Focus on Financial Planning

Keith Costello

Keith Costello is president and CEO of the Canadian Institute of Financial Planners (CIFPs) and the Canadian Institute of Financial Planning (CIFP). Over the past 15 years, Costello has led the creation of educational solutions, practitioner support services and advocacy support for financial planners.

This strategy rectifies the pitfalls of the traditional cross-sectional momentum investing approach

By Keith Costello |

Time-series momentum is an asset-pricing anomaly in financial markets that academia have documented and studied only recently. It's found to be present in different asset markets such as equities, commodities, fixed-income and currencies. Research shows that exploiting this anomaly tends to generate strong risk-adjusted returns.

Financial planners and financial advisors need to understand time-series momentum strategy to deliver more positive annualized investment returns for their clients. Moreover, you can use a time-series momentum strategy when constructing a customized investment portfolio, or it may be present in products you recommend for your clients' portfolios. Either way, you need to be aware of it.

A recent academic study entitled The Enduring Effect of Time-Series Momentum on Stock Returns Over Nearly 100-Years, which was written by Ian D'Sousa, Voraphat Srichanachaichok, George Wang and Cheldea Yaqiong Yao, found that time-series momentum for stocks performs well following both up and down markets. Furthermore, the strategy does not suffer from January losses and market crashes like the more popular cross-sectional momentum investing strategy. This empirical study documented the significant profitability of "time-series momentum" strategies in individual stocks in the U.S. markets from 1927–2014 and in international markets since 1975.

So, how does time-series momentum differ from traditional cross-sectional momentum investing? Although the technical model is similar, cross-sectional momentum compares the performance of different stocks available for investing at the same time to predict future winners vs losers. Time-series momentum relies on the observation that a security's own past return can be predictive of its future performance, and it doesn't depend on winners outperforming losers like cross-sectional momentum. Rather, time-series momentum simply requires a continuation of the security's price direction.

The research in the aforementioned study shows that the robustness of time-series stock momentum in global equities markets is a contradiction to the conventional wisdom of the random-walk theory, which predicts that a stock's past price movement or direction cannot be used to predict its future movement. From the period of 1927 to 2014, the data show that using a time-series momentum strategy produced an average monthly positive return of 0.55%, proving that unlike other momentum strategies, this strategy can deliver consistent year-over-year positive investment returns.

The research also highlights that the time-series momentum works because of investor behaviour. In particular, because of investors' underreaction to information and partly because they appear to have no bias in defining what is value or size as momentum is based on pure price signal, which is easy for the average investor to see and interpret.

Here are examples of each model to further extrapolate the concept in more detail:

Cross-sectional momentum strategy:

  1. Sort all the currently available stocks in 10 deciles based on their past 12-month cumulative performance (excluding the last month).
  2. Construct a zero-investment portfolio by selling the bottom decile of worst performing stocks and use the proceeds to buy the top decile of best performing stocks.
  3. Repeat and rebalance the portfolio monthly, skip a month before holding the rebalanced portfolio.


This strategy is profitable when the top decile "winners" outperform the bottom decile "losers."

Time-series momentum strategy:

  1. Use a 12-month timeframe to determine past performance when implementing the strategy.
  2. Instead of sorting these securities based on their performance, take a position in every security. A zero-investment portfolio is created by taking a long position in winners whose past 12-month cumulative performance is positive and taking a short position in losers whose past 12-month cumulative performance is negative.
  3. Repeat and rebalance the portfolio monthly, skip a month before holding the rebalanced portfolio.


This strategy evaluates momentum on a security-by-security basis, making it possible to be short all assets, or long all assets at the same time. This is in contrast with the cross-sectional momentum strategy, which relies on "winners" outperforming "losers."

The research also shows that even greater monthly positive investment returns could be realized by combining time-series momentum with cross-sectional momentum to create a dual-momentum investing strategy by using the following steps:

  1. At each month, assign stocks to a time-series loser group (T1) if their prior 11-month returns are negative and to a time-series winner group (T2) if their prior 11-month returns are positive.
  2. Within each of these time-series groups (T1 and T2), rank stocks further into quintiles based on prior 11-month returns, in which P1 is the value-weighted portfolio of stocks in the worst-performing 20% from T1 and P5 is the value-weighted portfolio of stocks in the best performing 20% from T2.
  3. Complete the dual-momentum strategy by buying the strongest winner portfolio (T2 and P5) and short the weakest loser portfolio (T1 and P1) resulting in a zero-investment strategy. The research data from 1927–2014 show that if you had used this dual-momentum strategy that the average annualized returns would've been almost triple that of using a pure time-series momentum strategy.


The key to time-series momentum strategy is that it smooths out the up and downs found in traditional cross-sectional momentum investing during up and down markets, January losses, market crashes or monetary policy interventions, as described in the aforementioned study. Financial planners and financial advisors can use this strategy to secure consistent positive annualized investment returns and avoid the pitfalls of traditional cross-sectional momentum investing.