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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AgPa #73: Country and Industry Momentum

Can exchange traded funds be used to exploit industry and country momentum? (2013)
Laura Andreu, Laurens Swinkels, Liam Tjong-A-Tjoe
Financial Markets and Portfolio Management, URL/SSRN

Even if you believe in factor investing, it is very difficult for most investors to actually implement it. Trading portfolios with hundreds of stocks requires considerable infrastructure, enough money, and efficient transaction cost management. This is already a challenge for many institutional investors, so it is logically even more difficult for people like you and me. This week’s AGNOSTIC Paper addresses this issue and presents an idea to still benefit from momentum via equity indices and the corresponding ETFs.

  • Country and industry momentum worked historically
  • The strategies seem to be implementable via ETFs
  • The strategies remained profitable after trading costs

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AgPa #72: Machine-Reading of Private Equity Prospectuses

Limited Partners versus Unlimited Machines: Artificial Intelligence and the Performance of Private Equity Funds (2023)
Reiner Braun, Borja Fernández Tamayo, Florencio López-de-Silanes, Ludovic Phalippou, Natalia Sigrist
CEFS Research Paper, URL/SSRN

This week’s AGNOSTIC Paper is somewhat outside my major area of competence, but I think it is a good example where we are heading to in the investment industry. Over the last years, it became quite standard that investors use the latest tools of machine learning to analyze non-quantitative information like text or images at a scale that hasn’t been possible before. So far, however, the efforts were mostly focused on public markets. In their not yet published working paper, this week’s authors show that there seems to be also a lot of potential for such methods in private markets.

  • Portfolio Company, Management Team, Investment Opportunity – The most common words of PE-managers
  • The complexity of PE-fund documents is related to fundraising success and performance
  • Machine learning and text data helps to select PE-funds
  • The machines seem to pick up meaningful concepts

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AgPa #71: Go Where the Earnings (per Share) Are

What Matters More for Emerging Markets Investors: Economic Growth or EPS Growth? (2022)
Jason Hsu, Jay Ritter, Phillip Wool, Harry Zhao
The Journal of Portfolio Management Emerging Markets 2022, 48 (8), URL/PDF

This week’s AGNOSTIC Paper is one from the myth-busting category and examines the relation between countries’ GDP growth and stock market returns. The idea and analyses are admittedly not new and the paper is basically an update of one of the authors previous work. Nonetheless, I think the question is very interesting and still very relevant for regional asset allocation.

  • GDP growth and stock returns are not correlated over the long-term
  • Theoretically, the missing relation is not surprising
  • Go Where the Earnings (per Share) Are

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