By |Published On: September 12th, 2019|Categories: Factor Investing, Research Insights, Value Investing Research|

Value and Momentum each had back to back extreme returns (five sigma) days on Monday, September 9th and Tuesday, September 10th.  The Dow Jones Thematic Market Neutral Value Index (“Value”) started the week up 3.45%, its best day since inception on December 31st, 2001.  The Value Index followed this up on Tuesday, September 10th with a 2.56% return, its 7th best day since inception. The Dow Jones Thematic Market Neutral Momentum Index (“Momentum”) was down 4.53% and 4.08%, its two worst days in the past 10 years (10th and 15th worst days since inception).

Figure 1A shows the distribution of single-day returns for the Value Index:

Figure 1A: Distribution or daily returns for the Dow Jones Market Neutral Value Index Source: The Dow Jones Thematic Market Neutral Value Index, 12/31/2002 – 09/10/2019 The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index.

Figure 1B shows the distribution of single-day returns for the Momentum Index:

Figure 1B: Distribution or daily returns for the Dow Jones Market Neutral Momentum Index Source: The Dow Jones Thematic Market Neutral Momentum Index, 12/31/2002 – 09/10/2019 The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index.

Figure 2 shows us that it is normal for Momentum and Value to move in opposite directions.  The red points mark the past two days’ observations.  All but one of the points to the left of these are from the early part of the 2009 recovery – the last momentum crash.  The orange ellipse contains points within two standard deviations of the mean and the purple ellipse contains 95% of the samples.

Figure 2: Distribution of Daily Value and Momentum Returns Source: Dow Jones, 12/31/2002 – 09/10/2019 The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index.

It is an understatement to say that the recent factor moves are rare.  This is the sort of thing that factor geeks wait decades for.  The good news for those of us fitting that description is that these sorts of events tend to cluster.  This is evident from Figure 3, which shows historic rolling 20-day returns for the two-factor indexes.  Figure 3, also shows us that sharp reversals in these factors are the norm.  In fact, the worst day for Momentum was April 9, 2009 (down 7.56%).  Seven market days later, on April 20, 2009, Momentum had its best day (up 10.35%)!

Figure 3: Rolling 20-Day Value and Momentum Returns Source: Dow Jones, 12/31/2002 – 09/10/2019 The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index.

One last point, volatility in these indices is typically high around regime changes and big market moves.  While a lot has changed recently (I would argue we entered a new regime in Q4 2018) the S&P 500 is up only 3% from where it was 12 months ago.  It wouldn’t surprise me to see a few more large moves in Momentum and Value in the near future. (1)

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About the Author: Josh Russell, PhD, CFA

Josh Russell, PhD, CFA
Josh Russell, Phd, CFA is a Quantitative Analyst in the Equity Research group at QS Investors. Part practitioner and part academic, he is focused on implementing quantitative investment research in the real world. Currently, he is exploring systematic equity factors and ESG integration. He is especially interested in the interplay between factors, rates, and economic cycles. Prior to working with investments, Josh was an engineer specializing in algorithms for optimal estimation in distributed systems. He spent many fine years at the University of California, Santa Barbara where he earned a Ph.D. in Electrical and Computer Engineering and a Master’s Degree in Economics. While a student, he worked on projects for the Army Research Laboratory, the Air Force Office of Strategic Research, and NASA.

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