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Strategy vault / Breakout

Turtle Trend Trading System

This strategy is the actual code implementation of the famous Turtle trading system, using a 55-period channel for entry signals and a 20-period channel for exit signals to track longer-term trends, belonging to the…

Author
ChaoZhang
Complexity
Starter · 38 lines
Parameters
2
Backtest bar
1h · intraday
Tested on
BTC/USDT · futures

IMG

Overview

This strategy is the actual code implementation of the famous Turtle trading system, using a 55-period channel for entry signals and a 20-period channel for exit signals to track longer-term trends, belonging to the trend-following strategy type.

Strategy Logic

The strategy is mainly based on two indicators: the 55-period highest price (HI) and lowest price (LO) to construct the entry channel, and the 20-period highest price (hi) and lowest price (lo) to construct the exit channel.

When the price breaks above the 55-period channel, a buy signal is generated; when the price breaks below the 55-period channel, a sell signal is generated. This is the typical trend-following entry logic.

When the price breaks below the 20-period channel, long positions are closed; when the price breaks above the 20-period channel, short positions are closed. This is the exit logic of the strategy.

The strategy also plots the 55-period channel and 20-period channel, which can visually see the entry and exit points of the strategy.

Advantage Analysis

The main advantages of this strategy are:

  1. Tracking mid-to-long-term trends with relatively small drawdowns
  2. Clear entry signals using channel principle and good drawdown control
  3. Strict exit mechanism to avoid losses from reversals
  4. Simple parameter settings, easy to implement

Risk Analysis

There are also some risks with this strategy:

  1. Unable to capture short-term opportunities, relatively weak profitability
  2. Unable to cope with sudden events, prone to stop loss
  3. Cannot effectively control excessive losses in one-way markets
  4. Very sensitive to parameters

The risks can be reduced through:

  1. Parameter optimization to find optimal combinations
  2. Adding stop loss strategies to control one-way market losses
  3. Combining other indicators to identify potential reversal opportunities

Optimization Directions

The strategy can be optimized in several aspects:

  1. Optimize parameters of entry and exit channels to find optimal combination
  2. Add volatility indicators to avoid choppy markets
  3. Combine trading volume indicators to ensure amplified volumes on entry signals
  4. Add moving stop loss strategies to follow dynamic stop loss lines
  5. Combine multiple timeframes for comprehensive multi-timeframe trading

Conclusion

In summary, this is a very typical trend-following strategy, using channels to capture mid-to-long term trends with good drawdown control. It also has some typical issues of trend-following strategies, like insufficient trend capturing ability and difficulty dealing with reversals. With comprehensive optimizations, the advantages can be fully realized to become a reliable quantitative strategy.

Parameters

NameDefaultWhat it controls
v_input_155Entry Length
v_input_220Exit Length

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"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © racer8
//@version=4
strategy("Turtle System", overlay=true)

n = input(55,"Entry Length")
e = input(20,"Exit Length")

HI = highest(n)
LO = lowest(n)
hi = highest(e)
lo = lowest(e)

if close>HI[1]
    strategy.entry("Buy", strategy.long)

if close<LO[1]
    strategy.entry("Sell", strategy.short)
    
if low<lo[1]
    strategy.close("Buy")

if high>hi[1]
    strategy.close("Sell")

plot(HI,color=color.lime)
plot(LO,color=color.red)
plot(hi,color=color.blue)
plot(lo,color=color.maroon)

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/Turtle-Trend-Trading-System.md
  1. npx agenkit install engineering-kit in your project
  2. Paste the command into your agent and approve each phase
  3. Get tests, backtest, risk controls and a paper-trading switch

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.

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