이 전략은 가격 트렌드를 결정하기 위해 슈퍼 트렌드 지표를 사용하며 트렌드를 따르는 거래를 위한 스톱 로스 메커니즘을 포함합니다. 슈퍼 트렌드는 두 개의 이동 평균에서 구성됩니다. 상향 크로스오버에서 길고 하향 크로스오버에서 짧습니다. 과도한 손실을 피하기 위해 스톱 로스가 설정됩니다.
빠른 라인과 느린 라인의 DEMA를 계산한다. 슈퍼 트렌드 방향은 두 라인의 차이에서 결정된다. 상승 추세에서, 느린 라인의 위의 빠른 라인의 교차는 긴 입력을 신호한다. 하락 추세에서, 느린 라인의 아래에 있는 빠른 라인의 교차는 짧은 입력을 신호한다. 입시에 따라 스톱 로스 라인을 설정한다. 손실이 스톱 로스 퍼센트에 도달하면 포지션은 닫는다.
이동 평균 기간을 단축하고, 스톱 로스 비율을 최적화하고, 거래 빈도를 줄임으로써 위험을 완화할 수 있습니다.
이 간단한 전략은 트렌드 방향 및 위험 통제를 위한 스톱 로스를 위한 지표를 사용하며, 내일 거래에 적합합니다. 매개 변수 조정으로 성능을 더욱 향상시킬 수 있습니다.
/*backtest start: 2023-09-10 00:00:00 end: 2023-09-13 00:00:00 period: 2m basePeriod: 1m exchanges: [{"eid":"Binance","currency":"BTC_USDT"}] */ //@version=3 strategy(title = "[Prod] SuperTrend with Stoploss+TrendZones - 1H", default_qty_type=strategy.percent_of_equity, default_qty_value=100, shorttitle = "[Prod] SuperTrend with Stoploss+TrendZones - 1H", overlay = true, commission_type=strategy.commission.percent, commission_value=0.3) //--cyberfunk 2018 //////////////////////////////////////////////////////////// // This section of code was borrowed from "Trend Trader Strategy" to // help us det. if we are in an uptrend or downtrend. //////////////////////////////////////////////////////////// Length = input(12, minval=1), // 19 / 5 also works for lenth /multiplier... but 11 /4 seems slightly more optimal somehow Multiplier = input(4, minval=1) avgTR = wma(atr(1), Length) highestC = highest(Length) lowestC = lowest(Length) hiLimit = highestC[1]-(avgTR[1] * Multiplier) loLimit = lowestC[1]+(avgTR[1] * Multiplier) ret = na pos =na ret := iff(close > hiLimit and close > loLimit, hiLimit,iff(close < loLimit and close < hiLimit, loLimit, nz(ret[1], 0))) pos := iff(close > ret, 1,iff(close < ret, -1, nz(pos[1], 0))) //barcolor(pos == -1 ? red: pos == 1 ? green : blue ) plot(ret, color= blue , title="Trend Trader Strategy") uptrend = if close > ret // this will be used later to determine which domain we are in (uptrend or downtrend) true else false ///////////////////////////////////////////////////////////////////// // This script has been optimized for the 1 hr candle window view. // An older Pine2 ancestor of this script suffered from repainting issues when // viewing in lower resolutions than the res/2 parameter. // running this in Pine3 mode seems to fix those problems, see https://www.tradingview.com/wiki/Pine_Script:_Release_Notes#Pine_Version_3 and https://backtest-rookies.com/2017/11/29/tradingview-indicator-repainting/ for references on the problem. // // There does seem to be ocassional repainting that affects backtrading here though, somehow.. and i'm not sure how to fix it. V3 SHOULD have made it impossible. Any help appreciated. // // Also note that the length of the DEMA sampling shouldn't be longer than a // candle, which could happen if you made resolution > chartres^2. For example, // a chartres=5min and a res=30 setting would cause sampling = 6, which is longer // than the length of a candle (5 min, b/c chartres=5 min) ///////////////////////////////////////////////////////////////////// fastPeriod = input(title="fastPeriod",defval=4, minval=1) slowPeriod = input(title="slowPeriod",defval=31, minval=1) resInteger = input(title="resolution",defval=98) // The parameters above that work well highly oscillating sideways markets, // struggle with longer-term trends, particularly strong ones, where there's the // potential for a lot of loss or strong gain. To make sure we don't get burned // by long term losses, a stoploss mechanism is implemented to compensate. // *stoplossPercent* is the point at which it becomes useful to "panic sell". // *letitRidePercent* is the point beyond which it's more profitable NOT to panic sell. // Like the periods, these values will have to be tuned to a particuliar market behavior. stoplossPercent = input(title="stopLossPercentage",type=float,defval=2, minval=1, maxval=100) letitRidePercent = input(title="letItRidePercentage",type=float,defval=3, minval=1, maxval=100) //To try to recapture the value of the long term strong-uptrends, first we // detected when we are in strong uptrend mode, by using an indicator (uptrend?) // Then, if we are in strong uptrend mode, we use a different // set of variables for fast/slow periods that's better suited to that situation. uptrendFastPeriod = input(title="Uptrend FastPeriod",defval=4, minval=1) uptrendSlowPeriod = input(title="Uptrend SlowPeriod",defval=16, minval=1) //uptrendResInteger = input(title="Uptrend resolution",defval=98) // Now that we have everything setup, for each bar we calculate the difference of emas for the downtrend/uptrend situations res = tostring(resInteger) sampling = (resInteger / timeframe.period ) demaFastNormal = security(syminfo.tickerid, res, 2 * ema(close, fastPeriod) - ema(ema(close, fastPeriod), fastPeriod)) demaSlowNormal = security(syminfo.tickerid,res, 2 * ema(close, slowPeriod) - ema(ema(close, slowPeriod), slowPeriod) ) demaFastUT = security(syminfo.tickerid, res, 2 * ema(close, uptrendFastPeriod) - ema(ema(close, uptrendFastPeriod), uptrendFastPeriod)) demaSlowUT = security(syminfo.tickerid,res, 2 * ema(close, uptrendSlowPeriod) - ema(ema(close, uptrendSlowPeriod), uptrendSlowPeriod) ) // now, based on our uptrend indicator, we decide which of the two line pairs to // use to determine the crossover signals that tell us to buy/sell. demaFast = uptrend? demaFastUT:demaFastNormal demaSlow = uptrend? demaSlowUT:demaSlowNormal // Now, we calculate the crossover signals. // **IMPORTANT TRADING NOTE** : You should buy/sell on the CLOSE of the // highlighted bar with the signal, to adhere to back-tested results! // (Technically, the open of the NEXT bar, but these are usually effectively the same.) // Note that if you check "calculate on every tick", you might be decieved until // you reload the page, this is NOT, however, a repaint issue, as after the bar // after the signal closes there is a consistent buy/sell indicator at the open // price of the bar after the the signal, which is basically as close to same as // the close price of the signal (red/green highlighted) bar. buy = crossover(demaSlow[sampling], demaFast[sampling]) stoploss = ( strategy.openprofit <-1*stoplossPercent/100*strategy.equity) and not ( strategy.openprofit < -1*letitRidePercent/100*strategy.equity ) sell = strategy.opentrades!=0 and (crossunder(demaSlow[sampling], demaFast[sampling]) or crossover(ret,close) ) and not stoploss // "and not stoploss" here helps us not over-color when both conditions are true. The stoploss is more interesting than a regular sell condition /////////////////////////////////////// // PLOTTING SECTION // This is a collected place for Plotting and coloring all the things // for easy toggling on/off. /////////////////////////////////////// //plot(buyPrice, title="BuyPriceLine", color = purple ) // For a study, this replaces the strategy.openprofit way to guard against stoploss plot(demaFast) // These are the crossover lines that trigger the buy/sell plot(demaSlow) bgcolor( buy ? lime : na, transp=50) bgcolor( stoploss ? orange : na, transp=10) bgcolor( sell ? red : na, transp=50) bgcolor( strategy.openprofit < -1*letitRidePercent/100*strategy.equity ? purple : na, transp= 50) bgcolor( demaSlow[sampling]> demaFast[sampling] ? lime : na, transp=96) bgcolor( demaSlow [sampling]< demaFast[sampling] ? red : na, transp=99) // the below is for backtesting from different timeframes. By default it is set to 1/1/2017 at 1:00 AM startdate=timestamp(2017, 01, 01, 01, 00) // year , month, day, hour, minute strategy.entry("BUY", strategy.long, when = buy and (time>=startdate) ) strategy.close("BUY", when = sell or stoploss)