This strategy captures strong bullish momentum by combining a 200-period SMA baseline, a custom Bollinger Band, the True Strength Index (TSI) smoothed with WMAs, and the ADX trend strength indicator. It initiates long positions when price is above the 200 SMA,
Strategy · Pine Script v4 · Own pane
Bayesian BBSMA Oscillator Strategy
This Pine Script strategy calculates Bayesian probabilities of price breaking up or down relative to Bollinger Bands and a Simple Moving Average.
GitHub stars25on the repository
Pine versionv4older, still runs
Lines of code92
Settings11inputs
LicenceNone statedfile: MPL-2.0
Last update6 years ago29 Jun 2020
Add It to Your TradingView Chart
- 1Copy the scriptPress Copy script above, or the copy button on the code below.
- 2Open the Pine EditorOpen a TradingView chart and choose Pine Editor at the bottom of the screen.
- 3Paste over the templateCreate a new strategy, select all of the template text and paste. Press Save and give it a name.
- 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
92 lines of Pine Script v4 from bayesian/strategies/bbsmastrat.pine, published under MPL-2.0 (file header). Keep the author's credit and licence lines when you reuse it.
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © tista
//@version=4
strategy("Bayesian BBSMA Oscillator Strategy", shorttitle="BayesBBSMAOscStrategy", default_qty_type=strategy.percent_of_equity, default_qty_value=100, currency="USD")
bbSmaPeriod = input(20, title="BB SMA Period")
bbStdDevMult = input(2.5, title="BB Standard Deviation", maxval=50.0)
bbBasis = sma(close, bbSmaPeriod)
bbStdDev = bbStdDevMult * stdev(close, bbSmaPeriod)
bbUpper = bbBasis + bbStdDev
bbLower = bbBasis - bbStdDev
// SMA
smaPeriod = input(20, title="SMA Period")
smaValues = sma(close, smaPeriod)
// Bayesian Theorem Starts
bayesPeriod = input(20, title="Bayesian Lookback Period")
// Next candles are breaking Down
probBbUpperUpSeq = close > bbUpper ? 1 : 0
probBbUpperUp = sum(probBbUpperUpSeq, bayesPeriod) / bayesPeriod
probBbUpperDownSeq = close < bbUpper ? 1 : 0
probBbUpperDown = sum(probBbUpperDownSeq, bayesPeriod) / bayesPeriod
probUpBbUpper = probBbUpperUp / (probBbUpperUp + probBbUpperDown)
probBbBasisUpSeq = close > bbBasis ? 1 : 0
probBbBasisUp = sum(probBbBasisUpSeq, bayesPeriod) / bayesPeriod
probBbBasisDownSeq = close < bbBasis ? 1 : 0
probBbBasisDown = sum(probBbBasisDownSeq, bayesPeriod) / bayesPeriod
probUpBbBasis = probBbBasisUp / (probBbBasisUp + probBbBasisDown)
probSmaUpSeq = close > smaValues ? 1 : 0
probSmaUp = sum(probSmaUpSeq, bayesPeriod) / bayesPeriod
probSmaDownSeq = close < smaValues ? 1 : 0
probSmaDown = sum(probSmaDownSeq, bayesPeriod) / bayesPeriod
probUpSma = probSmaUp / (probSmaUp + probSmaDown)
sigmaProbsDown = nz(probUpBbUpper * probUpBbBasis * probUpSma / probUpBbUpper * probUpBbBasis * probUpSma + ((1 - probUpBbUpper) * (1 - probUpBbBasis) * (1 - probUpSma))) * 100
// Next candles are breaking Up
probDownBbUpper = probBbUpperDown / (probBbUpperDown + probBbUpperUp)
probDownBbBasis = probBbBasisDown / (probBbBasisDown + probBbBasisUp)
probDownSma = probSmaDown / (probSmaDown + probSmaUp)
sigmaProbsUp = nz(probDownBbUpper * probDownBbBasis * probDownSma / probDownBbUpper * probDownBbBasis * probDownSma + ( (1 - probDownBbUpper) * (1 - probDownBbBasis) * (1 - probDownSma) )) * 100
showNextCandleDown = input(true, title="Plot Next Candles Breaking Down?")
plot(showNextCandleDown ? sigmaProbsDown : na, title="Next Candle Breaking Down Probs", transp=0, color=color.red)
showNextCandleUp = input(true, title="Plot Next Candles Breaking Up?")
plot(showNextCandleUp ? sigmaProbsUp : na, title="Next Candle Breaking Up Probs", transp=0, color=color.green)
longSignal = sigmaProbsUp < 100 and sigmaProbsUp[1] == 100
shortSignal = sigmaProbsDown < 100 and sigmaProbsDown[1] == 100
longTrailPerc = input(title="Trail Long Loss (%)", type=input.float, minval=0.0, step=0.1, defval=4) * 0.01
longStopPrice = 0.0
longStopPrice := if (strategy.position_size > 0)
stopValue = close * (1 - longTrailPerc)
max(stopValue, longStopPrice[1])
else
0
shortTrailPerc = input(title="Trail Short Loss (%)", type=input.float, minval=0.0, step=0.1, defval=4) * 0.01
shortStopPrice = 0.0
shortStopPrice := if (strategy.position_size < 0)
stopValue = close * (1 + shortTrailPerc)
min(stopValue, shortStopPrice[1])
else
999999999
startingYear = input(2019, title="Year started")
doLongs = input(true, title="Calculate longs?")
strategy.entry("Long", strategy.long, when=strategy.position_size == 0 and longSignal and year >= startingYear and doLongs)
if (strategy.position_size > 0)
strategy.exit(id="Long Trail Stop", stop=longStopPrice)
doShorts = input(true, title="Calculate shorts?")
strategy.entry("Short", strategy.short, when=strategy.position_size == 0 and shortSignal and year >= startingYear and doShorts)
if (strategy.position_size < 0)
strategy.exit(id="Short Trail Stop", stop=shortStopPrice)
Overview
Bayesian BBSMA Oscillator Strategy plots these breakout and breakdown probability lines as oscillators in a separate pane. Long entries trigger when the upward probability crosses down from maximum, while short entries trigger when downward probability drops from maximum. Trades are protected using a percentage-based trailing stop loss. Settings allow customization of Bollinger Band parameters, Bayesian lookback period, trailing stop percentages, start year, and directional long/short toggles.
- Bayesian probability calculation for candle breakouts
- Bollinger Bands and SMA probability integration
- Percentage-based trailing stop loss execution
- Separate pane probability oscillator plots
Details
Published by
tistaharahap on GitHub
Code credit
tista, as written in the script's header
Type
Strategy, Pine Script v4
Draws
Separate pane below the chart
Category
Oscillators & momentum, Volatility & bands, Moving averages
Markets
Any symbol
Timeframes
Any timeframe
Risk Notes
No repainting, lookahead or stacked entries were found in its code or README. That says nothing about how well it works: test it first.
Settings
The inputs you can change from the gear icon on the chart. Defaults are the author's.
| Setting | Type | Default | Variable |
|---|---|---|---|
| BB SMA Period | int | 20 | bbSmaPeriod |
| BB Standard Deviation | float | 2.5 | bbStdDevMult |
| SMA Period | int | 20 | smaPeriod |
| Bayesian Lookback Period | int | 20 | bayesPeriod |
| Plot Next Candles Breaking Down? | bool | true | showNextCandleDown |
| Plot Next Candles Breaking Up? | bool | true | showNextCandleUp |
| Trail Long Loss (%) | float | 4 | longTrailPerc |
| Trail Short Loss (%) | float | 4 | shortTrailPerc |
| Year started | int | 2019 | startingYear |
| Calculate longs? | bool | true | doLongs |
| Calculate shorts? | bool | true | doShorts |
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.
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