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动态均线与MACD交叉策略Dynamic-EMA-and-MACD-Crossover-Strategy.md

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Name

动态均线与MACD交叉策略Dynamic-EMA-and-MACD-Crossover-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

该策略通过计算快线EMA(3)、慢线EMA(11)和再慢线EMA(18)的交叉情况,结合MACD的零轴交叉来决定入场和出场。是一个利用双EMA和MACD指标进行交易决策的动态策略。

策略原理

该策略主要基于两个技术分析指标:

  1. EMA均线交叉。通过快线EMA(3)、慢线EMA(11)和再慢线EMA(18)的交叉判断趋势,并作为入场出场信号。

  2. MACD指标及其零轴交叉。 MACD由差离值(DIFF)和DEA组成。DIFF为快线EMA(3)减去慢线EMA(11)构成。DEA为MACD的EMA(27)。 MACD>0表示多头,MACD<0表示空头。零轴交叉则作为入场出场信号。

根据EMA交叉和MACD零轴交叉的组合情况,设定三次入场机会和两次出场机会:

  1. MACD在零轴上方且向上交叉为第一次做多机会
  2. 快线EMA(3)上穿慢线EMA(11)为第二次做多机会
  3. 快线EMA(3)上穿慢线EMA(18)为第三次满仓做多机会
  4. 快线EMA(3)下穿慢线EMA(11)为第一次清仓做空机会
  5. MACD在零轴下方且向下交叉为第二次清仓做空机会

总体来说,该策略综合双EMA交叉系统和MACD指标,通过动态调整均线参数和MACD参数,可以提高策略盈利能力。

策略优势

  1. 充分利用了EMA均线交叉和MACD指标的优势,综合双重指标判断,提高准确度。

  2. 设置三次做多机会,两次清仓机会,使策略交易频次增加,盈利空间扩大。

  3. 动态参数优化的空间大。快线EMA、慢线EMA、零轴EMA和MACD长度都可优化调整。

  4. 策略逻辑清晰易理解,便于调试与优化。

策略风险

  1. EMA交叉和MACD指标都会产生一定误报比例,可能导致不必要的亏损。

  2. 交易频次高,每次止损幅度小,亏损有积累风险。

  3. 参数优化难度大,不当优化可能会过拟合历史数据。

  4. 需充分考量交易成本的影响。

针对风险:

1)合理设置止损,缩小单笔亏损。

2)适当调整参数,防止过拟合。

3)考虑成本的影响,如减少交易频次。

策略优化方向

  1. 更换其他指标试验:如布林带,KDJ等。

  2. 优化EMA均线交叉的参数:改变快线EMA和慢线EMA的长度参数。

  3. 优化MACD的参数:改变MACD的DIFF和DEA计算EMA长度。

  4. 增加止损策略:如交易次数止损,时间止损,移动止损等。

  5. 考量交易成本的影响,调整入场次数。

总结

本策略通过双EMA交叉系统和MACD指标的组合,构建一个交易频次高、盈利潜力大的动态参数策略。同时策略逻辑简单清晰,易于理解和优化调整。但也存在一定的误报风险和参数优化难度,这需要通过合理止损、防过拟合等方法来应对。总的来说,该策略具有很强的实用性。

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Overview

This strategy determines entries and exits based on the crossover situations of the fast EMA line (3), slow EMA line (11) and slower EMA line (18), combined with MACD's zero line crossovers. It is a dynamic strategy that utilizes the combination of dual EMA and MACD indicators for trading decisions.

Strategy Logic

The strategy is mainly based on two technical analysis indicators:

  1. EMA Crossover. It uses the crossover of fast EMA (3), slow EMA (11) and slower EMA (18) to determine the trend and as entry and exit signals.

  2. MACD Indicator and Its Zero Line Crossover. MACD consists of DIFF and DEA. DIFF is constructed by fast EMA (3) minus slow EMA (11). DEA is the EMA (27) of MACD. MACD>0 indicates bullishness and MACD<0 indicates bearishness. Zero line crossover acts as the entry and exit signal.

According to the combination of EMA crossover and MACD zero line crossover, there are 3 entry opportunities and 2 exit opportunities:

  1. The first long opportunity occurs when MACD is above zero line and has an upward crossover.
  2. The second long opportunity occurs when fast EMA (3) crosses above slow EMA (11).
  3. The third long opportunity with full position occurs when fast EMA (3) crosses above slower EMA (18).
  4. The first exit signal occurs when fast EMA (3) crosses below slow EMA (11).
  5. The second exit signal occurs when MACD is below zero line and has a downward crossover.

In summary, this strategy makes full use of the advantages of dual EMA crossover system and MACD indicator. By dynamically tuning the parameters of moving averages and MACD, it can improve the profitability of the strategy.

Advantages of the Strategy

  1. It utilizes the strengths of both EMA crossover and MACD indicator, improving accuracy through dual-indicator confirmation.

  2. There are 3 long entry opportunities and 2 exit opportunities, increasing trading frequency and profit potential.

  3. Large room for dynamic parameter optimization. The lengths of fast EMA, slow EMA, zero line EMA and MACD can all be optimized.

  4. The clear logic makes it easy to debug and optimize.

Risks of the Strategy

  1. Both EMA crossover and MACD indicator have some false signals, which may lead to unnecessary losses.

  2. High trading frequency with small stop loss size in each trade, so losses could accumulate.

  3. Difficulty in parameter optimization. Improper optimization may lead to overfitting.

  4. Impact of trading costs needs to be fully considered.

To mitigate the risks:

  1. Set proper stop loss to limit losses in single trades.

  2. Adjust parameters appropriately to avoid overfitting.

  3. Consider trading costs impact, like reducing trading frequency.

Directions for Optimization

  1. Test alternatives like Bollinger Bands, KDJ etc.

  2. Optimize EMA crossover parameters: Changing length of fast and slow EMA.

  3. Optimize MACD parameters: Changing DIFF and DEA calculation EMA lengths.

  4. Add stop loss strategies: number of trades stops, time stops, trailing stops etc.

  5. Adjust entry frequency considering trading costs.

Summary

This strategy combines dual EMA crossover system and MACD indicator to construct a dynamic parameter strategy with high trading frequency and strong profitability. Also, the clear logic makes it easy to understand and optimize. But there are also risks of false signals and overfitting that need addressing via proper stop loss, anti-overfitting measures etc. Overall, the strategy has great practical utility.

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Strategy Arguments

Argument Default Description
v_input_1 3 fastLength
v_input_2 11 slowlength
v_input_3 27 MACDLength

Source (PineScript)

/*backtest
start: 2024-01-29 00:00:00
end: 2024-02-05 00:00:00
period: 15m
basePeriod: 5m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("MACD+EMA crossovers Strategy custom",initial_capital=10000,max_bars_back=150,commission_type=strategy.commission.percent , commission_value=0.1, shorttitle="MACD+EMAcross",pyramiding = 10,default_qty_type=strategy.percent_of_equity,default_qty_value=33,overlay=false)

short = ema(close,3)
long = ema(close, 11)
long2 = ema(close, 18)
//plot(short, color = red, linewidth = 4)
//plot(long, color = blue, linewidth = 4)
//plot(long2, color = green, linewidth = 4)

isCross1 = crossover(short, long)
isCross2 = crossover(short, long2)
isCrossSell = crossunder(short, long)
//isCross3 = crossover(long, long2)

//plotshape(isCross1 and not isCross2, color=lime, style=shape.arrowup, text="1st in",size = size.tiny, location = location.belowbar)
//plotshape(isCross2 , color=lime, style=shape.arrowup, text="2nd in",size = size.tiny, location = location.belowbar)

//plotshape(isCross3 , color=lime, style=shape.arrowdown, text="All in",size = size.normal, location = location.abovebar)

//plotshape(isCrossSell , color=red, style=shape.arrowdown, text="SELL",size = size.small, location = location.abovebar)

fastLength = input(3)
slowlength = input(11)
MACDLength = input(27)

MACD = ema(close, fastLength) - ema(close, slowlength)
aMACD = ema(MACD, MACDLength) //signal
delta = MACD - aMACD // histograma

strategy.entry("MacdLE 1st in", strategy.long, comment="MacdLE 1st in",when=crossover(delta, 0))

strategy.entry("2nd in", strategy.long, comment="2nd in",when=isCross1)

strategy.entry("all in", strategy.long, comment="all in",when=isCross2)

strategy.close("2nd in",when=isCrossSell) 
strategy.close("all in",when=isCrossSell)
//strategy.close("2nd in",when=crossunder(delta, 0)) 
//strategy.close("all in",when=crossunder(delta, 0))
strategy.close("MacdLE 1st in",when=crossunder(delta, 0)) 
    
histColour = (delta > 0) ? green : (delta < 0) ? red :  #4169E1
    
plot(MACD,color=red,linewidth=2)
plot(aMACD,color=blue,linewidth=2)
plot(delta,style=histogram, color=histColour, linewidth=10)
plot(0,color=white)

Detail

https://www.fmz.com/strategy/441174

Last Modified

2024-02-06 14:29:23