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Strategy vault / Trend following

Supertrend Tracking Strategy

This strategy is named "Supertrend Tracking Strategy". It develops an automated trading system for both long and short positions based on the Supertrend indicator, which can automatically identify the trend direction…

Pine ScriptTrend followingBreakoutMean reversionRSIBollinger BandsATRSupertrendADX / DMI
Author
ChaoZhang
Complexity
Starter · 44 lines
Parameters
4
Backtest bar
1d · swing
Tested on
BTC/USDT · futures
Jump to codeView in vaultOriginal on FMZ

IMG

Overview

This strategy is named "Supertrend Tracking Strategy". It develops an automated trading system for both long and short positions based on the Supertrend indicator, which can automatically identify the trend direction and make entries and exits combined with the RSI and ADX indicators.

Principles

The core of this strategy is using the Supertrend indicator to determine the current price trend. The Supertrend combines moving averages and ATR, which is effective in judging the direction of price trends. When the direction of the Supertrend makes a reversal, it signals that the price trend is changing.

Specifically, this strategy first calculates the Supertrend direction, RSI and ADX. When the Supertrend turns down, and the RSI shows that the uptrend is fading, it makes short entry. When the Supertrend turns up again, it closes the short position.

Advantages

The biggest advantage of this strategy is that it can automatically identify price trends and make entries and exits based on the trends, without manual judgment. In addition, using RSI and ADX as filters can effectively avoid false breakouts and improve profitability.

Risks

The biggest risk is that the Supertrend itself is not highly accurate in judging price trends, which may generate incorrect signals. Also, no stop loss is set, so the loss per trade can be significant.

Optimization can be made by adjusting Supertrend parameters and adding trailing stop loss to reduce risks.

Optimization

Several aspects of this strategy can be optimized:

  1. Optimize Supertrend parameters to improve accuracy

  2. Add trailing stop loss to control per trade loss

  3. Add more filters like Bollinger Bands, KDJ to improve profitability

  4. Develop similar long entry and exit rules to make the strategy complete

Conclusion

In conclusion, this is an automated trading strategy that judges trends based on the Supertrend. The advantage is high degree of automatization and auto trend detection. The disadvantage is the low accuracy of Supertrend itself and no stop loss. Parameter tuning, adding filters, and stop loss can enhance profitability and risk control.

Parameters

NameDefaultWhat it controls
v_input_110ATR Length
v_input_float_13Factor
v_input_27ADX Smoothing
v_input_37DI Length

Source Pine Script

/*backtest
start: 2023-01-16 00:00:00
end: 2024-01-22 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Supertrend Strategy", overlay=true)

atrPeriod = input(10, "ATR Length")
factor = input.float(3.0, "Factor", step = 0.01)

[_, direction] = ta.supertrend(factor, atrPeriod)

adxlen = input(7, title="ADX Smoothing")
dilen = input(7, title="DI Length")
dirmov(len) =>
    up = ta.change(high)
    down = -ta.change(low)
    plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
    minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
    truerange = ta.rma(ta.tr, len)
    plus = fixnan(100 * ta.rma(plusDM, len) / truerange)
    minus = fixnan(100 * ta.rma(minusDM, len) / truerange)
    [plus, minus]

adx(dilen, adxlen) =>
    [plus, minus] = dirmov(dilen)
    sum = plus + minus
    adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), adxlen)
    adx

sig = adx(dilen, adxlen)

if ta.change(direction) < 0 and ta.rsi(close, 21) < 66 and ta.rsi(close, 3) > 80 and ta.rsi(close, 28) > 49 and sig > 20
    strategy.entry("My Long Entry Id", strategy.long)

if ta.change(direction) > 0
    strategy.close("My Long Entry Id")

//plot(strategy.equity, title="equity", color=color.red, linewidth=2, style=plot.style_areabr)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-23. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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