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 history of the Turtle Trend.

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 price 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 this kind trend-following strategies of 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 to 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 used for entry and exit signals.

• Additional filters excluding 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 the period of the last 30 years from 1994-02.2025.

The backtest automatically selects stocks that meet the criteria from the S&P 500 index. Remember that the list of stocks included in the index changed in different years, which is taken into account in the Stockpicker data (survivorship bias).

Invested capital: $100k

Tested period in years: 30

Tested years: 1994-02.2025

Tested Index: S&P500

Equity chart for this test:

Basic statistics and results:

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

Backtest 2, % Money Management

In this backtest, we are investing in a strategy that constantly uses 100% of the current capital (starting with $100k capital). 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

Net profit above $ 4 million is 2x higher than the Benchmark (S&P 500 Index in the form of SPY ETF marked in yellow on the chart), which is $ 2 million, translating to a CAGR of 12.8% vs 10.6%. This means that the analyzed strategy achieves a higher net profit and a higher average annual return rate, indicating its good efficiency in generating profits over the long term.

Drawdown and Return/Drawdown ratio

The maximum open drawdown in the analyzed strategy was -34.4% vs -55.19% in the benchmark, resulting in a significantly better Return/Open Drawdown Ratio of 10.74 vs 4.41.

Exposure

The average exposure in the analyzed strategy was 69% vs 100% in the benchmark. The study was conducted on the underlying instrument, which are S&P 500 index stocks. Exposure is measured by a dedicated study, which you can read about here.

The analyzed strategy used less capital on average, making it less exposed to market risks, and the free capital can be used in other strategies.

Winning percent

The winning percentage in the analyzed strategy was 46.0%. This means that less than half of the transactions were profitable, which is typical for trend-following strategies. The strategy makes money because the average win is 2.4 times larger than the average loss.

SL & TP

The strategy doesn't use a typical stop-loss and 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 taken into account in the backtests. You can check our last research about trading costs using 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 was tested by conducting a large number of stock transactions for the period from 1994-02.2025 for the Nasdaq 100 (max open positions 50) 1'245 transactions and Russell 1000 (max open positions 100) 5'597 transactions indexes with %MM.

Nasdaq 100 max transactions: 1'245

Russell 1000 max transactions: 5'597

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.

Primary Instrument: S&P500

Supplementary Instrument: Nasdaq 100

Pattern Day Trader

Statistically, the strategy did not close any trades on the same day, so it does not meet the Pattern Day Trader (PDT) criteria. This means it can also operate successfully on accounts below $25k.

Correlation

To check the correlation of the strategy with others, visit the correlations page.

The strategy shows an inverse correlation to reversal strategies, which is a significant advantage. This means that if the market sharply declines after an uptrend, reversal strategies incur losses while Turtle Trend

Titan collects long-accumulated profits from its positions, offsetting the losses of the former. 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 of the strategy

Strengths of the strategy:

• Inverse Correlation to Reversal Strategies

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

• Profit and Ret/DD Stability

In the analyzed strategy, Net Profit was $4 million, while the Benchmark achieved $2 million. The CAGR was 12.8%, higher than the Benchmark's 10.6%, but the maximum open drawdown in the analyzed strategy was almost half of the Benchmark's, resulting in a significantly better Return/Drawdown ratio of 10.74 vs. 4.41.

• Strategy Robustness

The strategy was tested on the S&P 500, Nasdaq 100, and Russell 1000 indices, with over 8,000 trades. Also, parameters permutation (SPP) indicates stable results, which testify to the strategy's robustness.

Weaknesses of the strategy:

• Capital Engagement

The strategy involves relatively high capital engagement.

• Low Winning Percent

A weak aspect of the strategy is its relatively lower win-rate of 47%, which is normal for trend-following/momentum strategies. This is compensated by the average win to average loss ratio, where the average winning position is 2.4 times larger than the average losing position.

Summary

In our opinion this is not a strategy designed to "pull" all the results of a stock trading portfolio. The biggest profits come from reversal strategies in our experience. 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:

• Ebook describing detailed rules and results of the strategy

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

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