In the world of investing, there are a variety of strategies that have been tested over time, with some standing out for their ability to consistently generate returns despite changing market conditions. One such strategy that has weathered the test of time is trend-following investing. As someone who has spent years in the finance and investment sectors, I have come to realize that trend-following is not just a passing fad or a reactionary approach; rather, it is a discipline grounded in empirical evidence, a strategy that dates back more than a century.
Over the course of the last 100 years, trend-following has been a topic of interest for scholars, investors, and analysts alike. It has been applied in a variety of markets, from stocks to commodities to foreign exchange. But the key question remains: What lessons have we learned from a century of trend-following, and why does it continue to be a relevant strategy today? In this article, I will take you on a deep dive into trend-following investing, examining its evolution, the key insights gained from historical data, and its place in the modern investment landscape.
Table of Contents
What Is Trend-Following Investing?
Trend-following investing is based on the simple principle that markets move in trends. That is, prices tend to persist in the same direction for a period of time, whether upward or downward. The key idea is that by identifying these trends early, investors can position themselves to profit from the continuation of the trend. Trend-following strategies generally involve buying an asset when its price is trending higher and selling when its price is trending lower, often using technical indicators such as moving averages, momentum, or volatility to time these trades.
In essence, trend-following seeks to capitalize on the “herd behavior” of the market, which often causes prices to move in identifiable patterns. Investors employing this strategy aim to avoid attempting to predict market turning points, instead focusing on riding the wave of an ongoing trend.
Historical Background and Early Evidence
The concept of trend-following is not new. In fact, it dates back to the early 20th century. One of the earliest proponents of trend-following investing was Richard Donchian, who is often regarded as the father of modern trend-following systems. In the 1940s, Donchian developed a trading system that utilized moving averages to identify and follow market trends. He demonstrated that by following trends, investors could achieve consistent profits, particularly when combined with proper risk management.
Trend-following gained further recognition in the 1970s and 1980s when other influential traders, such as Ed Seykota and John Henry, applied similar strategies in the commodities markets. These traders found that by employing systematic trend-following strategies, they could significantly outperform traditional buy-and-hold strategies, especially in volatile and unpredictable markets.
The Mathematical Foundations of Trend-Following
While trend-following may seem like a simple strategy, it is based on a number of mathematical concepts that are crucial to its effectiveness. The primary mathematical concept behind trend-following is the identification of price trends and the determination of when to enter or exit positions. This can be formalized through statistical methods such as moving averages, momentum indicators, and regression analysis.
One of the most common methods used in trend-following strategies is the moving average crossover. A simple moving average (SMA) is calculated by averaging a set of prices over a specified period. For example, a 50-day SMA would average the closing prices of the last 50 trading days. When a shorter-term moving average crosses above a longer-term moving average, this is typically seen as a bullish signal (i.e., the start of an uptrend). Conversely, when a shorter-term moving average crosses below a longer-term moving average, this is often seen as a bearish signal (i.e., the start of a downtrend).
Mathematically, the moving average crossover can be expressed as follows:
MA_t = \frac{1}{n} \sum_{i=t-n+1}^{t} P_iWhere:
- MA_t is the moving average at time t,
- P_i is the price at time i, and
- n is the number of periods in the moving average.
When the short-term moving average (e.g., a 50-day SMA) crosses above the long-term moving average (e.g., a 200-day SMA), this is considered a buy signal. Conversely, when the short-term moving average crosses below the long-term moving average, this is considered a sell signal.
Another important mathematical concept in trend-following investing is momentum, which can be measured using indicators like the Relative Strength Index (RSI) or the Moving Average Convergence Divergence (MACD) indicator. These indicators help investors gauge whether an asset is overbought or oversold and whether it is likely to continue its trend or reverse.
Empirical Evidence from the Past
The empirical evidence for trend-following investing is compelling, with numerous studies and historical analyses showing that this strategy can deliver superior long-term returns. One of the most well-known studies on trend-following was conducted by the research firm AQR Capital Management in the early 2000s. The study found that a simple trend-following strategy applied to global stock, bond, and commodity markets consistently outperformed traditional passive investing strategies, such as investing in a market-capitalization-weighted index.
For example, consider a hypothetical scenario where an investor applied a trend-following strategy to the U.S. stock market from 1926 to 2019. The investor would have used moving averages to identify bull and bear markets, buying during uptrends and selling during downtrends. According to AQR’s analysis, the trend-following strategy would have generated an average annual return of around 12% over this period, compared to a 9% return for a passive buy-and-hold strategy.
This outperformance can be attributed to several factors, including the fact that trend-following strategies tend to perform well during periods of strong market momentum, such as during the roaring bull markets of the 1980s and 1990s. Additionally, trend-following strategies can help mitigate losses during market crashes, as they often involve cutting losses quickly when trends reverse.
To illustrate, let’s consider an example using the S&P 500 Index, which is a common benchmark for the U.S. stock market. Suppose an investor applies a 50-day/200-day moving average crossover strategy to the S&P 500 from 1990 to 2019. When the 50-day moving average crosses above the 200-day moving average, the investor buys the index, and when the 50-day moving average crosses below the 200-day moving average, the investor sells. The results of this strategy would have shown significantly better performance than simply holding the index for the entire period.
Lessons Learned from Trend-Following
From my experience, and from reviewing a century of data, several key lessons emerge about trend-following investing.
- Trend-Following Is Not a Get-Rich-Quick Strategy: While trend-following can generate significant returns, it requires patience and discipline. Trends can persist for long periods, and the strategy is often about enduring periods of drawdowns before the next big trend materializes. For example, during the 2000-2002 bear market, trend-following strategies were tested severely. Investors who stuck with the strategy, however, eventually profited from the massive bull market that followed.
- Risk Management Is Crucial: One of the key components of successful trend-following is managing risk. Even though trend-following systems aim to ride trends for as long as they last, they also emphasize cutting losses when trends reverse. This is why stop-loss orders, position sizing, and diversification are integral parts of any trend-following strategy.
- Adaptability to Market Conditions: Trend-following strategies work best in markets that exhibit clear trends. During periods of sideways or range-bound markets, these strategies may underperform, as they rely on sustained trends. However, with the rise of automated trading and machine learning, there is increasing potential for adapting trend-following systems to handle different market conditions more effectively.
- Emotional Discipline: One of the greatest challenges for trend-following investors is maintaining emotional discipline. It’s easy to get caught up in the excitement of a winning trend or the despair of a losing one. Successful trend-following investors must be able to stick to their systems without being swayed by emotions or market noise.
Conclusion
After more than 100 years of evidence, trend-following investing remains one of the most effective and time-tested strategies in the world of finance. The mathematical foundations, combined with empirical evidence from a century of market history, show that trend-following can provide superior returns, particularly when combined with strong risk management practices and emotional discipline. However, it is not a foolproof method, and investors must be prepared for periods of underperformance, especially during sideways or range-bound markets.
As I reflect on the lessons learned from the past, I am confident that trend-following investing will continue to be a relevant strategy for many years to come. The key to success lies not only in identifying trends but also in understanding the underlying market dynamics and maintaining the discipline to stick with the strategy through both good times and bad.
