SuperTrend Strategy for Ethereum Trading

This strategy is based on the SuperTrend indicator and uses ATR to dynamically set stop loss lines to profit from strong trends in Ethereum. It can run on the ETH/USD trading pair on Coinbase exchange.

Pine ScriptTrend following Mean reversion Volatility ATR Supertrend

Author: ChaoZhang
Complexity: Intermediate · 64 lines
Parameters: 7
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy uses a classic trend-following indicator - SuperTrend indicator to determine the trend direction. The SuperTrend indicator consists of two lines:

Uptrend stop loss line to hold long positions in uptrends;
Downtrend stop loss line to hold short positions in downtrends.

When price turns from uptrend to downtrend, open short position. When price turns from downtrend to uptrend, open long position.

In addition, the strategy utilizes the ATR indicator to dynamically adjust the stop loss line. Specifically, the uptrend stop loss line position is the average of highest high and lowest low minus ATR multiplied by a coefficient; the downtrend stop loss line position is the average of highest high and lowest low plus ATR multiplied by a coefficient. This allows adjusting the stop loss based on market volatility.

After entry signals are triggered, if price breaks back above the stop loss line, stop out with loss.

Advantages

This is a relatively mature trend following strategy with the following advantages:

Use SuperTrend indicator to determine trend direction reliably;
Apply adaptive ATR stop loss to effectively control risks;
Simple and clear strategy logic, easy to understand and modify;
Profitable in the high volatility cryptocurrency market.

Risks

There are also some risks with this strategy:

Probability of SuperTrend indicator judging wrongly exists, may cause unnecessary losses;
ATR stop loss may be too aggressive, stopped out by price reversals;
High volatility in crypto markets increases probability of stop loss being hit;
Higher transaction fees on some exchanges impacts final profitability.

To mitigate the above risks, ATR coefficient can be adjusted, or add filters with other indicators. Stop loss buffer can also be considered.

Improvement Directions

There is room for further improvements:

Introduce more indicators to improve signal accuracy;
Research optimal values for ATR length and coefficient;
Implement dynamic position sizing based on risk-reward ratio;
Test strategy effectiveness across more crypto trading pairs.

Conclusion

Overall this is a mature and reliable trend following strategy. It uses SuperTrend indicator to determine trend direction and adapts stop loss with ATR to control risks while profiting. The strategy works well for high volatility cryptocurrencies like Ethereum. Further optimizations can expand its application across more markets for steady outperformance.

Parameters

Name	Default	What it controls
v_input_1	21	ATR Period
v_input_2	6.2	ATR Multiplier
v_input_3	false	Take Wicks into Account ?
v_input_4	false	Start from Specific Date ?
v_input_5	2019	Start Year
v_input_6	true	Start Month
v_input_7	true	Start Day

Source Pine Script

/*backtest
start: 2023-01-01 00:00:00
end: 2024-01-07 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4 
strategy("SuperTrend Strategy", 
     overlay=true, 
     initial_capital=2e3, 
     process_orders_on_close=true, 
     commission_type=strategy.commission.percent, 
     commission_value=0.1 
     ) 
  
length = input(title="ATR Period", type=input.integer, defval=21) 
mult = input(title="ATR Multiplier", type=input.float, step=.25, defval=6.2) 
wicks = input(title="Take Wicks into Account ?", type=input.bool, defval=false) 
  
useDate = input(title="Start from Specific Date ?", defval=false) 
yearStart = input(title="Start Year", defval=2019) 
monthStart = input(title="Start Month", minval=1, maxval=12, defval=1) 
dayStart = input(title="Start Day", minval=1, maxval=31, defval=1) 
  
startTime = timestamp(yearStart, monthStart, dayStart, 0, 0) 
startFrom = useDate ? time(timeframe.period) >= startTime : true 
  
atr = mult * ta.atr(length) 
  
longStop = hl2 - atr 
longStopPrev = nz(longStop[1], longStop) 
longStop := (wicks ? low[1] : close[1]) > longStopPrev ? math.max(longStop, longStopPrev) : longStop 
  
shortStop = hl2 + atr 
shortStopPrev = nz(shortStop[1], shortStop) 
shortStop := (wicks ? high[1] : close[1]) < shortStopPrev ? math.min(shortStop, shortStopPrev) : shortStop 
  
dir = 1 
dir := nz(dir[1], dir) 
dir := dir == -1 and (wicks ? high : close) > shortStopPrev ? 1 : dir == 1 and (wicks ? low : close) < longStopPrev ? -1 : dir 
  
longColor = color.green 
shortColor = color.red 
  
plot(dir == 1 ? longStop : na, title="Long Stop", style=plot.style_linebr, linewidth=2, color=longColor) 
plotshape(dir == 1 and dir[1] == -1 ? longStop : na, title="Long Start", location=location.absolute, style=shape.circle, size=size.tiny, color=longColor, transp=0) 
  
plot(dir == 1 ? na : shortStop, title="Short Stop", style=plot.style_linebr, linewidth=2, color=shortColor) 
plotshape(dir == -1 and dir[1] == 1 ? shortStop : na, title="Short Start", location=location.absolute, style=shape.circle, size=size.tiny, color=shortColor, transp=0) 
  
longCondition = dir[1] == -1 and dir == 1 
if longCondition and startFrom 
    strategy.entry("Long", strategy.long, stop=longStop) 
else 
    strategy.cancel("Long") 
  
shortCondition = dir[1] == 1 and dir == -1 
if shortCondition and startFrom 
    strategy.entry("Short", strategy.short, stop=shortStop) 
else 
    strategy.cancel("Short")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-08. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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