Trend following is one of the classic investment styles. “Find a trend and follow it” is a common adage passed on throughout the centuries. The concept of trend following is simple. When there is a trend, follow it; when things move against you or if the trend isn’t really there, cut your losses. Despite the simplicity of the concept, the strategy has roused substantial criticism among neoclassical economists. For decades, trend following has been shunned as the black sheep of investment styles. In the classroom, in research, and even in the popular press, many have preached the word of efficient markets, touted the value of the equity premium, and asserted the importance of buying and holding for the long term.

Fig.1 presents the performance for trend following and equity markets. Fig.2 presents the drawdown profile for trend following and equity markets. Over the past two decades, equity markets have experienced rather severe boom and bust cycles. Although trend followers follow trends across markets, the approach is seemingly uncorrelated with this dramatic boom and bust cycle. The drawdown profile for equity markets is akin to a high-speed roller coaster ride. Although there are many benefits to long-term investing, this simple example demonstrates that the ride may be a bumpy one. In comparison, trend followers have a rather persistent drawdown profile. Despite a history of criticism, there is clearly something to following the trend.[1]

Given the rather stable performance of trend following over a turbulent period for equity markets, this gives rise to several questions. What would happen if the trend-following index had the same volatility? Or even more interesting, what would happen if equity markets and trend following were combined 50/50.

Fig.3 plots the cumulative performance for equity markets, trend following at the same volatility, and a 50/50 combination of the two. The combination of trend following and equity markets seems to provide the most stable return series over time. Table 1 lists the performance statistics for equity markets, trend following, and a 50/50 combination of the two. Both equity markets and trend following have similar Sharpe ratios, but an equal combination of the two increases the Sharpe ratio for equity markets by 66%. The maximum drawdown for the combined portfolio reduces the maximum drawdown for equity markets from 51% to 22%. Despite the simplicity of this example, there is clearly something unique and complementary to a trend-following approach that deserves further analysis and inspection.

Modern-day trend-following strategies are about systematically finding trends in market prices, riding them, and getting out before they revert. For this type of momentum strategy, there is both an art and a science to execution. The science of modern systematic trend following is facilitated by computational power and trading automation. Subjective (or discretionary) rules of thumb and heuristics have been replaced by structured systems of trading rules creating autonomous trading systems, the synonymous “black boxes.” A modern systematic trend-following system has become more like a finely tuned and engineered machine. These machines adjust their outputs (trading positions) as a function of price movements (inputs). Each system includes internal components (risk management systems) to regulate stressors and shocks.[2] The design of these systems is structurally simple, efficient and transparent. Simplicity and robustness are essential, as these trading systems manage hundreds to thousands of positions simultaneously.

The art of modern trend following is in signal processing and trading execution. Trend followers use signals to determine when a trend is beginning or ending. These signals must be quantified, processed, and combined with other signals. Creating a connection between the signal processing and the corresponding trading execution for implementation is a skill that requires eloquence, experience, and a fine attention to detail.[3]

As with any comprehensive and arduous endeavour, this book begins with history by taking a philosophical and historical look at the concept of trend following over the centuries. Using a unique dataset dating back roughly 800 years, the performance of trend following can be examined across a wide array of economic environments, documenting low correlation with traditional asset classes, positive skewness, and robust performance during crisis periods.[4]

The performance of trend following has been discussed extensively in the applied and academic literature (see Moskowitz, Ooi, and Pedersen, 2012).[5] Despite this, most of the data series that are examined are typically limited to actual track records over several decades or futures/cash data from the past century. In this article, an 800-year dataset is examined to extend and confirm previous studies.[6] To examine trend following over the long haul, monthly returns of 84 markets in equity, fixed income, foreign exchange, and commodity markets are used as they became available from the 1200s through to 2013.[7] There are several assumptions and approximations that are made to allow for a long-term analysis of trend following. (For simplicity, an outline of assumptions and approximations as well as a list of included markets is not contained here, but is included in the appendix to the book.)

Market behaviour has varied substantially throughout the ages. To correctly construct a representative dataset through history, it is important to be particularly mindful of dramatic economic developments. This means that the dataset should, as closely as possible, represent investment returns that could have actually been investable. For a specific example, from the early seventeenth century to the 1930s, the United Kingdom, the United States, and other major countries were committed to the gold standard. During this period, the price of gold was essentially fixed. As a result, gold must be removed from the sample of investable markets during this particular time period. As a second example, during most of the nineteenth century, capital gains represented an insignificant portion of equity returns. On average, US investors in the nineteenth century received only a 0.7% annualized capital gain, but a 5.8% dividend per annum (see Fig.4). In fact, up to the 1950s, stocks consistently paid a higher dividend yield than corporate bonds.[8] As a consequence, total return indices must be used represent equity market returns over time.

Using return data collected from as far back as 1223, a representative trend-following system can be built for a period spanning roughly 800 years.[9] A representative trend-following system represents the performance of “following the trend” throughout the centuries in whatever markets might be available. Although certain commodity markets, such as rice, date all the way back to around 1000 AD, the analysis begins in 1223, where there are at least a handful of available markets. At any point in time, to calculate whether a trend exists, the portfolio consists only of the markets that have at least a 12-month history.

The trend-following portfolio is assumed to be allowed to go both long and short. Monthly data is used for the analysis. Based on a set of simple liquidity constraints, the portfolio is constructed of available markets. Fig.5 depicts the number of markets in the portfolio over time. The growth of futures markets has facilitated trend followers by making more markets available for trading.

Trend following requires dynamic allocation of capital to both long and short trends across many different assets over time. Fig.6 plots the log scale performance of a trend-following strategy for roughly 800 years. Over the entire historical period from the 1300s to 2013, the representative trend-following system generates an annual return of 13%, with an annualized volatility of 11%. This results in a Sharpe ratio of 1.16.[10]

Many finance experts have argued for the reduction of risks in the long run or that one should just simply buy and hold. Trend-following strategies dynamically adjust positions according to trends, making them the counter to a buy-and-hold, long-only strategy. The difference between these two can give insight into the value added of active management across asset classes. Position sizes for both trend following and a buy-and-hold strategy are rebalanced on a monthly basis to achieve equal risk. In contrast with the buy-and-hold, the trend-following system is free to go short.[11]

For comparison, the buy-and-hold portfolio represents a diversified long-only portfolio consisting of equities, bonds, and commodities.[12] Table 2 displays performance statistics for the long-only buy-and-hold portfolio and the representative trend-following portfolio. In terms of Sharpe ratio, the total performance of trend following over the past 800 years is far superior. This suggests that there may be a premium to active management and directional flexibility in allowing short positions. Given the spectacular outperformance of trend following over a long-only buy-and-hold portfolio, it is only natural to take a closer look at various factors that may impact this performance. The role of interest rates, inflation, market divergence, and financial bubbles and crisis are examined in closer detail throughout the book.

Excerpted with permission of the publisher, John Wiley & Sons, Inc., from Trend Following with Managed Futures: The Search for Crisis Alpha, by Alex Greyserman and Kathryn Kaminski. This book and e-book is available in all good bookshops, online booksellers and from the Wiley web site at www.wiley.com, or call 1-800-225-5945.

For more discussion of trend following with Kathryn Kaminski, see the Top Traders Unplugged podcast, available here.

Footnotes

1. Market efficiency, equity premiums, and buy and hold are all important notions in finance. The point to be made here is that they do not negate the value of trend following. In fact, trend following is a natural complement to these concepts. The goal of this book is to demonstrate and motivate this point.
2. A cellular phone (or any mobile device) provides a good practical example. Mobile devices have a structured methodology for processing external inputs from a user. The functionality of a mobile device is organized by a network of systems coupled together with rules and instructions. These rules and instructions are initiated by external inputs. External inputs are processed and an action takes place if the proper parameters of that action create a sequence of actions by the device. If there are actions that stress the system, there are internal blocks similar to circuit breakers and controls that deal with external inputs that are not within the bands acceptable for the device.
3. Returning to the analogy of a mobile phone, the structure and operating system of a mobile device must be functional. The art is in the external user interface and the eloquence in which it processes external inputs.
4. In Chapters 7 through 10 in the book, the modern version of systematic trend following is examined as an alternative asset class.
5. Moskowitz, Ooi, and Pedersen (2012) document a phenomenon they dub “time series momentum.” They show that a multi-asset momentum portfolio earns a positive premium. Time series momentum is different from the classic cross-sectional momentum of Jegadeesh and Titman (1993) and the vast academic literature that follows it.
6. The authors note that the analysis in this article is meant to tell the “tale of trend following.” This article provides a historical perspective of the concept of trend following. It is not meant to be replaced by a more rigorous analysis seen in modern academic papers or the detailed analysis later in the book. With any long-term analysis, there are many issues related to tradability, trading constraints such as short sales constraints, reliability of long-term data series, and other concerns.
7. The data sources are Reuters, Bloomberg, and Global Financial Data.
8. See also “The GFD Guide to Total Returns” (Taylor).
9. Using 12-month rolling returns, a trend signal is constructed at the end of each month. A particular market (for example corn) enters a long (or short) position when its return is positive (or negative) during the past 12 months. Position sizing is based on equal risk allocation between markets. This concept is developed further in Chapter 3 of the book.
10. Sharpe ratios are calculated assuming that the risk-free rate is zero. This assumption is made because risk-free lending rates are not available for the entire dataset.
11. Short selling is simple with futures contracts but historically, short selling would have been difficult or not possible during many periods in history.
12. FX markets are not included in the traditional buy-and-hold portfolio. For the buy-and-hold portfolio, monthly rebalancing is done to maintain equal risk with the corresponding trend-following portfolio.