The wealth of information contained in daily stock returns has been hiding in plain sight—and when properly extracted, it generates remarkable predictive power for future performance.
CAPE has long been a cornerstone of long-horizon return forecasting. Critics argue that its predictive power has faded in recent decades. This paper pushes back.
Trend following is finally moving while U.S. stocks are flat. And so—like with most assets or strategies that post strong returns—investors may be eyeing this particular strategy and asking: Is it time to get in? The answer, while not surprising, is definitely nuanced.
Intangible assets—things like brand reputation, proprietary knowledge, and organizational capabilities—have become more valuable than physical factories and equipment with many studies estimating that intangibles now [...]
Which defensive strategies have actually worked, and do the conclusions survive when we evaluate them over multiple centuries rather than a few decades?
Once borrowing is realistically restricted, the Sharpe ratio can stop lining up with what investors actually care about: utility. This paper argues that in this constrained world, the geometric mean is a better compass.
Artificial intelligence is rapidly transforming the investment landscape in ways that extend far beyond algorithmic trading and robo-advisors. One of AI's most promising applications lies [...]
Markets are often assumed to be efficient across horizons, with prices reflecting fundamentals regardless of who holds the asset or for how long. Recent research challenges this assumption by showing that the investment horizon of shareholders itself shapes prices and future returns.
While public listings are often viewed as a sign of strength, scale, or access to capital, recent research suggests a more subtle consequence: going public changes how banks take risk.
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 [...]
Financial regulation has always faced a trade-off between simplicity and precision. Simple rules are transparent and robust, but often miss where risks actually build up. More sophisticated tools can be more precise, but they are harder to understand, harder to explain, and sometimes change behavior in unexpected ways.
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"
Over the last 20 years, a massive shift has occurred, with "shadow banks"- non-depository institutions like Quicken Loans -capturing nearly half of all originations. While many attribute this to new technology or post-crisis rules, recent research reveals a deeper economic catalyst: the secular decline in interest rates..
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.
It is well-known that box spreads offer investors the ability to lend via the options market at similar rates to Treasury Bills. But there is another, less popular side of the box spread market – borrowing money. This articles dives into the mechanics of how to use box spreads to borrow at low costs.
Retirement creates a sudden jump in leisure time. That should reduce information-processing barriers. The question is: does having more time change how people trade, and does it improve outcomes?
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.
By reading earnings calls and analyst reports at scale, algorithms can identify who is applying pressure, who is being targeted, which instruments are used, and how firms respond. The result is a new way to observe geopolitical risk as it actually enters corporate decision making.
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