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Summary

  • Trend following is an investment strategy that buys assets exhibiting strong absolute performance and sells assets exhibiting negative absolute performance.
  • Despite its simplistic description, trend following has exhibited considerable empirical robustness as a strategy, having been found to work in equity indices, bonds, commodities, and currencies.
  • A particularly interesting feature about trend following is its potential ability to avoid significant losses. Evidence suggests that trend following approaches can be used as alternative risk management techniques.
  • However, if investors expect to fully participate with asset growth while receiving significant protection, they are likely to be disappointed.
  • Relative to other risk management techniques, even very simple trend following strategies have exhibited very attractive return profiles.

What is Trend Following?

At its core, trend following – also called “absolute” or “time-series” momentum – is a very basic investment thesis: investments exhibiting positive returns tend to keep exhibiting positive returns and those exhibiting negative returns tend to keep exhibiting negative returns.

While the approach may sound woefully simplistic, the empirical and academic evidence that supports it extends back nearly two centuries.  Lempérière, Deremble, Seager, Potters, and Bouchard (2014), for example, test trend following approaches on commodities, currencies, stock indices, and bonds going back to 1800 and find that “the existence of trends [is] one of the most statistically significant anomalies in financial markets.”[1]

While LDSPB (2014) may have one of the longest backtests to date, a variety of other authors have demonstrated the existence of trends, and the success of trend following, in a variety of environments and markets.  We won’t list them here, but for those interested, a more thorough history can be found in our own paper Two Centuries of Momentum.

The driving theory behind trend following is that investor (mis-)behavior causes the emergence of trends.  When new information enters the market, investors underreact due to an anchoring bias that causes them to overweight prior information.  As price begins to drift towards fair value, herding takes over and causes investors to overreact.  This under and subsequent over-reaction is what causes a trend to emerge.

While somewhat contradictory to the notion that investors should not “chase performance” or “time markets,” evidence suggests that when systematically applied, trend following approaches can create a potentially significant return premium and potentially help investors avoid significant losses.

The Basic Trend Following Setup

In our experience, the two most popular methods of implementing a trend following signal are (1) a simple moving average cross-over system and (2) a measure of trailing total return.

In a simple moving average system cross-over system, when price is above the simple moving average, the system stays invested.  When price falls below, the strategy divests (usually into a risk-free asset, like U.S. Treasury Bills).  This sort of “in-or-out” system is often called “long/flat.”  For example, below we show a 12-month simple moving average and highlight when the system would buy and sell based upon when price crosses over.

The second form of trend following is more commonly referred to as “time-series momentum.”  In this approach, prior realized returns are calculated and the signal is generated depending upon whether returns were positive or negative.  For example, a popular academic approach is to use a “12-1” model, which takes the prior 12-month returns and subtracts the most recent month’s return (to avoid short-term mean reversion effects).  If this value is positive, the system invests and if the value is negative, it divests.

By looking at the example graphs, we can see that while these systems are similar, they are not exactly equal.  Nor are they the only way trend following approaches are implemented by practitioners.  What is important here is not the specific methodology, but that these methodologies attempt to capture the same underlying dynamics.

Empirical Evidence: Trend Following in a Crisis

To explore how a simple 12-1 time-series momentum system has worked in the past, we will apply the process to a broad U.S. equity index.  At the end of each month, we will calculate the trend following signal.  If the signal is positive, we will remain invested in the index (i.e. we are “long”).  If the signal is negative, we will divest into U.S. Treasury Bills (i.e. we are “flat”).

To explore the potential risk management capabilities of trend following, we will define a “crisis” as any period over which the broad U.S. equity market suffers a drawdown exceeding 25% from a recent market high.  We will then measure the maximum peak-to-trough drawdown of U.S. equities over the period and compare it to the maximum peak-to-trough drawdown of the 12-1 time series momentum strategy.

Since the early 1900s, we identify eight such scenarios.

Source: Kenneth French Data Library.  Calculations by Newfound Research.  Past performance is not indicative of future returns.  All performance is hypothetical and backtested.  Performance assumes the reinvestment of all distributions.  Returns are gross of all fees, including management fees, transaction costs, and taxes.

A few important takeaways:

  • Trend following is not a risk panacea. Even with trend following applied, drawdowns in excess of 15% occurred in each of these cases.  This is the cost of market participation, which will address a bit later.
  • Trend following did not limit losses in all cases. The market sell-off in October 1987 was so rapid that there was not sufficient time for trends to emerge and the system to be able to exit.  When trend following ends up protecting from quick sell-offs, it is more likely a function of luck than skill.
  • In many cases, trend following did help cut losses significantly. In the bear markets of the 1970s and 2000s, trend following helped reduce realized losses by over 50%.

Of course, the experience of these losses is very different than the summary numbers.  Below we plot the actual returns of equities versus a trend following overlay for several of the scenarios.

 

Source: Kenneth French Data Library.  Calculations by Newfound Research.  Past performance is not indicative of future returns.  All performance is hypothetical and backtested.  Performance assumes the reinvestment of all distributions.  Returns are gross of all fees, including management fees, transaction costs, and taxes.

We can see that the in many cases, when the trend following system got out, the market subsequently rallied, meaning that a trend follower would have a larger drawdown.  For example, in the Great Depression after the trend following system divested into U.S. Treasury Bills, the equity market rallied significantly.  This left the trend follower with a realized loss of -32% while a buy-and-hold investor would only be down -19%.

It is only with the benefit of hindsight that we can see that markets continued to fall and the patient trend follower was rewarded.

Ex-Ante Expectations About Participation

Of course, protecting capital is only half of the equation.  If we only cared about capital preservation, we could invest in short-term inflation-protected Treasuries and, barring a default by the U.S. government, sleep very well at night.

Before we demonstrate any empirical evidence about trend following’s ability to participate in growth, we want to use one of our favorite exercises – a coin flip game – to help establish reasonable expectations.

Imagine that we approach you with the offer to play a game.  We are going to flip a coin and you are going to try to guess how it lands.  If the coin lands on heads and you guess heads, the game is a push.  If it lands on tails and you guess tails, we give you $1.  If you guess wrong, you give us $1.

Does this sound like a game you would want to play?  Our guess is “no.”

Yet when we talk to many investors about their expectations for trend following strategies, this is the game they have created by choosing the U.S. equity market as a benchmark.

Consider the four scenarios that can happen:

  • The market goes up and trend following participates.
  • The market goes down and trend following goes down.
  • The market goes up and trend following is in cash.
  • The market goes down and trend following is in cash.

In the first scenario, even though trend following got the call right, we created a mental “push.”  In the middle two scenarios, trend following was incorrect and either participates on the downside or fails to participate on the upside (i.e. we “lose”).  It is only in the last scenario that trend following adds value.

In other words, by choosing U.S. equities as our benchmark for a long/flat trend following strategy, the strategy can only add value when the market is going down.  If we believe that the market will go up over the long run, that leaves very few scenarios for trend following to add value and plenty of scenarios for it to be a detractor.

Which is, unsurprisingly, exactly what you see if you plot the growth of a buy-and-hold investor versus a time-series momentum strategy: success in periods of significant market drawdown and relative underperformance in other periods.

Source: Kenneth French Data Library.  Calculations by Newfound Research.  Past performance is not indicative of future returns.  All performance is hypothetical and backtested.  Performance assumes the reinvestment of all distributions.  Returns are gross of all fees, including management fees, transaction costs, and taxes.

We can see, for example, that the trend following strategy lost its entire lead to the buy-and-hold investor from 1942 to 1962.  That is a frustratingly long period of underperformance for any investor to weather.

Determining the appropriate benchmark, however, is often a matter of preference.  We believe the appropriate way to address the problem is by asking whether trend following materially outperforms U.S. equities on a risk-adjusted basis.

To answer this question, we calculate the strategy’s full-period sensitivity to the U.S. equity index (i.e. its “beta”) and then re-create a new index that is comprised of a mixture U.S. equities and U.S. Treasury Bills that shares the same beta.  In this case, that index is 50% U.S. equities and 50% U.S. Treasury Bills.

Source: Kenneth French Data Library.  Calculations by Newfound Research.  Past performance is not indicative of future returns.  All performance is hypothetical and backtested.  Performance assumes the reinvestment of all distributions.  Returns are gross of all fees, including management fees, transaction costs, and taxes.

We can see that compared to a risk-adjusted benchmark, trend following exhibits a significant return premium without necessarily materializing significant excess downside risk.

Our take away from this is simple: investors who expect long/flat trend following strategies to keep up with equities are sure to be disappointed eventually.  However, if we use a benchmark that allows both “in” and “flat” decisions to add value (e.g. a 50% U.S. equity index + 50% U.S. Treasury Bill portfolio), trend following has historically added significant value.

One interpretation may be that trend following may be best suited as a “risk pivot” within the portfolio, rather than as an outright replacement for U.S. equity.  For example, if an investor has a 60% equity and 40% bond portfolio, rather than replacing equity with a trend strategy, the investor could replace a mix of both stocks and bonds.  By taking 10% from stocks and 10% from bonds to give to the trend allocation, the portfolio now has the ability to pivot between a 70/30 and a 50/50.  You can read more about this idea in our whitepaper Achieving Risk Ignition.

Another potential interpretation of this data is that long/flat trend following is a risk management technique and should be compared in light of alternative means of managing risk.

Pre-2008 versus Post-2008 Experience

Unfortunately, many investors have had their expectations for long/flat trend following strategies set by the period leading up to the 2008 financial crisis as well as the crisis itself, only to find themselves disappointed by subsequent performance.

Several years of whipsaws (including 2011, 2015 and 2016) leading to relative underperformance have caused many to ask, “is trend following broken?”

When we evaluate the data, however, we see that it is not the post-2008 period that is unique, but rather the pre-2008 period.

In fact, the pre-2008 period is unique in how calm a market environment it was, with drawdowns rarely eclipsing 10%.  While the post-2008 period has had its calm years (e.g. 2013 and 2017), it has also been punctuated by periods of volatility.  We can see the difference by plotting the drawdowns over the two periods.

Source: Kenneth French Data Library.  Calculations by Newfound Research. 

The unfortunate reality is that the calm period of pre-2008 and the strong performance of trend following in 2008 gave investors the false confidence that trend following had the ability to nearly fully participate on the upside and protect almost entirely on the downside.

Unfortunately, this simply is not true.  As we have said many times in the past, “risk cannot be destroyed, only transformed.”  While trend following tends to do well in environments where trends persist, it does poorly in those periods that exhibit sharp and sudden price reversals.

However, if we compare our trend following system against the more appropriate long-term risk-adjusted benchmark, we still see a significant return premium earned.

Source: Kenneth French Data Library.  Calculations by Newfound Research.  Past performance is not indicative of future returns.  All performance is hypothetical and backtested.  Performance assumes the reinvestment of all distributions.  Returns are gross of all fees, including management fees, transaction costs, and taxes.

One question we may ask ourselves is, “if we are using trend following to manage risk, how did other risk management techniques perform over the same period?”

Annualized Return
(2009 – 2017)
Annualized Volatility
(2009 – 2017)
Maximum Drawdown
(2007 – 2009)
S&P 50014.4%12.0%-52.3%
12-1 TS Momentum11.7%12.3%-10.9%
80/2012.3%9.4%-42.5%
60/4010.1%6.9%-32.0%
CBOE S&P 500 5% Put Protection Index10.2%10.1%-36.6%
Salient Trend Index (Managed Futures)1.2%10.3%-14.3%
Salient Risk Parity Index6.6%8.7%-30.8%
HFRX Global Hedge Fund Index1.5%4.0%-23.4%

Source: Kenneth French Data Library, CSI, Salient, HFRI, CBOE.  Calculations by Newfound Research.  Past performance is not indicative of future returns.  Performance assumes the reinvestment of all distributions.  Returns are gross of all fees, including management fees, transaction costs, and taxes.  60/40 and 80/20 portfolios are mixtures of the SPDR S&P 500 ETF (“SPY”) and iShares Core U.S. Bond ETF (“AGG”) in 60%/40% and 80%/20% proportional allocations, rebalanced annually.

We can see that while trend following has failed to keep up with U.S. equities in the post-crisis period (again, we would expect this), it has kept up much better than other potential risk management alternatives while providing significantly more protection during the crisis period.

Another important takeaway is that during the post crisis period, the trend following strategy had the highest volatility of any of the strategies measured.  In other words, while we might be able to rely on trend following for crisis risk management (i.e. avoiding the large left tail of returns), it is not necessarily going to reduce volatility during a bull market.

Conclusion

As an investment strategy, trend following has a long history of academic and empirical support.  Evidence suggests that trend following can be an effective means of avoiding large negative returns that coincide with traditional bear markets.

However, trend following is not a panacea.  In line with our philosophy that “risk cannot be destroyed, only transformed,” the risk management benefit often seen in trend following strategies comes with higher risks in other environments (i.e. “whipsaw”).

Investors who have relied upon the realized participation of trend following strategies during the pre-crisis period (2003-2007), as well as the protection afforded during the 2008 crisis itself, may have unrealistic expectations for forward performance.  Simply put: long/flat trend following strategies are very likely to underperform the underlying asset during strong bull markets.  In this case, replacing traditional equity exposure with a long/flat trend following strategy will likely lead to long-term underperformance.

However, when compared against other means of risk management, trend following has historically exhibited considerable downside protection for the upside participation it has realized.  Compared to a risk-adjusted benchmark, a long/flat U.S. equity trend following strategy exhibits an annualized excess return of 2.89%.

For investors looking to diversify how they manage risk, we believe the trend following represents a high transparent, and historically effective, alternative.

 


 

[1] https://arxiv.org/pdf/1404.3274.pdf

Corey is co-founder and Chief Investment Officer of Newfound Research, a quantitative asset manager offering a suite of separately managed accounts and mutual funds. At Newfound, Corey is responsible for portfolio management, investment research, strategy development, and communication of the firm's views to clients.

Prior to offering asset management services, Newfound licensed research from the quantitative investment models developed by Corey. At peak, this research helped steer the tactical allocation decisions for upwards of $10bn.

Corey is a frequent speaker on industry panels and contributes to ETF.com, ETF Trends, and Forbes.com’s Great Speculations blog. He was named a 2014 ETF All Star by ETF.com.

Corey holds a Master of Science in Computational Finance from Carnegie Mellon University and a Bachelor of Science in Computer Science, cum laude, from Cornell University.

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