Overview

This strategy is a mean reversion trading system based on weekly pivot points. It determines entry and exit points by calculating weekly support (S1-S4) and resistance (R1-R4) levels. The strategy employs a stepped position building approach, executing multiple buys at different support levels and taking profits at corresponding resistance levels. This method effectively utilizes market volatility characteristics and performs well in range-bound markets.

Strategy Principles

The core mechanism calculates the pivot point for the current week using the previous week's high, low, and closing prices, then determines multiple support and resistance levels based on preset point distances. Buys are executed when price touches support levels, with profit targets set at corresponding resistance levels. The specific formula is:
Pivot Point = (Previous Week's High + Previous Week's Low + Previous Week's Close) / 3
The strategy allows up to 4 concurrent positions, each corresponding to different support and resistance levels. All positions are recalculated at the beginning of each week. This design ensures trading continuity while adapting to market changes.

Strategy Advantages

1. Clear trading logic that is easy to understand and execute
2. Stepped position building approach reduces single trade risk
3. Weekly level support/resistance reduces daily noise impact
4. Parameters can be flexibly adjusted for different markets
5. Risk control through percentage-based position sizing
6. No time-based forced exits, allowing sufficient profit potential

Strategy Risks

1. Absence of stop-loss may lead to significant drawdowns in trending markets
2. Multiple positions may tie up substantial capital
3. False signals may occur in highly volatile markets
4. Improper support level settings may result in suboptimal entry positions
   To mitigate risks, consider adding trend filters to only enter during uptrends and implementing dynamic ATR-based stop-losses.

Optimization Directions

1. Add volume confirmation mechanism to improve entry signal reliability
2. Incorporate technical indicators like RSI for overbought/oversold filtering
3. Develop multiple timeframe confirmation to reduce false signals
4. Optimize position management system with dynamic position sizing based on volatility
5. Include correlation analysis to avoid simultaneous positions in highly correlated markets

Summary

This is a mean reversion strategy based on classical technical analysis theory, capturing trading opportunities through weekly support and resistance level breakouts and reversals. The strategy design is concise yet flexible, suitable for markets with significant volatility. Through proper parameter optimization and risk management, this strategy can maintain stable performance across different market environments. Traders are advised to thoroughly test parameter settings and make appropriate adjustments based on specific market characteristics before live trading.