Academic Finance Research and Insights

Wes Talks with Belle about Creating Your Own ETF

By |August 10th, 2023|ETF Operations, Podcasts and Video, Research Insights, Media, Tax Efficient Investing, ETF Investing|

In this episode host Belle Osvath, CFP® talks with Dr. Wesley Gray the founder of ETF Architect and Alpha Architect, about how advisors can create their own ETFs which can be used to help manage client funds and taxes. They discuss the creation process, the cost, and what type of advisory practice would benefit the most from their own ETF.

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Investor demand, rating reform and equity returns

By |August 7th, 2023|Price Pressure Factor, Factor Investing, Research Insights, Basilico and Johnsen, Academic Research Insight, Momentum Investing Research, Active and Passive Investing|

The traditional financial theory attributes security returns to market- or factor-based risk, with no role ascribed to other influences. In this research, the authors argue for including investor demand as an additional variable in explaining returns.  Can changes in investor demand generate systematic changes in security returns?

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The Quality Factor and the Low-Beta Anomaly

By |August 4th, 2023|Larry Swedroe, Factor Investing, Research Insights, Low Volatility Investing|

The empirical evidence demonstrates that returns to the low-beta anomaly are well explained by exposure to other common factors, and it has only justified investment when low-beta stocks were in the value regime, after periods of strong market and small-cap stock performance, and when they excluded high-beta stocks that had low short interest.

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Conditioning anomalies using retail attention metrics

By |July 28th, 2023|Relative Sentiment, Research Insights, Factor Investing, Guest Posts|

By using a novel measure of investor attention, generated from InvestingChannel’s clickstream data on online financial news consumption, we can identify broad groups of stocks which are less efficiently priced and therefore where anomalies such as Value and Momentum are likely to produce greater cross sectional differentiation in returns.  We also apply these groupings to proprietary ExtractAlpha stock selection signals.

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