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基于均线和周期判断的动量突破策略Momentum-Breakout-Strategy-Based-on-Cycle-Judgment-with-Moving-Averages.md

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Name

基于均线和周期判断的动量突破策略Momentum-Breakout-Strategy-Based-on-Cycle-Judgment-with-Moving-Averages

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

该策略通过计算不同周期的EMA均线,判断目前行情处于哪个周期阶段,再结合ATR进行突破判断,实现高概率的趋势追踪交易。

策略原理

  1. 计算5日线、20日线、40日线3条EMA均线
  2. 通过比较3条均线的大小关系,判断目前行情处于6种不同的周期阶段之一
    • 5日线>20日线>40日线 为第1周期
    • 20日线>5日线>40日线 为第2周期 ......
  3. 在确定周期后,再计算ATR指标,并设定ATR倍数作为突破标准
  4. 当价格超过上一个BAR的ATR trailing stop时产生买入信号
  5. 当价格跌破上一个BAR的ATR trailing stop时产生卖出信号
  6. 通过这样的组合判断,实现高概率的趋势追踪交易

策略优势

  1. 周期判断增加了信号的可靠性

    通过判断不同EMA均线的大小关系,可以有效判断市场目前所处的周期阶段,避免在不适宜的周期产生错误信号。

  2. ATR突破判断过滤假信号

    ATR指标能够有效表达市场的波动性,设定一定倍数的ATR作为突破标准,可以过滤掉很多假突破信号。

  3. 组合判断形成高概率交易机会

    周期判断和ATR突破判断的有机结合,使得产生信号的概率大大提高,从而也提高了交易的盈利概率。

策略风险

  1. 参数优化难度较大

    由于策略包含多个参数,优化难度较大,不当的参数设置可能影响策略表现。

  2. 存在一定的滞后

    在行情快速变化时,EMA均线和ATR指标都存在一定滞后,可能产生错误信号或错过机会。

  3. 需要严格的止损

    任何技术指标都难以完全避免错误信号的产生,需要设定严格的止损来控制风险。

策略优化方向

  1. 进一步优化参数

    通过更丰富的历史数据进行参数优化,找到最佳参数组合。

  2. 增加自适应能力

    可以考虑根据市场波动性自动调整ATR参数,提高策略的自适应能力。

  3. 结合其它指标

    可尝试结合波动率、成交量等其它指标来辅助判断,提高信号质量。

总结

该策略通过EMA均线判断周期和ATR指标设定动量突破标准,实现高概率的趋势追踪交易。具有判断周期、过滤假信号、提高信号质量等优势。但也存在参数优化难度大、存在滞后等风险,需要进一步优化参数、增加自适应能力等来改进策略。

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Overview

This strategy calculates EMA lines of different periods to determine the current cycle stage of the market, and uses ATR to generate momentum breakout signals for high-probability trend-following trades.

Strategy Logic

  1. Calculate 3 EMA lines - 5-day, 20-day and 40-day
  2. Compare the EMA lines to determine which of the 6 cycle stages the market is currently at
    • 5-day > 20-day > 40-day is Cycle 1
    • 20-day > 5-day > 40-day is Cycle 2 ......
  3. After cycle determination, calculate ATR indicator and set ATR multiples as breakout criteria
  4. A buy signal is generated when price breaks above the ATR trailing stop of previous bar
  5. A sell signal is generated when price drops below the ATR trailing stop of previous bar
  6. Through this combination of judgments, high-probability trend-following trades can be achieved

Advantages

  1. Cycle judgment increases signal reliability

    By judging the relative positions of different EMA lines, the current cycle stage of the market can be effectively determined, avoiding wrong signals in unsuitable cycles.

  2. ATR breakout filters false signals

    ATR can effectively express the volatility of the market. Setting ATR multiples as breakout criteria can filter out many false breakout signals.

  3. Combined judgment forms high-probability trading opportunities

    The organic combination of cycle judgment and ATR breakout creates signals with much higher probability, thus also increasing the profitability of trades.

Risks

  1. Difficult parameter optimization

    With multiple parameters, optimization difficulty is high. Improper parameter settings may affect strategy performance.

  2. Lagging exists

    In fast changing markets, both EMA and ATR have certain degree of lagging, which may generate wrong signals or miss opportunities.

  3. Strict stop loss needed

    No technical indicators can completely avoid wrong signals. Strict stop loss is required to control risks.

Optimization Directions

  1. Further parameter optimization

    Find optimal parameter combinations through more extensive historical data.

  2. Increase adaptivity

    Consider automatically adjusting ATR parameters based on market volatility to improve adaptivity.

  3. Incorporate other indicators

    Try incorporating other indicators like volatility and volume to assist judgment and improve signal quality.

Conclusion

This strategy determines cycles with EMA and sets momentum breakout criteria with ATR to achieve high-probability trend-following trades. It has advantages like cycle judgment, false signal filtering and signal quality improvement. But risks like difficult parameter optimization and lagging exist. Further optimization on parameters, adaptivity etc. can improve the strategy.

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Strategy Arguments

Argument Default Description
v_input_1 2 Key Vaule. 'This changes the sensitivity'
v_input_2 7 ATR Period
v_input_int_1 25 atr_length

Source (PineScript)

/*backtest
start: 2024-01-15 00:00:00
end: 2024-01-22 00:00:00
period: 15m
basePeriod: 5m
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/
// © kgynofomo

//@version=5
strategy(title="[Salavi] | Andy Advance Pro Strategy",overlay = true)

ema_short = ta.ema(close,5)
ema_middle = ta.ema(close,20)
ema_long = ta.ema(close,40)

cycle_1 = ema_short>ema_middle and ema_middle>ema_long
cycle_2 = ema_middle>ema_short and ema_short>ema_long
cycle_3 = ema_middle>ema_long and ema_long>ema_short
cycle_4 = ema_long>ema_middle and ema_middle>ema_short
cycle_5 = ema_long>ema_short and ema_short>ema_middle
cycle_6 = ema_short>ema_long and ema_long>ema_middle

bull_cycle = cycle_1 or cycle_2 or cycle_3
bear_cycle = cycle_4 or cycle_5 or cycle_6
// label.new("cycle_1")
// bgcolor(color=cycle_1?color.rgb(82, 255, 148, 60):na)
// bgcolor(color=cycle_2?color.rgb(82, 255, 148, 70):na)
// bgcolor(color=cycle_3?color.rgb(82, 255, 148, 80):na)
// bgcolor(color=cycle_4?color.rgb(255, 82, 82, 80):na)
// bgcolor(color=cycle_5?color.rgb(255, 82, 82, 70):na)
// bgcolor(color=cycle_6?color.rgb(255, 82, 82, 60):na)

// Inputs
a = input(2, title='Key Vaule. \'This changes the sensitivity\'')
c = input(7, title='ATR Period')
h = false

xATR = ta.atr(c)
nLoss = a * xATR

src = h ? request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, close, lookahead=barmerge.lookahead_off) : close

xATRTrailingStop = 0.0
iff_1 = src > nz(xATRTrailingStop[1], 0) ? src - nLoss : src + nLoss
iff_2 = src < nz(xATRTrailingStop[1], 0) and src[1] < nz(xATRTrailingStop[1], 0) ? math.min(nz(xATRTrailingStop[1]), src + nLoss) : iff_1
xATRTrailingStop := src > nz(xATRTrailingStop[1], 0) and src[1] > nz(xATRTrailingStop[1], 0) ? math.max(nz(xATRTrailingStop[1]), src - nLoss) : iff_2

pos = 0
iff_3 = src[1] > nz(xATRTrailingStop[1], 0) and src < nz(xATRTrailingStop[1], 0) ? -1 : nz(pos[1], 0)
pos := src[1] < nz(xATRTrailingStop[1], 0) and src > nz(xATRTrailingStop[1], 0) ? 1 : iff_3

xcolor = pos == -1 ? color.red : pos == 1 ? color.green : color.blue

ema = ta.ema(src, 1)
above = ta.crossover(ema, xATRTrailingStop)
below = ta.crossover(xATRTrailingStop, ema)

buy = src > xATRTrailingStop and above
sell = src < xATRTrailingStop and below

barbuy = src > xATRTrailingStop
barsell = src < xATRTrailingStop




atr = ta.atr(14)
atr_length = input.int(25)
atr_rsi = ta.rsi(atr,atr_length)
atr_valid = atr_rsi>50

long_condition =  buy and bull_cycle and atr_valid
short_condition =  sell and bear_cycle and atr_valid

Exit_long_condition = short_condition
Exit_short_condition = long_condition

if long_condition
    strategy.entry("Andy Buy",strategy.long, limit=close,comment="Andy Buy Here")

if Exit_long_condition
    strategy.close("Andy Buy",comment="Andy Buy Out")
    // strategy.entry("Andy fandan Short",strategy.short, limit=close,comment="Andy 翻單 short Here")
    // strategy.close("Andy fandan Buy",comment="Andy short Out")


if short_condition
    strategy.entry("Andy Short",strategy.short, limit=close,comment="Andy short Here")


// strategy.exit("STR","Long",stop=longstoploss)
if Exit_short_condition
    strategy.close("Andy Short",comment="Andy short Out")
    // strategy.entry("Andy fandan Buy",strategy.long, limit=close,comment="Andy 翻單 Buy Here")
    // strategy.close("Andy fandan Short",comment="Andy Buy Out")




inLongTrade = strategy.position_size > 0
inLongTradecolor = #58D68D
notInTrade = strategy.position_size == 0
inShortTrade = strategy.position_size < 0

// bgcolor(color = inLongTrade?color.rgb(76, 175, 79, 70):inShortTrade?color.rgb(255, 82, 82, 70):na)
plotshape(close!=0,location = location.bottom,color = inLongTrade?color.rgb(76, 175, 79, 70):inShortTrade?color.rgb(255, 82, 82, 70):na)


plotshape(long_condition, title='Buy', text='Andy Buy', style=shape.labelup, location=location.belowbar, color=color.new(color.green, 0), textcolor=color.new(color.white, 0), size=size.tiny)
plotshape(short_condition, title='Sell', text='Andy Sell', style=shape.labeldown, location=location.abovebar, color=color.new(color.red, 0), textcolor=color.new(color.white, 0), size=size.tiny)


//atr > close *0.01* parameter

Detail

https://www.fmz.com/strategy/439749

Last Modified

2024-01-23 14:51:27