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.
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.
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.
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.
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 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.
Large language models are increasingly being used to forecast stock prices and guide investment decisions. But what happens when these models cross borders?
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.
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.
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.
Rather than streamlining oversight, overlapping mandates between regulatory agencies create confusion, redundancy, and sometimes outright inconsistency.
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.
A longstanding belief in household finance is that wealthier people should buy less insurance because they can afford to self-insure. But this new research turns that idea on its head. This analysis shows that wealthier U.S. households actually purchase more life and property insurance - not less.
Simpler structures—like low-dimensional lotteries or intuitive cash flows—can actually encourage investors to take on more risk.
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.
Can machine learning models help us exploit stock market anomalies more effectively? This paper says yes—but with a few important caveats. By applying gradient boosting algorithms to a wide array of established anomalies (like value, momentum, and quality), the authors show that machine learning methods can significantly improve the performance of long-short strategies.
This paper explores how value, momentum, low-risk, and size factors explain differences in corporate bond returns across firms and over time.
Younger and less-wealthy individuals are more prone to increasing their exposure to riskier assets in low-interest environments. Investors experiencing losses are more likely to seek higher yields.
Over 75% of the cross-sectional variation in P/E ratios is driven by future return differences, not growth expectations. This challenges many common asset pricing models and changes how investors should think about value, growth, and long-term return forecasting.
This study investigates whether firms' divestitures of pollutive assets genuinely contribute to environmental sustainability or merely serve as greenwashing tactics.
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