SuperJump Turn Back Bollinger Band
This is a simple indicator using bolinger band return. After the candle's bolinger band broke out, Turn back inside BB is the entry point. Usually there are more than two triangles, so you can wait after ordering a…
This is a simple indicator using bolinger band return.
After the candle's bolinger band broke out, Turn back inside BB is the entry point.
Usually there are more than two triangles, so you can wait after ordering a better price.
backtest
Parameters
| Name | Default | What it controls |
|---|---|---|
| v_input_int_1 | 68 | (?Bollinger)length |
| v_input_1_open | 0 | Source: open | high | low | close | hl2 | hlc3 | hlcc4 | ohlc4 |
| v_input_float_1 | 2 | StdDev |
| v_input_float_2 | 2.5 | Wide StdDev |
| v_input_int_2 | 14 | (?ATR)ATR Length |
| v_input_string_1 | 0 | Smoothing: RMA | SMA | EMA | WMA |
| v_input_float_3 | true | Stop Loss ATR Ratio |
Source Pine Script
/*backtest
start: 2022-04-17 00:00:00
end: 2022-05-16 23:59:00
period: 30m
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/
//@SuperJump
//@version=5
indicator(shorttitle="SuperJump TBBB", title="SuperJump Turn Back Bollinger Band", overlay=true, timeframe="", timeframe_gaps=true)
length = input.int(68, minval=1, group="Bollinger", inline='1')
src = input(open, title="Source", group="Bollinger", inline='1')
mult = input.float(2.0, minval=0.001, maxval=50, title="StdDev", group="Bollinger", inline='1')
b_mult = input.float(2.5, minval=0.001, maxval=50, title="Wide StdDev", group="Bollinger", inline='1')
basis = ta.sma(src, length)
dev = mult * ta.stdev(src, length)
upper = basis + dev
lower = basis - dev
b_dev = b_mult * ta.stdev(src, length)
b_upper = basis + b_dev
b_lower = basis - b_dev
atrlength = input.int(title="ATR Length", defval=14, minval=1,group="ATR" ,inline='2')
smoothing = input.string(title="Smoothing", defval="RMA", options=["RMA", "SMA", "EMA", "WMA"],group="ATR", inline='2')
SLAtr = input.float(title="Stop Loss ATR Ratio", defval=1.0, minval=1,group="ATR" ,inline='2')
ma_function(source, length) =>
switch smoothing
"RMA" => ta.rma(source, length)
"SMA" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
=> ta.wma(source, length)
atr = ma_function(ta.tr(true), atrlength)
LongSig = ta.crossunder(lower,src) and close > open
ShortSig = ta.crossover(upper,src) and close < open
WLongSig = ta.crossunder(b_lower,src) and close > open
WShortSig = ta.crossover(b_upper,src) and close < open
//Plots
plot(basis, "Basis", color=#FF6D00)
plot(upper, "Upper", color=#2962FF)
plot(lower, "Lower", color=#2962FF)
plot(b_upper, "Wide Upper", color=#2962FF)
plot(b_lower, "Wide Lower", color=#2962FF)
plot(b_upper + atr*SLAtr, "SL Upper", color=color.red)
plot(b_lower - atr*SLAtr, "SL Lower", color=color.red)
plotchar(ShortSig and WShortSig == false ? src : na, location = location.abovebar, char= "▼", size = size.tiny, color = color.white )
plotchar(LongSig and WLongSig == false ? src : na, location = location.belowbar, char= "▲", size = size.tiny, color = color.white)
plotchar(WShortSig ? src : na, location = location.abovebar, char= "▼", size = size.tiny, color = color.yellow )
plotchar(WLongSig ? src : na, location = location.belowbar, char= "▲", size = size.tiny, color = color.yellow)
alertcondition(LongSig and WLongSig == false, title='Bollinger Band Long', message='Bollinger Band Long Price is {{close}}, SL :{{plot_4}}')
alertcondition(ShortSig and WShortSig == false, title='Bollinger Band Short', message='Bollinger Band Short Price is {{close}},SL :{{plot_3}} ')
alertcondition(WLongSig, title='Wide Bollinger Band Long', message='Wide Bollinger Band Long Price is {{close}}, SL :{{plot_4}}')
alertcondition(WShortSig, title='Wide Bollinger Band Short', message='Wide Bollinger Band Short Price is {{close}},SL :{{plot_3}} ')
if LongSig
strategy.entry("Enter Long", strategy.long)
else if ShortSig
strategy.entry("Enter Short", strategy.short)Published by ChaoZhang on the FMZ strategy square · last modified 2022-05-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.
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