Time-Varying Drivers of Stock Prices
This paper examines the time-varying roles of subjective expectations in driving stock price and return variations.
This paper examines the time-varying roles of subjective expectations in driving stock price and return variations.
An anomaly is a pattern in stock returns that deviates from what is expected based on established financial theories or models. These patterns can sometimes [...]
The propagation of factors actually reflect valid characteristics of the markets and market fluctuations.
The bottom line is that returns to the low volatility anomaly have only justified investing when low-volatility stocks were in the value regime, after periods of strong market performance, and when they excluded high-volatility stocks that have low short interest (providing clues as to how to improve its performance). This may be why live funds have been generating large negative alphas once we account for common factor exposures.
This paper examines the level of financial literacy across the 27 EU member states, using data from the 2023 Flash Eurobarometer 525 survey.
The growth rate of private credit has been so rapid (growing to nearly $2 trillion by the end of 2023, roughly ten times larger than it was in 2009), that concerns about there being a bubble have been raised.
Measures of asset growth add considerable explanatory power to asset pricing models, but wait, there’s a twist. The formulation for measuring asset growth in risk [...]
Greenwood and Sammon’s findings of a disappearing index effect provides further support for the findings of McLean and Pontiff, Does Academic Research Destroy Stock Return Predictability? 2016. Once anomalies are well recognized by the market they decline and may even disappear, though limits to arbitrage can allow them to persist. Their findings also provide support for Andrew Lo’s The Adaptive Markets Hypothesis (2004). The bottom line is that markets are becoming more efficient, raising the hurdles for active managers to generate alpha.
By quantifying how non-performance-based fees dominate the cost structure, this research questions whether current fee models effectively align with investor interests, which could influence future fee arrangements and industry standards.
The authors of the research discussed developed a machine learning model that can accurately predict trading volume for individual stocks. They then demonstrated how this model can be used to construct a portfolio that outperforms a traditional market-cap weighted portfolio.
Full exposure to domestic equities. Full exposure to international equities. Full exposure to REITs. No exposure to commodities. Full exposure to intermediate-term bonds.
If the task is to identify a firm’s true profitability, can AI outsmart seasoned analysts?
The hurdles to adding alpha for active managers are getting higher—investment practitioners make use of it as soon as or shortly after it is available.
Access to automated online credit boosts sales, transactions, and customer capital for firms, particularly in regions underserved by traditional banks.
There’s no reason to think that the use of AI should lead to persistent fund outperformance, with any advantages gained likely being short lived.
AI-powered growth concentrates among larger firms and is associated with higher industry concentration. Our results highlight that new technologies like AI can contribute to growth and superstar firms through product innovation.
Because the Sahm rule focuses solely on the unemployment rate, caution is warranted before assuming it is signaling a recession.
The following factor performance modules have been updated on our Index website.
How can textual analysis of business news, specifically The Wall Street Journal (WSJ), be used to measure the state of the economy?
An index-tracking approach generally lacks flexibility, which detracts from performance, leaving returns on the table. Intelligent design can overcome such issues. For example, an S&P 500 Index could choose to rebalance one month ahead of the scheduled reconstitution, minimizing the impact of reconstitution. Direct index funds are already engaging in such strategies with ETFs.
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