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基于意义柱线过滤的突破累积策略AlexIncs-Bar-v12-Breakout-Accumulation-Strategy-Based-on-Meaningful-Bar-Filtering.md

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Name

基于意义柱线过滤的突破累积策略AlexIncs-Bar-v12-Breakout-Accumulation-Strategy-Based-on-Meaningful-Bar-Filtering

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

该策略通过判断K线的“意义柱线”来预测趋势,并结合突破信号发出交易信号。策略会过滤掉过小的K线,只对“意义柱线”做分析,可以避免被过于频繁的小涨跌干扰,使信号更加平稳可靠。

策略原理

  1. 判断当前K线的实体长度body,如果大于过去6根K线body平均值的3倍,就认为是“意义柱线”。

  2. 如果连续3根“意义柱线”都是阳线,则判断为多头信号;如果连续3根“意义柱线”都是阴线,则判断为空头信号。

  3. 在判断信号的同时,如果价格突破之前高点或低点,也会产生附加的交易信号。

  4. 使用SMA均线作为过滤器,只有价格突破SMA时才开仓。

  5. 持仓后,如果价格再次突破入场点或SMA均线,则平仓。

优势分析

  1. 使用“意义柱线”判断趋势,可过滤掉过多不必要的干扰,使信号更加清晰。

  2. 结合趋势信号和突破信号,可提高信号质量,减少假信号。

  3. SMA均线过滤可避免追高杀跌。Closing以下买入,Closing以上卖出,增加信号的可靠性。

  4. 设定止盈止损条件,可以及时止损止盈,有利于资金保全。

风险分析

  1. 本策略较为激进,使用3根K线判断信号,可能会误判短期震荡为趋势反转。

  2. 测试数据不充足,不同品种和不同周期效果可能会有所差异。

  3. 未加入夜盘隔夜仓位控制,存在隔夜仓位风险。

优化方向

  1. 对“意义柱线”的参数可进一步优化,如判断的K线数量、“意义”的定义等。

  2. 可测试不同周期参数对效果的影响,寻找最佳周期。

  3. 可加入ATR止损来控制风险。

  4. 可考虑加入隔夜仓位控制逻辑。

总结

本策略利用“意义柱线”滤波和趋势判断,结合突破形成交易信号,可有效过滤掉过多不必要的小幅波动,信号更加清晰可靠。但由于判断周期较短,可能存在一定的误判风险。可通过参数优化和风控手段进一步完善。

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Overview

This strategy predicts trends by judging the "meaningful bar" of K-lines, and generates trading signals combined with breakout signals. The strategy filters out excessively small K-lines and only analyzes "meaningful bars" to avoid interference from frequent minor fluctuations, making the signals smoother and more reliable.

Strategy Logic

  1. Judge the entity length body of the current K-line. If it is greater than 3 times the average body value of the past 6 K-lines, it is considered a "meaningful bar".

  2. If there are 3 consecutive "meaningful bars" with long bodies, it is judged as a long signal. If 3 consecutive bars with short bodies, it is judged as a short signal.

  3. While judging the signal, if the price breaks through the previous high or low point, additional trading signals will also be generated.

  4. Use SMA as a filter. Open positions only when the price breaks through the SMA.

  5. After taking a position, if the price breaks through the entry point or SMA again, close the position.

Advantage Analysis

  1. Using “meaningful bars” to judge trends can filter out unnecessary interference and make clearer signals.

  2. Combining trend signals and breakout signals improves signal quality and reduces false signals.

  3. SMA filters avoid buying high and selling low. Only buy below Close, sell above Close, thus improving reliability.

  4. Setting profit taking and stop loss conditions facilitates timely risk control.

Risk Analysis

  1. This aggressive strategy judges signals from only 3 bars and may misjudge short-term fluctuations as trend reversals.

  2. Insufficient backtesting data. Results may vary between products and timeframes.

  3. No overnight position control, with overnight holding risk.

Optimization Directions

  1. Further optimize parameters for “meaningful bars”, such as number of bars judged and definition of “meaningful”.

  2. Test impacts of different timeframes to find optimum parameters.

  3. Add ATR based stop loss to control risks.

  4. Consider adding overnight position control.

Summary

This strategy utilizes “meaningful bar” filtering and trend judgment to generate trading signals combined with breakouts. It effectively filters out unnecessary minor fluctuations for clearer and more reliable signals. However, due to short judging cycles, certain misjudgment risks exist. Further improvements can be made through parameter optimization and risk control.

[/trans]

Strategy Arguments

Argument Default Description
v_input_1 true Long
v_input_2 true Short
v_input_3 false Use Martingale
v_input_4 6 Number of candles to take profit anyway
v_input_5 100 Capital, %
v_input_6 false Use SMA filter
v_input_7 10 SMA filter limit
v_input_8 3 Body Size Multiplier
v_input_9 3 Meanful Bar size Divider
v_input_10 false Show Arrows
v_input_11 2018 From Year
v_input_12 2100 To Year
v_input_13 true From Month
v_input_14 12 To Month
v_input_15 true From day
v_input_16 31 To day

Source (PineScript)

/*backtest
start: 2023-12-26 00:00:00
end: 2024-01-02 00:00:00
period: 30m
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//AlexInc
//2018

// закрытие - вычислить и в течение скольки-то баров его добиваться
// если нет, то по первому противоположному
// по стоп-лоссу в любом случае - стоп вычислить

//@version=2
strategy(title = "AlexInc's Bar v1.2", shorttitle = "AlexInc Bar 1.2", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 0)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
usemar = input(false, defval = false, title = "Use Martingale")
tryprofitbars = input(6, defval = 6, minval = 1, maxval = 100, title = "Number of candles to take profit anyway")
capital = input(100, defval = 100, minval = 1, maxval = 10000, title = "Capital, %")

useSMAfilter = input(false, defval = true, title = "Use SMA filter")
SMAlimit = input(10, defval = 10, minval = 1, maxval = 30, title = "SMA filter limit")
bodysizeMlt = input(3, defval = 3, minval = 1, maxval = 10, title = "Body Size Multiplier")
meanfulbardiv = input(3, title = "Meanful Bar size Divider")

showarr = input(false, defval = false, title = "Show Arrows")
fromyear = input(2018, defval = 2018, minval = 1900, maxval = 2100, title = "From Year")
toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year")
frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month")
tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month")
fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From day")
today = input(31, defval = 31, minval = 01, maxval = 31, title = "To day")

//SMA #
index = 0
index := barstate.isfirst ==true ? 0 : nz(index[1])+1

buyindex = 0
buyindex := barstate.isfirst ==true ? 0 : buyindex[1]

sellindex = 0
sellindex := barstate.isfirst ==true ? 0 : sellindex[1]

//predictprofit = barstate.isfirst ==true ? 0 : predictprofit[1]

smafilter = sma(close, SMAlimit)

//Body
body = abs(close - open)
range = abs(high - low)
abody = sma(body, 6)

max3 = 0
if body >= body[1] and body >= body[2]
    max3 := body
else
    if body[1] >= body and body[1] >= body[2]
        max3 := body[1]
    else 
        if body[2] >= body and body[2] >= body[1]
            max3 := body[2]

prevmax3 = 0
prevmax3 := nz(max3[1])


bar = close > open ? 1 : close < open ? -1 : 0
firstbullishopen = 0
firstbullishopen := bar == 1 and bar[1] != 1 ? open : nz(firstbullishopen[1])
firstbearishopen = 0
firstbearishopen := bar == -1 and bar[1] != -1 ? open : nz(firstbearishopen[1])

meanfulbar = body > abody / meanfulbardiv

meanfulbearish = 0
meanfulbearish := nz(meanfulbearish[1])

meanfulbullish = 0
meanfulbullish := nz(meanfulbullish[1])

if meanfulbar
    if bar == 1
        meanfulbullish := 1 + meanfulbullish
        meanfulbearish := 0
    else
        if bar == -1
            meanfulbearish := 1 + meanfulbearish
            meanfulbullish := 0


plot(min(low, high)-10, style=circles, color = meanfulbar ? yellow:black, linewidth=3)

//Signals
up1 = (meanfulbearish >= 3) and (close < firstbullishopen or 1) and (strategy.position_size == 0 or close < strategy.position_avg_price) and body > abody / 5 and (useSMAfilter == false or close < smafilter)
if up1 == true
	predictprofit = sma(body, 3)
up2 = sma(bar, 1) == -1 and body > prevmax3 * bodysizeMlt and (strategy.position_size == 0 or close < strategy.position_avg_price) and body > abody / 5 and (useSMAfilter == false or close < smafilter)
if up2 == true
	predictprofit = body * 0.5
plot(min(low, high), style=circles, color = up1?blue:up2?green:gray, linewidth=3)

dn1 = (meanfulbullish >= 3) and (close > firstbearishopen or 1)  and (strategy.position_size == 0 or close > strategy.position_avg_price) and body > abody / 5 and (useSMAfilter==false or close > smafilter)
if dn1 ==true 
	predictprofit = sma(body, 3)
dn2 = sma(bar, 1) == 1 and body > prevmax3 * bodysizeMlt and (strategy.position_size == 0 or close > strategy.position_avg_price) and body > abody / 5 and (useSMAfilter==false or close > smafilter)
if dn2 ==true	
	predictprofit = body * 0.5
plot(max(low, high), style=circles, color = dn1?blue:dn2?green:gray, linewidth=3)


exit = (((strategy.position_size > 0 and bar == 1 ) or (strategy.position_size < 0 and bar == -1)) and body > abody / 2 )
// or index >= buyindex (or sellindex) + tryprofitbars


//Arrows
col = exit ? black : up1 or dn1 ? blue : up2 or dn2 ? red : na
needup = up1 or up2
needdn = dn1 or dn2
needexitup = exit and strategy.position_size < 0
needexitdn = exit and strategy.position_size > 0
plotarrow(showarr and needup ? 1 : na, colorup = blue, colordown = blue, transp = 0)
plotarrow(showarr and needdn ? -1 : na, colorup = blue, colordown = blue, transp = 0)
plotarrow(showarr and needexitup ? 1 : na, colorup = black, colordown = black, transp = 0)
plotarrow(showarr and needexitdn ? -1 : na, colorup = black, colordown = black, transp = 0)


//Trading
profit = exit ? ((strategy.position_size > 0 and close > strategy.position_avg_price) or (strategy.position_size < 0 and close < strategy.position_avg_price)) ? 1 : -1 : profit[1]
mult = usemar ? exit ? profit == -1 ? mult[1] * 2 : 1 : mult[1] : 1
lot = strategy.position_size == 0 ? strategy.equity / close * capital / 100 * mult : lot[1]

if up1 or up2
    if strategy.position_size < 0
        strategy.close_all()
		buyindex = index
		sellindex = index
	if strategy.position_size == 0
		buyindex = index
		
        
    strategy.entry("Long", strategy.long, needlong == false ? 0 : lot )

if dn1 or dn2
    if strategy.position_size > 0
        strategy.close_all()
		buyindex = index
		sellindex = index
	if strategy.position_size == 0
		sellindex = index
        
    strategy.entry("Short", strategy.short, needshort == false ? 0 : lot )
    
if  exit
    strategy.close_all()

Detail

https://www.fmz.com/strategy/437548

Last Modified

2024-01-03 16:30:16