With over nearly 150 years of data, the study finds that when inflation and interest rates rise, stocks and bonds tend to move together, reducing diversification benefits. This has critical implications for portfolio construction and risk management.
US exceptionalism provided the same explanation for the outperformance of US stocks in the 1990s. However, that regime changed. From 2000-2007, while the S&P 500 Index returned just 1.9% per annum (underperforming riskless one-month Treasury bills by 1.3% per annum), the MSCI EAFE Index returned 5.6% per annum, and the MSCI Emerging Markets Index returned 15.3% per annum.
This study improves how private equity (PE) fund performance is evaluated, which is crucial for investors making allocation decisions.
The listing domicile explained about 50% of the valuation gap. In other words, US-listed stocks are substantially more expensive than internationally listed stocks for no reason other than the place of listing.
NAV timing investors could potentially create trading strategies which would systematically transfer wealth from buy-and-hold investors to themselves.
The following guest piece outlines the SIMPLE framework (SIMPLE) for making better decisions. SIMPLE was developed by a Navy SEAL with combat and business experience. An application of the SIMPLE framework, applied to financial advisors, is at the end of the piece.
This paper seeks to address three pivotal questions that explore the broader economic and social impacts of IPO activity, particularly its role in influencing stock market participation through localized attention and wealth effects.
While the media headlines are preaching doom, the fundamentals are telling a very different story—credit spreads have widened, and EBITDA multiples are the lowest they have been in a decade. The bottom line is that for investors able to accept its limited liquidity, private, senior, secured and sponsored by private equity direct lending continues to be a compelling component of a diversified portfolio deliver what has always attracted investors: high current income, resilience through market cycles, and a disciplined approach to risk management. We are far from a bubble.
In 2024 investors were provided with nine lessons. Many of them are repeats from prior years. Unfortunately, too many investors fail to learn them—they keep making the same errors.
Divestment, a commonly used strategy, involves withdrawing support from companies that contribute to these issues, with the intention of creating positive societal change. Despite its appeal, the connection between divestment actions and their actual impact on society remains unclear.
What matters is not the expectation of future growth, but the deviation between projected growth and realized growth, which, by definition is a surprise, and, thus, is not forecastable.
Because AI systems can produce hundreds of seemingly coherent theoretical explanations for mined empirical results, investors need to establish high hurdles before allocating to anomaly-based strategies.
This paper investigates how modeling choices impact MLM outcomes such as cross-sectional return predictability.
Given the similar net returns that UMM and LMM loans have delivered, allocators should consider diversifying across borrower size cohorts. Since LLM loans are somewhat riskier, careful due diligence should be performed in terms of a lender’s credit loss history, fees/expenses, and use of leverage.
Advisors and managers will have to adopt a more nuanced view of risk as recognition of the frequency of equity underperformance becomes widespread.
Simple, easy-to-implement, systematic formula-based investing can still generate market outperformance, providing investors with efficient exposure to well-documented factor premiums.
One critical, yet often overlooked, choice is how stocks are weighted in the objective function during training, with equally weighted (EW) approaches being the norm. This paper investigates how such choices impact cross-sectional return predictability and the performance of trading strategies derived from these predictions, focusing on the interplay between objective function design and model outcomes.
A critical task in stock selection is identifying a firm’s true profitability. Given the potential of AI to deal with large data, an important question is: Can AI outsmart seasoned analysts?
Managers are more likely to vote for analysts who exhibit greater “say-buy/whisper-sell” behavior toward these man agers. This suggests that analysts reduce the accuracy of their public recommendations, thereby maintaining the value of their private advice to funds.
Systematic factor-driven value strategies have underperformed broad market indices (such as the S&P 500) over the past 15+ years. That has led many to question [...]
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