SMA and ATR Based Trend Tracking Strategy

The strategy is named SMA and ATR Based Trend Tracking Strategy . This strategy uses the SMA indicator to determine the price trend direction and sets stop loss positions with the ATR indicator to track the trend. It…

Pine ScriptTrend following Breakout SMA ATR

Author: ChaoZhang
Complexity: Starter · 83 lines
Parameters: 3
Backtest bar: 1m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

I. Strategy Name

The strategy is named SMA and ATR Based Trend Tracking Strategy.

II. Strategy Overview

This strategy uses the SMA indicator to determine the price trend direction and sets stop loss positions with the ATR indicator to track the trend. It goes short when the price breaks down an uptrend and goes long when the price breaks through a downtrend to implement trend trading.

III. Strategy Principle

1. Entry Signals

(1) Go long when the close price rises and is higher than SMA.
(2) Go short when the close price falls and is lower than SMA.

2. Stop Loss Setting

Use the ATR indicator's value multiplied by the set stop loss multiple as the stop loss position.

3. Stop Loss Updating

After each bar's close, check the stop loss position and update it to a stop loss value closer to the current price.

4. Exit Signals

Actively stop loss when price touches stop loss line.

IV. Advantages of Strategy

1. Strong Trend Tracking Ability

The dynamic stop loss setting of the ATR indicator enables automatic tracking of trends.

2. Good Drawdown Control

Strict stop loss rules help control maximum drawdown per trade.

3. Simple Parameter Setting

Only 3 parameters make adjustment and optimization easy.

V. Risks of Strategy

1. Risk of Stop Loss being too Loose

If the stop loss multiple is set too high, the stop loss position may be too loose, thus increasing drawdown.

2. Risks of False Breakout

Price false breakouts may lead to missing the trend direction. Other indicators should be used to filter signals.

3. Risks of Parameter Optimization

Excessive reliance on parameter optimization may lead to curve fitting. The stability of parameters should be carefully evaluated.

VI. Strategy Optimization Directions

1. Optimizing Stop Loss Algorithm

Other types of stop loss algorithms can be tested, such as moving stop loss, proportional stop loss, etc.

2. Adding Filter Signals

Other indicators can be added to filter false breakouts. For example, adding trading volume conditions.

3. Evaluating Stability of Parameters

Back-testing history to evaluate parameters' adaptability to different products and timeframes.

VII. Summary

The overall idea of this strategy is clear. It judges trend direction through SMA and uses ATR to track trends with good drawdown control. It is suitable for medium-long term trend trading. But parameters still need proper adjustment in live trading, and risks of over-optimization should be prevented.

Parameters

Name	Default	What it controls
v_input_int_1	100	SMA Length
v_input_int_2	10	ATR Length
v_input_float_1	4	Stop Offset Multiple

Source Pine Script

/*backtest
start: 2024-01-16 00:00:00
end: 2024-01-16 17:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © omererkan

//@version=5
strategy(title="SMA with ATR", overlay=true)

smaLen = input.int(100, title="SMA Length")

atrLen     = input.int(10, title="ATR Length")
stopOffset = input.float(4, title="Stop Offset Multiple", step=0.25)


smaValue  = ta.sma(close, smaLen)
stopValue = ta.atr(atrLen) * stopOffset


lowerCloses = close < close[1] and 
     close[1] < close[2] and
     close[2] < close[3]

enterLong = close > smaValue and 
     lowerCloses


longStop = 0.0
longStop := if enterLong and strategy.position_size < 1
    close - stopValue
else
    math.max(close - stopValue, longStop[1])


higherCloses = close > close[1] and 
     close[1] > close[2] and
     close[2] > close[3]

enterShort = close < smaValue and 
     higherCloses


shortStop = 0.0
shortStop := if enterShort and strategy.position_size > -1
    close + stopValue
else
    math.min(close + stopValue, shortStop[1])


plot(smaValue, color=#4169e1, linewidth=2, title="SMA")

plot(strategy.position_size > 0 ? longStop : na, color=color.lime,
     style=plot.style_linebr, title="Long stop", linewidth=2)

plot(strategy.position_size < 0 ? shortStop : na, color=color.red,
     style=plot.style_linebr, title="Short stop", linewidth=2)


if enterLong
    strategy.entry("EL", strategy.long)

if enterShort
    strategy.entry("ES", strategy.short)


if strategy.position_size > 0
    strategy.exit("SL Long", from_entry="EL", stop=longStop)

if strategy.position_size < 0
    strategy.exit("SL Short", from_entry="ES", stop=shortStop)


if enterLong
    strategy.cancel("Exit Short")

if enterShort
    strategy.cancel("Exit Long")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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