Funds & ETFs

SA #4: QMOM – Best-In-Class Momentum, Now 20% Cheaper

QMOM: Best-In-Class Momentum, Now 20% Cheaper
December 30, 2022

Summary

  • Momentum is one of the best-researched systematic investing strategies and has produced significant outperformance in the past.
  • The Alpha Architect U.S. Quantitative Momentum ETF follows a differentiated investment process that delivered strong momentum exposure in the past.
  • Over the last 5 years, QMOM outperformed several other momentum exchange-traded funds and an academic benchmark from Kenneth French.
  • On December 1, 2022, Alpha Architect (the manager of QMOM) announced that they will lower the management fee from 0.49% to 0.39% per 01/31/2023.
  • This is a reduction of about 20% and makes the QMOM ETF even more attractive for investors who seek active momentum exposure.


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SA #3: MTUM – Momentum, But Somewhat Slow

MTUM: Momentum, But Somewhat Slow
December 28, 2022

Summary

  • Momentum is one of the best-researched systematic investing strategies, and has provided significant outperformance in the past.
  • The MTUM ETF tracks the MSCI USA Momentum SR Variant Index and is an easy way to add momentum to a portfolio.
  • The ETF follows a transparent methodology and has performed mostly in line with the academic momentum benchmark from Kenneth French since 2013.
  • The key problem of the methodology, however, is the slow, six-month rebalancing – also the reason why MTUM suffered in 2022.
  • For investors who don’t want to take too much active risk and/or monitor active managers, the MTUM ETF is still a reasonable momentum implementation.


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SA #2: QMOM – A Close Look At The Methodology

QMOM: A Close Look At The Methodology
November 20, 2022

Summary

  • Momentum is one of the best-researched systematic investing strategies and produced significant outperformance in the past.
  • Over the last 5 years, the QMOM ETF outperformed the academic benchmark from Kenneth French and several other momentum ETFs.
  • The QMOM ETF achieved this by a differentiated momentum-investment process, which I will analyze in this article.
  • The QMOM ETF delivered momentum exposure and helps to add momentum to basically all portfolios.


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AgPa #21: AI-Powered vs. Human Funds

Do AI-Powered Mutual Funds Perform Better? (2022)
Rui Chen, Jinjuan Ren
Finance Research Letters, Volume 47, Part A, URL/SSRN

This week’s AGNOSTIC Paper compares the performance of AI-powered- and human mutual funds between 2017 and 2019 in the US. Although AI-powered funds are not the holy grail some investors may have hoped for, they still added value compared to their human peers…

  • AI-powered mutual funds did not outperform the US market
  • But AI-powered funds outperformed their human peers
  • And AI-powered funds avoided the disposition- and rank effect

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AgPa #17: European Fund Selection

Fund Selection: Sense and Sensibility (2022)
Guido Baltussen, Stan Beckers, Jan Jaap Hazenberg, Willem Van Der Scheer, CFA
Financial Analysts Journal, 78(3), 30-48, URL

Coincidentally, this week’s AGNOSTIC Paper is a pretty good sequel to the last one. The authors study the performance of globally investing mutual fund that were available for European investors between 2008 and 2020. The results are seamlessly consistent with the literature and are anything but a sales-pitch for active fund managers…

  • In aggregate, active managers underperformed the passive alternative
  • Cheap funds with good track records were more likely to outperform

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AgPa #16: Concentrated Stock Markets (7/7)

Mutual Fund Performance at Long Horizons (2022)
Hendrik Bessembinder, Michael J. Cooper, Feng Zhang
SMU Cox School of Business Research Paper No. 22-11 via SSRN, URL

The seventh and final AGNOSTIC Paper on the extreme concentration in stock markets. This one is an out-of-sample test and documents very similar concentration and positive skewness for US mutual funds between 1991 and 2020.

  • Longer investment-horizons lead to extremer return distributions – also for mutual funds
  • Most active managers underperform passive benchmarks – especially over the long-term
  • Compared to the S&P 500, mutual fund investors lost about $1.3T between 1991 and 2020

But a picture is worth a thousand words…


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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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