Retail Investors and the Mispricing Puzzle
Institutional investors are frequently spoken of in the finance literature as “smart money” while retail investors are considered “noise traders” who suffer from a variety [...]
Institutional investors are frequently spoken of in the finance literature as “smart money” while retail investors are considered “noise traders” who suffer from a variety [...]
Long volatility should be considered a factor that earns positive returns over the long term. At least that's what One River Asset Management’s Patrick Kazley suggests in his piece "Heretical Thinking: The Long Volatility Premium"
Past returns often include non-repeatable revaluation alpha. Since structural alpha is the only component likely to persist, it’s essential for investors to distinguish this from one-off valuation windfalls before placing trust—or capital—in any factor or fund.
After years in what can be now called one of the worst (if not the worst) period for value investing, many investors have packed their bags and called it quits. We’ve heard this be said over and over again; and yet, many of their arguments look extremely compelling. So are they in the right? Let's examine.
This paper shows there is a durable, stock-specific momentum component tied to how prices react to firm news around earnings dates. The result is a cleaner, lower-risk way to capture momentum without leaning so heavily on broad factor moves.
ChatGPT and similar large language models can enhance traditional investment strategies through superior interpretation of financial news. The improvements are economically meaningful, statistically robust, and persist under realistic implementation constraints.
Success lies not in collecting exotic anomalies like rare zoo specimens, but in understanding the economic forces that drive sustainable return patterns. Focus on strategies with solid macroeconomic foundations, maintain healthy skepticism about new discoveries, and always account for implementation costs.
Momentum works, across markets, time periods, and portfolio designs. But it also has weak spots, especially during market reversals, which risk-aware construction can help manage.
The size effect is alive and well, but it's more nuanced than we once thought. Rather than viewing it as a simple "small beats large" phenomenon, we should understand size as a critical dimension that shapes how effectively other investment factors perform.
Can machine learning techniques improve the prediction of cross-sectional factor returns in equity markets?
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.”
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.
Fueled by the persistent failure of active management, passive investing now commands the majority of assets under management.
This paper reveals a striking pattern in U.S. stock markets: the prices of individual stocks often reverse direction at the very end of the trading day. Using high-frequency data, the authors find that the last few minutes—particularly the closing auction—are dominated by large institutional flows that cause temporary price pressure. This is followed by a reversal the next day.
Diversification is the only free lunch in investing. If you’ve spent even a day exploring the world of finance, you’ve likely encountered this common truism. But chances are, you’ve also heard stories of someone turning a small stake into millions by going all-in on just one or two stocks. That contrast raises a natural question for many investors: how many stocks should I actually own in my portfolio? Too many stocks, and you might be leaving opportunities on the table. Too few and you risk losing your shirt! So how do we strike a balance?
This paper explores how value, momentum, low-risk, and size factors explain differences in corporate bond returns across firms and over time.
If you’re a factor investor, there will come a time where you will have to choose between mom and dad: Should you combine or separate your factor exposures? And make no mistake: You will have to make a decision! While there’s no right answer, the way you structure your portfolio can have significant implications for returns, costs, and even your own behavior as an investor. Let’s walk through the logic behind both approaches.
© Copyright 2025 alpha architect | All Rights Reserved | Home | Terms of Use | Privacy Policy | Disclosures | Subscribe | Contact Us
