Can Machine Learning Predict Factor Returns?
Can machine learning techniques improve the prediction of cross-sectional factor returns in equity markets?
Can machine learning techniques improve the prediction of cross-sectional factor returns in equity markets?
Today, machines are not only processing data but interpreting narratives, forecasting returns, and constructing investment theses once reserved for humans. This paper examines how AI is reshaping the role of the discretionary PM, arguing that the edge isn’t disappearing — it’s migrating.
Today, phrases like “HODL” and “buy the dip” have become rallying cries for equity investors. But is this mindset always correct? Could there come a time when buying dips or holding at all costs turns out to be a mistake? To dig deeper, let’s look at insights from Michael Mauboussin and Dan Callahan’s recent paper, Drawdowns & Recoveries: Base Rates for Bottoms and Bounces, and consider what the evidence tells us about the nature of drawdowns and recoveries.
Candès, Hastie, Hogan, Kahn, Luo, and Spector develop a novel framework to measure whether thematic baskets capture real, coherent risks that matter for investors. Their findings challenge conventional risk models and highlight both the dangers and opportunities of betting on investment “themes.”
Buffer ETFs have become one of the fastest-growing product lines in finance. But what risks are buffer investors carrying without realizing it? Let's zoom in on the two areas where they fall short and propose potential solutions that seek to address these issues.
A sufficient portfolio consists solely of a ladder of inflation-indexed bonds, such as U.S. Treasury Inflation-Protected Securities (TIPS), and a stock market index fund. We explain theoretically and demonstrate empirically how this strategy is less risky and more effective at maximizing lifetime retirement income than are methods commonly used by financial advisors.
On the surface, buffer ETFs appear attractive: they seek to capture some upside while mitigating a portion of losses. However, this does not mean they are risk-free. In fact, under certain market conditions, these products can significantly underperform.
Our friends Corey Hoffstein and Rodrigo Gordillo over at Return Stacked have done some interesting research on the potential for gold to improve your run-of-the-mill [...]
Large language models are increasingly being used to forecast stock prices and guide investment decisions. But what happens when these models cross borders?
As portfolios incorporate more sustainability data—from climate impact assessments to labor practices and board diversity metrics—a critical question emerges: Does this wealth of ESG information actually enhance portfolio performance, or is it merely additional data without tangible investment value?
Most platforms now intermediate—pooling loans into short-dated portfolios and, increasingly, offering bank-like products that absorb liquidity risk. Why did credit marketplaces evolve away from pure peer-to-peer? This paper quantifies the welfare value of those design choices.
A historical review of Buffett’s implementation of diversification and concentration in practice, as well as his perspective on these concepts, documents a long tradition of heterodox thinking and application.
Equity duration has increased dramatically. As firms reinvest more and delay payouts to the future, asset prices become more sensitive to changes in expected returns rather than fundamentals.
In the ongoing debates about the virtues of active versus passive investment strategies, a fundamental problem undermines meaningful discussion: there is no universally accepted definition of what constitutes a "passive" strategy.
This paper rethinks how financial regulators should design stress tests. Rather than treating stress testing as a pass/fail assessment, the authors show it should be viewed as an exercise in information gathering.
Buffer ETFs have moved from niche idea to mainstream product in just a few years. That’s not just growth—it’s a trend! But what’s behind it? Are buffer ETFs a breakthrough in risk management… or are they more complex and potentially riskier than they appear?
Rather than streamlining oversight, overlapping mandates between regulatory agencies create confusion, redundancy, and sometimes outright inconsistency.
Letdin, Seagraves, and Sirmans advanced our understanding of REIT asset pricing by developing and rigorously testing six REIT-specific return factors—size, value, momentum, earnings quality, low volatility, and short-term reversal—using decades of data.
A longstanding belief in market finance is that short-term funding markets like repo are relatively stable and transparent. But this new research turns that idea on its head.
This paper reveals a striking pattern in U.S. mortgage markets: minority borrowers are more likely to complete applications, be approved, and avoid default when they interact with minority loan officers.
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