AgPa #83: How Much of the US Market is Passive?

The passive ownership share is double what you think it is (2024)
Alex Chinco (URL), Marco Sammon (URL)
Journal of Financial Economics, URL/SSRN

After my post on passive investing (see AgPa #77) and its consequences for active managers, I had a long and very interesting discussion with David Einhorn about the issue. David was very gracious with his time and we ended up agreeing on many things, but also agreed to disagree on a few others. Overall, I think it is fair to say that I am still somewhat more supportive for passive than he is.

So what I am going to do over the following weeks is to challenge my views further. For that purpose, I went back to the episode of the Rational Reminder podcast with Michael Green (URL) from Simplify Asset Management. Mike describes the potential problems of passive investing in great detail and brings a lot of arguments to the table. He also mentions some interesting research papers on the subject. This week’s AGNOSTIC Paper is the starting point and attempts to measure how much of the US equity market is actually passive. Spoiler: it is hard to say precisely, but probably much more than most people think…

  • Trading data suggest that 1/3 of the US market is passive
  • Index changes trigger massive trading volumes
  • Passive trading affects prices – but (usually) not on reconstitution day

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AgPa #82: Equity Risk Premiums and Interest Rates (2/2)

Expected Stock Returns When Interest Rates Are Low (2022)
David Blitz
The Journal of Portfolio Management 48(7), URL/SSRN

The second AGNOSTIC Paper on equity risk premiums when interest rates are high(er). This one was actually published before the last one, so David Blitz deserves credit for the original idea. He also examines a longer and more comprehensive dataset that serves as a nice out-of-sample test. So I think it makes sense to conclude the posts on equity risk premiums and interest rates with this more comprehensive paper.

  • Equity risk premiums were lower when interest rates are higher
  • Controlling for other factors doesn’t change the negative relation
  • EPS growth seems to explain the pattern

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AgPa #81: Equity Risk Premiums and Interest Rates (1/2)

Honey, the Fed Shrunk the Equity Premium: Asset Allocation in a Higher-Rate World (2024)
Thomas Maloney
The Journal of Portfolio Management 50(6), URL/AQR

Risk-free interest rates, the most fundamental anchor of asset prices, increased dramatically in 2022 and are still considerably higher than over the last 10+ years. At the same time, equity markets around the world posted strong performance in 2023 and 2024 (so far). Many investors thus wonder how this fits together. Why should we pay the same multiple for stocks when the risk-free alternative is much better than a few years ago? Or more technically, why should we accept such a low equity risk premium? This week’s AGNOSTIC Paper is the first of two that sheds some light on this (very important, but also very difficult) issue.

  • Equity returns and risk-premiums were lower in higher-rates environments
  • EPS growth, valuations, and interest rate changes explain the effect
  • Treasuries and absolute-return strategies historically benefitted from higher rates

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AgPa #80: Forget Factors and Keep it Simple?

Keeping it Simple: The Disappearance of Premia for Standard Non-Market Factors (2023)
Avanidhar Subrahmanyam
SSRN Working Paper, URL

This week’s AGNOSTIC Paper is almost a cheat as it is only 3 pages long. I found the paper in the newsletter of a German journalist and thought it is so unconventional that I have to write about it. The author, Avanidhar Subrahmanyam, is a well-known financial economist at the UCLA School of Management and articulates a very simple statistical critique on factor investing. I believe it is important to seek disconfirming evidence, so I regard it as duty to look at this paper with an open mind.

  • Only two factors are significant over the last 27+ years

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AgPa #79: The Momentum OGs – 30 Years Later

Momentum: Evidence and insights 30 years later (2023)
Narasimhan Jegadeesh, Sheridan Titman
Pacific-Basin Finance Journal, URL/SSRN

Momentum is one of the strongest phenomena in financial markets. Narasimhan Jegadeesh and Sheridan Titman were among the first who documented the factor in the academic literature back in 1993. Now, 30 years later, they wrote a little overview about what happened since then. In this week’s AGNOSTIC Paper, they particularly focus on Asian stock markets and the potential explanations for sustained momentum profits. Having a good idea why someone takes the other side of a winning trade is crucial to really understand a strategy and I think this paper is quite interesting in this respect.

  • Momentum worked internationally and out-of-sample
  • Momentum is most likely not data mining
  • The evidence speaks against risk-based explanations
  • Underreaction and noise traders seem a plausible explanation

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AgPa #78: Hedge Funds – Man vs. Machine

Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance (2017)
Campbell R. Harvey, Sandy Rattray, Andrew Sinclair, Otto Van Hemert
The Journal of Portfolio Management 43(4), URL/SSRN

This week’s AGNOSTIC Paper examines the ongoing Man vs. Machine question in asset management at the example of hedge funds. The paper is therefore a predecessor to AgPa #21 that examines the same question for AI-powered mutual funds. The authors mention that there are still myths around systematic investing and many investors seem to have some kind of algorithm aversion. This is in-line with my own experiences, so I believe the paper fills an important gap for better education. In addition to that, the authors provide a practical framework to evaluate the performance and risks of hedge funds which I believe goes beyond the question of Man vs. Machine.

  • Macro hedge funds: systematic beat discretionary
  • Equity hedge funds: a draw between systematic and discretionary
  • Systematic and discretionary funds are quite similar
  • Hedge fund investing is more difficult than averages suggest

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AgPa #77: Too Much Passive Investing?

The Rise of Passive Investing and Active Mutual Fund Skill (2023)
Da Huang
SSRN Working Paper, URL

This week’s AGNOSTIC Paper is a quite recent working paper that examines the impact of passive investing on the US stock market. The debate about a potential tipping point when too many assets go passive is ongoing and often quite emotional. Depending on who you ask, you hear everything from “fundamentally broken” markets to the idea that we only need very few skilled active managers who compete for all the alpha. This week’s paper provides some interesting theoretical and empirical results on that matter.

  • Passive investing in the US grew tremendously
  • Passive investing forces unskilled managers to quit
  • Surviving active managers have more skill, but take less risk
  • We are probably not yet at the point of too much passive

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AgPa #76: ESG Myth Debunking

Applying Economics – Not Gut Feel – to ESG (2023)
Alex Edmans
Financial Analysts Journal 79(4), URL/SSRN

I like myth debunking and this week’s AGNOSTIC Paper is one from this category. Alex Edmans, one of the leading scholars in the field, takes on a few widespread ESG beliefs. He shows that economics already offers a lot of tools to deal with the issues. To me, this paper was therefore kind of a relief as it shows that ESG doesn’t have to be as complicated as many people make it.

  • #1: Shareholder value is a very long-term concept
  • #2: Shareholders care about more than just money
  • #3: Sustainability risks affect cash flows more than discount rates
  • #4: Sustainable stocks not necessarily outperform
  • #5: Climate risk is an unpriced externality, not investment risk
  • #6: Companies‘ ESG metrics not necessarily capture their impact on society
  • #7: More ESG is not necessarily better than less
  • #8: More investor engagement is not necessarily better than less
  • #9: Paying for ESG performance does not necessarily improve ESG performance
  • #10: Not all market failures justify regulation

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AgPa #75: Optimal Investment Committees

Optimal Design of Investment Committees (2023)
Bernd Scherer
The Journal of Asset Management, URL/SSRN

After a long break of almost exactly 3 months – I had several other tasks that required my intellectual capacity – it is time for a new AGNOSTIC Paper. This one examines the design and challenges of investment committees (ICs). Even more important, the author suggests a simple and powerful solution for some of their most common challenges. As someone who regularly enjoys the process of committee-based decision-making, I believe this week’s paper is quite powerful and offers a lot of valuable lessons for both investment managers and their clients.

  • Good theory: ICs ensure the same quality for all clients
  • Bad practice: ICs suffer from psychological biases
  • Solution: Anonymous member-portfolios

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AgPa #74: Peer-Reviewed Research is Not Helpful to Predict Returns – Really?

Does peer-reviewed theory help predict the cross-section of stock returns? (2023)
Andrew Y. Chen, Alejandro Lopez-Lira, Tom Zimmermann
Working Paper, URL

This week’s AGNOSTIC Paper examines the holy grail of empirical research and systematic investing. Is all the research from those smart academics and practitioners really helpful to predict stock returns? Or are we all victims of data mining? The paper if of course not the first one examining this issue, but the approach is in my opinion quite interesting and the authors derive some thought-provoking implications. Pure data mining matches the results from decades of peer-reviewed research surprisingly well. The practical implications, however, are in my opinion not as clear as the statistical ones.

Putting all of this together, the authors may be right that peer-reviewed research and theory are (statistically) not helpful to predict stock returns. I do believe, however, that theory and rigor research in the sense of understanding what you are attempting to do is helpful for real-world investing.

  • Return predictors decay out-of-sample – with and without theory
  • Data mining generates similar patterns like peer-reviewed research
  • Out-of-sample decays are similar for data mining and peer-reviewed research

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