Our guests this week recently published a paper that calls those core ideas of asset pricing theory into question. We speak with Andrew Chen, Principal Economist at the Federal Reserve's Capital Markets Section and Alejandro Lopez-Lira, Assistant Professor of Finance at the University of Florida about their new paper "Does Peer Reviewed Theory Predict the Cross Section of Stock Returns." The paper compared anomalies with behavioral and risk-based explanations to others that were purely data mined. They found no difference in out of sample returns among the 3 groups. In the interview, we take a deep dive into their findings and what they mean for both the world of academic research and real-world investment strategies.
00:00 - Intro
03:14 - How Andrew and Alejandro got the idea for the paper
04:42 - What is an anomaly?
07:15 - Why it is important to study anomalies
08:14 - A summary of the anomalies literature
11:08 - The risk-based and behavioral explanations for why factors work
16:01 - What is data mining?
18:37 - A high level summary of the paper
22:32 - What is a t-stat and why is it important?
24:27 - Inside the process of mining accounting data
28:39 - Comparing data mined factors to traditional factors
37:18 - Data mining using tickers
40:00 - Why did performance of all the anomalies deteriorate in the post 1990 period?
44:08 - Does economic theory help predict stock returns?
50:02 - Future areas for follow up research
DOWNLOAD THE PAPER
https://arxiv.org/pdf/2212.10317.pdf
FOLLOW ANDREW ON TWITTER
https://twitter.com/achenfinance
FOLLOW ALEJANDRO ON TWITTER
https://twitter.com/alejandroll10
SEE LATEST EPISODES
https://www.validea.com/excess-returns-podcast
FIND OUT MORE ABOUT VALIDEA
https://www.validea.com
FIND OUT MORE ABOUT VALIDEA CAPITAL
https://www.valideacapital.com
FOLLOW JACK
Twitter: https://twitter.com/practicalquant
LinkedIn: https://www.linkedin.com/in/jack-forehand-8015094
FOLLOW JUSTIN
Twitter: https://twitter.com/jjcarbonneau
LinkedIn: https://www.linkedin.com/in/jcarbonneau

