이 글은 여러 지표들을 종합하여 트렌드를 판단하는 양적 거래 전략을 소개한다. 이 전략은 평평선 방향, 신상고, 신저, 연계 조건 등 여러 기술 지표들을 결합하여 주식 가격의 중장선 트렌드를 추적한다.
이 전략은 다음과 같은 아이디어에 기반을 두고 있습니다.
평균선 방향, 신 고, 신 저 지수 등으로 가격 경향 방향을 판단한다.
연도와 함께 긴 흐름을 판단하고, 단기적인 흔들림에 착각하는 것을 피하십시오.
다중 지표 번들 합성 신호가 들어올 때만, 가짜 신호를 효과적으로 필터링할 수 있다.
슈퍼 트렌드 스톱 로스를 사용하여 트렌드 수익을 잠금 할 수 있습니다.
가격이 평균선을 돌파했을 때 적절한 상쇄.
이 전략은 다음과 같은 장점을 가지고 있습니다.
여러 지표들을 종합해 판단을 통해 의사결정의 정확성을 높일 수 있다.
트렌드가 명확할 때만 입점하여 불필요한 거래를 피하십시오.
슈퍼 트렌드 중지 손실은 수익을 효과적으로 고정하고 회수를 줄일 수 있습니다.
가격 돌파에 따라 적시 중지 손실에 따라 승률을 높일 수 있다.
전략 논리는 명확하고 이해하기 쉽고, 최적화하기 쉽습니다.
이 전략에는 다음과 같은 위험도 있습니다.
여러 지표가 동시에 놓친 거래 기회를 판단합니다.
슈퍼 트렌드는 기계적으로 너무 많은 손실을 초래하여 수익을 제한 할 수 있습니다.
평행선 돌파는 판단이 부적절하면 불필요한 손해를 초래할 수 있다.
트레이더들은 세팅된 파라미터가 전략에 미치는 영향을 신중하게 평가해야 합니다.
이 전략은 여러 가지 기술 지표들을 종합적으로 사용하여 추세를 판단한다. 변수를 최적화하는 것이 합리적인 경우, 더 나은 수익을 얻을 수 있다. 그러나 거래자는 여전히 추세를 판단하는 정확성에 주의를 기울이고, 적절한 경우에 변수를 조정해야 한다.
/*backtest
start: 2023-08-16 00:00:00
end: 2023-09-15 00:00:00
period: 1h
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/
// © HeWhoMustNotBeNamed
//@version=4
strategy("AlignedMA and Cumulative HighLow Strategy V2", overlay=true, initial_capital = 1000, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, commission_type = strategy.commission.percent, pyramiding = 1, commission_value = 0.01, calc_on_order_fills = true)
MAType = input(title="Moving Average Type", defval="hma", options=["ema", "sma", "hma", "rma", "vwma", "wma"])
includePartiallyAligned = input(true)
HighLowPeriod = input(22, minval=1,step=1)
LookbackPeriod = input(10, minval=1,step=1)
considerYearlyHighLow = input(false)
dirTBars = input(1)
dirRBars = input(30)
PMAType = input(title="Moving Average Type", defval="ema", options=["ema", "sma", "hma", "rma", "vwma", "wma"])
PMALength = input(10, minval=2, step=10)
shift = input(2, minval=1, step=1)
//Use 2 for ASX stocks
supertrendMult = input(3, minval=1, maxval=10, step=0.5)
supertrendLength = input(22, minval=1)
riskReward = input(2, minval=1, maxval=10, step=0.5)
tradeDirection = input(title="Trade Direction", defval=strategy.direction.all, options=[strategy.direction.all, strategy.direction.long, strategy.direction.short])
backtestYears = input(1, minval=1, step=1)
f_getMovingAverage(source, MAType, length)=>
ma = sma(source, length)
if(MAType == "ema")
ma := ema(source,length)
if(MAType == "hma")
ma := hma(source,length)
if(MAType == "rma")
ma := rma(source,length)
if(MAType == "vwma")
ma := vwma(source,length)
if(MAType == "wma")
ma := wma(source,length)
ma
f_getMaAlignment(MAType, includePartiallyAligned)=>
ma5 = f_getMovingAverage(close,MAType,5)
ma10 = f_getMovingAverage(close,MAType,10)
ma20 = f_getMovingAverage(close,MAType,20)
ma30 = f_getMovingAverage(close,MAType,30)
ma50 = f_getMovingAverage(close,MAType,50)
ma100 = f_getMovingAverage(close,MAType,100)
ma200 = f_getMovingAverage(close,MAType,200)
upwardScore = 0
upwardScore := close > ma5? upwardScore+1:upwardScore
upwardScore := ma5 > ma10? upwardScore+1:upwardScore
upwardScore := ma10 > ma20? upwardScore+1:upwardScore
upwardScore := ma20 > ma30? upwardScore+1:upwardScore
upwardScore := ma30 > ma50? upwardScore+1:upwardScore
upwardScore := ma50 > ma100? upwardScore+1:upwardScore
upwardScore := ma100 > ma200? upwardScore+1:upwardScore
upwards = close > ma5 and ma5 > ma10 and ma10 > ma20 and ma20 > ma30 and ma30 > ma50 and ma50 > ma100 and ma100 > ma200
downwards = close < ma5 and ma5 < ma10 and ma10 < ma20 and ma20 < ma30 and ma30 < ma50 and ma50 < ma100 and ma100 < ma200
upwards?1:downwards?-1:includePartiallyAligned ? (upwardScore > 5? 0.5: upwardScore < 2?-0.5:upwardScore>3?0.25:-0.25) : 0
f_getHighLowValue(HighLowPeriod)=>
currentHigh = highest(high,HighLowPeriod) == high
currentLow = lowest(low,HighLowPeriod) == low
currentHigh?1:currentLow?-1:0
f_getDirection(Series)=>
direction = Series > Series[1] ? 1 : Series < Series[1] ? -1 : 0
direction := direction == 0? nz(direction[1],0):direction
direction
f_getDirectionT(Series, tBars, rBars)=>
compH = Series > 0? Series[tBars] : Series[rBars]
compL = Series < 0? Series[tBars] : Series[rBars]
direction = Series > compH ? 1 : Series < compL ? -1 : 0
direction := direction == 0? nz(direction[1],0):direction
direction
f_getYearlyHighLowCondition(considerYearlyHighLow)=>
yhigh = security(syminfo.tickerid, '12M', high[1])
ylow = security(syminfo.tickerid, '12M', low[1])
yhighlast = yhigh[365]
ylowlast = ylow[365]
yhighllast = yhigh[2 * 365]
ylowllast = ylow[2 * 365]
yearlyTrendUp = na(yhigh)? true : na(yhighlast)? close > yhigh : na(yhighllast)? close > max(yhigh,yhighlast) : close > max(yhigh, min(yhighlast, yhighllast))
yearlyHighCondition = ( (na(yhigh) or na(yhighlast) ? true : (yhigh > yhighlast) ) and ( na(yhigh) or na(yhighllast) ? true : (yhigh > yhighllast))) or yearlyTrendUp or not considerYearlyHighLow
yearlyTrendDown = na(ylow)? true : na(ylowlast)? close < ylow : na(ylowllast)? close < min(ylow,ylowlast) : close < min(ylow, max(ylowlast, ylowllast))
yearlyLowCondition = ( (na(ylow) or na(ylowlast) ? true : (ylow < ylowlast) ) and ( na(ylow) or na(ylowllast) ? true : (ylow < ylowllast))) or yearlyTrendDown or not considerYearlyHighLow
[yearlyHighCondition,yearlyLowCondition]
f_getOpenCloseMA(MAType, length)=>
openMA = f_getMovingAverage(open, MAType, length)
closeMA = f_getMovingAverage(close, MAType, length)
direction = openMA < closeMA ? 1 : -1
[openMA, closeMA, direction]
inDateRange = true
maAlignment = f_getMaAlignment(MAType,includePartiallyAligned)
alignedMaIndex = sum(maAlignment,LookbackPeriod)
maAlignmentDirection=f_getDirectionT(alignedMaIndex,dirTBars, dirRBars)
atr = atr(22)
highLowIndex = f_getHighLowValue(HighLowPeriod)
cumulativeHighLowIndex = sum(highLowIndex,LookbackPeriod)
hlDirection = f_getDirectionT(cumulativeHighLowIndex,dirTBars,dirRBars)
[yearlyHighCondition,yearlyLowCondition] = f_getYearlyHighLowCondition(considerYearlyHighLow)
[supertrend, dir] = supertrend(supertrendMult, supertrendLength)
[esupertrend, edir] = supertrend(supertrendMult+1, supertrendLength)
movingAverage = f_getMovingAverage(close, PMAType, PMALength)
secondaryBuyFilter = movingAverage > movingAverage[shift]
secondarySellFilter = movingAverage < movingAverage[shift]
closeBuyFilter = dir == 1
closeSellFilter = dir == -1
buyFilter = (maAlignmentDirection == 1 and hlDirection == 1 and yearlyHighCondition)
sellFilter = (maAlignmentDirection == -1 and hlDirection == -1 and yearlyLowCondition)
barColor = buyFilter?color.lime:sellFilter?color.orange:color.gray
bandColor = secondaryBuyFilter ? color.green : secondarySellFilter ? color.red : color.gray
compound = strategy.position_size > 0? strategy.position_avg_price + (atr* supertrendMult * riskReward) : strategy.position_size < 0 ? strategy.position_avg_price - (atr* supertrendMult * riskReward) : na
riskFree = na(compound)?false:strategy.position_size > 0 ? supertrend > compound : strategy.position_size < 0 ? supertrend < compound : false
trailingStop = riskFree?(dir==-1?supertrend - 2*atr : supertrend + 2*atr) :supertrend
trailingStop := (strategy.position_size > 0 and trailingStop < trailingStop[1]) ? trailingStop[1] : ((strategy.position_size < 0 and trailingStop > trailingStop[1])? trailingStop[1] :trailingStop)
plot(trailingStop, title="Supertrend", color=riskFree? color.blue:dir==-1?color.green:color.red, linewidth=2)
buyEntry = buyFilter and secondaryBuyFilter and not closeBuyFilter and low > trailingStop
sellEntry = sellFilter and secondarySellFilter and not closeSellFilter and low < trailingStop
Fi1 = plot(movingAverage[shift], title="MA", color=color.red, linewidth=1, transp=50)
Fi2 = plot(movingAverage, title="Shift", color=color.green, linewidth=1, transp=50)
fill(Fi1, Fi2, title="Band Filler", color=bandColor, transp=40)
barcolor(barColor)
//plot(compound, title="Compound"mzn, color=dir==-1?color.lime:color.orange, linewidth=2)
strategy.risk.allow_entry_in(tradeDirection)
strategy.entry("Buy", strategy.long, when=buyEntry and inDateRange and (riskFree or strategy.position_size==0), oca_name="oca_buy")
strategy.exit("ExitBuy", "Buy", stop = trailingStop)
strategy.close("Buy", when=closeBuyFilter)
strategy.entry("Sell", strategy.short, when=sellEntry and inDateRange and (riskFree or strategy.position_size==0), oca_name="oca_sell")
strategy.exit("ExitSell", "Buy", stop = trailingStop)
strategy.close("Sell", when=closeSellFilter)