Dual Tracking Turtle Trading Strategy

This strategy utilizes two tracking stop loss points based on the turtle trading rules to limit losses, while setting different parameters to filter out market noise and enter on more pronounced trends.

Pine ScriptBreakout Trend following

Author: ChaoZhang
Complexity: Intermediate · 90 lines
Parameters: 6
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy primarily relies on two tracking stop loss points, long_1 and long_2, to determine entry signals. Long_1 tracks the longer term trend while long_2 tracks the shorter term. Profit1 and profit2 act as the stop loss points.

If price is above long_1, the market is in a longer term uptrend. If price then drops below long_2, it indicates a short term pullback providing good entry opportunity to go long. If price is below long_1, there is no confirmed longer term trend. But if price then surpasses long_2, it signals a short term bounce and can also take long position.

After entering, two tracking stop losses stoploss1 and stoploss2 are set and compared with profit1 and profit2 to take the maximum value, in order to lock in profits.

Advantage Analysis

Dual tracking stop loss effectively controls risks and locks in profits
Combining both long term and short term indicators filters out some noise and enters on more pronounced trends
Flexibility to adjust conservatism of strategy by tuning parameters

Risk Analysis

Strategy is conservative and could miss some opportunities
Improper stop loss setting may prematurely exit
Less trades so single losing trade impact could be big

Can make strategy more aggressive by adjusting long and profit parameters for more trades. Also optimize stop loss algorithms for adaptive adjustments.

Optimization Directions

Find optimal parameter combinations for long and profit
Experiment with zigzag or shadow stop losses to reduce unnecessary stops
Add more entry filters to detect stronger established trends
Incorporate volume indicators to catch true breakouts

Summary

This is an overall conservative strategy suited for investors seeking steady growth. By tuning parameters and optimizing stop loss algorithms, aggression can be increased. Adding mechanisms to filter out market noise is also a direction for further optimizations.

Parameters

Name	Default	What it controls
v_input_1	55	entry_1
v_input_2	20	profit_1
v_input_3	20	entry_2
v_input_4	10	profit_2
v_input_5	true	stop_1
v_input_6	2	stop_2

Source Pine Script

/*backtest
start: 2023-11-19 00:00:00
end: 2023-12-19 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("Turtle Project",overlay= true)
//-----------------------------------------------------------
entry_1 =  input(55) 
profit_1 =  input(20)             

long_1 = float(na)                                                             
long_1:= if high[entry_1] >= highest(high,entry_1)                   
    high[entry_1]                                                            
else                                                                              
    long_1[1]                                                                   


profit1 = float(na)                                                            
profit1:= if low[profit_1] <= lowest(low,profit_1)                   
    low[profit_1]                                                            
else                                                                            
    profit1[1]                      
//-----------------------------------------------------------
entry_2 =  input(20) 
profit_2 =  input(10)             

long_2 = float(na)                                                             
long_2:= if high[entry_2] >= highest(high,entry_2)                   
    high[entry_2]                                                            
else                                                                              
    long_2[1]                                                                   


profit2 = float(na)                                                            
profit2:= if low[profit_2] <= lowest(low,profit_2)                   
    low[profit_2]                                                            
else                                                                           
    profit2[1]                      
//------------------------------------------------------------
stoploss_1= lowest(low,1) < long_1 and highest(high,1) > long_1
stoploss_2= lowest(low,1) < long_2 and highest(high,1) > long_2 

stop_1 = input(1)/100
stop_2 = input(2)/100

plotchar(stoploss_1, "high1", "▲",location.top,color=color.red )
plotchar(stoploss_2, "high2", "▲",location.top,color=color.blue)


//------------------------------------------------------------
if strategy.position_size == 0
    if low < long_1
        if high < long_1 
            strategy.entry("longlong_4",strategy.long, stop=long_1)

if strategy.position_size == 0    
    if low > long_1
        if high < long_2 
            strategy.entry("longlong_3",strategy.long, stop=long_2)

stoploss1 = float(na)
stoploss1:= stoploss_1 ? strategy.position_avg_price * (1 - stop_1) : stoploss1[1]
stoploss__1 = max(stoploss1,profit1)

if high > long_1 and strategy.position_size > 0
    strategy.exit("exit_1 ","longlong_4",stop=stoploss__1)

stoploss2 = float(na)
stoploss2:= stoploss_2 ? strategy.position_avg_price * (1 - stop_2) : stoploss2[1]
stoploss__2 = max(stoploss2,profit2)

if high > long_2 and strategy.position_size > 0
    strategy.exit("exit_2 ","longlong_3",stop=stoploss__2)
//--------------------------------------------------------------
plot(long_1,color=color.red ,linewidth=3)
plot(long_2,color=color.blue,linewidth=3)

plot(profit1,color=color.red,   linewidth=1)
plot(profit2,color=color.blue,  linewidth=1)

//plot(stoploss__1,style=plot.style_circles, color=color.yellow) 
//plot(stoploss__2,style=plot.style_circles, color=color.yellow) 

plot(stoploss1,style=plot.style_circles, color=color.blue) 
plot(stoploss2,style=plot.style_circles, color=color.red) 
//--------------------------------------------------------------

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-20. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/Dual-Tracking-Turtle-Trading-Strategy.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.