(Factor) Timing Isn’t Everything in Equity Investing

14 February 2020

6 min read

Andrew Y. Chin| Chief Artificial Intelligence Officer

Many equity investors are enamored by the idea of timing factors to enhance returns, but our research suggests that it’s not the best way to enhance active equity performance. And skill in factor timing may not be a good gauge of future success.

Rising Interest in Factor Timing… But a Lack of Research

There’s an allure to the idea of exploiting factor performance, but factors can be fickle—whipsawing portfolios with sudden, volatile shifts. It’s a major reason why most active equity managers don’t have factor timing in their toolkits. Despite the challenges, big swings in factors such as beta, size and momentum since the Global Financial Crisis (GFC) have recharged interest. The asset-management industry has responded with research, strategies and vehicles to encourage and facilitate factor timing.

To put it bluntly, the idea of factor timing is back in vogue.

Unfortunately, research into the extent to which factor timing drives active returns—and whether it indicates manager skill—has been fairly limited. To address these topics, we extended our prime-alpha research. The original prime-alpha work indicated that the residual return remaining after stripping out the benchmark return and common factor exposures is persistent. That may make prime alpha a useful indicator of equity managers’ skill.

If we take the research a bit further, we can separate the individual components of active equity returns into strategic factor contributions, tactical factor contributions (factor timing) and security selection. By slicing the return contributors this way, we can take a closer look at what factor timers are actually bringing to the table.

Insights from Active Equity Return Patterns

Running this analysis on active large-cap equity manager returns over a fairly long period—1991 through 2017—yields important high-level insights about the patterns and composition of active equity returns:

Factor success ebbed and flowed. Strategic factor exposures added slightly to active returns but suffered through ebbs and flows along the way. Factor timing was actually a slight negative over the period: 2007 and 2009 were very strong years, for example, while the late 1990s were a struggle.

Factor exposure is fairly widespread. Across the full 27-year period, strategic factor exposures and factor timing each explained 25% to 30% of returns—whether good or bad—and stock selection explained the most, at 45%. The percentages vary across managers and by time period, but it’s clear that factor exposures play a sizable role in returns. Even stock pickers have factor exposures that influence performance.

The impact of individual factor-timing decisions is wide-ranging. There’s a huge variation in the impact of individual factor contributions over time (Display). In 1999, during the tech-bubble buildup, a value overweight hurt returns. During the ensuing crash, managers were generally overweight companies that were conservative in their business investments versus aggressive firms, which helped returns. Finally, at the 2008 depths of the GFC, portfolios were generally underweight profitability, which was a negative.

The Effectiveness of Factor Timing Ebbs and Flows

Contribution to Active Returns (Average Across All Portfolios)

Past performance does not guarantee future results
Based on Morningstar returns from 1991 through 2017 of US large cap equity open-end mutual funds with at least one-year performance history and a benchmark of the S&P 500 Index, Russell 1000 Index, Russell 1000 Growth Index or Russell 1000 Value Index. Strategies are represented by the share class with the longest history.
Through December 31, 2017
Source: Carhartt, Fama—French, Morningstar and AllianceBernstein (AB)

Based on the performance history, it’s clear that factor timing was a big active-return driver in the years before and during the GFC, but a much smaller one over the past decade (Display). It seems the decline isn’t the result of smaller factor swings—it’s because active equity managers have been making smaller factor bets. This may reflect an increased focus on risk management and portfolio construction.

Most active equity portfolios are bottom-up. About 75% of the portfolios in the analysis had three or fewer significant factors over the long term. This makes sense, since the bulk of managers are still fundamentally driven and built from bottom-up security selection. The portfolio factor exposures we did see in these cases may be indirectly driven by the underlying stocks—and likely vary over time.

Key Return Drivers: How Much Ability Is Really Involved?

After looking at historical return patterns of the contributors to active equity returns, the next logical question is: How much of a role does skill play? If a manager has truly demonstrated skill, we’d expect a consistent ability to deliver its active-return components. In other words, prior three-year returns should show similarities with subsequent three-year returns.

Consistent with our earlier prime-alpha analysis, we found that active equity returns tend to be mean reverting, with high returns followed by low returns and low returns followed by high returns. We see the same mean reversion in strategic factor contributions, which isn’t surprising: because factor returns ebb and flow over time, their impact on portfolio returns will do the same.

Contributions from factor timing, on the other hand, seemed more persistent, which suggests to us that active equity managers have generally demonstrated skill in this component. Of course, differences are likely among managers depending on how much factor timing they’re actually implementing. Finally, our research suggests that active equity managers have also demonstrated skill in security selection.

Taking a Deeper Dive into Factor Timers: Looking for Success

To get a closer look at active equity managers who are committed factor timers, we drilled down into our broad group to identify managers that made a higher percentage of significant factor bets and derived more of their risk from factor timing.

For this cohort, the research suggests that factor timing can be fool’s gold. The data indicate that factor timers haven’t been effective at their job description—tactically adjusting factor exposures—even though they bet on factors more often. Managers who travel this road are often at risk of being whipsawed by changing factor patterns, and factor timing has reduced returns more for this cohort of managers than for the broader set of managers (Display).

Factor Timers Have Struggled to Find Success

Annualized Return Contribution from Factor Timing, 1991-2017

What Really Matters for Manager Returns

Strategic factors, factor timing and security selection have all made meaningful contributions to active equity managers’ returns—with security selection being the largest. And based on the numbers, factor timers and stock pickers have demonstrated skill in plying their trades.

But do the success of any of these contributors hold promise as indicators of future active returns? Our research suggests that the answer is no for both strategic factors and factor timing, highlighting how challenging it is for managers using these tools to find factor success consistently. On the other hand, security selection seems to exhibit a small positive relationship with forward active returns, although the results aren’t statistically significant.

What about the two components of manager skill—factor timing and security selection? Do either of these prime-alpha building blocks suggest the ability to drive success in the future? Based on the results from our extended prime-alpha research, security selection is that driver. In other words, manager skill is expressed through security selection, not factor timing.

To sum this all up, active equity managers seem to have some level of persistent ability in tactical factor timing and security selection, but we don’t see the same persistence when we dig deeper into the data on managers who are true factor timers. Portfolio managers may be tempted to time factors, but will likely find that it’s very hard to get right.

Based on the current evidence, security selection seems to be in the driver’s seat in determining manager skill. In our view, this means investors would be well-served by zeroing in on that component of the toolset when evaluating active equity managers.

Special thanks to Piyush Gupta for his collaboration in this research.

The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams.

About the Author

Andrew Y. Chin

Andrew Chin is Chief Artificial Intelligence (AI) Officer and a member of the firm’s Operating Committee. In this role, he leads the firm’s strategy to leverage AI in transforming the organization and driving better outcomes for clients and the firm. Previously, Chin was the Head of Investment Solutions and Sciences, overseeing the research, management and strategic growth of the firm’s asset-allocation, data science, index and tax-management businesses. From 2022 to 2023, he was the head of Quantitative Research and chief data scientist, developing and optimizing quantitative research and data science infrastructure, capabilities and resources across the organization. As the firm’s chief risk officer from 2009 to 2021, Chin led all aspects of risk management and built a global team to identify, manage and mitigate the various risks across the organization. He has held various leadership roles in quantitative research, risk management and portfolio management in New York and London since joining the firm in 1997. Before joining AB, Chin spent three years as a project manager and business analyst in global investment management at Bankers Trust. He holds a BA in math and computer science, and an MBA in finance from Cornell University. Location: New York

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