Golden Cross with Bollinger Bands Momentum Strategy

Pine ScriptMomentum Trend following Volatility RSI EMA SMA Bollinger Bands VWAP

Author: ChaoZhang
Complexity: Intermediate · 160 lines
Parameters: 14
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy combines moving average, Bollinger bands and volume weighted average price (VWAP) indicators. It enters long positions when the golden cross forms and the fast moving average breaks above the slow one. The strategy also utilizes the Bollinger band channel and only considers entering when the price touches the lower band, thus avoiding frequent entries and exits amid market fluctuations.

Strategy Logic

The core logic relies on moving averages to determine the trend direction, and Bollinger bands to locate the fluctuation range for buying signals. Specifically, it has the following key rules:

Construct the golden cross system using 50-day EMA and 200-day EMA. An up trend is identified when the fast EMA crosses above the slow EMA.
When the price is above VWAP, it indicates the price is in an upward phase which favors long positions.
When the price just touches or breaks the Bollinger lower band, it suggests the price may be near a rebound point thus providing a good opportunity.
Exit long positions with profit when the price exceeds the Bollinger upper band.

By combining these rules, the strategy is able to locate appropriate long entries in bull markets and set stop loss/profit taking to secure returns.

Advantages

The golden cross system determines the major trend direction, avoiding small wins and losses amid consolidations.
VWAP gauges the price wave direction for more precise buying signals.
The Bollinger bands add resilience by locating buys while setting stop loss/profit taking locks in gains.
Multiple confirming indicators enhance reliability.

Risks and Solutions

The golden cross may give false signals. Fine tune the MA periods and add other confirmations.
Improper Bollinger parameters could render the strategy ineffective. Optimize periods and standard deviation.
A stop loss threshold too wide fails to effectively limit losses. Tighten the stop loss range to ensure controllable risks.

Optimization Directions

Optimize MA combinations by testing different parameters to find the best.
Test Bollinger periods and parameter sets for better bandwidth and volatility.
Test and tune stop loss ranges for balancing risk control and avoiding premature triggering.

Conclusion

This strategy strikes a balance between discovering opportunities and controlling risks by integrating MA, Bollinger and VWAP analysis for entries. Continuous fine tuning and optimization will allow it to capitalize on sector and market trends over time.

Parameters

Name	Default	What it controls
v_input_1	true	From Day
v_input_2	6	From Month
v_input_3	2020	From Year
v_input_4	true	To Day
v_input_5	8	To Month
v_input_6	2020	To Year
v_input_7	50	fast EMA
v_input_8	200	slow EMA
v_input_9	7	BB SMA Length
v_input_10_close	0	BB Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_11	0	strategy to use: BB \| BB_percentageB
v_input_12	true	Stop Loss%
v_input_13	2	StdDev
v_input_14	false	Offset

Source Pine Script

/*backtest
start: 2022-11-14 00:00:00
end: 2023-11-20 00:00:00
period: 1d
basePeriod: 1h
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/
// © mohanee

//@version=4
strategy(title="VWAP and BB strategy [$$]", overlay=true,pyramiding=2, default_qty_value=1, default_qty_type=strategy.fixed,    initial_capital=10000, currency=currency.USD)


fromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
fromMonth = input(defval = 6, title = "From Month", minval = 1, maxval = 12)
fromYear = input(defval = 2020, title = "From Year", minval = 1970)
 
// To Date Inputs
toDay = input(defval = 1, title = "To Day", minval = 1, maxval = 31)
toMonth = input(defval = 8, title = "To Month", minval = 1, maxval = 12)
toYear = input(defval = 2020, title = "To Year", minval = 1970)
 
// Calculate start/end date and time condition
DST = 1 //day light saving for usa
//--- Europe
London = iff(DST==0,"0000-0900","0100-1000")
//--- America
NewYork = iff(DST==0,"0400-1300","0500-1400")
//--- Pacific
Sydney = iff(DST==0,"1300-2200","1400-2300")
//--- Asia
Tokyo = iff(DST==0,"1500-2400","1600-0100")

//-- Time In Range
timeinrange(res, sess) => time(res, sess) != 0

london = timeinrange(timeframe.period, London)
newyork = timeinrange(timeframe.period, NewYork)

startDate = timestamp(fromYear, fromMonth, fromDay, 00, 00)
finishDate = timestamp(toYear, toMonth, toDay, 00, 00)
time_cond = time >= startDate and time <= finishDate 


is_price_dipped_bb(pds,source1) =>
    t_bbDipped=false
    for i=1 to pds
        t_bbDipped:=  (t_bbDipped   or  close[i]<source1) ? true : false
        if t_bbDipped==true
            break
        else
            continue
            
    t_bbDipped


is_bb_per_dipped(pds,bbrSrc) =>
    t_bbDipped=false
    for i=1 to pds
        t_bbDipped:=  (t_bbDipped   or  bbrSrc[i]<=0) ? true : false
        if t_bbDipped==true
            break
        else
            continue
            
    t_bbDipped
    

// variables  BEGIN
shortEMA = input(50, title="fast EMA", minval=1)
longEMA = input(200, title="slow EMA", minval=1)

//BB

smaLength = input(7, title="BB SMA Length", minval=1)
bbsrc = input(close, title="BB Source")

strategyCalcOption = input(title="strategy to use", type=input.string, options=["BB", "BB_percentageB"],      defval="BB")



//addOnDivergence = input(true,title="Add to existing on Divergence")
//exitOption = input(title="exit on RSI or BB", type=input.string, options=["RSI", "BB"],      defval="BB")

//bbSource = input(title="BB  source", type=input.string, options=["close", "vwap"],      defval="close")
     
//vwap_res = input(title="VWAP Resolution", type=input.resolution, defval="session")
stopLoss = input(title="Stop Loss%", defval=1, minval=1)

//variables  END

longEMAval= ema(close, longEMA)
shortEMAval= ema(close, shortEMA)
ema200val = ema(close, 200)


vwapVal=vwap(close)



// Drawings

//plot emas
plot(shortEMAval, color = color.green, linewidth = 1, transp=0)
plot(longEMAval, color = color.orange, linewidth = 1, transp=0)
plot(ema200val, color = color.purple, linewidth = 2, style=plot.style_line ,transp=0)



//bollinger calculation 
mult = input(2.0, minval=0.001, maxval=50, title="StdDev")
basis = sma(bbsrc, smaLength)
dev = mult * stdev(bbsrc, smaLength)
upperBand = basis + dev
lowerBand = basis - dev
offset = input(0, "Offset", type = input.integer, minval = -500, maxval = 500)

bbr = (bbsrc - lowerBand)/(upperBand - lowerBand) 
//bollinger calculation 

//plot bb
//plot(basis, "Basis", color=#872323, offset = offset)
p1 = plot(upperBand, "Upper", color=color.teal, offset = offset)
p2 = plot(lowerBand, "Lower", color=color.teal, offset = offset)
fill(p1, p2, title = "Background", color=#198787, transp=95)


plot(vwapVal, color = color.purple, linewidth = 2, transp=0)


// Colour background

//barcolor(shortEMAval>longEMAval and close<=lowerBand ? color.yellow: na)
  

//longCondition=  shortEMAval > longEMAval and  close>open and  close>vwapVal
longCondition=  ( shortEMAval > longEMAval  and close>open and close>vwapVal and close<upperBand ) //and time_cond //     and  close>=vwapVal 



//Entry
strategy.entry(id="long", comment="VB LE" , long=true,  when= longCondition and ( strategyCalcOption=="BB"? is_price_dipped_bb(10,lowerBand) : is_bb_per_dipped(10,bbr)  )   and strategy.position_size<1 )   //is_price_dipped_bb(10,lowerBand))  //and strategy.position_size<1       is_bb_per_dipped(15,bbr) 


//add to the existing position
strategy.entry(id="long", comment="Add" , long=true,  when=strategy.position_size>=1 and close<strategy.position_avg_price and close>vwapVal) //and time_cond)

barcolor(strategy.position_size>=1  ? color.blue: na)



strategy.close(id="long", comment="TP Exit",   when=crossover(close,upperBand) )

//stoploss
stopLossVal =   strategy.position_avg_price * (1-(stopLoss*0.01) )
//strategy.close(id="long", comment="SL Exit",   when= close < stopLossVal)

//strategy.risk.max_intraday_loss(stopLoss, strategy.percent_of_equity)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-21. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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