AgPa #56: The Equity Risk Premium of Small Businesses

Small Business Equity Returns: Empirical Evidence from the Business Credit Card Securitization Market (2023)
Matthias Fleckenstein, Francis A. Longstaff
The Journal of Finance 78(1), URL

In 2020, there were more than 31M small private businesses in the US. Even though the estimated value of those businesses is “just” $12T, the sheer number is astonishing when compared to about 4,000 tradable US stocks (excluding penny stocks). For stocks, we typically use measures like returns, multiples, and volatilities. But given the lack of daily prices, it is difficult to calculate those measures for small private businesses. This week’s AGNOSTIC Paper is an attempt to change that…

  • Small businesses had an equity risk premium of 10.7% and a volatility of 56%
  • Robustness: the model generates plausible results for S&P 500 stocks

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AgPa #55: Backtests in the Age of Machine Learning

A Backtesting Protocol in the Era of Machine Learning (2019)
Rob Arnott, Campbell R. Harvey, Harry Markowitz
The Journal of Financial Data Science Winter 2019, URL/SSRN/PDF

I have already written about the pitfalls of research in asset management and the importance of good research practices for the application of machine learning. This week’s AGNOSTIC Paper takes this idea even further and provides a seven-point protocol for empirical research in finance.

Exhibit 2 of Arnott et al. (2019).

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AgPa #54: Transitory Inflation

How Transitory Is Inflation? (2023)
Rob Arnott, Omid Shakernia
The Journal of Portfolio Management April 2023, URL/Research Affiliates/SSRN

Full disclosure: I am generally skeptic about macro forecasts and I don’t think statements like “We had the same situation in 1980 and therefore things will develop like XYZ.” are much helpful. In economics, two situations are never exactly the same and we humans are very good when it comes to finding patterns in essentially random data. However, given how important the topic over the last years was and still is, I couldn’t resist the temptation. This week’s AGNOSTIC Paper is a little scenario analysis how “transitory” inflation actually was in the past.

  • Transitory inflation would be a historical best-quintile outcome
  • Historically, it took >5 years to get >8% inflation down to 3%

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AgPa #53: Investing in Interesting Times

Investing in Interesting Times (2023)
Annti Ilmanen
The Journal of Portfolio Management Multi-Asset Special Issue 2023, URL/AQR

Almost exactly one year ago, Antti Ilmanen (Partner at AQR Capital Management) released his outstanding book Investing Amid Low Expected Returns: Making the Most When Markets Offer the Least. The book is (in my opinion) a must-read and the timing couldn’t have been better. Many of the key themes began to materialize in 2022. Given how much markets have changed since then, Antti released a few updates for six of his major ideas in this week’s AGNOSTIC Paper.

  • The low expected return challenge
  • Investors’ response to low expected returns – private markets
  • What happened in 2022 and where we stand now
  • Long-only versus long-short strategies
  • Downside protection via trend-following

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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 #51: Short Sellers vs. Firms

Go Down Fighting: Short Sellers vs. Firms (2012)
Owen A. Lamont
The Review of Asset Pricing Studies 2(1), URL

I like controversial and (in my opinion) misunderstood topics and this week’s AGNOSTIC Paper examines the next big one: short selling. The paper is unfortunately already more than 10 years old, but it is still a go-to reference for short selling. Apart from that, the fights between firms and short sellers are also quite entertaining – at least from an outsider’s perspective…

  • Short-seller-fighting firms tend to massively underperform
  • The results are robust after controlling for the major factors

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AgPa #50: Should We Trust Asset Management Research?

The Pitfalls of Asset Management Research (2022)
Campbell R. Harvey
Journal of Systematic Investing Volume II Issue 1, URL/SSRN

Can we trust the results of academic and practitioner research in asset management? For a blog focusing on summaries of research papers, this is of course a very important question. But even without such an obvious bias, this is a very interesting issue for all who use some form of research for their investment decisions. The author of this week’s AGNOSTIC Paper presents several concerning facts and strongly recommends to not take all research insights at face value…

  • Some concerning facts about finance research
  • Research incentives and multiple testing
  • Practitioner research in asset management

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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 #48: Investable Machine Learning for Equities

Investable and Interpretable Machine Learning for Equities (2022)
Yimou Li, Zachary Simon, David Turkington
The Journal of Financial Data Science Winter 2022, 4(1), URL

Regular readers of this blog know that machine learning in asset management is one of my favorite topics and I recently found new interesting material. This week’s AGNOSTIC Paper is the first of two studies and examines an important issue with machine learning models in great detail: interpretability…

  • Machine learning models outperform simpler methods
  • Different models learn different investment approaches

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AgPa #47: Equity Factors without Shorting

When Equity Factors Drop Their Shorts (2020)
David Blitz, Guido Baltussen, Pim van Vliet
Financial Analysts Journal, 76(4), URL

This week’s AGNOSTIC Paper examines the important issue of performance contributions from the long and short legs of the major factor premiums. In English: can we profitably invest in factors without shorting a large number of stocks?

  • The long-legs of factors are more important than the short-legs
  • The same pattern holds in international markets

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