The context
Well before factor investing became popular in the late 2000s, many investors were already exploiting individual factor premiums. Value strategies are a good example. The value effect is the empirically-documented tendency of inexpensive securities to achieve above-market returns relative to their intrinsic value as measured for example by the book-to-price ratio of a company.
For decades, prominent investors have advocated buying securities trading below their intrinsic value and many traditional active managers have been offering so-called value strategies. As early as the 1930s,1 Benjamin Graham and David Dodd of Columbia Business School advocated investing in undervalued stocks. Later on, Warren Buffett became famous for his very successful investment philosophy largely based on this same principle.
In this context, many investors have recently turned to factor investing as a systematic and cost-efficient way to achieve exposure to a particular factor premium, such as value or momentum, or to a specific set of factors. In fact, a recent FTSE Russell survey of asset owners found that getting specific factor exposure ranked fifth among the top investment goals that led them to consider factor-based strategies.
Scientific basis
As discussed in a previous article in this series, decades of academic research have shown that strategies focusing on a handful of well-vetted factor premiums deliver statistically and economically significant abnormal returns. These factor premiums are distinct phenomena, which exist beside one another, and have been identified across markets and asset classes.2
Targeting different factor premiums will therefore normally lead to different investment outcomes. Figure 1 provides an illustration of this. It shows the Sharpe and information ratios generated with four generic single-factor strategies – based on popular equity indices like the MSCI World Value Weighted index, the MSCI World Momentum index, the MSCI World Minimum Volatility index or the MSCI World Quality index – investing global equity markets, over the period from June 1988 to December 2015.
Source: Blitz, Huij, Lansdorp and van Vliet, ‘Efficient factor investing strategies’, Robeco whitepaper, 2016. Excess returns were measured relative to the MSCI World index from June 1988 to December 2015. Returns were measured in USD. The MSCI Value Weighted Index, MSCI Momentum Index, MSCI Minimum Volatility Index and MSCI Quality Index were used for generic factor strategies. The value of your investments may fluctuate. Results obtained in the past are no guarantee for the future.
The differences between different single-factor strategies are not only visible over long periods of time. In the shorter term, for instance, factor premiums can experience periods of underperformance or outperformance, relative to the market as well as other factor premiums. Such periods can continue uninterrupted for several years.
All these findings illustrate how different factors perform independently over time. It therefore makes sense to consider exposures individually and to allocate to each individual factor, depending on the needs and priorities of each investor, using single-factor strategies. For example, investors that have a clear preference for income, can allocate more to value or low volatility strategies, which typically deliver high dividends. Other investors may prefer to limit turnover, and therefore choose not to allocate to momentum which tends to lead to higher portfolio rotation.
Other considerations
But while monitoring and adjusting individual factor exposures depending on the strategic interests of each investor may look like a simple task on paper, there is much more to it in practice. The body of academic literature on the subject is extensive and there are many products available in the market for quantitative factor exposure measurement and performance attribution, including Robeco’s own tool.
Nevertheless, accurately measuring exposures to these factors often remains a challenge, in particular for the less sophisticated investors, who typically lack the necessary resources. Many academics and practitioners have warned about the dangers of poorly designed or inappropriate models.3
Without the relevant measurement tools, investors may, for example, confuse systematic exposure to one particular factor with alpha generated by an active portfolio manager. This explains why asset managers increasingly offer (multi-factor) solutions that provide exposure to a preset blend of factors.
Another important pitfall for those looking for specific factor exposures has to do with the way factors interact and in some cases clash with each other. Generic single-factor strategies usually ignore these interactions and therefore provide suboptimal factor exposures, resulting in, e.g. a value strategy that has very negative momentum exposures.4 This underscores the need for efficient factor strategies that use enhanced factor definitions that prevent negative exposures to other proven factors.
Footnotes
1Benjamin Graham and David Dodd, ‘Security analysis’, 1934
2See for example our recently published book of collected research articles: G. Baltussen, M. Martens, P. van Vliet, ‘Quant Allocation - Collected Robeco Articles’, 2018.
3See for example: Israel R. and Ross A., ‘Measuring Factor Exposures: Uses and Abuses’, The Journal of Alternative Investments”, 2017.
4For more information, see for example: Blitz D. and Vidojevic M., ‘The Characteristics of Factor Investing’, Robeco working paper, 2018.
探索量化價值
訂閱我們的電子報,獲取尖端的量化策略和見解。
免責聲明
本文由荷宝海外投资基金管理(上海)有限公司(“荷宝上海”)编制, 本文内容仅供参考, 并不构成荷宝上海对任何人的购买或出售任何产品的建议、专业意见、要约、招揽或邀请。本文不应被视为对购买或出售任何投资产品的推荐或采用任何投资策略的建议。本文中的任何内容不得被视为有关法律、税务或投资方面的咨询, 也不表示任何投资或策略适合您的个人情况, 或以其他方式构成对您个人的推荐。 本文中所包含的信息和/或分析系根据荷宝上海所认为的可信渠道而获得的信息准备而成。荷宝上海不就其准确性、正确性、实用性或完整性作出任何陈述, 也不对因使用本文中的信息和/或分析而造成的损失承担任何责任。荷宝上海或其他任何关联机构及其董事、高级管理人员、员工均不对任何人因其依据本文所含信息而造成的任何直接或间接的损失或损害或任何其他后果承担责任或义务。 本文包含一些有关于未来业务、目标、管理纪律或其他方面的前瞻性陈述与预测, 这些陈述含有假设、风险和不确定性, 且是建立在截止到本文编写之日已有的信息之上。基于此, 我们不能保证这些前瞻性情况都会发生, 实际情况可能会与本文中的陈述具有一定的差别。我们不能保证本文中的统计信息在任何特定条件下都是准确、适当和完整的, 亦不能保证这些统计信息以及据以得出这些信息的假设能够反映荷宝上海可能遇到的市场条件或未来表现。本文中的信息是基于当前的市场情况, 这很有可能因随后的市场事件或其他原因而发生变化, 本文内容可能因此未反映最新情况,荷宝上海不负责更新本文, 或对本文中不准确或遗漏之信息进行纠正。