Trend-Following Strategies in Stocks
A trend-following strategy for stocks attempts to capture sustained price movements by entering positions when assets exhibit strong momentum and exiting when trends weaken. Trend-following methods have been widely used across asset classes for decades.
This paper revisits the classic study by Wilcox and Crittenden (2005) and examines whether trend-following strategies still work in stock markets.
Dataset and Research Methodology
To evaluate the effectiveness of trend-following on stocks, we analyze a survivorship-bias-free dataset covering all liquid U.S. stocks from 1950 through November 2024.
Across this dataset we simulate more than 66,000 long-only trend trades, providing a large sample for assessing the long-term statistical behavior of trend-following systems.
Profit Distribution in Trend-Following Trades
Our analysis confirms that trend-following profits are highly skewed. Less than 7% of trades generate the majority of cumulative profits, while most trades produce small gains or losses.
Importantly, these statistical properties remain stable in an out-of-sample period from 2005 to 2024, suggesting that trend-following dynamics continue to persist in equity markets.
Trend-Following Portfolio Strategy
In the second part of the paper, we construct a long-only trend-following portfolio designed to capture large outlier moves in individual stocks.
The theoretical portfolio demonstrates strong gross-of-fees performance from 1991 through 2024, including:
• 15.19% compound annual growth rate (CAGR)
• 6.18% annualized alpha
These results highlight the potential effectiveness of trend-following when applied to diversified stock portfolios.
Impact of Transaction Costs
Despite strong theoretical performance, transaction costs pose a major challenge for high-turnover strategies.
Our analysis shows that the base trend-following strategy becomes difficult to implement for portfolios with assets under management below $1 million, as trading costs significantly reduce net returns.
Turnover Control Algorithm
To address this issue, we introduce a Turnover Control algorithm designed to reduce unnecessary trading activity.
This approach significantly lowers transaction costs while maintaining exposure to the strongest trends in the market. As a result, the strategy becomes viable across a wide range of portfolio sizes, even after accounting for realistic fees.
Key Takeaways
- Trend-following strategies still work on stocks, with strong long-term statistical evidence.
- A small percentage of trades generates the majority of profits.
- Transaction costs significantly affect high-turnover trend strategies.
- A Turnover Control algorithm can improve the strategy’s viability across different portfolio sizes.