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移动平均线双轨道交易策略Dual-Moving-Average-Channel-Trading-Strategy.md

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Name

移动平均线双轨道交易策略Dual-Moving-Average-Channel-Trading-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

移动平均线双轨道交易策略是一种追踪双移动平均线交叉信号的趋势交易策略。该策略同时使用指数移动平均线(EMA)和加权移动平均线(WMA)作为交易信号指标。当短期EMA上穿长期WMA时,策略做多;当短期EMA下穿长期WMA时,策略做空。

策略原理

该策略的交易信号来源是EMA周期为10的短期EMA和WMA周期为20的长期WMA的金叉死叉。当短期EMA上穿长期WMA时,表示行情由下向上反转,做多;当短期EMA下穿长期WMA时,表示行情由上向下反转,做空。

策略首先判断交易方向后,设置止损位于入场价下方或上方1个ATR周期的距离,同时设置两个止盈位,第一个止盈位于入场价上方或下方1个ATR的距离,第二个止盈位于入场价上方或下方2个ATR的距离。当第一止盈触发后平仓50%,余下头寸以第二止盈和移动止损方式平仓。

移动止损逻辑是,只要最高价或最低价触及第一个止盈位后开始启用,根据K线实时刷新,将止损移动到盈利最大值和入场价之间作为防止止损,锁定利润。

优势

该策略利用了移动平均线的双重平滑去噪功能,可以有效滤除行情中的随机波动,识别到中长线的趋势信号,避免被套。同时设置两个分批止盈增加了策略盈利区间,让利润最大化。移动止损机制也使得策略可以锁定利润减少亏损。

风险

移动平均线本身滞后性较强,可能产生错过信号的风险;双移动平均线交叉在某些市场中可能产生大量假信号,带来亏损。 止损设置是策略中的重要组成部分,如果止损过小容易被突破造成损失,如果止损过大可能无法有效控制风险。

此外,在行情剧烈波动时,移动止损可能无法起到很好的保护作用。

优化方向

  1. 可以测试不同参数的EMA和WMA,找到最佳参数组合。短线EMA过短或长线WMA过长都可能影响策略表现。

  2. 可以根据不同品种特点和交易风格选择ATR倍数或固定点数止损。

  3. 可以测试部分仓位移动止损和全仓移动止损的效果。

  4. 可以通过引入其它指标判断过滤信号,辅助EMA和WMA,提高信号质量。

总结

移动平均线双轨道交易策略整体来说较为稳健,在趋势行情中表现较好。通过参数优化、止损优化以及信号质量提升,可以进一步增强策略的实盘表现。这是一个值得深入研究和投入实盘的有潜力的策略思路。

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Overview

The dual moving average channel trading strategy is a trend trading strategy that tracks crossovers between double moving averages. The strategy uses Exponential Moving Average (EMA) and Weighted Moving Average (WMA) as trading signal indicators. When the short-term EMA crosses above the long-term WMA, the strategy goes long. When the short-term EMA crosses below the long-term WMA, the strategy goes short.

Strategy Logic

The trading signals of this strategy come from the golden cross and death cross between the 10-period short-term EMA and the 20-period long-term WMA. When the short-term EMA crosses above the long-term WMA, it indicates the market is reversing up, thus going long. When the short-term EMA crosses below the long-term WMA, it indicates the market is reversing down, thus going short.

After determining the trading direction, the strategy sets the stop loss below or above the entry price by 1 ATR period, with two take profits - the first take profit is set at 1 ATR above or below the entry price, and the second take profit is set at 2 ATRs above or below the entry price. When the first take profit is triggered, 50% of the position will be closed. The remaining position will keep running towards the second take profit or with a trailing stop loss.

The trailing stop loss logic - it will be activated once the highest price or the lowest price has reached the first take profit level. According to realtime bar update, the stop loss will be trailed between the maximum profit point and entry price as the protection to avoid loss and lock in profit along the way.

Advantage

The strategy utilizes the dual smoothing noise reduction feature of moving averages to effectively filter out random fluctuations in the market and identify medium-to-long-term trend signals, thus avoiding being caught in whipsaws. In addition, the two staged take profits increase the profit zone of the strategy and maximize profits. The trailing stop mechanism also allows the strategy to lock in profits and reduce losses.

Risks

Moving averages themselves have greater lagging, which poses the risk of missing signals. The crossover between double moving averages may also generate excessive false signals in certain markets, causing losses.

The stop loss setting is an important component of the strategy. If the stop loss is too small, it is prone to be hit by market noise. If the stop loss is too large, it may fail to effectively control risks.

In addition, when the market fluctuates violently, the trailing stop may not work very well in protection.

Optimization Directions

  1. Test EMAs and WMAs with different parameters to find the optimal parameter combination. Overly short EMAs or overly long WMAs could both impact strategy performance.

  2. Choose fixed points or ATR multiple stop loss based on different product characteristics and trading styles.

  3. Test the effects of partial position trailing stop and full position trailing stop.

  4. Introduce other indicators for signal filtering to assist EMA and WMA, so as to improve signal quality.

Summary

In general, the dual moving average channel trading strategy is relatively robust and performs well in trending markets. By optimizing parameters, stop loss mechanisms, and improving signal quality, the real trading performance of this strategy can be further enhanced. This is a promising strategy idea that is worth in-depth research and application in actual trading.

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Strategy Arguments

Argument Default Description
v_input_1 true Buy
v_input_2 true Sell
v_input_3 2020 Start year
v_input_4 true Start month
v_input_5 true Start day
v_input_6 false Start hour
v_input_7 false Start minute
v_input_8 false set end time?
v_input_9 3019 end year
v_input_10 12 end month
v_input_11 31 end day
v_input_12 23 end hour
v_input_13 59 end minute
v_input_14 10 EMA period
v_input_15 20 WMA period
v_input_16 20 pip

Source (PineScript)

/*backtest
start: 2024-01-29 00:00:00
end: 2024-02-28 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © gpadihar

//@version=4
strategy("SL1 Pips after TP1 (MA)", commission_type=strategy.commission.cash_per_order, overlay=true)

// Strategy
Buy  = input(true)
Sell = input(true)

// Date Range
start_year    = input(title='Start year'   ,defval=2020)
start_month   = input(title='Start month'  ,defval=1)
start_day     = input(title='Start day'    ,defval=1)
start_hour    = input(title='Start hour'   ,defval=0)
start_minute  = input(title='Start minute' ,defval=0)
end_time      = input(title='set end time?',defval=false)
end_year      = input(title='end year'     ,defval=3019)
end_month     = input(title='end month'    ,defval=12)
end_day       = input(title='end day'      ,defval=31)
end_hour      = input(title='end hour'     ,defval=23)
end_minute    = input(title='end minute'   ,defval=59)

// MA
ema_period = input(title='EMA period',defval=10)
wma_period = input(title='WMA period',defval=20)
ema        = ema(close,ema_period)
wma        = wma(close,wma_period)

// Entry Condition
buy =
 crossover(ema,wma) and
 nz(strategy.position_size) == 0 and Buy and
 time > timestamp(start_year, start_month, start_day, start_hour, start_minute) and
 (end_time?(time < timestamp(end_year, end_month, end_day, end_hour, end_minute)):true)
 
sell =
 crossunder(ema,wma) and
 nz(strategy.position_size) == 0 and Sell and
 time > timestamp(start_year, start_month, start_day, start_hour, start_minute) and
 (end_time?(time < timestamp(end_year, end_month, end_day, end_hour, end_minute)):true)

// Pips
pip = input(20)*10*syminfo.mintick

// Trading parameters //
var bool  LS  = na
var bool  SS  = na
var float EP  = na
var float TVL = na
var float TVS = na
var float TSL = na
var float TSS = na
var float TP1 = na
var float TP2 = na
var float SL1 = na
var float SL2 = na

if buy or sell and strategy.position_size == 0
    EP  := close
    SL1 := EP - pip     * (sell?-1:1)
    SL2 := EP - pip     * (sell?-1:1)
    TP1 := EP + pip     * (sell?-1:1)
    TP2 := EP + pip * 2 * (sell?-1:1) 
   
// current trade direction    
LS := buy  or strategy.position_size > 0
SS := sell or strategy.position_size < 0

// adjust trade parameters and trailing stop calculations
TVL := max(TP1,open) - pip[1]
TVS := min(TP1,open) + pip[1]
TSL := open[1] > TSL[1] ? max(TVL,TSL[1]):TVL 
TSS := open[1] < TSS[1] ? min(TVS,TSS[1]):TVS

if LS and high > TP1
    if open <= TP1
        SL2:=min(EP,TSL)
    
if SS and low < TP1
    if open >= TP1
        SL2:=max(EP,TSS)

// Closing conditions
close_long  = LS and open < SL2
close_short = SS and open > SL2

// Buy
strategy.entry("buy"  , strategy.long, when=buy and not SS)
strategy.exit ("exit1", from_entry="buy", stop=SL1, limit=TP1, qty_percent=50)
strategy.exit ("exit2", from_entry="buy", stop=SL2, limit=TP2)

// Sell
strategy.entry("sell" , strategy.short, when=sell and not LS)
strategy.exit ("exit3", from_entry="sell", stop=SL1, limit=TP1, qty_percent=50)
strategy.exit ("exit4", from_entry="sell", stop=SL2, limit=TP2)

// Plots
a=plot(strategy.position_size >  0 ? SL1 : na, color=#dc143c, style=plot.style_linebr)
b=plot(strategy.position_size <  0 ? SL1 : na, color=#dc143c, style=plot.style_linebr) 
c=plot(strategy.position_size >  0 ? TP1 : na, color=#00ced1, style=plot.style_linebr) 
d=plot(strategy.position_size <  0 ? TP1 : na, color=#00ced1, style=plot.style_linebr) 
e=plot(strategy.position_size >  0 ? TP2 : na, color=#00ced1, style=plot.style_linebr) 
f=plot(strategy.position_size <  0 ? TP2 : na, color=#00ced1, style=plot.style_linebr) 
g=plot(strategy.position_size >= 0 ? na  : EP, color=#ffffff, style=plot.style_linebr) 
h=plot(strategy.position_size <= 0 ? na  : EP, color=#ffffff, style=plot.style_linebr) 

plot(ema,title="ema",color=#fff176)
plot(wma,title="wma",color=#00ced1)

Detail

https://www.fmz.com/strategy/443137

Last Modified

2024-02-29 14:54:25