ChaoZhang
Overview
This strategy uses adaptive Bollinger Bands indicator to identify the trend direction and market orders to track the trend with stop loss for efficient trend trading.
Strategy Logic
- Calculate the middle, upper and lower bands of Bollinger based on a certain period
- Go long when the price breaks through the upper band and go short when breaks the lower band to track the trend
- Use market orders for fast entry
- Set stop loss and take profit for position management
Advantages
- Adaptive Bollinger Bands are sensitive to market volatility for fast judgement of trend reversal
- Market orders ensure fast entry with reduced slippage risk
- Automatic stop loss and take profit strictly control the risk and lock in profit
Risks
- Bollinger Bands has some lagging nature, cannot fully avoid false breakouts
- Market orders cannot control the execution price precisely
- Proper setting of stop loss and take profit levels is needed
Optimization Directions
- Adjust Bollinger parameters for better sensitivity in judging trends
- Add indicators like volume or MACD to filter false breakouts
- Optimize stop loss and take profit levels
Summary
This strategy makes full use of Bollinger Bands’ advantage in judging trend directions and combines fast-exit market orders for trend tracking from both sides, gaining excess returns under controlled risk. Further improvements like optimizing Bollinger parameters, adding filtering indicators and adjusting stop loss/take profit logic can lead to better strategy performance. With clear logic and easy implementation, it is an efficient and reliable trend tracking trading strategy.
Strategy source code
/*backtest
start: 2024-01-04 00:00:00
end: 2024-02-03 00:00:00
period: 1h
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/
// © CryptoRox
//@version=4
//Paste the line below in your alerts to run the built-in commands.
//{{strategy.order.alert_message}}
strategy("Automated - Fibs with Market orders", "Strategy", true)
//Settings
testing = input(false, "Live")
//Use epochconverter or something similar to get the current timestamp.
starttime = input(1600976975, "Start Timestamp") * 1000
//Wait XX seconds from that timestamp before the strategy starts looking for an entry.
seconds = input(60, "Start Delay") * 1000
testPeriod = true
leverage = input(1, "Leverage")
tp = input(1.0, "Take Profit %") / leverage
dca = input(-1.0, "DCA when < %") / leverage *-1
fibEntry = input("1", "Entry Level", options=["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"])
//Strategy Calls
equity = strategy.equity
avg = strategy.position_avg_price
symbol = syminfo.tickerid
openTrades = strategy.opentrades
closedTrades = strategy.closedtrades
size = strategy.position_size
//Fibs
lentt = input(60, "Pivot Length")
h = highest(lentt)
h1 = dev(h, lentt) ? na : h
hpivot = fixnan(h1)
l = lowest(lentt)
l1 = dev(l, lentt) ? na : l
lpivot = fixnan(l1)
z = 400
p_offset= 2
transp = 60
a=(lowest(z)+highest(z))/2
b=lowest(z)
c=highest(z)
fib0 = (((hpivot - lpivot)) + lpivot)
fib1 = (((hpivot - lpivot)*.21) + lpivot)
fib2 = (((hpivot - lpivot)*.3) + lpivot)
fib3 = (((hpivot - lpivot)*.5) + lpivot)
fib4 = (((hpivot - lpivot)*.62) + lpivot)
fib5 = (((hpivot - lpivot)*.7) + lpivot)
fib6 = (((hpivot - lpivot)* 1.00) + lpivot)
fib7 = (((hpivot - lpivot)* 1.27) + lpivot)
fib8 = (((hpivot - lpivot)* 2) + lpivot)
fib9 = (((hpivot - lpivot)* -.27) + lpivot)
fib10 = (((hpivot - lpivot)* -1) + lpivot)
notna = nz(fib10[60])
entry = 0.0
if fibEntry == "1"
entry := fib10
if fibEntry == "2"
entry := fib9
if fibEntry == "3"
entry := fib0
if fibEntry == "4"
entry := fib1
if fibEntry == "5"
entry := fib2
if fibEntry == "6"
entry := fib3
if fibEntry == "7"
entry := fib4
if fibEntry == "8"
entry := fib5
if fibEntry == "9"
entry := fib6
if fibEntry == "10"
entry := fib7
profit = avg+avg*(tp/100)
pause = 0
pause := nz(pause[1])
paused = time < pause
fill = 0.0
fill := nz(fill[1])
count = 0.0
count := nz(fill[1])
filled = count > 0 ? entry > fill-fill/100*dca : 0
signal = testPeriod and notna and not paused and not filled ? 1 : 0
neworder = crossover(signal, signal[1])
moveorder = entry != entry[1] and signal and not neworder ? true : false
cancelorder = crossunder(signal, signal[1]) and not paused
filledorder = crossunder(low[1], entry[1]) and signal[1]
last_profit = 0.0
last_profit := nz(last_profit[1])
// if neworder and signal
// strategy.order("New", 1, 0.0001, alert_message='New Order|e=binancefuturestestnet s=btcusdt b=long q=0.0011 fp=' + tostring(entry))
// if moveorder
// strategy.order("Move", 1, 0.0001, alert_message='Move Order|e=binancefuturestestnet s=btcusdt b=long c=order|e=binancefuturestestnet s=btcusdt b=long q=0.0011 fp=' + tostring(entry))
if filledorder and size < 1
fill := entry
count := count+1
pause := time + 60000
p = close+close*(tp/100)
strategy.entry("Buy", 1, 1, alert_message='Long|e=binancefuturestestnet s=btcusdt b=long q=0.0011 t=market')
if filledorder and size >= 1
fill := entry
count := count+1
pause := time + 60000
strategy.entry("Buy", 1, 1, alert_message='Long|e=binancefuturestestnet s=btcusdt b=long q=0.0011 t=market')
// if cancelorder and not filledorder
// pause := time + 60000
// strategy.order("Cancel", 1, 0.0001, alert_message='Cancel Order|e=binancefuturestestnet s=btcusdt b=long c=order')
if filledorder
last_profit := profit
closeit = crossover(high, profit) and size >= 1
if closeit
strategy.entry("Close ALL", 0, 0, alert_message='Close Long|e=binancefuturestestnet s=btcusdt b=long c=position t=market')
count := 0
fill := 0.0
last_profit := 0.0
//Plots
// bottom = signal ? color.green : filled ? color.red : color.white
// plot(entry, "Entry", bottom)