What are the causes of weak trend following in strategies?

Frequent trend reversals

In the "Breaking Bad Trends" study, Research Affiliates examines various equity, bond, commodity and currency markets for characteristics of trend breaks.[1] The total period under consideration ranges from 1971 to 2019, although the individual data series in some cases begin later in this period.

The central result of the investigations is that there have been more frequent trend reversals in the last ten years than before. This helps to explain the weak trend following returns of the last decade. In concrete terms, a turning point in the studies is defined as a month in which the short-term momentum of a market (1 month) has a different sign than the long-term momentum (12 months).

The following graph shows a negative correlation between the number of turning points (x-axis) and the risk-adjusted return of a 12-month trend-following strategy. For each market examined, the number of turning points (months with different signs for 1-month and 12-month returns) was calculated in each year. The strategy was assumed to be a classic, static trend following strategy: Long (short), if 12-month return is positive (negative). The calculations were equally weighted, both within and between asset classes. In addition, the portfolio returns were normalized to an annualized volatility of ten percent. Period: 1990-2019.

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stratic trend strategy performance — **Figure 1) More trend reversals and lower returns in the last 10 years**
The graph shows a negative correlation between the number of turning points (x-axis) and the risk-adjusted return of a 12-month trend-following strategy.
Source: Garg, A. / Goulding, C. L. / Harvey, C. R. / Mazzoleni, M. G. (2020), Breaking Bad Trends, p. 9

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The number of turning points has a significant influence according to the studies: a multi-asset trend-following portfolio, normalized to an annualized volatility of 10 percent over the last 30 years, would lose about 9.2 percent of its annual return if the number of trend reversals was increased by one standard deviation.

A possible solution could be to use faster trend signals, i.e. to use shorter lookback periods than 12 months. However, the authors write that this is not a good idea. This would not solve the problem, but rather make it worse: This would increase the probability of bad trades, since faster signals contain an (even) higher proportion of noise.

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Using shorter lookback periods increase the probability of bad trades, since faster signals contain an (even) higher proportion of noise.

Garg, A. / Goulding, C. L. / Harvey, C. R. / Mazzoleni, M. G. (2020), Breaking Bad Trends

Low average movement ranges

In addition to the more frequent number of trend reversals, there is a second factor that helps explain the weak trend following returns. This was described in the AQR paper "You Can't Always Trend When You Want", which examined various plausible reasons for the underperformance of this trading approach. [2]

Based on their analyses, the authors exclude low trend efficiency - i.e. the ability of strategies to convert trends into profits - as an explanation. A lack of diversification of trend following portfolios across different markets is also rejected as a cause. According to the study, the actual explanation for the weak performance lies in the relatively low average amplitudes of the individual market movements.

The regression lines on the following figure show the relationship between the absolute size of market movements (x-axis) and the performance of the trend following strategy. In the period from 2010 to 2018, the regression line is almost identical to the one from 1880 to 2009, but the decisive factor is that the most recent data points (yellow) are significantly further to the left due to the smaller mean price movements in recent years. This means that trend following basically worked in terms of trend efficiency, but there were no large movements for correspondingly high returns.

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magnitude of market moves — **Figure 2) Size of market movement vs. trend-following return**
The regression lines show the relationship between the absolute size of market movements (x-axis) and the performance of the trend following strategy.
Source: Babu, A. / Hoffman, B. / Levine, A. / Ooi, Y. H. / Schroeder, S. / Stamelos, E. (2020), You Can't Always Trend When You Want, p. 8

From this it can be concluded that trend following basically continued to function and that higher returns can be expected in market phases with larger price movements. It is true that the phase of comparatively small movement amplitudes could continue for the time being. But the authors see no reason in the long term to assume that the characteristics of the markets have changed fundamentally and permanently over the last ten years.

Conclusion

The weak returns of trend-following strategies in the last ten years can be explained by a combination of more frequent trend reversals and low average ranges of movement. If the markets return to larger movements or less frequent trend changes in the future, correspondingly higher returns can be expected from these strategies.

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[1] Garg, A. / Goulding, C. L. / Harvey, C. R. / Mazzoleni, M. G. (2020), Breaking Bad Trends, Research Affiliates & Duke University
[2] Babu, A. / Hoffman, B. / Levine, A. / Ooi, Y. H. / Schroeder, S. / Stamelos, E. (2020), You Can't Always Trend When You Want, AQR Capital Management & Journal of Portfolio Management, Vol. 46, No. 4

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The causes of the weak trend following returns.

Frequent trend reversals

Low average movement ranges

Conclusion

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