Small Cap

AgPa #40: Size Effect – Fact and Fiction

Fact, Fiction, and the Size Effect (2018)
Ron Alquist, Ronen Israel, Tobias Moskowitz
The Journal of Portfolio Management Fall 2018, 45 (1) 34-61, URL/AQR

After examining several Facts and Fictions around factor investing in general, momentum, value, and low-risk, this week’s AGNOSTIC Paper tackles the final anomaly. The size effect received a lot of attention in both academia and the investment industry, probably because it is one of the oldest documented anomalies. In this final paper of their Fact and Fictions series, the authors examine some myths around it.

  • Fiction: Size is the strongest documented factor
  • Fact: The size effect weakened since its discovery
  • Fiction: The size effect is robust across different measures
  • Fact: The size effect is strongly related to the January effect
  • Fiction: Size also works in international equity markets
  • Fact: Size does not work within other asset classes
  • Fact: Most of the size effect are micro cap stocks
  • Fact: Size is difficult to implement in real-world portfolios
  • Fiction: The size effect is more than just a liquidity effect
  • Fiction: There are economic theories for the size effect
  • Fiction: Size works because other factors are stronger among small cap stocks
  • Fact: There are reasons to overweight small caps even without the size effect
  • Fact and Fiction: The size effect is stronger when controlling for other factors
  • Fact: Size receives a lot of attention despite weak evidence

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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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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.

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#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.


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