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Moving Average Tracking Trading Strategy

Author: ChaoZhang, Date: 2023-10-24 14:39:08
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Overview

This strategy is based on tracking moving averages combined with MACD indicator filtering for trade decision-making. It goes long when the fast moving average crosses above the slow moving average, and goes short when the fast MA crosses below the slow MA. Meanwhile, MACD indicator can be used to filter false breakouts.

Strategy Logic

The strategy is mainly based on the following principles:

  1. Using Heikin Ashi candles can filter market noise and identify trends.

  2. Fast MA crossing above slow MA indicates an upward trend, go long; crossing below indicates a downward trend, go short.

  3. MACD indicator can identify price trends and filter false breakouts. MACD histogram above 0 indicates a bullish market, below 0 indicates a bearish market.

  4. Specifically, the strategy first calculates the open and close prices of the Heikin Ashi candles. Then it calculates the fast and slow EMA lines. It goes long when fast EMA crosses above slow EMA, and goes short when fast EMA crosses below slow EMA. MACD indicator is used to filter false breakout signals.

Advantages

  1. Heikin Ashi candles can filter noise and help determine trend direction.

  2. Fast and slow EMA cross system is a mature trading strategy that follows the trend.

  3. MACD filter provides more accurate trading signals by reducing false breakouts.

  4. The strategy has large optimization space by adjusting EMA periods, MACD parameters etc.

  5. Simple and intuitive strategy logic, easy to understand and implement, suitable for highly volatile crypto markets.

Risks

  1. The strategy relies solely on technical indicators without fundamental analysis, may miss major news events and cause losses.

  2. Improper EMA period settings may generate excessive false signals and losses.

  3. MACD filter depends on parameter tuning, improper settings may fail to filter false breakouts effectively.

  4. Sudden price spikes may hit stop loss and cause large losses.

  5. Difficult to set proper stop loss in volatile markets, risks of loss amplification.

Optimization

  1. Optimize EMA period parameters to find optimal combinations.

  2. Optimize MACD parameters to improve trend identification ability.

  3. Add other technical indicators like RSI, KD etc. to filter signals.

  4. Determine trading range based on trendlines, support/resistance levels etc.

  5. Adjust parameters according to different crypto characteristics.

  6. Add stop loss strategies to control single trade loss amount.

Summary

The strategy has clear and easy-to-understand logic. Trading signals can be obtained from fast/slow EMA cross and MACD filter. But there are inherent system risks that need parameter optimization and risk management. The strategy suits the highly volatile crypto markets but requires regular updates for steady profits. With continuous improvements, it has the potential to become a stable profitable trend following strategy.


/*backtest
start: 2023-09-23 00:00:00
end: 2023-10-23 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
//Heikin Ashi Strategy  V3 by breizh29

// strategy("Heikin Ashi Strategy  V3",shorttitle="HAS V3",overlay=true,default_qty_value=100,initial_capital=100,currency=currency.EUR) 
res = input(title="Heikin Ashi Candle Time Frame",  defval="30")
hshift = input(1,title="Heikin Ashi Candle Time Frame Shift")
res1 = input(title="Heikin Ashi EMA Time Frame",  defval="180")
mhshift = input(0,title="Heikin Ashi EMA Time Frame Shift")
fama = input(1,"Heikin Ashi EMA Period")
test = input(1,"Heikin Ashi EMA Shift")
sloma = input(10,"Slow EMA Period")
slomas = input(1,"Slow EMA Shift")
macdf = input(false,title="With MACD filter")
res2 = input(title="MACD Time Frame",  defval="12")
macds = input(1,title="MACD Shift")




//Heikin Ashi Open/Close Price
ha_t = heikinashi(syminfo.tickerid)
ha_open = security(ha_t, res, open[hshift])
ha_close = security(ha_t, res, close[hshift])
mha_close = security(ha_t, res1, close[mhshift])

//macd
[macdLine, signalLine, histLine] = macd(close, 12, 26, 9)
macdl = security(ha_t,res2,macdLine[macds])
macdsl= security(ha_t,res2,signalLine[macds])

//Moving Average
fma = ema(mha_close[test],fama)
sma = ema(ha_close[slomas],sloma)
plot(fma,title="MA",color=lime,linewidth=2,style=line)
plot(sma,title="SMA",color=red,linewidth=2,style=line)


//Strategy
golong =  crossover(fma,sma) and (macdl > macdsl or macdf == false )
goshort =   crossunder(fma,sma) and (macdl < macdsl or macdf == false )


strategy.entry("Buy",strategy.long,when = golong)
strategy.entry("Sell",strategy.short,when = goshort)

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