Скачать или смотреть Challenging the Foundation of Asset Pricing Theory with Andrew Chen and Alejandro Lopez-Lira

Those of us that invest using factors have been taught that there needs to be a reason why they work. We have been taught that for their excess returns to persist in the future, there should be a behavioral or risk-based explanation as to why they exist in the first place. If that assumption is wrong, it would call into question the validity of much of the work that has been done in asset pricing research and would also have significant implications for real world investment strategies build using the research.

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

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