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Andrew Chen: "Is Everything I was Taught About Cross-Sectional Asset Pricing Wrong?!" | RR 316
13 segments available
Meet with PWL Capital: https://pages.pwlcapital.com/en-ca/contact-us?utm_source=content&utm_medium=youtube&utm_campaign=rationalreminder_yt Are you curious about the hidden factors driving your investment decisions? Today’s guest is Andrew Chen, a Principal Economist at the Federal Reserve Board who focuses on monetary policy and financial stability. Published in leading journals, his research informs key policy decisions and helps shape the Federal Reserve’s strategy for managing economic challenges effectively. In this episode, Andrew delves into the intricacies of meta-research and asset pricing, focusing on cross-sectional asset pricing predictors, replication, and out-of-sample performance in factor investing. We discuss the significance of open-source data and transparency, highlighting Andrew's creation of the Open Source Asset Pricing project, an indispensable and comprehensive dataset for asset pricing predictors. We also address the challenges of replicating financial studies, publication bias, data mining, and false discovery rates, with Andrew offering practical insights on how these factors impact financial research and investment decisions. For actionable insights that could refine your investment strategies and enhance your understanding of financial research, don’t miss this fascinating conversation! Timestamps: 0:00:00 Intro 0:04:44 Andrew defines asset pricing factors and how it is different from a predictor 0:06:22 Andrew explains how many predictors there are 0:10:55 How many asset pricing factors Andrew was successfully able to reproduce 0:15:58 The implications of this research for the supposed “replication crisis” in cross sectional asset pricing 0:22:01 How the false discovery rate relates to publication bias and out of sample returns 0:27:10 Whether these are the worst-case transaction costs, or if Andrew uses cost mitigation techniques 0:34:09 Which factors, or factor combinations, had the strongest investable expected returns in Andrew's data 0:38:33 How peer-reviewed factors with strong theoretical underpinnings perform relative to naively data mined factors 0:43:54 What this tells us about the academic peer review process 0:47:10 What this tells us about the usefulness of machine learning for asset pricing research 0:51:06 The implications for people using peer-reviewed research for asset allocation decisions 0:54:37 Andrew describes the current state of cross sectional asset pricing 0:58:54 Andrew defines success in his life Links From Today’s Episode: Rational Reminder on Apple Podcasts — https://podcasts.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 YouTube — https://www.youtube.com/@rationalreminder/ Rational Reminder Email — info@rationalreminder.ca Benjamin Felix — https://www.pwlcapital.com/author/benjamin-felix/ Benjamin on X — https://x.com/benjaminwfelix Benjamin on LinkedIn — https://www.linkedin.com/in/benjaminwfelix/ Cameron Passmore — https://www.pwlcapital.com/profile/cameron-passmore/ 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 Andrew Chen — https://sites.google.com/site/chenandrewy/ Federal Reserve Board — https://www.federalreserve.gov/ Andrew Chen on LinkedIn — https://www.linkedin.com/in/andrew-chen-63394169/ Andrew Chen on X — https://x.com/achenfinance Books From Today’s Episode: The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics — https://www.amazon.com/dp/0199681147 Papers From Today’s Episode: Andrew Chen, Tom Zimmermann, ’Open Source Cross-Sectional Asset Pricing’— https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3604626 Kewei Hou, Chen Xue, Lu Zhang, ’Replicating Anomalies’ — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3275496 R. David McLean, Jeffrey Pontiff, ’Does Academic Research Destroy Stock Return Predictability?’ — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2156623 Ilia D. Dichev, ’Is the Risk of Bankruptcy a Systematic Risk?’ — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=99868 Campbell R. Harvey, Yan Liu, Caroline Zhu, ‘...and the Cross-Section of Expected Returns’ — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2249314 Andrew Chen, Mihail Velikov, ‘Zeroing in on the Expected Returns of Anomalies’ — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3073681 Victor DeMiguel paper relating to which factors have the strongest investable expected returns — Andrew Chen, Alejandro Lopez-Lira, Tom Zimmermann, ‘Does Peer-Reviewed Research Help Predict Stock Returns?’ — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4308069
Segments Timeline
Introduction to the Episode
In this opening segment, hosts Benjamin Felix and Mark McGrath introduce the Rational Reminder podcast and set the stage for a compelling discussion with Andrew Chen, a Principal Economist at the Federal Reserve Board. They express excitement about the episode's focus on asset pricing and the insights Andrew will share regarding financial research and investment strategies.
"[Music] this is the rational reminder podcast a weekly reality check on sensible investing and financial decision- making from two Canadians we are hosted by me Benjamin Felix portfolio manager at pwl..."
Defining Asset Pricing Factors
Andrew Chen explains the concept of asset pricing factors and how they differ from predictors. He discusses the common confusion in terminology within the finance community, emphasizing the importance of clarity in understanding what constitutes a predictor versus a factor in asset pricing.
"like um how it sounds you know it's something that predicts asset returns uh like a very popular one is when you take book Equity of a firm and divide by the market value you get this variable that re..."
The Predictor Zoo: Understanding the Numbers
In this segment, Andrew addresses the overwhelming number of predictors in asset pricing literature, often referred to as the 'predictor zoo.' He estimates that there are around 200 well-documented predictors, clarifying the distinction between predictors and anomalies while discussing the challenges of categorizing them.
"predictors that are clearly documented in the academic literature um I would say there's roughly 200 I say roughly because it's not always very clear if one predictor is different than another predict..."
Replication Crisis in Asset Pricing
Andrew discusses the implications of his research on the replication crisis in cross-sectional asset pricing. He highlights the importance of replication in validating financial studies and the challenges faced by researchers in achieving consistent results across different studies.
"uh let let me let me back up a bit and say that of those 300 like variables only 200 actually were shown to predict returns in the original papers that kind of the a major comment that we wanted to ma..."
False Discovery Rates and Publication Bias
This segment delves into the relationship between false discovery rates, publication bias, and out-of-sample returns in financial research. Andrew explains how these factors can mislead researchers and investors, emphasizing the need for transparency and rigorous methodology in asset pricing studies.
"okay so I guess the replication crisis is interpreted in like a big way um you could mean replication crisis in that you just can't write the code to reproduce the numbers in the original papers that'..."
Transaction Costs in Asset Pricing
Andrew addresses the impact of transaction costs on asset pricing strategies. He discusses whether the transaction costs are the worst-case scenario and shares insights on cost mitigation techniques that can enhance the effectiveness of investment strategies.
"returns uh sure okay there's there's a lot in there um okay so public let's let's start with uh publication bias we haven't talked about that yet publication bias is like I was alluding to that no one..."
Strongest Investable Factors
In this segment, Andrew reveals which factors or combinations of factors have shown the strongest investable expected returns based on his research. He provides insights into how these factors can be utilized in practical investment strategies.
"but uh I mean there are definitely caveats on this like I mentioned people argue about how to measure transaction costs ours cost is the effective bit ass spread which kind of you can think of as assu..."
Peer-Reviewed vs. Data-Mined Factors
Andrew compares the performance of peer-reviewed factors with strong theoretical foundations against naively data-mined factors. He discusses the implications of these findings for investors and the importance of relying on robust research in asset allocation decisions.
"returns uh so as I uh kind of saying um once you once you account for trading cost and you account for like just modern ER of Technology nothing really does much there's some stuff in the tals but you..."
Insights on the Peer Review Process
This segment explores what Andrew's findings reveal about the academic peer review process in finance. He discusses the strengths and weaknesses of the current system and how it affects the credibility of financial research.
"is um this touches on this recent paper by uh by myself and Al Alejandra Lopez L and Tom Zimmerman um so uh the short answer is that it it you know this even the stuff with the strongest theoretical u..."
Machine Learning in Asset Pricing Research
Andrew shares his thoughts on the usefulness of machine learning techniques in asset pricing research. He discusses the potential benefits and challenges of integrating machine learning into traditional financial research methodologies.
"general so okay so um I think uh this is where uh I I want to uh be very cautious um uh cuz I I don't want to extrapolate you know I think um I think now that we have llms everyone kind of gets a sens..."
Using Peer-Reviewed Research for Asset Allocation
In this segment, Andrew discusses the implications of his research for individuals using peer-reviewed studies to inform their asset allocation decisions. He emphasizes the importance of critical evaluation of research findings before applying them in practice.
"research uh so there there's two ways to to think about this question um one way is to think about machine learning just as like purely statistical methods for appr for approaching um research or for ..."
Current State of Cross-Sectional Asset Pricing
Andrew provides an overview of the current state of cross-sectional asset pricing. He summarizes key trends and developments in the field, highlighting areas of ongoing research and potential future directions.
"still useful is it productive you know cross-sectional asset pricing has evolved a lot um I think the one reason why the I've been critical of this Harvey L and Zoo paper for um confusing false and in..."
Defining Success in Life
In the closing segment, Andrew reflects on what success means to him personally. He shares insights into his life philosophy and how it relates to his work in economics and finance.
"define success in your own life uh so um so I what I try to do every once in a while is try to think about um what it'll feel like to be at the end of my life and to be looking back on my life um and ..."