AgPa #52: Happier Employees, Better Returns?

Employee Satisfaction and Long-Run Stock Returns, 1984–2020 (2022)
Hamid Boustanifar, Young Dae Kang
Financial Analysts Journal 78(3), URL/SSRN

A common sales-pitch of ESG strategies is the idea that those strategies not only do good for the planet and other stakeholders, but also generate higher returns. I am generally skeptic about this, but there are studies showing that certain ESG variables historically indeed predicted higher returns. A prominent example for this is the paper on employee satisfaction by Alex Edmans (2011). This week’s AGNOSTIC Paper is an out-of-sample test of this study with somewhat more thorough testing.

  • “Best Companies” outperformed several benchmarks
  • “Best Companies” outperformed during crises and out-of-sample
  • Quality and Low-Risk factors explain some of the premium on “Best Companies”

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AgPa #49: Machine Learning in Quant Asset Management

How Can Machine Learning Advance Quantitative Asset Management? (2023)
David Blitz, Tobias Hoogteijling, Harald Lohre, Philip Messow
The Journal of Portfolio Management Quantitative Tools 2023, URL/SSRN

This week’s AGNOSTIC Paper is a broad overview about machine learning in investment management. The authors outline the benefits and pitfalls of machine learning compared to “traditional” econometrics and present several use cases in the world of (quantitative) asset management. They also provide ideas for research governance to keep those powerful methods under control.

  • Benefits and pitfalls of machine learning in finance
  • Use cases of machine learning in asset management
  • Keeping it under control: research governance and protocol

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AgPa #33: World Cups and Stock Markets

Sports Sentiment and Stock Returns (2007)
Alex Edmans, Diego García and Øyvind Norli
The Journal of Finance 62(4), 1967-1998, URL

Given that this week’s AGNOSTIC Paper coincides with the final of the World Cup, I couldn’t resist the temptation. Below you can see a chart of the knockout stage of this year’s tournament. But since you are visiting a nerdy finance website, the focus is not on the results, but on the post-match stock market returns of the playing countries…

You may (understandably) say that this is some nice storytelling but not much more. However, I didn’t made this up to create a story but the idea of this analysis actually comes from this week’s AGNOSTIC paper…

  • Stock markets of losing countries tend to underperform after important matches
  • The effect most likely comes from bad mood after sport losses

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AgPa #28: “Not Selling” of Insiders

Is “Not Trading” Informative? Evidence from Corporate Insiders’ Portfolios (2022)
Luke DeVault, Scott Cederburg, Kainan Wang
Financial Analysts Journal 78(1), 79-100, URL/SSRN

Transactions of insiders are usually a useful source of information when evaluating a stock. Insiders typically have a good understanding of the underlying business and buys are therefore often considered as positive signal. On the other hand, insider sales are not necessarily negative. There are many non-informative reasons to cash out. Maybe the insider needs some cash for personal expenditures or just wants to diversify his assets. This week’s AGNOSTIC Paper challenges this asymmetry and creatively shows that even those transactions convey important information…

  • “Not sold” stocks from insider portfolios outperformed
  • A portfolio of “not sold” stocks easily beat the US market
  • “Not sold” stocks with momentum are even better
  • Corporate insiders know more than institutional investors

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AgPa #26: Trading on Price Charts

(Re-)Imag(in)ing Price Trends (2022)
Jingwen Jiang, Bryan T. Kelly, Dacheng Xiu
The Journal of Finance, Forthcoming, URL

This week’s AGNOSTIC Paper is about technical analysis. Full disclosure: I never believed in technical analysis in the sense of drawing lines on charts or imagining somewhat arbitrary patterns.

But the approach of this week’s authors is quite different. They borrow methodology from image recognition and train a machine learning model to detect predictive patterns in price charts (Yes, the machine receives the price chart as picture, not the underlying numbers!)…

  • The model identifies very profitable short-term signals
  • The signals are also profitable over longer horizons
  • Some of the machine-learning-signals are explainable
  • The model disagrees with conventional technical analysis

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AgPa #23: Trading on the Weather

Global weather-based trading strategies (2022)
Ming Dong, Andréanne Tremblay
Journal of Banking & Finance, Volume 143, 106558, URL/SSRN

People tend to be in a better mood when the sun is shining. That’s nothing dramatically new but this week’s AGNOSTIC Paper shows that this apparently also applies to investors. An investment strategy that went long (short) the stock market index from the country with the best (worst) weather on a particular day generated meaningful (hypothetical) outperformance…

  • The global long-short weather strategy returned 15.2% p.a. between 1993 and 2012
  • The long-only version of the strategy returned 13.4% p.a.

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AgPa #20: Performance of ESG Exclusions

The Expected Returns of ESG Excluded Stocks. The Case of Exclusions from Norway’s Oil Fund (2022)
Erika Berle, Wanwei (Angela) He, Bernt Arne Ødegaard
SSRN Working Paper, URL

This week’s AGNOSTIC Paper examines the ESG exclusions of a popular investor: the Norwegian sovereign wealth fund, also known as the “oil fund”. Between 2005 and 2021, the fund excluded 189 companies that engage in different types of “bad” practices or products. These exclusions are interesting because they reveal insights about the impact of ESG for a large real-world institutional investor…

  • ESG-excluded stocks generated up to 6.85% alpha per year
  • There seems to be a return premium on “bad” stocks

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AgPa #19: ESG Confusion (2/2)

Aggregate Confusion: The Divergence of ESG Ratings (2022)
Florian Berg, Julian F. Kölbel, Roberto Rigobon
Review of Finance, Corrected Proof, 1-30, URL

The second AGNOSTIC Paper on the confusion around ESG. This one examines the disagreement of ESG ratings in much more detail and provide some explanations why they are so different…

  • ESG ratings disagree: the average correlation is just 0.54
  • 709 indicators and 64 categories: no wonder that there is disagreement
  • Most disagreement comes from “measurement” and “scope”
  • There is a “rater effect” for ESG ratings

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AgPa #18: ESG Confusion (1/2)

ESG Rating Disagreement and Stock Returns (2021)
Rajna Gibson Brandon, Philipp Krueger, Peter Steffen Schmidt
Financial Analysts Journal 77(4), 104-127, URL/SSRN

This week’s AGNOSTIC Paper is about a quite controversial topic: Environmental, Social, and Governance a.k.a. ESG. ESG refers to the idea that investors should consider those dimensions in their decisions and thereby contribute to a more sustainable economy. But as this week’s paper shows, there is little agreement on what ESG actually is…

  • ESG ratings disagree: the average correlation is just 0.45
  • There is less ESG disagreement for larger, more profitable firms with credit ratings
  • Investors demanded a risk premium for ESG uncertainty

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AgPa #7: Spotify Streaming and Stock Returns

Music sentiment and stock returns around the world (2021)
Alex Edmans, Adrian Fernandez-Perez, Alexandre Garel, Ivan Indriawan
Journal of Financial Economics, In Press, Corrected Proof, URL

This week’s AGNOSTIC Paper examines the role of music sentiment in the stock market. What sounds like statistical hocus-pocus is part of an important question. Do other factors than rational information drive stock markets?

I like the paper for its creative use of alternative data and its clean methodology. But to be honest, I was somewhat skeptical when I first heard about it. However, the authors present an intuitive economic rationale and rigorously test their hypotheses in various robustness checks. The results are quite interesting…

  • Music sentiment is related to stock market returns
  • Music sentiment is more important in less efficient markets
  • Music sentiment is also related to fund flows and bond market returns

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