Security Selection

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.


Read the Full Post

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%

Read the Full Post

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.

Read the Full Post

#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.

Read the Full Post

Report Analytics USA #1

This is the start of an ongoing series intended to share updates, insights, and backgrounds on the Report Analytics USA portfolios. To start with, I present the methodology that I currently use to implement the live portfolios on Wikifolio.

Heart of the process is a stock selection based on copy-paste of the most recently published annual and quarterly reports. I further divide this selection by market capitalization to create a “Large” and “Small” version of the Report Analytics USA portfolios.

All of this is just a starting point and I conclude this post with a roadmap of ideas to improve the strategy.

Read the Full Post

#2: Copy-Paste Outperformance

Every year, US companies must publish three quarterly and one annual report. Preparing those reports, however, is a lot of effort, does not improve operations, and reveals information to competitors.

How to deal with this? Correct, spend the time to create one comprehensive template and reuse it as long as possible. In an excellent research paper titled “Lazy Prices” (2020), the authors show that US companies are no exception from this: many annual and quarterly reports are basically just updated copies from the previous year.

What does this mean for investors? Since most of the report is just copy-paste, they should rather focus on differences between the current and previous report (for example, new paragraphs). It turns out that such changes are indeed very important: quantitative measures for report copy-paste predict future stock returns and help to achieve outperformance vs. common US indices.


Read the Full Post