Overview

This strategy generates buy and sell signals when two Moving Average of Exponential Moving Averages (MAEMA) with different periods cross over. The short period line is used to determine market trend and short term reversal signals, while the long period line is used to determine the major trend direction.

Principles

1. Calculate the fast MAEMA (80 periods) and slow MAEMA (144 periods).
2. The fast line reflects short term trend and reversal points. The slow line reflects major trend direction.
3. When the fast line crosses above the slow line, a buy signal is generated. When the fast line crosses below the slow line, a sell signal is generated.
4. The strategy also plots 3 predicted points, representing possible values for next period, to determine future crossover trend.
5. The strategy makes full use of the momentum and predictive functionality of the MAEMA itself.

Advantages

1. MAEMA itself incorporates momentum factor to capture trend changes faster.
2. Dual moving average strategy judges trends over different timeframes.
3. Combining fast and slow line crossovers and the predictive points of MAEMA itself makes trading signals more reliable.
4. Complete auto-charting provides intuitive reflection of market fluctuations.

Risks

1. When abnormal volatility occurs, sensitivity of MAEMA may be too high, generating false signals. Stop loss points can be loosened appropriately.
2. Moving average systems tend to give false signals during range-bound markets. Additional filters can be added.
3. The periods for fast and slow lines should be determined by finding optimal parameters for each product.

Enhancement

1. Optimize periods of fast and slow MAEMA to find best parameter combinations.
2. Add filter conditions to avoid opening positions during zigzag markets. For example introducing DMI, MACD to determine trendiness.
3. Keep adjusting ATR multiples, trailing stops based on backtest results to reduce false positives and control risks.

Summary

The strategy judges changes in market trend using MAEMA dual moving average crossovers. The basic principles are simple and clear. Combined with the momentum and predictive capabilities of MAEMA itself, it is effective in identifying reversal signals. Attention should be paid to parameter optimization and enhancing filters to improve robustness.