In the cryptocurrency derivatives market, the key to sustained profitability is not relying on subjective judgment, but rather building a quantifiable trading system. In the past month, through 27 contract trades, a 92.6% win rate was achieved, with average profits ranging from 8.3% to 14.7%. The account grew from 3300U to 28500U, demonstrating the effectiveness of systematic trading — focusing on mainstream cryptocurrency contracts, with the core being the establishment of an operational framework where 'rules take precedence over experience'.
1. The 'airspace kill' system: A logical model derived from a loss of 120,000 U.
This trading system, based on pure data-driven methods, strict disciplinary constraints, and automated warnings, focuses on solving three problems:
Eliminating emotional interference: Triggering trading signals through fixed parameters, replacing subjective decision-making;
Locking in high win rate intervals: Only participating in clearly defined trend waves, filtering out choppy noise;
Building a risk buffer mechanism: Using layered position design to respond to sudden market changes.
The underlying logic can be simplified into three principles:
Going with the trend: Not predicting turning points, only tracking trend confirmation signals;
Swing profit-taking: Locking in single trade profits within a preset range, refusing to give back profits;
Data anchoring: Using market capital behavior data as the sole decision-making basis, shielding from external interference.
II. Core system architecture: Building a closed trading loop with three dimensions.
1. Preemptive opening logic for taking profits.
Clearly define the profit-taking threshold before trading starts, with opening decisions relying solely on three core data sets:
Liquidation distribution map: Identifying long and short critical points (when the liquidation volume in one direction exceeds 60%, reverse signals are enhanced);
Long-short position ratio: Main capital inclination (when deviating from the mean by more than 3 standard deviations, trend-following signals are triggered);
Order density analysis: Eliminating interference from invalid orders (when the proportion of valid filled orders is less than 30%, it is considered a trap for inducing long/short positions).
1. Control the opening error rate within 10% through data cross-validation. 2. Trend filtering for market selection involves participating only in two types of high-certainty trends, automatically avoiding choppy markets:
Phase of trend initiation: Entering within 1 hour after breaking previous resistance levels, accompanied by a volume increase of more than 3 times;
Deep V pullback second confirmation: Entering when the downtrend reverses, and the neckline is not broken while a bottom divergence signal appears.
This screening mechanism increased the proportion of effective trades from 35% to 82% across all time periods. 3. A three-tier position management system divides each trade into three layers to achieve a dynamic balance of risk and reward:
Main position (70%): First batch entry after trend confirmation, undertaking basic profit tasks;
Secondary position (20%): Additional entry during trend acceleration stages (such as breaking key moving averages) to amplify profits;
Safety position (10%): Reserving funds for reverse operations to respond to black swan events, providing a buffer during market fluctuations.
III. Automated warnings: Upgrading risk control through tool empowerment.
Real-time monitoring of four core indicators through scripts, triggering operational alerts once thresholds are reached:
Concentration of liquidation points, long and short liquidation volume ratios, leverage capital density, and capital rate deviation.
This institutional-like monitoring system compresses the reaction delay of manual monitoring from an average of 15 minutes to under 30 seconds, significantly reducing the risk of signal omission.
IV. Empirical validation: The system's adaptability to different users.
A long-term investor with 3 years of losses: After applying the system, a principal of 1200U grew to 9400U, primarily by avoiding 80% of invalid trades;
A novice with zero experience: Achieving a daily average of 8% stable returns through signal following, proving that the system requires very low cognitive thresholds;
Full-time trader: Using automated tools to enhance operational efficiency, reducing daily trading decision time from 4 hours to 1 hour.
The essence of trading is a game of probability, and the value of systematic operation lies in: improving the winning rate through data anchoring, controlling odds through disciplined execution, and enhancing efficiency through tool empowerment. When most people rely on feelings to chase the market, a replicable system becomes the core competitive advantage to navigate through bull and bear markets.
Intraday focus: ETH LNIK XRP