Time Series Momentum (aka Trend-Following): A Good Time For A Refresh

Similar to some better-known factors like size and value, time-series momentum is a factor which has historically demonstrated above-average excess returns. Time-series momentum, also called trend momentum or trend-following, is measured by a portfolio which is long assets which have had recent positive returns and short assets which have had recent negative returns.(1) Compare this to the traditional (cross-sectional) momentum factor, which considers recent asset performance only relative to other assets. The academic evidence suggests that inclusion of a strategy targeting time-series momentum in a portfolio improves the portfolio’s risk-adjusted returns. Strategies that attempt to capture the return premium offered by time-series momentum are often called, “managed futures,” as they take long and short positions in assets via futures markets — ideally in a multitude of futures markets around the globe. This piece dives into time-series momentum and examines some of its specific qualities — qualities that make a managed futures strategy a good portfolio diversifier (example shown here).

In general, an asset that has low (or negative) correlation with broad stocks and bonds provides good diversification benefits. Low or near-zero correlation between two assets means that there is no relationship in their performance: Asset A performing above average does not tell us anything about Asset B’s expected performance relative to its average. The addition of a low-correlation asset to a portfolio will, depending on the specific return and volatility properties of the asset, improve the portfolio’s risk-adjusted returns either by improving the portfolio’s return, reducing the portfolio’s volatility, or both.

An Introduction to Time Series Momentum Research

AQR Capital Management’s Brian Hurst, Yao Hua Ooi and Lasse H. Pedersen contribute to the literature on time-series momentum with their June 2017 study, A Century of Evidence on Trend-Following Investing”— an update of their 2014 study, “Time Series Momentum.” They 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 indices, 15 bond markets and 12 currency pairs) from January 1880 to December 2016. For each of the three strategies (one-, three- and 12-month), the position taken 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. Each position is sized to target the same amount of volatility, both to provide diversification and to limit the portfolio risk from any one market (see risk parity for dummies). The 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 percent. Volatility scaling ensures that the combined strategy targets a consistent amount of risk over time, regardless of the number of markets that are traded at each point in time. Their results include implementation costs based on estimates of trading costs in the four asset classes. They further assumed management fees of 2 percent of asset value and 20 percent of profits, a traditional fee for hedge funds.

Below is a recap of the authors’ Time Series managed futures strategy versus a long-only strategy trading the same futures contracts.

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

The following is a summary of the AQR researchers’ findings:

While trend-following has done particularly well in extreme up or down years for the stock market, the performance was remarkably consistent over an extensive time horizon 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.

In each decade since 1880, time-series momentum has delivered positive average returns with low correlations to traditional asset classes. Further, time-series momentum has performed well in eight out of 10 of the largest crisis periods over the century, defined as the largest drawdowns for a 60/40 stock/bond portfolio — tending to perform well when its benefits were needed most.

The persistence, pervasiveness (there were positive average returns in each of the 67 markets, with an average Sharpe ratio of approximately 0.4) and robustness (three strategies) of the results makes it highly unlikely that existence of price trends in markets is a product of statistical randomness or data mining.

Annualized returns in excess of the risk-free rate, gross of fees but net of costs, were 11.0 percent over the full period, higher than the return for equities but with about half the volatility (an annual standard deviation of 9.3 percent). After applying a 2/20 fee typical of hedge funds, the net excess return was still 7.3 percent (note that investors now have access to lower-cost alternatives in the form of publicly available mutual funds and ETFs, which also provide daily liquidity).

Net returns were positive in every decade, with the lowest net return being the 1.6 percent return for the period beginning in 1910.

There was virtually no correlation between either stocks or bonds. Thus, the strategy provides strong diversification benefits while producing a high Sharpe ratio (net of fees and costs) of 0.76. (Even if future returns are not as strong, the diversification benefits would justify an allocation to the strategy.) The so-called “Trend Smile,” or the historical finding that time-series momentum-based managed futures programs tend to rise in both extreme positive — and negative — markets, is compelling for investors looking to hedge their tail risks.