1. Strategy Positioning and Scope

This trading system is a rule-based workflow designed to capture the cleanest segment of trends across markets and instruments. Its core is to filter high-quality structural opportunities from a large universe, then convert trading decisions from subjective monitoring into process-driven, state-machine execution through strict per-trade risk limits and predefined alert/execution rules. In execution, it uses strict passive trend-following position management and relies on positive mathematical expectancy to maintain a favorable portfolio-level payoff profile.

1.1 Markets and Instruments Covered

The system is designed for major global financial markets across multiple asset classes, including but not limited to:

Stocks
Futures
Forex
Crypto Assets

Instrument selection follows unified tradability standards: sufficient liquidity, continuous pricing, and no frequent structural gaps during normal trading sessions. Under this framework, the system can cover thousands of tradable symbols (currently about 3300+), ensuring statistically meaningful opportunity flow and diversification.

1.2 Timeframe and Holding Period

Decision timeframe: 1-hour (1H) as the primary cycle for structure recognition and decision-making.
Holding period: from hours to weeks/months, depending on trend progression efficiency and structural evolution. The goal is not ultra-long holding but efficient participation in the smoothest trend phase.
Signal frequency: medium, around 2-3 signals per week on average, with uneven distribution, consistent with the trend workflow of "wait -> trigger -> advance -> exit".

2. Methodology: From Large-Sample Screening to Key-Point Execution

Instead of over-focusing on a few instruments, the system compounds probability edge through a closed loop:

large-universe scan -> watchlist formation -> price trigger -> live confirmation -> risk-controlled execution -> trend-phase management.

Core principles include:

Rule-based visual structure recognition: price structure, bases, and breakout behavior are clearly defined to reduce ambiguity.
Alert-driven execution: key actions are bound to explicit conditions and alerts, reducing screen-time dependency.
Large-sample selection: broad coverage increases the probability of high-quality setups and reduces single-symbol randomness.
Focus on the smoothest trend phase: not trying to capture every tick, but the most efficient segment.
Risk-first mechanics: per-trade risk comes first; sizing is derived from stop structure and risk budget, not emotion.

3. Operational Workflow

3.1 Full-Market Scan: Low Frequency, High Coverage

The system scans the full universe on a fixed cadence:

Scan frequency: typically one structural scan of the full universe per day (adjustable by market regime and asset class behavior).
Scan method: rapid qualification per symbol; non-qualifying structures are immediately skipped.
Objective: isolate candidates with structure quality materially above average, rather than overfitting market noise.

3.2 Continuous Watchlist: From Candidate to Trigger-Ready

When a symbol meets baseline structural requirements, it is added to a continuous watchlist, then moved to the next stage:

No frequent intervention during observation; wait for characteristic price action or pre-breakout behavior.
Pre-set price alerts mark trigger zones, prompting rapid live review and intervention.

This separates opportunity discovery from execution, so action occurs near expansion points and avoids low-value effort and emotional depletion.

3.3 Daily Maintenance: Low Monitoring Burden

After entering the watchlist, the system updates status via daily scheduled scans:

No prolonged screen monitoring required;
Manual confirmation and execution only when alerts fire or structure shifts materially;
State-machine management divides the process into reusable steps (observe / pending trigger / confirm / position management / exit).

4. Opportunity Identification Framework: Quality Accumulation Structure

The system's core edge comes from a standardizable price behavior pattern summarized as:

"quality accumulation + key-level breakout".

In practical terms: price completes meaningful ownership transfer and structural convergence in a phase that increases directional consistency and follow-through efficiency after breakout.

Key dimensions in identification (principles only; internal thresholds/scores are undisclosed):

Quality and duration of consolidation
- Is consolidation duration sufficient for transfer?
- Is there convergence/stability instead of random oscillation?
Path profile and structural symmetry
- Does the path show a coherent "base -> retest -> continuation" logic?
- Are common pre-trend structural traits present?
Support/resistance platform location
- Is the platform in an advantageous zone (for example near key levels or dense cost areas)?
- Are boundaries clear enough to define risk?
Test count and reaction quality
- Do boundary tests show force transition?
- Are reactions to support/resistance consistent and repeatable?
Tail-state and pre-breakout compression
- Does the tail structure imply controlled risk and easier directional advance?
- Are there signs of elevated false-breakout risk (principles public, detailed exclusion logic private)?
Breakout validity and behavior
- Are there signs of effective breakout (advance speed, pullback form, structure retention, etc.)?
- Avoid dependence on a single indicator; use structure-consistency judgment.

Important note: these conditions are structurally defined by explicit internal rules and constrained by consistent execution workflows to minimize subjective interpretation. Specific thresholds, weights, scoring rules, and trigger combinations are core proprietary assets and are not disclosed externally.

5. Trade Trigger and Execution: Alerts + Live Confirmation

5.1 Trigger Mechanism

When a watchlist symbol approaches key price zones or meets breakout criteria, a price alert triggers the next step:

An alert is not an automatic order;
It starts the live confirmation stage.

The goal of live confirmation is to ensure structure validity, clear risk boundaries, and complete execution conditions.

5.2 Execution Principles

Execution emphasizes consistency and repeatability:

No impulsive chasing or emotional add-ons;
Standard chain: predefined per-trade risk -> size calculation -> planned execution;
The trader acts as a process executor, not an on-the-spot predictor.

6. Risk Management: Position Sizing and Stops with 1R as Core Unit

The system uses R (Risk Unit) as the unified risk metric:

1R = maximum allowed loss for one trade (expressed as a fraction of account equity).
In practice, per-trade risk is usually controlled in the 1%-3% range (adjustable by risk preference, asset volatility, and exposure profile).

6.1 Stop Logic: Structure-Derived, Not Arbitrary

Stop placement is derived from key pre-breakout structural invalidation points:

If price returns and breaks that structure, the breakout thesis is invalid and the position exits;
The stop is not a fixed point distance, but a structural stop aligned with strategy logic.

6.2 Position Sizing: Derived from Risk Budget and Stop Distance

Position size is determined by:

Allowed monetary risk per trade (1R)
Risk distance between entry and stop (structure-defined)
Contract/instrument unit value, tick value, fees, and slippage assumptions

This gives natural cross-asset portability: sizing auto-adapts to different volatility regimes while keeping comparable relative risk.

6.3 Concurrent Position and Correlated Exposure Limits

The system limits both concurrent positions and correlated cluster exposure based on:

Per-trade 1R budget;
Directional/concentration overlap in current holdings;
Tail-risk conditions under current volatility regime.

Purpose: prevent excessive stacking on the same macro factor or risk source and keep portfolio-level risk controllable.

7. Position Management and Exit: No Scaling, Staged Protection, and Tracking

Position management is designed to be simple, repeatable, and auditable.

7.1 No Adding, No Partial Reducing

No scale-in/scale-out during the trade;
Edge concentration stays in five core links: multi-symbol selection + specific price behavior + entry location + risk control + trend-phase tracking.

7.2 Staged Protection: From Risk Control to Profit Protection

The system typically sets alerts at key progression milestones to switch management logic:

Once price advances sufficiently, it shifts to more conservative risk protection (for example protective stops and near-cost protection principles);
After entering a better trend phase, it shifts toward a more trailing-exit framework to improve reward/drawdown efficiency.

External disclosure explains only staged principles; exact milestone formulas, trigger ratios, and internal parameters are not disclosed.

7.3 Tracking and Passive Exit: Structure-Based

After trend development, the system periodically checks for clear corrective structures:

If a clear correction/pullback structure appears, it applies preset trailing protection;
If trend continues without structural warning, it keeps the position;
In higher-profit zones, it introduces a more drawdown-constrained passive exit layer (for example frameworks using retracement thresholds) to balance tail capture with profit giveback control.

8. Additional Rules for Stocks (Compliance and Event-Risk Control)

For global equities, stricter discipline is applied to reduce event risk and structural distortion:

Long-only by principle in equities (to reduce short-side risks such as squeezes, borrow cost, policy shocks, and sentiment spikes).
No trading near major event windows (for example earnings) to avoid uncontrolled gaps and information asymmetry.

9. System Advantages and Boundary Conditions (Risk Disclosure)

9.1 Key Advantages

Lower monitoring burden: scan + watchlist + alert triggers focus attention on high-value moments.
Rule-based consistency: reusable recognition and execution chain improves training and auditability.
Large-sample probability edge: broad coverage increases high-quality opportunity frequency and reduces single-symbol dependence.
Risk-first architecture: sizing from structure stop + 1R controls single-trade and portfolio exposure.
Efficiency over full capture: focus on smooth trend segments to improve return efficiency per unit time.

9.2 Applicable Conditions and Failure Modes

Under extreme event-driven gaps, liquidity drought, or trading halts, structural stops may suffer amplified slippage;
In prolonged noisy regimes without trend extension, the system may shift to "more screening, fewer executions" or "more trial losses";
Microstructure differences across asset classes (session profile, spread model, leverage mechanics) affect execution detail, so process adaptation by asset class is required while core principles stay unchanged.

Risk notice: past performance does not guarantee future results. Any trading system can experience drawdowns and stage-based degradation. Investors should assess decisions according to their own risk tolerance and consult licensed professionals when needed.

Closing: An Explainable, Executable, and Auditable Trend-Structure System

In summary, this system does not depend on a single indicator or short-term prediction. It relies on structured screening of accumulation formations and key-level breakout triggers, unifies sizing and stop management through a 1R framework, and seeks trend-phase returns through concise position-management logic.

Trading Strategy Overview