How do common risk factors connect stocks, bonds, and options? In their recent study, which won the Jacobs Levy Center Research Paper Prize for Best Paper, Professor Nikolai Roussanov and his coauthors uncover the shared sources of variation driving returns across these asset classes.
Their findings reveal how shared exposures can influence portfolio risk and returns, providing valuable insights for investors. Explore the full conversation with Professor Roussanov below:
What inspired you and your coauthors to study the common risk factors across stocks, bonds, and options? Why is it important to understand how these asset classes are connected?
Nikolai Roussanov: We are considering three types of assets: individual U.S. stocks, corporate bonds, and individual equity options. These are all corporate securities, and at the most fundamental level, their payoffs are intimately linked: stocks and bonds are claims to different slices of firm cash-flows, and options are derivatives based on the former. So it is natural to expect that the same common sources of variation drive the returns on all three of these asset classes. And yet the evidence in the literature thus far has been primarily about asset-class specific factors. From the standpoint of standard finance theory, this is somewhat surprising. It would seem to suggest that financial markets are highly segmented and different slices of corporate cash-flows are held – and priced – by different types of investors.
Your paper uses a novel approach to uncover these “latent” – or unobservable – risk factors. Can you describe this method and why it’s different from traditional ways of identifying risk factors?
Nikolai Roussanov: Most of the “traditional” methods of identifying risk factors are “top down” in the sense that a variable is proposed that captures common market fluctuations (e.g., a macroeconomic variable, like unemployment or inflation rate), or an asset characteristic is used to group assets into portfolios, (e.g. value stocks vs. growth stocks), and a “factor” emerges when these different groups exhibit distinct behavior over time (say, “value” outperforms “growth”, or vice versa).
In contrast, we employ a “bottom up” approach, whereby we extract statistical factors that capture common variation in individual security returns. Typically this is hard to do since the set of returns is very large – we have several thousand traded stocks, the most liquid of these names have several options of different moneyness and maturity traded on them at a different point in time, and most have several different bond issues. We employ the “characteristics” of firms and specific assets that I mentioned above to reduce the dimensionality of this problem, which allows us to extract a set of common factors that are pervasive across all three asset classes.
A key finding of your paper is that stocks, bonds, and options all share some common risk factors. Why does this matter for investors and how might it change the way we think about diversification?
Nikolai Roussanov: The fact that the three asset classes, and specific strategies, or factors, that are meant to capture and exploit attractive investment opportunities in these asset classes, share a substantial amount of common variation suggests that the benefits to diversifying investor portfolios across asset classes might not be as great as one might think. While there might be some discrepancy across the asset classes in how much return investors receive (on average) as compensation for exposure to these risk factors (potentially due to some market segmentation), for most investors it might be sufficient to focus on obtaining exposure to these factors in one asset class that is easiest for them to access (e.g., equities).
You mention in Knowledge at Wharton that much of the “alpha” your study identified has already been arbitraged away by quantitative investors, especially in corporate bonds. Is there more opportunity for investors to find value in areas like stocks or options?
Nikolai Roussanov: While over the length of our sample period there was substantial “alpha,” i.e. average return not explained by factor risk exposures, in all three asset classes, it was the smallest among the most liquid corporate bonds. This makes sense since this is a market that is mostly dominated by large institutional investors. Alpha was the largest in options strategies, which also makes sense since these require substantial sophistication to exploit.
Over time, however, the “alpha” of well-known strategies tends to decline, whereas the returns to common factors is more stable. As mentioned above, however, there might be some discrepancy in how risk factors are ‘priced’ across asset classes due to “market segmentation.” This would imply that more sophisticated institutional investors with the capacity to access, say, options-based strategies, might be able to achieve superior returns.
How do you see this research influencing the way we approach investing or risk management in the future?
Nikolai Roussanov: Over the last couple of decades, the world of investment and asset management has evolved toward an increasing separation between “alpha” and “beta.” The latter represents earning compensation for exposure to known risk factors – such as market, value, momentum, and low volatility in equities, as well as duration and credit in bonds – that is accessible at a fairly low cost. This can often be achieved via “nearly-passive” or “minimally-active” ETFs.
In contrast, the former represents “true” outperformance, which is harder to generate and costlier to access. Examples include hedge funds that charge high fees and are not accessible to most retail investors.
I think this trend will continue, even though more and more of the strategies are becoming “democratized” due to the rise of quantitative investing, making what looked “alpha” achievable in almost the same way as “beta.” Where I think our research points towards a future shift is in how investors approach asset allocation. It is typical to think of portfolio allocation as, say 60% stocks, 30% bonds, 10% “alternatives.” Then investments within each of these buckets are chosen individually, without considering the investments in the other “buckets.” If some of these investments end up exploiting “factors” within a particular asset class, chances are these factor exposures will be correlated with those in the other asset class buckets as well. This increases the overall risk exposure of the portfolio without necessarily increasing its expected return sufficiently.
Our research points to the need to consider overall portfolio risk more “holistically” in that overweighing a particular factor bet in one “sleeve” of the portfolio might call for a reduction in the other sleeves’ exposures to this risk factor. While this requires somewhat greater statistical sophistication than the “traditional” approach, our paper provides a fairly simple and intuitive methodology for doing so effectively.
How can future research build upon your findings?
Nikolai Roussanov: There are several dimensions for improvement – one obvious direction is to consider even broader asset classes, such as international equity as well as fixed income, currencies, and commodities, which, we know often share exposures to common sources of risk (e.g., see my recent research on inflation risk).
Another direction is to bring more variables that could be useful for capturing sources of investment opportunities as well as common risk exposures, e.g. by considering alternative data sources, as well as textual information, which are becoming increasingly more easily accessible to the emergence of powerful AI tools such as large language models, etc.
Learn more about Professor Nikolai Roussanov.
This research was supported by the Jacobs Levy Center. View the study, “Common Risk Factors in the Returns on Stocks, Bonds (and Options), Redux” on the Jacobs Levy Center’s SSRN page.
Learn more about this research on Knowledge at Wharton.