The Stock Market and Bank Risk-Taking
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.
Financial Regulation and AI: A Faustian Bargain?
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.
The Secular Decline in Interest Rates and the Rise of Shadow Banks
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..
Retired Investors Should Stop Trading So Much
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?
Do indexes time the market?
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.
How Geopolitics is Being Priced in Real Time
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.
Does regulation actually clean up bad behavior?
This paper explores how FINRA’s efforts to discipline “bad brokers” often lead to regulatory leakage—problematic advisors leaving one firm only to resurface elsewhere.
Institutions’ return expectations across assets and time
This paper shows how return expectations are formed: largely via a common “building-block” model (dividend yields, earnings growth, inflation, P/E changes), and how they vary across asset classes, time periods, and institutions.
How costly are cultural biases? Evidence from FinTech
This paper examines how cultural biases affect high-stakes decisions in a FinTech setting, showing that even when information is the same, the social groups we prefer can lead us into worse outcomes. The result: bias isn’t just unethical, it’s expensive.
Policy news and stock market volatility
This paper builds a new measure of “equity market volatility” using newspaper articles and finds that policy-related news (fiscal, monetary, trade, regulation) explains a large share of volatility spikes.
Momentum factor investing: Evidence and evolution
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.
How New Laws Reshaped Stock Market Participation
Over the past two decades, middle-class Americans have quietly changed how they invest. This paper shows that the share of investable wealth held in stocks has risen—and become systematically linked to age. The driving force? The Pension Protection Act (PPA), which made target date funds (TDFs) the default option in retirement plans.
Do persuasive personalities deliver subpar performance?
Using thousands of real pitch recordings, the authors find that presentation style drives funding success even when fundamentals are identical. The catch: the most persuasive founders don’t always build the best businesses.
Do Mutual Fund Flows Really Say What We Think They Say?
For decades, mutual fund flows have been a workhorse variable for understanding investor behavior, market sentiment, and price impact. But what if the way we measure them distorts the story?
How does inflation impact trading?
When inflation rises, trading behavior changes in systematic ways: liquidity deteriorates, bid-ask spreads widen, and investors trade less on fundamentals and more on short-term noise.
Should Limited Partners use AI to assist with investment decisions?
This paper reviews early evidence that algorithms can read GP reports, forecast cash flows, and benchmark funds. But it also shows where the limits lie.
When the Machine Becomes the Portfolio Manager
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.
Thematic Investing: a Risk-Based Perspective
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 TIPS Ladder Plus Stocks: Retirement Planning Solved?
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.
When LLMs Go Abroad: Why U.S. AI Models Are Too Optimistic on Chinese Stocks
Large language models are increasingly being used to forecast stock prices and guide investment decisions. But what happens when these models cross borders?