Regulatory fragmentation drags down efficiency.
Rather than streamlining oversight, overlapping mandates between regulatory agencies create confusion, redundancy, and sometimes outright inconsistency.
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.
Handy and Meksi provided a clear warning: relying on past performance to select CTAs is a strategy fraught with risk, largely due to behavioral biases that distort our perception of skill and persistence. For investors, the lesson is to stay humble, diversify, and focus on robust processes rather than chasing yesterday’s winners.
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.
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?
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.
Is volatility (the standard deviation of returns) a good measure of the risk that investors actually care about?
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.
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.
The empirical research (for example, here, here, here and here) on insider trading demonstrates that insider transactions have significant predictive power for future stock returns [...]
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 article examines and compares, from a digital signal processing (DSP) time domain perspective, several filters that are modeled on the assumption that the input follows a second order process, i.e., the input contains a linear trend. These filters are, by design, better able to track linear trends than some other more commonly-used filters, such as moving average, exponential smoothing, etc., which exhibit lag, or a time delay, in response to trends. Filters modeled on a second order process are commonly referred to in the technical analysis literature as “zero lag” filters.
Modern Portfolio Theory (MPT) has long served as a foundational framework for asset allocation and portfolio construction. This concept remains influential in both academic finance and practical investment management. But the question investors face today is not whether MPT was revolutionary—it clearly was—but whether its insights still hold up under real-world conditions, decades later.
This study investigates whether firms' divestitures of pollutive assets genuinely contribute to environmental sustainability or merely serve as greenwashing tactics.
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