Strategy · Pine Script v4 · Own pane

Bollinger %B Candles Strategy

by hasnocool· code credited to HeWhoMustNotBeNamed

The Bollinger %B Candles Strategy evaluates price volatility and momentum by calculating Bollinger Bands %B oscillator values in a separate pane.

View on GitHub

GitHub stars106on the repository
Pine versionv4older, still runs
Lines of code103
Settings14inputs
LicenceGPL-3.0
Last update2 years ago18 Sep 2024

Add It to Your TradingView Chart

  1. 1Copy the scriptPress Copy script above, or the copy button on the code below.
  2. 2Open the Pine EditorOpen a TradingView chart and choose Pine Editor at the bottom of the screen.
  3. 3Paste over the templateCreate a new strategy, select all of the template text and paste. Press Save and give it a name.
  4. 4Add it to the chartPress Add to chart. The trades and results appear in the Strategy Tester tab; adjust the settings with the gear icon.

Source Code

103 lines of Pine Script v4 from Bollinger -B Candles Strategy.pine, published under GPL-3.0. Keep the author's credit and licence lines when you reuse it.

Bollinger -B Candles Strategy.pine
// 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("Bollinger %B Candles Strategy", overlay=false, initial_capital = 10000, default_qty_type = strategy.percent_of_equity, default_qty_value = 10, commission_type = strategy.commission.percent, pyramiding = 1, commission_value = 0.01)
BBLength = input(100, minval=1, step=1)
StdDev = 10
useMovingAverage = input(true)
MAType = input(title="Moving Average Type", defval="rma", options=["ema", "sma", "hma", "rma", "vwma", "wma"])
lookbackPeriod = input(22, minval=10, step=10)
colorByPreviousClose = input(true)
delaySignalBars = input(2, minval=2)
AtrMAType = input(title="Moving Average Type", defval="hma", options=["ema", "sma", "hma", "rma", "vwma", "wma"])
AtrLength = input(10)
AtrMult = input(4)
wicks = input(false)
considerYearlyHighLow = input(false)
considerNewLongTermHighLows = input(false)
shortHighLowPeriod = 100
longHighLowPeriod = 200
tradeDirection = input(title="Trade Direction", defval=strategy.direction.all, options=[strategy.direction.all, strategy.direction.long, strategy.direction.short])
backtestYears = input(10, minval=1, step=1)
//////////////////////////////////// Calculate new high low condition //////////////////////////////////////////////////
f_calculateNewHighLows(shortHighLowPeriod, longHighLowPeriod, considerNewLongTermHighLows)=>
    newHigh = highest(shortHighLowPeriod) == highest(longHighLowPeriod) or not considerNewLongTermHighLows
    newLow = lowest(shortHighLowPeriod) == lowest(longHighLowPeriod) or not considerNewLongTermHighLows
    [newHigh,newLow]
//////////////////////////////////// Calculate Yearly High Low //////////////////////////////////////////////////
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
    
    label_x = time+(60*60*24*1000*1)
    [yearlyHighCondition,yearlyLowCondition]
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
inDateRange = time >= timestamp(syminfo.timezone, year(timenow) - backtestYears, 01, 01, 0, 0)
[yearlyHighCondition,yearlyLowCondition] = f_getYearlyHighLowCondition(considerYearlyHighLow)
[newHighS,newLowS] = f_calculateNewHighLows(shortHighLowPeriod, longHighLowPeriod, considerNewLongTermHighLows)
[middleclose, upperclose, lowerclose] = bb(close, BBLength, StdDev)
[middleopen, upperopen, loweropen] = bb(open, BBLength, StdDev)
[middlehigh, upperhigh, lowerhigh] = bb(high, BBLength, StdDev)
[middlelow, upperlow, lowerlow] = bb(low, BBLength, StdDev)
percentBClose = (close - lowerclose)*100/(upperclose-lowerclose)
percentBOpen = (open - loweropen)*100/(upperopen-loweropen)
percentBHigh = (high - lowerhigh)*100/(upperhigh-lowerhigh)
percentBLow = (low - lowerlow)*100/(upperlow-lowerlow)
percentBMAClose = f_getMovingAverage(percentBClose, MAType, lookbackPeriod)
percentBMAOpen = f_getMovingAverage(percentBOpen, MAType, lookbackPeriod)
percentBMAHigh = f_getMovingAverage(percentBHigh, MAType, lookbackPeriod)
percentBMALow = f_getMovingAverage(percentBLow, MAType, lookbackPeriod)
newOpen = useMovingAverage? percentBMAOpen : percentBOpen
newClose = useMovingAverage? percentBMAClose : percentBClose
newHigh = useMovingAverage? percentBMAHigh : percentBHigh
newLow = useMovingAverage? percentBMALow : percentBLow
truerange = max(newHigh, newClose[1]) - min(newLow, newClose[1])
averagetruerange = f_getMovingAverage(truerange, AtrMAType, AtrLength)
atr = averagetruerange * AtrMult
longStop = newClose - atr
longStopPrev = nz(longStop[1], longStop)
longStop := (wicks ? newLow[1] : newClose[1]) > longStopPrev ? max(longStop, longStopPrev) : longStop
shortStop = newClose + atr
shortStopPrev = nz(shortStop[1], shortStop)
shortStop := (wicks ? newHigh[1] : newClose[1]) < shortStopPrev ? min(shortStop, shortStopPrev) : shortStop
dir = 1
dir := nz(dir[1], dir)
dir := dir == -1 and (wicks ? newHigh : newClose) > shortStopPrev ? 1 : dir == 1 and (wicks ? newLow : newClose) < longStopPrev ? -1 : dir
trailingStop = dir == 1? longStop : shortStop
candleColor = colorByPreviousClose ?
                 (newClose[1] < newClose ? color.green : newClose[1] > newClose ? color.red : color.silver) : 
                 (newOpen < newClose ? color.green : newOpen > newClose ? color.red : color.silver)
plotcandle(newOpen, newHigh, newLow, newClose, title='PercentBCandle', color = candleColor)
plot(trailingStop, title="TrailingStop", style=plot.style_linebr, linewidth=1, color= dir == 1 ? color.green : color.red)
buyCondition = lowest(dir,delaySignalBars)==1 and yearlyHighCondition and newHighS
exitBuyCondition = highest(dir,delaySignalBars) == -1
sellCondition = highest(dir,delaySignalBars) == -1 and yearlyLowCondition and newLowS
exitSellCondition = lowest(dir,delaySignalBars) == 1
strategy.risk.allow_entry_in(tradeDirection)
barcolor(buyCondition? color.lime : sellCondition ? color.orange : color.silver)
strategy.entry("Buy", strategy.long, when=buyCondition and inDateRange, oca_name="oca_buy", oca_type=strategy.oca.none)
strategy.close("Buy", when=exitBuyCondition)
strategy.entry("Sell", strategy.short, when=sellCondition and inDateRange, oca_name="oca_sell", oca_type=strategy.oca.none)
strategy.close("Sell", when=exitSellCondition)
Expand (124 lines)

Overview

Bollinger %B Candles Strategy incorporates customizable moving average filters, ATR multipliers, and optional higher-timeframe yearly high or low trend checks to confirm entry conditions. Traders can select between various moving average types like EMA, SMA, HMA, RMA, VWMA, and WMA, adjust signal delay parameters, and define backtest periods. The strategy executes trades according to the specified direction filter without an explicit stop-loss rule.

Details

Published by

hasnocool on GitHub

Code credit

HeWhoMustNotBeNamed, as written in the script's header

Type

Strategy, Pine Script v4

Draws

Separate pane below the chart

Category

Volatility & bands, Moving averages, Trend, Oscillators & momentum

Markets

Crypto

Timeframes

Any timeframe

Risk Notes

  • The strategy enters trades without a stop loss

Topics

analysisbtcusdtcryptocurrencydatapandaspythonsimulationtradingtradingview

Settings

The inputs you can change from the gear icon on the chart. Defaults are the author's.

SettingTypeDefaultVariable
BBLengthint100BBLength
useMovingAveragebooltrueuseMovingAverage
Moving Average TypestringrmaMAType
lookbackPeriodint22lookbackPeriod
colorByPreviousClosebooltruecolorByPreviousClose
delaySignalBarsint2delaySignalBars
Moving Average TypestringhmaAtrMAType
AtrLengthint10AtrLength
AtrMultint4AtrMult
wicksboolfalsewicks
considerYearlyHighLowboolfalseconsiderYearlyHighLow
considerNewLongTermHighLowsboolfalseconsiderNewLongTermHighLows
Show all 14 settings
SettingTypeDefaultVariable
Trade Directioninputstrategy.direction.alltradeDirection
backtestYearsint10backtestYears
Third-party code. ForexR did not write, test or endorse this script, and the summary above was generated automatically from its code and README. Indicators describe the past, and a strategy's backtest can look better than live trading, especially when a script repaints. Check it in the Strategy Tester and on a demo account before you rely on it.

Similar Pine Scripts

EMA Ribbon MACD

by iamrichardD
57 stars

This strategy combines an EMA ribbon with MACD confirmation and plots in a separate pane. It enters when ribbon alignment, optional MACD zero or signal crosses, volume, smart-money, and multi-timeframe filters agree, then exits with percentage stop loss and ta

Strategy v6 TrendMoving averages
Updated 1 year ago · Apache-2.0 GitHub repository of EMA Ribbon MACD

Sentiment 2

by ggamer5555
1 stars

Sentiment 2 is a trend-following strategy that calculates a normalized composite market sentiment score ranging between 0 and 1. It combines exponential and Hull moving average slopes, high/low midpoints, Supertrend distances, and Parabolic SAR metrics. Plotte

Strategy v6 TrendMoving averages
Updated 5 months ago · None stated GitHub repository of Sentiment 2

SOLETH MTPI

by Mikelkulla
1 stars

This strategy detects relative performance between Solana and Ethereum using a liquidity-weighted supertrend (LWST) derived from fast and slow weighted moving averages of liquidity times close. It plots the Tsl2 trend line in a separate pane and issues buy sig

Strategy v5 TrendMoving averages
Updated 1 year ago · None stated GitHub repository of SOLETH MTPI

Momentum Rider DAILY FINAL

by greenpeas007
58 stars

This strategy combines exponential moving averages (EMA 9, 21, 50), RSI, MACD, and Supertrend indicators to enter long positions. It triggers trades using six dynamic setups based on momentum breakouts, EMA crossovers, and pullbacks. Position sizing is compute

Strategy v6 TrendOscillators & momentum Repaints
Updated 4 months ago · Custom licence GitHub repository of Momentum Rider DAILY FINAL

CombinedBinHAndClucV6

by viktors1982
36 stars

CombinedBinHAndClucV6 is a trading strategy based on the popular BinHV45 and ClucMay72018 algorithms. It calculates dual Bollinger Bands, Exponential Moving Averages, Relative Strength Index, Average True Range, and volume metrics across primary and one-hour h

Strategy v4 Volatility & bandsOscillators & momentum Repaints
Updated 2 years ago · None stated GitHub repository of CombinedBinHAndClucV6

More strategys

Trade Your Charts With a Regulated Broker

Compare brokers that connect to TradingView, with spreads, minimum deposits and leverage side by side.

Compare brokers