The theory of factor-based investing has been around for nearly 50 years, though it has gained popularity in recent years because of the low cost to implement and the transparency in its methodology. Factor-based investing involves selecting securities based on persistent drivers, allowing investors to target specific risk factors and harvest the risk premia. Since individual factors are as cyclical as equity markets, many asset managers have launched multifactor index-based exchange-traded funds (ETFs) combining three or more factors that have historically shown performance success, such as value, size, momentum and price volatility. For example, to provide diversification benefits and help moderate risk. Despite factor diversification, as a "buy and hold" strategy, these may still experience periods of underperformance. Factor timing, in addition to factor diversification, has the potential to improve portfolio performance. Today, we will examine the importance of factor rotation with a simple demonstration of how factor timing may be used to outperform both the multifactor index and equity benchmark index.
How do traditional factors behave in the different economic cycles? Let us review U.S. stock market data between 1963 and 2020 from the Kenneth R. French Data Library. Six portfolios have been created by sorting and selecting the top 20% and bottom 20% of stocks by these three popular factor definitions: 1) value, 2) quality and 3) momentum. The data is separated into “bull” and “bear” periods, where a bear period is defined by a drawdown greater than 15% until it beats the previous peak. When we compare the annualized returns of these top 20% and bottom 20% portfolios in the different periods, we see the following performance results:
|
U.S. Stock Market 1963 to 2020 Portfolios by Factor Definition |
Bull Periods | Bear Periods |
| Factor 1: Value |
Top underperforms Bottom (-1.54% AR) |
Top outperforms Bottom (+1.63% AR)
|
| Factor 2: Quality |
Top outperforms Bottom (+1.43% AR) |
Top outperforms Bottom (+4.34% AR) |
| Factor 3: Momentum |
Top outperforms Bottom (+8.88% AR) |
Top underperforms Bottom (-0.69% AR) |
According to these results, one may consider investing in the value and quality factors during bear periods and invest in the momentum factor during bull periods. Although some evidence suggests momentum factor returns are not as strong in recent periods, it is still a popular factor that outperformed the MSCI USA Total Net Return Index in 2020 by approximately 8%. Intuitively, this strategy makes sense because value and quality stocks generally have lower betas than momentum stocks. Therefore, if the whole market declines, value and quality stocks will decline less and protect the portfolio in this environment. Now let us see the hypothetical performance of this factor rotation strategy using the following data sets:
- MSCI USA Value Net Total Return Index
- MSCI USA Quality Net Total Return Index
- MSCI USA Momentum Net Total Return Index
- MSCI USA Total Net Return Index
- Bloomberg United States Recession Probability Index
Predicting the economic cycle is difficult. For the factor rotation signal, I used the Bloomberg United States Recession Probability Index. However, I have also used the University of Michigan Consumer Sentiment Index and Conference Board U.S. Leading Index, and the resulting performance still outperformed the MSCI USA Total Net Return Index by more than 3.0%.
The Bloomberg United States Recession Probability Index incorporates a range of data spanning economic conditions, payroll employment, production and manufacturing. Using different trigger levels of this index, from 20% to 80%, I found that the alpha is not too sensitive to the trigger levels and the results did not change significantly. In this week’s chart, I used a 60% trigger for the factor rotation. That is, if the Bloomberg United States Recession Probability Index from two months ago was greater than 60%, I invested in MSCI USA Value Net Total Return Index and MSCI USA Quality Net Total Return Index equally. If it was less than 60%, I invested in the MSCI USA Momentum Net Total Return Index.
Based on this strategy, the factor rotation outperformed MSCI USA Total Net Return Index by 4.1% and outperformed the average of the three MSCI factor indexes by 2.7% since 1994. Since 2008, the factor rotation strategy has only underperformed MSCI USA Total Net Return Index in four of the last 13 years. The hypothetical performance of the factor rotation strategy not only beat the two benchmarks, but also all three individual factors. This provides a compelling argument that factor rotation may be an effective strategy to generate alpha and merits further investigation. For example, does the transactional costs increase with the cyclical rotations and will they offset any potential gains?
Key Takeaway
In summary, individual factors behave differently in different economic cycles and can underperform for an extended period. My research shows that value and quality stocks have defensive exposures that may protect the portfolio when the economy contracts, while momentum stocks have growth exposures that may benefit the portfolio when the economy expands. In this post, we have looked at the performance of three different factors in different economic cycles. We built out a simple recession signal using public data to harvest the factors' characteristics and constructed a factor rotation strategy. The factor rotation strategy outperformed the MSCI USA Total Net Return Index by 4.1% and outperformed the average of the three MSCI factor indexes by 2.7% since 1994. With dozens of low-cost factor ETFs out there, factor rotation may be profitable even when accounting for the trade cost, which I believe merits more research and investigation.
The material provided here is for informational use only. The views expressed are those of the author, and do not necessarily reflect the views of Penn Mutual Asset Management.
This material is for informational use only. The views expressed are those of the author, and do not necessarily reflect the views of Penn Mutual Asset Management. This material is not intended to be relied upon as a forecast, research or investment advice, and it is not a recommendation, offer or solicitation to buy or sell any securities or to adopt any investment strategy.
Opinions and statements of financial market trends that are based on current market conditions constitute judgment of the author and are subject to change without notice. The information and opinions contained in this material are derived from sources deemed to be reliable but should not be assumed to be accurate or complete. Statements that reflect projections or expectations of future financial or economic performance of the markets may be considered forward-looking statements. Actual results may differ significantly. Any forecasts contained in this material are based on various estimates and assumptions, and there can be no assurance that such estimates or assumptions will prove accurate.
Investing involves risk, including possible loss of principal. Past performance is no guarantee of future results. All information referenced in preparation of this material has been obtained from sources believed to be reliable, but accuracy and completeness are not guaranteed. There is no representation or warranty as to the accuracy of the information and Penn Mutual Asset Management shall have no liability for decisions based upon such information.
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