Swedroe: Why Financial Trends Persist

March 19, 2018

In 2007, The Journal of Wealth Management published a paper by Mebane Faber of Cambria Investment Management, “A Quantitative Approach to Tactical Asset Allocation.” The paper reviewed the results of a simple market-timing strategy using a 10-month version of the popular 200-day moving average technical indicator (in other words, a time-series momentum strategy). It went on to become the most downloaded paper on SSRN’s website, with more than 200,000 downloads.

Ten years later, Faber thought it was time to review how the strategy had held up out-of-sample. The update, “A Quantitative Approach to Tactical Asset Allocation Revisited 10 Years Later,” was published in a special 2018 issue of The Journal of Portfolio Management.

In his update, Faber noted: “It’s important to understand that ‘beating the market’ was never the goal of the model. The intent was to identify a trading system that largely approximated market returns, yet did so with significantly less volatility. The reason for this was simple—emotions can wreak havoc on investors’ ability to follow their stated investment plan. All too often, we fall victim to fear when markets have turned against us and sell at nearly the worst possible time.”

The original article was published with data up through 2005, so Faber examined the historical in-sample results (1972 through 2005) as well as the out-of-sample returns in the 11 years since. He found that from 2006 through 2016, the simple timing strategy had provided higher returns than the S&P 500 Index (8.5% versus 7.7%), did so with much less volatility (7.4% versus 14.7%) and had a much lower maximum drawdown (16.7% versus 51%). The result was a dramatic improvement in Sharpe ratio, from 0.45 to 0.80.

In reviewing his findings, Faber noted: “Though the timing system outperformed by a

significant amount during the 2008–2009 bear market, it went on to underperform stocks six of the next eight years. Many investors who had implemented the timing model after the crash likely struggled with staying the course with a tactical approach.”

Pervasiveness Of The Data

One test of whether investors should have faith in the results of an investment strategy is that it also work in other asset classes—reducing the risk of data mining. Thus, in addition to reviewing the results in U.S. stocks, Faber also reviewed the performance of his 10-month moving average strategy across foreign stocks, U.S. bonds, REITs and commodities. The timing model used equal weightings and treated each asset class independently; it is either long the given asset class or its 20% allocation sits in cash.

This second analysis produced the same result: improved returns (4.9% versus 3.5%), much lower volatility (6.6% versus 12.8%), dramatically higher Sharpe ratio (0.59 versus 0.19) and much lower maximum drawdown (9.5% versus 46%).

Robustness Of The Data

Another important test of whether investors should have faith in an investment strategy is that it be robust to various definitions. Faber found similar results for strategies using periods of six, eight and 12 months.

He also tested a more conservative strategy, which had a 40% allocation to U.S. bonds, and a more aggressive strategy, which begins with the moderate allocation and then selects the top three of the five assets he examined as ranked by an average of one-, three-, six- and 12-month total returns (time-series momentum), only including assets if they are above their long-term moving average (otherwise that portion of the portfolio is moved to cash using T-bills).

In addition, Faber tested the strategy using long-term bonds for cash management. Finally, he tested a more diversified version of the strategy, using a long list of other asset classes, including TIPS, high-yield bonds, emerging market bonds, foreign REITs, fundamental indexes and currencies.

The results were similar in each of the tests. And with the help of diversification benefits, the broader strategy, which included more asset classes, improved results, increasing the return of the quantitative strategy from 9.8% to 11.3%, with only a modest 0.2% increase in volatility. The result was that the Sharpe ratio increased from 0.71 to 0.91.

 

A Century Of Data

Faber’s results are consistent with those of AQR Capital Management’s Brian Hurst, Yao Hua Ooi and Lasse Pedersen in their June 2017 study on time-series momentum, “A Century of Evidence on Trend-Following Investing.”

The authors constructed an equal-weighted combination of one-month, three-month and 12-month time-series momentum strategies for 67 markets across four major asset classes (29 commodities, 11 equity indexes, 15 bond markets and 12 currency pairs) from January 1880 to December 2016. The position these one-, three- and 12-month strategies take in each market is determined by assessing the past return in that market over the relevant look-back horizon.

A positive past excess return is considered an “up” trend and leads to a long position; a negative past excess return is considered a “down” trend and leads to a short position. In addition, each position is sized to target the same amount of volatility, both to provide diversification and to limit portfolio risk from any one market. Positions across the three strategies are aggregated each month, and scaled such that the combined portfolio has an annualized ex-ante volatility target of 10%.

Volatility scaling ensures the combined strategy targets a consistent amount of risk over time, regardless of the number of markets traded at each point in time. The authors’ results include implementation costs based on estimates of trading costs in the four asset classes. They further assumed management fees of 2% of asset value and 20% of profits, a traditional fee for hedge funds.

Following is a summary of their findings:

  • Performance was remarkably consistent over an extended time horizon, one that included the Great Depression, multiple recessions and expansions, multiple wars, stagflation, the global financial crisis of 2008, and periods of rising and falling interest rates.
  • Annualized gross returns were 18.0% over the full period, with net returns (after fees) of 11.0%, higher than the return for equities, but with approximately half the volatility (an annual standard deviation of 9.7%).
  • Net returns were positive in every decade, with the lowest net return, at 4.1%, coming in the period beginning in 1919.
  • There was virtually no correlation to either stocks or bonds. Thus, the strategy provides a strong diversification benefit. After considering all costs and the 2/20 hedge fund fee, the Sharpe ratio was 0.76. Thus, even if future returns are not as strong, the diversification benefits could justify an allocation to the strategy.

Hurst, Ooi and Pedersen write that “a large body of research has shown that price trends exist in part due to long-standing behavioral biases exhibited by investors, such as anchoring and herding [and I would add to that list the disposition effect and confirmation bias], as well as the trading activity of non-profit-seeking participants, such as central banks and corporate hedging programs.”

They observe, for instance, that “when central banks intervene to reduce currency and interest-rate volatility, they slow down the rate at which information is incorporated into prices, thus creating trends.”

 

Long-Running Trend

Hurst, Ooi and Pedersen continued: “The fact that trend-following strategies have performed well historically indicates that these behavioral biases and non-profit-seeking market participants have likely existed for a long time.”

Why would this be the case? They explain: “The intuition is that most bear markets have historically occurred gradually over several months, rather than abruptly over a few days, which allows trend followers an opportunity to position themselves short after the initial market decline and profit from continued market declines…. In fact, the average peak-to-trough drawdown length of the 10 largest drawdowns of a 60% stocks/40 bonds portfolio between 1880 and 2016 was approximately 15 months.”

They noted that trend-following has done particularly well in extreme up or down years for the stock market. In fact, they found that during the 10 largest drawdowns experienced by the traditional 60/40 portfolio over the past 135 years, the time-series momentum strategy experienced positive returns in eight of these stress periods and delivered significant positive returns during a number of these events.

While Hurst, Ooi and Pedersen provided results that included a 2/20 fee structure, today there are funds that can be accessed with much lower, although still not exactly cheap, expense ratios. An example is AQR’s Managed Futures Strategy (AQMRX), which has an expense ratio of 1.15%.* (Full disclosure: My firm, Buckingham Strategic Wealth, recommends AQR funds in constructing client portfolios.)

Additionally, AQR has found that, in implementing time-series momentum strategies, their actual trading costs have been only about one-sixth of the study’s estimates used for much of the sample period (1880 through 1992), and approximately one-half of the estimates used for the later period from 1993 through 2002.

Summary

As an investment style, trend-following has existed for a long time. Data from recent research provides strong out-of-sample evidence, beyond the substantial evidence that already existed in the literature. It also provides consistent, long-term evidence that trends have been pervasive features of global stock, bond, commodity and currency markets.

Addressing the issue of whether investors should expect trends to continue, the AQR researchers concluded: “The most likely candidates to explain why markets have tended to trend more often than not include investors’ behavioral biases, market frictions, hedging demands, and market interventions by central banks and governments. Such market interventions and hedging programs are still prevalent, and investors are likely to continue to suffer from the same behavioral biases that have influenced price behavior over the past century, setting the stage for trend-following investing going forward.”

The bottom line is that, given the diversification benefit and its downside (tail-risk) hedging properties, a moderate portfolio allocation to trend-following strategies merits consideration. Note, however, the generally high turnover of trend-following strategies renders them relatively tax inefficient. Thus, investors should strongly prefer to hold such strategies in tax-advantaged accounts.

 

*Discussion of AQMRX is provided for informational purposes only and is not intended to serve as specific investment or financial advice. This discussion does not constitute a recommendation to purchase a single specific security, and it should not be assumed that the security referenced herein was or will prove to be profitable. Prior to making any investment, an investor should carefully consider the fund’s risks and investment objectives and evaluate all offering materials and other documents associated with the investment.

 

Larry Swedroe is the director of research for The BAM Alliance, a community of more than 140 independent registered investment advisors throughout the country.

Find your next ETF

CLEAR FILTER