Investment Philosophy

Standard Stupidities: Introduction

It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent.

Other people are trying to be smart. All I’m trying to be is non-idiotic. I find that all you have to do to get ahead in life is to be non-idiotic and live a long time. It’s harder to be non-idiotic than most people think.

Charlie Munger Quotes from Chapter 8 of Green (2021)

What is a Standard Stupidity? For me, it is a situation or problem with a clear rational solution which many people still screw up massively.

There is a large supply of Standard Stupidities in investing and I am looking forward to disentangle some of them in this series.

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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 #63: Fire the Winners and Hire the Losers

The Folly of Hiring Winners and Firing Losers (2018)
Rob Arnott, Vitali Kalesnik, Lillian Wu
The Journal of Portfolio Management Fall 2018, 45 (1), URL/research affiliates

I am still in my research on manager selection, so apologies to everyone who doesn’t find that too interesting. We already touched the question on what to do with underperforming managers in AgPa #59 and #60. This week’s AGNOSTIC Paper, however, examines this problem somewhat more generally and delivers some really simple (but psychologically hard-to-execute) common-sense conclusions.

  • Current winners tend to be future losers
  • High fees are the most reliable way to underperform
  • Investors should use factor exposures and valuations to evaluate fund managers

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AgPa #60: Some Advice for Asset Manager Selection

Manager Selection, Deselection, and Termination (2020)
Mark Anson
The Journal of Portfolio Management Fund Manager Selection 2020, 46(5), 6-16, URL

After examining the end of the asset manager selection process (i.e. firing decisions) in the last post, this week’s AGNOSTIC Paper provides a broader overview. The author touches a lot of issues and provides some general advice how to cope with them in practice…

  • Asset owners seem to be bad in hiring and firing managers
  • How to decide about firing a manager
  • Style Drift, Style Clustering, and Fees
  • The very important difference between Alpha and Beta
  • Momentum and Crowding

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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 #43: Buffett’s Alpha

Buffett’s Alpha (2018)
Andrea Frazzini, David Kabiller, Lasse Heje Pedersen
Financial Analysts Journal 74(4), URL

In this week’s AGNOSTIC Paper, the authors use the major factor premiums to examine one of the best long-term investment track records in the world – Warren Buffett and Berkshire Hathaway. The latest annual report just came out a few days ago and (as usual) summarizes Berkshire’s performance on the first page. From 1965 to 2022, Berkshire returned 19.8% per year versus 9.9% for the S&P 500. That’s a 24,708% cumulative return for the S&P 500, and an unbelievable 3,787,464% return for Berkshire. There are some investors who achieved even better results over shorter time periods. But to the best of my knowledge, there is no 58-year track record that is even remotely comparable to Buffett.

  • How good is Berkshire? Damn good…
  • The Buffett Style: cheap stocks with high-quality and low-risk
  • Don’t practice what you preach – Buffett’s Leverage…
  • Systematizing Buffett and Berkshire

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