingly. This change presents new challenges for traders: how to maintain strategy effectiveness in a persistently declining market?

Crypto markets are more sensitive than ever to macroeconomic factors. Tighter global liquidity, rising real interest rates, and fluctuating policy expectations now directly influence Bitcoin’s every move. Bitcoin’s 30-day price change has reached -22.05%, and Ethereum’s has hit -32.22%, indicating sustained downward pressure.

Intelligent Adaptation

In such a market environment, GateAI offers data-driven intelligent solutions. By analyzing vast amounts of historical data and real-time market information, GateAI helps traders build strategy parameters suited for long-term bearish markets. GateAI’s backtesting is not just simple historical data replay; it’s a deeply integrated AI-powered strategy optimization system.

Compared to traditional backtesting tools, GateAI emphasizes the engineering philosophy of “verify first, then generate.” This means the system prioritizes analysis based on verifiable historical data and market facts rather than speculative assumptions without basis. This feature is especially important for developing strategies in a long-term bearish market environment.

GateAI’s backtesting function helps users evaluate how different parameter combinations perform historically under similar market conditions. For example, in grid trading, the system can analyze how key parameters like price range, grid type (arithmetic or geometric), and grid quantity perform under various market scenarios. Notably, GateAI emphasizes assessing a strategy’s adaptability across different market environments (bull, bear, sideways), rather than optimizing for the best performance in a single historical segment. This comprehensive evaluation aids in building long-term, robust trading systems, especially during prolonged downturns.

Core Adjustments

In a long-term bearish market, parameter adjustments tailored to different asset classes are crucial. Here are GateAI’s recommended parameter settings for mainstream crypto assets in a sustained downtrend.

Bitcoin, as the market leader,’s price fluctuations often directly reflect macro sentiment shifts. According to GateMarket data, as of February 10, Bitcoin’s price is $70,108, fluctuating between $68,302.1 and $71,439.2 over 24 hours. During a persistent downtrend, it’s advisable to set a wider price range to prevent gradual price decline from breaching the range and invalidating the strategy. Grid spacing should be moderately enlarged (commonly using geometric grids) to ensure that profit per grid can cover higher volatility risks and transaction costs.

Ethereum exhibits different characteristics, with a current price of $2,110.72. Its volatility is generally higher than precious metals but lower than Bitcoin, so parameter settings can be intermediate.

According to GateMarket data, as of February 2026, Ethereum’s market cap is $252.82B. The scale difference compared to Bitcoin’s $1.41T market cap suggests they may react differently to the same market environment, so their parameters should differ accordingly.

Gate platform’s token GT is currently priced at $7.05, with a market cap of $759.29M and a market share of 0.032%. Its price volatility is closely tied to platform ecosystem development; historical data shows GT once reached $25.94, but has recently been oscillating.

The table below compares parameter setting differences across asset classes in a long-term bearish market:

Practical Guide

In a long-term bearish market, traders can optimize GateAI strategy parameters through the following steps to prepare for continued decline.

First, use GateAI’s intelligent backtesting to conduct forward-looking tests. Simply navigate to the Gate trading robot page, select the relevant strategy, and run backtests. The system simulates historical similar environments and provides key performance metrics like total return, maximum drawdown, and Sharpe ratio to support informed decisions.

Second, monitor market depth and liquidity changes. Prolonged downtrends often lead to decreasing market depth and widening bid-ask spreads. In such cases, grid parameters should be adjusted accordingly—possibly enlarging grid spacing to accommodate liquidity shifts.

Third, differentiate asset-specific configurations. During uncertain markets, different assets may perform divergently. As of February 2026, Bitcoin’s market cap is $1.41T, while Ethereum’s is $252.82B. This scale difference implies their parameters should differ as well.

Fourth, set reasonable risk control parameters. GateAI allows users to set price trigger conditions for strategies, where the system automatically takes profit or stops loss when target assets reach specific prices. This feature is especially important during sustained market declines.

Fifth, adopt a gradual optimization approach. First, determine approximate price range boundaries based on recent volatility and technical analysis. Then, test different grid spacings to find a balance between trading frequency and single-trade profit.

Risks and Protections

In highly volatile crypto markets, what’s most scarce isn’t profit opportunities but the ability to protect assets long-term. According to GateMarket data, Bitcoin’s 24-hour change is -0.43%, Ethereum’s is +1.40%. This ongoing market fluctuation makes risk control an indispensable part of AI trading.

As AI technology becomes the core driver of crypto trading, simply pursuing returns is no longer enough to measure a strategy’s true value. GateAI’s preemptive risk control features allow users to preset global stop-loss and profit protection rules before executing strategies.

The global stop-loss feature enables users to set a unified stop-loss for the entire AI trading strategy; when overall losses reach a preset threshold, all related trades automatically cease. This design prevents a single losing trade from spreading risk across the entire portfolio. Additionally, the automatic transfer of profits into a “safety box” when gains are realized helps lock in profits periodically, avoiding “paper wealth” and ensuring users retain some actual gains.

Regarding stop-loss settings, Gate recommends a dynamic range of 5%-15%, balancing profit and drawdown. Notably, AI’s ability to identify price turning points and optimize entry/exit timing is more precise and stable than human subjective judgment.

Outlook and Adaptation

Looking ahead to the remaining time in 2026, macro policies will continue to play a key role in the crypto market. Federal Reserve policy paths, global inflation trends, and geopolitical developments will all influence market volatility. In this environment, flexible, adaptive trading strategies will have a competitive edge.

Over 6,100 accounts weekly use GateAI’s backtesting to optimize their strategies. These users see more than just numbers—they experience performance improvements from optimized parameters, smoother profit curves, more controlled drawdowns, and more stable long-term results.

For quantitative traders using GateAI, parameter optimization aligned with current market conditions can significantly enhance strategy adaptability and robustness. When Bitcoin hovers around $70,108 and Ethereum seeks direction at $2,110.72, GateAI’s grid trading robots can automatically adjust buy and sell rhythms according to market phases.

Market volatility won’t stop, but with precisely calibrated GateAI parameters, market risks are quietly transformed into structured profit opportunities. The sensitivity of crypto markets to macro policies continues to rise, with thousands of traders weekly optimizing strategies via GateAI to respond to these changes.

When market sentiment is influenced by macro factors, history shows that when fear dominates, it’s the time to focus on long-term value rather than short-term panic. GateAI is designed to help traders stay rational in such environments, managing investments through data-driven decisions rather than emotional reactions.

Open the Gate platform’s trading robot page, click “Backtest,” and you’ll find the intelligent backtesting feature has been fully upgraded. In the latest GateAI system, AI is no longer just a bystander in the crypto world; it has become part of the market infrastructure. Over 6,100 active accounts weekly rely on this system to optimize their strategies, weaving macro volatility into orderly profit curves.

As Bitcoin seeks support around $70,108 and Ethereum builds a line of defense at $2,110.72, GateAI’s precise parameter settings are quietly transforming traders’ ability to navigate market fluctuations. Changes in the market environment are no longer intimidating but become opportunities for structured profits.

Meta description: Explore GateAI’s intelligent parameter setting strategies for long-term bearish markets. This article analyzes Bitcoin, Ethereum, and GT grid trading optimization in a bear market, covering price range setup, grid spacing adjustments, and risk management techniques to help traders achieve low buy and high sell during market downturns. Learn how to use GateAI’s smart backtesting to build robust trading systems. (Word count: 107)