The key issue we wanted to address was that for many years, investors had been
relying on the assumption that combining different asset classes within a portfolio
was an effective way to maximize risk-adjusted returns. We believe, however, that
different asset classes may be exposed to the same systematic sources of risk,
or factors, which may lead an investor to believe that they are more diversified
than they actually are. In contrast, examining a portfolio through a factor lens may
identify overlapping sources of risk across asset classes. We believe that this allows
for more efficient management of portfolio risk and expected return.
We debuted the Two Sigma Factor Lens with a set of 8 factors, split across Core
Macro and Secondary Macro categories. These original factors were specifically
designed to analyze multi-asset portfolios and were derived from returns of broad,
liquid, asset class proxy indexes (Exhibit 1 below).
Through the Two Sigma Factor Lens, we wanted to provide a set of actionable
factors that could collectively explain much of the cross-sectional and time-series
risk in typical portfolios.
Our 2018 paper went into detail on how to construct and assess these factors,
as well as how we could extend our lens to include additional factors that might
capture new sub-asset class or cross-sectional risks. The factor lens we laid out in
this paper, and our ongoing work to expand it, also formed the foundations of our
VennTM platform. Venn was originally designed as a cloud-based investment analysis
software, helping institutional investors evaluate and manage their multi-asset
class portfolios.
In the years since, we have extended the lens to include an additional 10 factors,
which we split between two new groupings: Macro Styles and Equity Styles. We
wanted to add new factors that could increase the explanatory power of the Factor
Lens by covering less common, but still sizable drivers of portfolio risk. These
additions were crafted to be orthogonal to existing factors, while still following
a similar research and construction methodology. Together, this expanded set of
factors was intended to even better capture and explain the risk attribution of
investment portfolios.
As our Factor Lens continued to expand, so too did the Venn platform. Venn was
officially launched to the external investment community in 2019, and has seen
broad-based growth in clients since. Originally designed for institutional allocators,
Venn soon expanded its client base to also include teams at: wealth managers,
family offices, asset managers, insurance companies, and investment consultants.
For many Venn clients, the platform became their entry point to a more transparent
understanding of risk across their investments and portfolios.
The current Two Sigma Factor Lens includes a broader holistic set of factors chosen
to identify risk and return drivers in both diversified portfolios and individual
investments. A thoughtfully chosen and constructed factor lens can assist with
answering questions such as what risks investors may be over- or underexposed to,
how their risk exposures differ from their benchmark, or what is driving their overall
and benchmark-relative returns.
Current Factor Lens
Today, our Factor Lens consists of the following 18 factors:
Even as we expanded the number of factors, the core principles we followed in constructing this lens remain unchanged. Just as when we first published our 2018
piece, we still believe today that the following four attributes should characterize
any factor lens that is ideally suited for portfolio and manager analysis:
- Holistic, by capturing the large majority of cross-sectional and time–series risks for typical institutional portfolios
- Parsimonious, by using as few factors as possible
- Orthogonal, with each risk factor capturing a statistically uncorrelated risk across assets
- Actionable, such that desired changes to factor exposure can be readily translated into asset allocation changes
We classify our current set of factors across four categories that we mentioned previously, starting from the more liquid and high capacity factors that often form the foundation of most institutional investors’ portfolios. The four categories are:
- Core Macro: The Core Macro factors are the most prevalent factors, and are
designed to consist of high-capacity, highly liquid factors that are considered
the principal drivers of asset class returns. - Secondary Macro: The Secondary Macro factors seek to identify key risks
that can cut across multiple asset classes in diversified portfolios, and are
considered to have lower capacity and liquidity than the Core Macro factors. - Equity Styles: Each Equity Style factor represents returns of a portfolio of
global stocks that is designed to be market-neutral and region-neutral, except
the Crowding factor, which is U.S.-focused. These factor portfolios also target
discrete, systematic characteristics shown by academic finance research¹ to
generate positive returns over time. - Macro Styles: Each of our Macro Style factors targets discrete, systematic
characteristics shown by academic research to generate positive returns over
time. Shortly after we added a few of these Macro Styles factors to our lens, we
published a piece in which we provided background on what these factors were
meant to capture, with a special focus on how Trend Following compares to one
of our Equity Styles factors, Momentum.
Although these newly added Style factors require more skill to capture and manage,
and are more costly to access than the Macro factors, they are still less expensive
and higher-capacity than “alpha”. Alpha can consist of idiosyncratic sources of return
(i.e., uncorrelated to other known factors) that are often limited in capacity and
have historically commanded higher fees. When using returns-based statistical
factor analysis, these idiosyncratic sources of return generally appear as “residual”
given their low correlation with known factors. However, not all residual return
represents true “alpha”. It can often just be uncompensated risk, and investors
should be careful when interpreting the residual from any statistical analysis of
historical performance.
A factor lens, such as the one we have been discussing here, can help determine
if an investment is indeed providing residual risk and return as opposed to simple
exposure to a combination of macro and style factors.
Finally, we believe that any outputs from the factor analysis we discuss here should
be translatable into asset allocation insights. For this reason, we constructed each of
these individual factors to be “investible,” meaning there should be a relatively stable
relationship between individual factors and a readily investible set of liquid assets.
To find more statistical and economic evidence for the factor lens we originally
constructed, including both quantitative and qualitative tests of our factor lens, please refer to our original paper from 2018, as well as our follow-up from 2019 that estimated long-term expected returns to each of the factors in our lens.
Conclusion
In the years that have followed our 2018 publication, “Introducing the Two Sigma Factor Lens”, we have continued to build upon our original framework of
systematically identifying, and then constructing, a practical set of risk factors.
Today, the Two Sigma Factor Lens contains 18 factors, with the latest addition
coming in 2020. Through our work on the Venn platform, we’ve also seen this
lens find broad applications among a multitude of client types. As we continue to
research and expand upon this lens, we maintain our founding principles: that risk
factors should be holistic, parsimonious, orthogonal, and actionable. Together, these
criteria continue to guide us through construction and expansion of a flexible risk
factor lens that we believe can be used broadly across the investment community.
We will address further applications of our factor lens in future publications, and
encourage those interested in seeing these applications in action to please contact
the Venn team through our website.
References
1 For more information on the academic research we cite, and the construction methodology of our factors, please reference the Two Sigma Factor Lens FAQ we have prepared here: https://help.venn.twosigma.com/en/articles/1392786-two-sigma-factor-lens-faq
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