The Rational Reminder Podcast
Episode 342 - Matthew Ringgenberg: When Do Anomaly Returns Happen?
· Summarized
Key takeaways
- An asset pricing anomaly is a trading signal that predicts future stock returns.
- Anomaly returns typically occur immediately after the release of relevant information.
- The annual formation of portfolios in June can significantly weaken the manifestation of anomalies.
- Current barriers in accessing financial data contribute to the persistence of anomalies.
- Short sellers tend to be informed traders and the high loan fees reflect their confidence in bearish predictions.
- Many cross-sectional predictors do not provide reliable time series predictions.
- Understanding the risk-return trade-off is a vital lesson in investing.
- True success is defined by long-term happiness and fulfillment.
Summary
Introduction to Anomaly Returns
In this episode of the Rational Reminder Podcast, hosts Benjamin Felix and Mark McGrath welcome Matthew Ringgenberg, a Professor of Finance at the University of Utah. The conversation begins by defining an asset pricing anomaly, focusing on Ringgenberg's research surrounding these phenomena. The guest's work predominantly examines the behaviors of short sellers and various types of anomalies, which are signals that predict future abnormal returns.
The Timing of Anomaly Returns
The discussion advances to when anomaly returns manifest in relation to when relevant information is released. Ringgenberg's research reveals that returns tend to occur shortly after the release of information that indicates an anomaly exists. Importantly, this ties into how empirical studies often ignore the precise timing of information release, which can undervalue the potential existence of anomalies.
Impact of Annual Portfolio Formation
The hosts and Ringgenberg dive into the conventional practice of annually forming portfolios in June, identifying it as a critical factor that compromises anomaly returns. This method often occurs long after the relevant information has been released, thereby diminishing the observable returns tied to anomalies. Ringgenberg highlights that academic studies often misstate the strength of anomalies due to this delayed implementation.
Anomalies and Mispricing Debate
The conversation addresses the ongoing debate surrounding the causes of anomalies, weighing the arguments for mispricing against those for risk-based explanations. Ringgenberg’s findings suggest that anomalies can be attributed to delayed processing of information rather than being purely risk-based.
Barriers to Financial Data Access
Ringgenberg shares insights on the barriers researchers and investors face in accessing financial data, which perpetuates the existence of anomalies. Even in an era of information overload, challenges remain, including transaction costs and the speed at which market participants can process incoming information.
Analyzing the Loan Fee Anomaly
Further along in the episode, the hosts discuss Ringgenberg's noteworthy paper on the Loan Fee Anomaly. This concept demonstrates that stocks with high equity lending fees tend to exhibit lower future returns. The reasoning highlights that informed traders, generally more confident about their short positions, are willing to bear these costs, which indicates potentially bearish sentiment.
The Role of Cross-Sectional Predictors
The episode later critiques existing cross-sectional predictors in financial literature, questioning their efficacy in predicting time series returns. Ringgenberg articulates that while some predictors hold value, many lack systematic information, emphasizing that genuine predictability in returns remains elusive.
Teaching Investment Principles
Towards the end of the episode, Ringgenberg shares the key lessons he imparts in his Introduction to Investments course, most notably the importance of understanding the risk-return trade-off. He highlights that real-world financial decisions often involve navigating trade-offs rather than simple calculations.
Defining Personal Success
Ringgenberg concludes with a reflective note on success, underscoring that true success involves maximizing happiness over a lifetime. He suggests that qualitative metrics, such as personal fulfillment, should be viewed as integral to defining one’s success.
Sponsors
- PWL Capital · Meet with PWL Capital: schedule a meeting through Calendly.
Show notes
Today we are joined by the Professor of Finance at the University of Utah, Matt Ringgenberg to discuss everything related to anomaly returns. Matt's research – mainly centred on the actions of short sellers – has been published in all the major journals including the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies. We begin with the definition of an asset pricing anomaly before learning about the anomalies that Matt's research is primarily focused on. Then, we unpack anomaly returns and how they relate to anomaly signal information, what causes anomalies, the risk versus mispricing debate, and the barriers to accessing financial data that allow anomalies to persist. We also weigh Matt's research against its anomaly-denying counterparts, assess anomaly behaviour before and after publicly available signal information, explore models that help to predict future anomalies, and learn more about the economic mechanism underlying asset pricing anomalies. To end, we dive into Matt's paper, 'The Loan Fee Anomaly' and explore the relationship between cross-sectional predictors and market returns, and Matt explains why long-term happiness is the only true marker of success.
Key Points From This Episode:
(0:05:07) Matt Ringgenberg defines an asset pricing anomaly and describes the anomalies his research is focused on.
(0:06:27) When anomaly returns appear relative to the release of anomaly signal information.
(0:07:57) How the annual forming of portfolios in June affects anomaly returns.
(0:08:50) The cause of anomalies, and the risk versus mispricing debate on anomaly returns.
(0:10:35) Unpacking the barriers to accessing financial data that allow anomalies to persist.
(0:13:41) How Matt's rebalancing approach could affect anomaly-denying research.
(0:14:37) Applying his work to valuation-based anomalies and to investors capturing anomaly returns in live-traded portfolios.
(0:16:04) How anomalies behave before anomaly signal information is publicly available.
(0:17:48) Exploring the models that can be used to predict future anomaly signals.
(0:19:05) How anomaly premiums traded on predicted signals compare to trades on actual information release dates.
(0:19:37) Understanding the economic mechanism underlying asset pricing anomalies.
(0:24:38) Dissecting one of Matt's short-selling papers, 'The Loan Fee Anomaly'.
(0:32:51) The relationship between cross-sectional predictors and market returns.
(0:39:11) What Matt hopes to pass on to his students in his Introduction to Investments course.
(0:40:48) How Matthew Ringgenberg defines success.
Links From Today's Episode:
Meet with PWL Capital: https://calendly.com/d/3vm-t2j-h3p
Rational Reminder on iTunes — https://itunes.apple.com/ca/podcast/the-rational-reminder-podcast/id1426530582.
Rational Reminder Website — https://rationalreminder.ca/
Rational Reminder on Instagram — https://www.instagram.com/rationalreminder/
Rational Reminder on X — https://x.com/RationalRemind
Rational Reminder on TikTok — www.tiktok.com/@rationalreminder
Rational Reminder on YouTube — https://www.youtube.com/channel/
Rational Reminder Email — info@rationalreminder.ca
Benjamin Felix — https://pwlcapital.com/our-team/
Benjamin on X — https://x.com/benjaminwfelix
Benjamin on LinkedIn — https://www.linkedin.com/in/benjaminwfelix/
Cameron Passmore — https://pwlcapital.com/our-team/
Cameron on X — https://x.com/CameronPassmore
Cameron on LinkedIn — https://www.linkedin.com/in/cameronpassmore/
Mark McGrath on LinkedIn — https://www.linkedin.com/in/markmcgrathcfp/
Mark McGrath on X — https://x.com/MarkMcGrathCFP
Matthew Ringgenberg on Google Scholar — https://scholar.google.com/citations?user=NArgYXUAAAAJ
Matthew Ringgenberg on LinkedIn — https://www.linkedin.com/in/matthewringgenberg/
Matthew Ringgenberg on X — https://x.com/Ringgenberg_M
University of Utah — https://www.utah.edu/
Davidson Heath on LinkedIn — https://www.linkedin.com/in/davidson-heath-5a28999a/
Management Science — https://pubsonline.informs.org/journal/mnsc
Journal of Financial and Quantitative Analysis — https://jfqa.org/
Morningstar Direct — https://www.morningstar.com/business/brands/data-analytics/products/direct
YCharts — https://ycharts.com/
Andre Chen — https://andrewchen.substack.com/
David Booth | Dimensional Fund Advisors — https://www.dimensional.com/hk-en/bios/david-booth
Papers From Today's Episode:
'A Conversation with Benjamin Graham' — https://www.jstor.org/stable/4477960
'The Loan Fee Anomaly: A Short Seller's Best Ideas' — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3707166
'Do Cross-Sectional Predictors Contain Systematic Information?' — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3459229
Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)
Follow this show on AudioBrevity and new episodes get summarized for you. Create a free account