Equity

AgPa #11: Concentrated Stock Markets (2/7)

Long-Term Shareholder Returns: Evidence from 64,000 Global Stocks (2021)
Hendrik Bessembinder, Ta-Feng Chen, Goeun Choi, K.C. John Wei
SSRN Working Paper, URL

The second of seven AGNOSTIC Papers about the extreme concentration within stock markets. This one goes beyond the US and examines global stock markets between 1990 and 2020. The pattern of extreme concentration is very similar for 41 countries beside the US and in some cases even stronger.

  • Longer investment-horizons lead to extremer return distributions – also outside the US
  • Just 2.4% of all companies created the entire net wealth in global stock markets
  • All stock markets are concentrated but there are regional differences

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AgPa #10: Concentrated Stock Markets (1/7)

Do stocks outperform Treasury bills? (2018)
Hendrik Bessembinder
Journal of Financial Economics 129(3), 440-457, URL

I try to be careful with superlatives, but I think that this week’s AGNOSTIC Paper(s) are a must-read for everyone seriously interested in stock markets.

A few very successful companies drive the entire US market while the majority of stocks underperform even risk-free treasuries. Moreover, the most frequent lifetime return for U.S. companies is -100%. Those brutal empirical facts have strong implications for investors.


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AgPa #9: The Age of Intangible Assets

Equity Investing in the Age of Intangibles (2021)
Amitabh Dugar & Jacob Pozharny
Financial Analysts Journal, 77(2), 21-42, URL

Given the exceptional decade for technology companies, I am late to the party with this one. This week’s AGNOSTIC Paper examines the role of intangible assets for equity investors.

The issue is at the heart of fundamental analysis and also relevant for systematic investors. The authors present several interesting results for a global sample of thousands of companies between 1994 and 2018.

  • A measure for intangible-intensity of industries
  • Book values became less relevant for intangible-intense industries but still remain important

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AgPa #8: Neuroscientific Insights for Alpha

Harnessing Neuroscientific Insights to Generate Alpha (2022)
Elise Payzan-LeNestour, James Doran, Lionnel Pradier, Tālis J. Putniņš
Financial Analysts Journal, 78(2), 79-95, URL

We are all prone to psychological biases that are very hard to control. This week’s AGNOSTIC Paper examines the after-effect, one particular example for this.

The idea of the after-effect is simple. If you are long enough exposed to a certain stimuli, you will have the illusion of the exact opposite stimuli after the first one disappears. Apparently, this pattern was very relevant for the US stock market…

  • The after-effect distorted the VIX Index
  • Exploiting the after-effect yielded significant alpha

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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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AgPa #6: Predicting Returns with (Alternative) Consumer Data

Predicting Performance Using Consumer Big Data (2022)
Kenneth Froot, Namho Kang, Gideon Ozik, Ronnie Sadka
The Journal of Portfolio Management 48(3), 47-61, URL

This week’s AGNOSTIC Paper is again more related to my other content. The authors use proxies for in-store activity, brand awareness, and web traffic to predict fundamentals and returns of consumer-oriented companies.

I like the paper because it examines alternative data and is published in a peer-reviewed journal. Other studies on the topic are often just white papers of data providers. So it is nice to have a more scientific analysis.

  • Alternative consumer-data predicts firm fundamentals
  • Trading on alternative consumer-data generated monthly alphas of up to 1.9%

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AgPa #5: The Return on Everything

The Rate of Return on Everything, 1870–2015 (2019)
Òscar Jordà, Katharina Knoll, Dmitry Kuvshinov, Moritz Schularick, Alan M. Taylor
The Quarterly Journal of Economics 134(3), 1225-1298, URL

This week’s AGNOSTIC Paper is a deep dive into financial history. The authors estimate the total return of equity, housing, bonds, and bills in 16 advanced economies for the period from 1870 to 2015.

The paper is very comprehensive and I focused on the issues that are (in my opinion) most interesting for investors:

  • Real returns on risky assets were 7-8% from 1870 to 2015
  • Returns on risky assets were substantial but volatile
  • Realized risk premiums fluctuate widely across time and countries

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AgPa #2: What Moves Stock Prices?

What Moves Stock Prices? The Role of News, Noise, and Information (2022)
Jonathan Brogaard, Thanh Huong Nguyen, Talis J. Putnins, Eliza Wu
The Review of Financial Studies, Forthcoming, URL

This week’s AGNOSTIC Paper attempts to answer a very fundamental question: What drives the day-to-day volatility of stock prices? Of course, there are many things active at the same time. News about the underlying businesses, news about the economy, market impact of large investors, and various more.

The authors develop a novel model to isolate the impact of those different types of information. They also applied it to the US stock market and derive some interesting results:

  • Stock-Specific information is most important
  • Markets became more efficient over time
  • Smaller stocks are more noisy

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Report Analytics USA #2

This post contains a lot of unsexy calculations and is fairly technical. But (in my opinion) there are some very interesting results. Not just for my particular strategy but for everyone who is active on Wikifolio.

First. Overall and especially after costs, my two Wikifolios weren’t a good alternative to a standard ETF on the S&P 500 index (from inception to March 11, 2022). To my defense, however, I stressed several times that the two Wikifolios are just a real-world test of my master thesis and I never marketed them as investments.

Second. I still believe that Wikifolio is a great platform to test strategies like mine, but it is not perfect. There are annoying technical issues, pretty high fees, and significant indirect trading costs. Depending on the liquidity of the stock, bid-ask-spreads and/or unfavorable FX rates amount to 40-80 basis points per transaction on average.

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#3: Big Data & Machine Learning in Asset Management

This week I gave a talk on “Big Data and Machine Learning in Asset Management” at Goethe-University in Frankfurt. Thanks again to my thesis-supervisor Sasan Mansouri for the invitation. In this post I will summarize a few points of the talk and share the slides. The key result is the following framework to evaluate investment strategies that claim to use big data and machine learning. I also apply this to several real world funds.

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