# Dual Moving Average Crossover Strategy

Author: ChaoZhang, Date: 2023-09-21 16:40:01
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## Overview

This strategy is designed based on the golden cross and death cross of dual moving averages. It goes long when the short period moving average crosses above the long period moving average, and closes position when the short period moving average crosses below the long period moving average. The strategy is simple and easy to understand, suitable for beginners to learn.

## Strategy Logic

The strategy is mainly based on the sma(close, 14) and sma(close, 28) indicators.

First define the short and long moving averages:

``````short_ma = sma(close, 14)
long_ma = sma(close, 28)
``````

Then determine entry and exit based on golden cross and death cross:

``````longCondition = crossover(short_ma, long_ma)
shortCondition = crossunder(short_ma, long_ma)
``````

Go long when the short MA crosses above the long MA:

``````strategy.entry("Buy", strategy.long, when = longCondition)
``````

Close position when the short MA crosses below the long MA:

``````strategy.close_all(when = shortCondition)
``````

The logic is simple and clear, utilizing the crossovers of dual MAs to determine entries and exits. It has some trend following capacity.

• Simple logic, easy for beginners to use
• Utilizes MA crossovers to determine trends
• Customizable MA periods for parameter optimization
• Allows stop loss to control single trade loss

## Risk Analysis

• Sensitive to market fluctuation, may generate multiple losing trades
• Lagging nature of MAs, may miss price reversal points
• Prone to being trapped near MA crossover points
• Need to optimize MA periods, different periods may lead to different results
• Unable to quickly cut loss when trend changes violently

## Optimization Directions

The strategy can be optimized in the following aspects:

1. Optimize MA periods to find the best combination

Test different short and long MA periods, such as (5, 10), (10, 20), (20, 60) etc to find the optimal combination.

1. Add filters to avoid false signals

Add filters like trading volume, price gap etc. near MA crossovers to avoid excessive trades in ranging markets.

1. Incorporate stop loss

Set stop loss price or use MA as stop loss line to control single trade loss.

1. Combine with other indicators

Add auxiliary indicators like MACD, KDJ etc. to improve strategy performance.

1. Optimize entry points

Find better entry points near MAs instead of entering right at the crossover. For example, enter on MA divergence points.

## Summary

The dual MA strategy is simple for beginners to use. But it is sensitive to market fluctuations and has risks of losses. We can improve it by optimizing parameters, adding filters, incorporating stop loss, combining other indicators etc. It can perform well in strong trends but should be used with caution or proper stop loss in ranging markets.
[/trans]

```/*backtest
start: 2023-08-21 00:00:00
end: 2023-09-20 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Binance","currency":"BTC_USDT"}]
*/

//@version=2
// strategy("Tester", pyramiding = 50, default_qty_type = strategy.cash, default_qty_value = 20, initial_capital = 2000, commission_type = strategy.commission.percent, commission_value = 0.25)

minGainPercent = input(0.6)
gainMultiplier = minGainPercent * 0.01 + 1

longCondition = crossover(sma(close, 14), sma(close, 28))
shortCondition = crossunder(sma(close, 14), sma(close, 28))

avg_protection = input(1)
gain_protection = input(1)

strategy.entry("Buy", strategy.long, when = longCondition    and (avg_protection >= 1 ? (na(strategy.position_avg_price) ? true : close <= strategy.position_avg_price) : true))
strategy.close_all(when = shortCondition  and (gain_protection >=1 ? (close >= gainMultiplier * strategy.position_avg_price) : true))
```

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