Super Trend V Strategy

Pine ScriptTrend following Mean reversion Multi-timeframe EMA SMA ATR Supertrend VWAP Pivots / S&R

Author: ChaoZhang
Complexity: Intermediate · 163 lines
Parameters: 12
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

The Super Trend V strategy is a short-term trading strategy based on moving averages and standard deviations. It uses the Super Trend indicator to determine the price trend direction and combines the support and resistance formed by moving averages to enter the market. Meanwhile, it uses the standard deviation channel to predict the potential support and resistance zones of the price and sets the stop loss and take profit price range to implement a trend-following and efficient-exiting short-term trading strategy.

Strategy Logic

Firstly, this strategy calculates the Super Trend indicator. The Super Trend indicator uses the relationship between ATR and price to determine the trend direction. When the price is above the rising trend, it is bullish. When the price is below the falling trend, it is bearish.

Then it calculates the EMA of price and the EMA of open price. When the price crosses above the EMA and is higher than the open price EMA, it is a buy signal. When the price crosses below the EMA and is lower than the open price EMA, it is a sell signal.

Next, it uses standard deviation to calculate the upper and lower bands of the price channel and makes smoothing processing. When the price breaks through the upper band of standard deviation, it is a stop loss signal. When the price breaks through the lower band of standard deviation, it is a take profit signal.

Finally, it combines moving averages of different timeframes to determine the trend direction, together with the Super Trend indicator, to form a stable trend judgment.

Advantages of the Strategy

Use Super Trend indicator to determine the price trend direction, avoiding losses caused by trend reversal
Moving averages combined with open price help determine entry timing, avoiding false breakdowns
Standard deviation channel predicts potential support and resistance zones of the price for stop loss and take profit
Multiple timeframes combination improves the stability of trend judgment

Risks of the Strategy

Super Trend indicator has lagging effect, may miss trend change points
Crossovers of moving averages have lagging effect, entry timing may not be accurate
Range of standard deviation channel is too fixed to reflect market fluctuation in real time
Judgment based on multiple timeframes may conflict with each other

Risk Management:

Shorten Super Trend parameters properly to improve sensitivity
Optimize moving average periods, or add other indicators to determine entry
Adjust standard deviation channel dynamically to match the market
Define clear logic for multi-timeframe judgments to handle conflicts

Optimization Directions

Optimize Super Trend parameters to find the best combination
Try other indicators combined with moving averages to determine entry
Try dynamic adjustment of standard deviation channel
Test different multi-timeframe combinations to find the best match
Optimize stop loss and take profit strategies to improve profit space

Conclusion

The Super Trend V strategy integrates the advantages of trend, moving average, standard deviation channel and other indicators to achieve stable trend judgment, proper entry timing, and stop loss and take profit based on price zones. By optimizing parameters, indicators, stop loss and take profit, etc., it can improve the stability and profitability of the strategy. Its solid logic and rigorous thinking are worth learning and researching.

Parameters

Name	Default	What it controls
v_input_1	0	Strategy Direction: long \| short \| all
v_input_2	720	tf
v_input_3	true	SuperTrend Multiplier
v_input_4	10	SuperTrend Period
v_input_5	2	TP VWAP Deviation
v_input_6	150	TP length
v_input_7	2016	Backtest Start Year
v_input_8	true	Backtest Start Month
v_input_9	true	Backtest Start Day
v_input_10	2030	Backtest Stop Year
v_input_11	12	Backtest Stop Month
v_input_12	30	Backtest Stop Day

Source Pine Script

/*backtest
start: 2022-10-11 00:00:00
end: 2023-10-17 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// © theCrypster 2020

//@version=4
strategy(title = "Super trend V Strategy version", overlay = true, pyramiding=1,initial_capital = 1000, default_qty_type= strategy.percent_of_equity, default_qty_value = 100, calc_on_order_fills=false, slippage=0,commission_type=strategy.commission.percent,commission_value=0.075)
strat_dir_input = input(title="Strategy Direction", defval="long", options=["long", "short", "all"])
strat_dir_value = strat_dir_input == "long" ? strategy.direction.long : strat_dir_input == "short" ? strategy.direction.short : strategy.direction.all
strategy.risk.allow_entry_in(strat_dir_value)
hilow = ((high - low)*100)
openclose = ((close - open)*100)
vol = (volume / hilow)
spreadvol = (openclose * vol)
VPT = spreadvol + cum(spreadvol)
window_len = 28

v_len = 14
price_spread = stdev(high-low, window_len)

v =  spreadvol + cum(spreadvol)
smooth = sma(v, v_len)
v_spread = stdev(v - smooth, window_len)
shadow = (v - smooth) / v_spread * price_spread

out = shadow > 0 ? high + shadow : low + shadow
//
src = out
src1=open
src2=low
src3=high
tf =input(720)
len = timeframe.isintraday and timeframe.multiplier >= 1 ? 
   tf / timeframe.multiplier * 7 : 
   timeframe.isintraday and timeframe.multiplier < 60 ? 
   60 / timeframe.multiplier * 24 * 7 : 7

c = ema(src, len)
plot(c,color=color.red)
o = ema(src1,len)
plot(o,color=color.blue)
//h = ema(src3,len)
//l=ema(src2,len)
//
col=c > o? color.lime : color.orange
vis = true
vl = c
ll = o
m1 = plot(vl, color=col, linewidth=1, transp=60)
m2 = plot(vis ? ll : na,  color=col, linewidth=2, transp=80)

fill(m1, m2,  color=col, transp=70)
//

vpt=ema(out,len)

// INPUTS //
st_mult   = input(1,   title = 'SuperTrend Multiplier', minval = 0, maxval = 100, step = 0.01)
st_period = input(10, title = 'SuperTrend Period',     minval = 1)

// CALCULATIONS //
up_lev = vpt - (st_mult * atr(st_period))
dn_lev = vpt + (st_mult * atr(st_period))

up_trend   = 0.0
up_trend   := close[1] > up_trend[1]   ? max(up_lev, up_trend[1])   : up_lev

down_trend = 0.0
down_trend := close[1] < down_trend[1] ? min(dn_lev, down_trend[1]) : dn_lev

// Calculate trend var
trend = 0
trend := close > down_trend[1] ? 1: close < up_trend[1] ? -1 : nz(trend[1], 1)

// Calculate SuperTrend Line
st_line = trend ==1 ? up_trend : down_trend

// Plotting
plot(st_line[1], color = trend == 1 ? color.green : color.red , style = plot.style_cross, linewidth = 2, title = "SuperTrend")
buy=crossover( close, st_line) and close>o
sell=crossunder(close, st_line) and close<o
//plotshape(crossover( close, st_line), location = location.belowbar, color = color.green,size=size.tiny)
//plotshape(crossunder(close, st_line), location = location.abovebar, color = color.red,size=size.tiny)
plotshape(buy, title="buy", text="Buy", color=color.green, style=shape.labelup, location=location.belowbar, size=size.small, textcolor=color.white, transp=0)  //plot for buy icon
plotshape(sell, title="sell", text="Sell", color=color.red, style=shape.labeldown, location=location.abovebar, size=size.small, textcolor=color.white, transp=0)  //plot for sell icon


//
multiplier = input(title="TP VWAP Deviation", type=input.float, defval=2, minval=1)
src5 = vwap
len5 = input(title="TP length", defval=150, minval=1)
offset = 0

calcSlope(src5, len5) =>
    sumX = 0.0
    sumY = 0.0
    sumXSqr = 0.0
    sumXY = 0.0
    for i = 1 to len5
        val = src5[len5-i]
        per = i + 1.0
        sumX := sumX + per
        sumY := sumY + val
        sumXSqr := sumXSqr + per * per
        sumXY := sumXY + val * per
        
        
    slope = (len5 * sumXY - sumX * sumY) / (len5 * sumXSqr - sumX * sumX)
    average = sumY / len5
    intercept = average - slope * sumX / len5 + slope
    [slope, average, intercept]

var float tmp = na
[s, a, i] = calcSlope(src5, len5)

vwap1=(i + s * (len5 - offset))
sdev = stdev(vwap, len5)
dev = multiplier * sdev
top=vwap1+dev
bott=vwap1-dev

//
z1 = vwap1 + dev
x1 = vwap1 - dev

low1 = crossover(close, x1)  
high1 = crossunder(close, z1) 

plotshape(low1, title="low", text="TP", color=color.red, style=shape.labelup, location=location.belowbar, size=size.small, textcolor=color.white, transp=0)  //plot for buy icon
plotshape(high1, title="high", text="TP", color=color.green, style=shape.labeldown, location=location.abovebar, size=size.small, textcolor=color.white, transp=0)  //plot for sell icon



//
// Testing Start dates
testStartYear = input(2016, "Backtest Start Year")
testStartMonth = input(1, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay,0,0)
//Stop date if you want to use a specific range of dates
testStopYear = input(2030, "Backtest Stop Year")
testStopMonth = input(12, "Backtest Stop Month")
testStopDay = input(30, "Backtest Stop Day")
testPeriodStop = timestamp(testStopYear,testStopMonth,testStopDay,0,0)


testPeriod() =>
    time >= testPeriodStart and time <= testPeriodStop ? true : false

l = buy
s1 = sell
        
if l and testPeriod()
    strategy.entry("buy", strategy.long)
if s1 and testPeriod()
    strategy.entry("sell", strategy.short)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-10-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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