First, I want to highlight that this study aims to present a momentum/trend-following strategy that has consistently outperformed the S&P 500 index. The results are as follows:

However, to understand the nature and merits of this strategy, it is worth learning a bit about the Turtle Trend's history.

Inspiration

The original Turtle Trend strategy gained popularity after Dennis and Eckhardt conducted an experiment in which they quickly taught a group of people, later called "Turtles," how to trade according to their system.

Basic rules of the Turtle Trend strategy:

Turtle Trend uses the highest and lowest prices from a given period in the past, also known as Donchian channels.

In the standard Turtle Trend strategies, 2 types are used:

Strategy 1: breakout of the 20-day Donchian for entry and 10-day for exit;

Strategy 2: breakout of the 55-day Donchian for entry and 20-day for exit.

The Turtle Trend is based on the principle of entering a position when the price crosses the upper or lower range of the Donchian channel. If the price crosses the upper range, a signal is given to open a long position. If the price crosses the lower range, a signal is given to close that position or open a short position.

For stocks that naturally have an upward drift, we focus on long positions.

Before discussing whether and how this strategy can be applied to stocks, we will conduct some tests to show how default values perform in a reversal stock market.

To demonstrate the specificity of applying this strategy, I executed two buying strategies for the SPY ETF at market close according to the original rules:

Strategy 1 opens a position if the closing price is above the maximum High of the last 20 days, and closes the position if the Close is below the lowest Low of the last 10 days.

The strategy only started to work in a way that we could consider acceptable after 2008, but when compared to the benchmark, the strategy performs very poorly.

The situation looks even worse if we apply Strategy 2, where the Donchian setting is 55 for entry vs. 20 for exit.

The above results, unfortunately are not improved at all by using other instruments represented by ETFs such as QQQ or IWM, as well as using a wide range of stocks.

Should we then consider that these kinds of trend-following strategies this type are not worth our attention in the stock market?

I believe they are definitely worth considering, mainly because it is a type of strategy that works in the different mechanics from the dominant reversal strategies here.

A balanced portfolio of strategies should, in my opinion, be based on a mix of different types of strategies, so trend/breakout strategies are very desirable in such a mix, even if they are not our best strategies.

Below, I present the Turtle Trend Titan strategy based on the Turtle Trend philosophy and Donchian Channels, which I have adapted to the specifics of the stock market.

Key components

• Detecting breakouts from large consolidations or trend reversals.

• Donchian Channel is used for entry and exit signals.

• Additional filters exclude trading in unfavorable market conditions for the strategy.

• Stockpicker mechanism, which searches for and automatically selects stocks that meet the criteria.

Backtest 1 - $ Money Management

In this variant, we invest a constant amount of $100k, which is divided by the maximum number of open positions.

We are testing a period of 31 years  from 1995 to 2025

The backtest automatically selects stocks that meet the criteria from the S&P 500 index. Note that the list of stocks included in the index changed across years, which is accounted for in the Stockpicker data (survivorship bias).

Invested capital:  $100k

Tested period in years: 31

Tested years: 1995–2025

Tested index: S&P 500

Equity chart for this test:

Basic statistics and results:

 In the table, we highlighted the moment when the strategy was published.

Summary of statistics - all data according to the position closing date.

Click the button to see the latest backtest:

Backtest 2 - % Money Management

In this backtest, we are investing in a strategy that allocates 100% of the current capital (starting with $100k). This means that as the capital grows or decreases, the position value changes proportionally. The rest of the parameters remain unchanged.

The Equity Chart for this test looks as follows:

Basic statistics resulting from the test:

Trading Strategy Analysis

Net profit and CAGR

In this backtest, the strategy achieved a net profit of $2,780,938 with a compound annual growth rate (CAGR) of 11.45%. Over the same period, the benchmark (S&P 500 via SPY) reached a net profit of $2,443,284 with a CAGR of 11.0%. This means the strategy delivers a very similar long-term return rate to the index while maintaining its character as a trend-following approach rather than aiming to dramatically outperform the benchmark in absolute profit.

Drawdown and Return/Drawdown ratio

The maximum open drawdown of the analyzed strategy was 36.89% compared to 55.19% for the benchmark. This translates into a clearly better Return/Open Drawdown ratio of about 21.89 versus 5.77 for the index, highlighting a much more favorable trade-off between risk and long-term return than a simple buy-and-hold of the S&P 500.

Exposure

Over the 31‑year test, the benchmark ETF maintains 100% exposure to the S&P 500, while the strategy is in the market on average with around 80% exposure. This lower equity exposure allows part of the capital to be allocated to other, uncorrelated strategies, and yet, when we adjust the results for time spent in the market, the strategy achieves a higher exposure‑adjusted return of 14.31% versus 11.0%  for the benchmark, meaning each percent of exposure is used more efficiently.

Winning percent

The winning percentage in the analyzed strategy was 46.6%. This means that less than half of the trades were profitable, which is typical for trend-following and momentum strategies. The strategy remains profitable because the average winning trade was about 2.62 times the average losing trade, so a handful of long trends more than compensates for a series of smaller losses.

SL & TP

The strategy doesn't use a typical stop-loss; instead, it relies on an exit condition. But you can add an SL if it makes you more comfortable. Instead, diversifying positions within a single strategy and across the whole portfolio helps protect against the significant impact of a potential price change in one stock on the entire portfolio. Visit the stop loss order page.

Market regime

The strategy was tested in all basic market regimes and includes filters implemented based on this.

Read more about market regimes.

Trading costs

Trading costs and slippage were accounted for in the backtests. You can check our latest research on trading costs using the Alpaca Broker here. With a diversified portfolio of stocks and strategies, transaction costs can determine your profit or loss, so take the time to thoroughly test and choose a broker.

Robustness

The robustness of the strategy was tested on a large number of stock trades over the full test period, with up to 40 simultaneously open positions.

On the Nasdaq 100, we tested 1,672 trades, while on the Russell 1000 we ran 2,266 trades , both using percentage capital management MM%.

The results are as follows:

This strategy also passed our parameter modification tests.

System Parameter Permutation, i.e., varying key strategy parameters by 20% up and 20% down. The results are as follows:

We adhere to the principle that the fewer parameters, the more robust the strategy. Therefore, we make an effort for our strategies to have as few parameters as possible and to only select parameters that have a significant impact on strategy effectiveness while also aligning with its nature.

Recommended Instruments

The recommended primary instrument for this strategy in Algocloud Stockpicker is the S&P500 index, which has shown the best historical results. However, the strategy also yields stable results with Nasdaq 100 stocks.

Correlation

To check the strategy's correlation with others, visit the correlations.

The strategy shows an inverse correlation to reversal strategies in terms of closed positions. This means that if the market sharply declines, reversal strategies can incur losses, while Turtle Trend Titan collects long-accumulated profits from its positions, offsetting those losses. The reverse situation occurs at the beginning after implementation, where some quick losses generated by TTT may be present but are balanced by the profits of reversal strategies. This is the synergy resulting from the strategy portfolio.

Summary & Strengths and Weaknesses

Strengths of the strategy:

• Inverse Correlation to Reversal Strategies

The strategy shows an inverse correlation to reversal strategies, which is an important advantage.

• Profit and Ret/DD Stability

 In the analyzed strategy, net profit reached about $2.78M with a CAGR of around 11.45%, while the benchmark (SPY) achieved roughly 11.0% CAGR over the same period. The main edge of the strategy is not an explosive outperformance in absolute profit, but a more favorable combination of long-term return and drawdown compared with a simple buy-and-hold of the index.

The maximum open drawdown of the strategy was about 36.89% versus 55.19% for the benchmark. This resulted in a Return/Open Drawdown ratio of roughly 21.89 compared to 5.77  for the index, meaning that for each unit of risk taken, the strategy historically generated a much higher return than pure buy-and-hold.

• Strategy Robustness

The strategy was tested on several stock universes (S&P 500, Nasdaq 100, Russell 1000), with a total of several thousand trades. Also, parameter permutation (SPP) yields stable results, indicating the strategy's robustness.

Weaknesses of the strategy:

• Capital Engagement

The strategy involves relatively high capital engagement.

• Low Winning Percent

 A further weakness is the relatively low win rate of about 46.6%. This is typical of trend-following strategies and is compensated by the payoff profile: the average winning trade has historically been about 2.62 times larger than the average losing trade, so a small number of large trends can offset many smaller losses.

Summary

In our opinion, this is not a strategy designed to "pull" all the results of a stock trading portfolio. In our experience, the biggest profits come from reversal strategies. However, strategies like the Turtle Trend Titan have a very important characteristic, namely, a low correlation to reversal strategies. During strong upward impulses, when most reversals have already taken profits, these strategies provide satisfaction from "catching" the trend and pushing the result higher. Similar behavior of collecting profits at the end of trends balances any potential losses during the time of reversal strategies.

What you get in the package for this strategy:

• An eBook describing detailed rules and results of the strategy

• The SQX file is ready to use on the Algocloud and StrategyQuant platforms.

• Pseudocode that describes all the rules in an easy-to-understand way.