Momentum Investing

AgPa #73: Country and Industry Momentum

Can exchange traded funds be used to exploit industry and country momentum? (2013)
Laura Andreu, Laurens Swinkels, Liam Tjong-A-Tjoe
Financial Markets and Portfolio Management, URL/SSRN

Even if you believe in factor investing, it is very difficult for most investors to actually implement it. Trading portfolios with hundreds of stocks requires considerable infrastructure, enough money, and efficient transaction cost management. This is already a challenge for many institutional investors, so it is logically even more difficult for people like you and me. This week’s AGNOSTIC Paper addresses this issue and presents an idea to still benefit from momentum via equity indices and the corresponding ETFs.

  • Country and industry momentum worked historically
  • The strategies seem to be implementable via ETFs
  • The strategies remained profitable after trading costs

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AgPa #45: Factor Investing in Private Debt

Investing with Style in Liquid Private Debt (2022)
Thomas Mählmann, Galina Sukonnik
Financial Analysts Journal 78(3), URL

This week’s AGNOSTIC Paper is yet another out-of-sample test of the Momentum and Value factor. The authors apply the factors within the relatively new asset class of private debt. More specifically, for “[…] loans to non-investment grade issuers, commonly known as leveraged loans.” This is obviously not my main area of expertise, but I learned from the paper that there is quite some trading of such loans in private secondary markets. Implementing a factor strategy for leveraged loans is obviously more complicated than for equities, but this is exactly what makes this study so interesting.

  • Private debt improves multi-asset portfolios
  • Value and Momentum are profitable within private debt

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SA #11: QMOM – Second-Best In The Momentum Crash of January 2023

QMOM: Second-Best In The Momentum Crash Of January 2023
February 06, 2023

Summary

  • January 2023 was brutal for momentum because many of last year’s losers suddenly outperformed – a momentum crash par excellence.
  • The Dow Jones US Market Neutral Momentum Index, a simple and transparent implementation of the long-short momentum factor, lost 19% YTD (as of February 3, 2023).
  • Most of the losses came from the short-side. The Dow Jones US Low Momentum Index, the portfolio of past losers, returned 25.68% YTD.
  • The Alpha Architect U.S. Quantitative Momentum ETF returned -0.83% YTD and underperformed the US market by >10% points. Although painful, this is still second-best in a peer-group of other momentum ETFs.
  • This speaks for the differentiated momentum process of Alpha Architect. Nobody likes bad months, but momentum crashes are actually a plausible reason why momentum worked historically and probably continues to do so in the future.


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SA #8: SPMO – Large Cap Momentum At Its Best

SPMO: Large Cap Momentum At Its Best
January 19, 2023

Summary

  • Momentum is the simple idea that stocks which performed relatively strong over the recent past (winners) tend to outperform those that performed poorly (losers).
  • The Invesco S&P 500 Momentum ETF invests in the 100 stocks with the highest “momentum score” (12-month return) from the S&P 500 Index.
  • Since inception in 2015, SPMO delivered momentum exposure with respect to the academic benchmark of Kenneth French. Since 2017, it also outperformed most momentum-peers.
  • SPMO especially outperformed MTUM, a similar large cap momentum ETF. However, most of this outperformance is unlikely systematic and probably comes from different rebalancing dates in 2022.
  • For investors who actively want large-cap momentum exposure, SPMO is a reasonable and cheap instrument. For those who want general momentum exposure, a fund with a larger universe is probably the better choice.


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AgPa #37: Momentum Investing – Fact and Fiction

Fact, Fiction, and Momentum Investing (2014)
Clifford Asness, Andrea Frazzini, Ronen Israel, Tobias Moskowitz
The Journal of Portfolio Management Special 40th Anniversary Issue 2014, 40(5) 75-92, URL/AQR

After examining the general Facts and Fictions about factor investing, this week’s AGNOSTIC Paper examines momentum in more detail. Specifically, the authors combat 10 misleading myths about momentum…

  • Myth 1: Momentum returns are economically not meaningful
  • Myth 2: Long-only investors cannot capture momentum
  • Myth 3: Momentum is much stronger among small-caps
  • Myth 4: Momentum does not survive trading costs
  • Myth 5: Momentum produces a huge tax bill
  • Myth 6: Momentum is better as a screen than as a factor
  • Myth 7: Momentum returns should disappear in the future
  • Myth 8: Momentum is too volatile to rely on
  • Myth 9: Different momentum measures lead to different results
  • Myth 10: There is no theory behind momentum

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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 #28: “Not Selling” of Insiders

Is “Not Trading” Informative? Evidence from Corporate Insiders’ Portfolios (2022)
Luke DeVault, Scott Cederburg, Kainan Wang
Financial Analysts Journal 78(1), 79-100, URL/SSRN

Transactions of insiders are usually a useful source of information when evaluating a stock. Insiders typically have a good understanding of the underlying business and buys are therefore often considered as positive signal. On the other hand, insider sales are not necessarily negative. There are many non-informative reasons to cash out. Maybe the insider needs some cash for personal expenditures or just wants to diversify his assets. This week’s AGNOSTIC Paper challenges this asymmetry and creatively shows that even those transactions convey important information…

  • “Not sold” stocks from insider portfolios outperformed
  • A portfolio of “not sold” stocks easily beat the US market
  • “Not sold” stocks with momentum are even better
  • Corporate insiders know more than institutional investors

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AgPa #26: Trading on Price Charts

(Re-)Imag(in)ing Price Trends (2022)
Jingwen Jiang, Bryan T. Kelly, Dacheng Xiu
The Journal of Finance, Forthcoming, URL

This week’s AGNOSTIC Paper is about technical analysis. Full disclosure: I never believed in technical analysis in the sense of drawing lines on charts or imagining somewhat arbitrary patterns.

But the approach of this week’s authors is quite different. They borrow methodology from image recognition and train a machine learning model to detect predictive patterns in price charts (Yes, the machine receives the price chart as picture, not the underlying numbers!)…

  • The model identifies very profitable short-term signals
  • The signals are also profitable over longer horizons
  • Some of the machine-learning-signals are explainable
  • The model disagrees with conventional technical analysis

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