Is Reverse Cap Weighting the “MoreyBall” of Financial Products?

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Is Reverse Cap Weighting the “MoreyBall” of Financial Products?

2019-11-15T13:10:49-05:00By |

Throughout the NBA season and Playoffs, the viewing public has discussed at length the continued evolution of the sport into a 3-point shooting league. Just as Oakland A’s GM Billy Bean and “Sabermetric Godfather” Bill James are perhaps the two most visible proponents of the “Moneyball” adoption in Baseball. Rockets GM Daryl Morey and stats-maven Ken Pomeroy have contributed to an evolution in Basketball strategy. There are many strategic innovations that these two have championed, specifically, the research done by Ken Pomeroy which essentially shows that 3-point percentage is largely random. Therefore, the only thing that an offense or defense can control is the number of 3-pointers attempted or allowed. If a team wants to capture the additional value allotted by a 3-point shot, then the most reliable way to do that is to attempt more of them.

So, what does this have to do with Index investing and why should you care? Historically, market cap weighted indices dominated the landscape because of their self-adjusting nature and lower operational requirements. However, as technology has reduced spreads and trading costs while increasing liquidity and hedging capabilities; Alternatives to Cap Weighting (such as Smart Beta, Thematic funds etc.) have become viable. The Reverse Cap Weighted US Large Cap Index (Reverse), is one such evolutionary index that is challenging the existing landscape by Reverse Cap weighting the S&P 500. In the absence of additional information predicting that the largest companies will continue to be the best performing, selecting an index that is weighted in a way which benefits a higher number of names (much like taking more 3’s – to make more 3’s) seems to be a beneficial strategy.

A deeper dive into the attribution of the Cap Weighted S&P 500 vs the Reverse Cap Weighted S&P 500 over the 10 year period from 1/2008-12/2017, reveals that although the S&P 500 had a few positions (such as Apple, Microsoft and Amazon) that performed far better in the traditional cap weighted scheme – over 2/3 of the constituents in the S&P 500 during that timeframe benefited more (i.e. higher contribution, or less negative contribution) when Reverse weighted, than the corresponding position in the S&P 500. The below data will show that companies which continue to perform at the pace, size and scale of the Apple’s, Microsoft’s and Amazon’s of the world are rare and difficult to predict. The “MoreyBall” element to Reverse, is the systematized and intuitive “Buy Low, Sell High” attribute inherent in the strategy, which is in direct opposition to the traditional cap-weighted Indices which allocate money to companies simply because they are large.

Introduction to Reverse

This Reverse Index– calculated by S&P Dow Jones – weights the constituents of the S&P 500 by (1/Market Cap), resulting in an index whose constituents are weighted in the reverse order of the S&P 500. While cap weighting is a widely utilized index method, it leads to an investment system which “Buys High” and “Sells Low” (an outcome that would be thought of as counter-intuitive in any other construct). Reverse, given its redistribution of weight, gives more weight to a segment of the S&P 500 (the smaller end of large-cap) that is underrepresented by traditional market cap weighted indices and seeks to take advantage of the “Size Factor”, where smaller cap names tend to outperform their larger cap peers over time. By utilizing this factor within the S&P 500 universe, investors may be avoiding many of the asymmetric information and liquidity concerns which restricts capacity and plagues true Small- or Micro-Cap names. While comprised of the same 500 stocks as the highly benchmarked S&P 500.

Comparing Reverse and S&P 500 Contribution

Exhibit 1

* The Reverse Index has an inception date of October 23, 2017, with a back tested time-series inception date of December 31, 1996 calculated by S&P Dow Jones Indices. All information for an index prior to its Launch Date is back-tested, based on the methodology that was in effect on the Launch Date. Back-tested performance, which is hypothetical and not actual performance, is subject to inherent limitations because it reflects application of an Index methodology and selection of index constituents in hindsight. No theoretical approach can take into account all of the factors in the markets in general and the impact of decisions that might have been made during the actual operation of an index. Actual returns may differ from, and be lower than, back-tested returns. Past Performance is no guarantee of future returns.

Over the 10-year period examined, the Reverse Index provided 328 basis points of additional return, albeit at a higher volatility than the benchmark S&P 500. During that period there were 733 positions which at one time or another appeared in the S&P 500 and at-all-times during that period, the indices were comprised of the same 500 to 505 positions. Therefore, we can compare the cumulative contribution of the positions in each fund and gain a sense of what drove the differences in performance. All contribution data for this study (including the annualized risk/return figure above) was pulled from Morningstar.

Exhibit 2

As referenced above, this chart shows that over two-thirds of the of the S&P 500 stocks contributed more profit (or less loss) when reverse weighting, as opposed to a traditional market cap weighted scheme. Of the 32.7% of observations that contributed more profit (or less loss) to the S&P 500, the average magnitude of that differential is about 15% greater (0.53% vs 0.46%) as demonstrated by the skinny tail on the right half of the graph. To drill further into the complexion of which names drive outperformance in each weighting scheme, Exhibit 3below displays the top ten largest differentials in favor of each strategy. Please note that the (+/-) figures are all displayed in terms of “Reverse relative to the S&P 500”, meaning that a positive figure indicates that a stock contributed more profit (or less loss) to Reverse and a negative figure indicates that a stock contributed more profit (or less loss) to S&P 500.

Exhibit 3

*All Return and Contribution data above was pulled from Morningstar

The “Return” column above references the total return of the stock from 1/2008-12/2017, or else for the sub-period of time that the security was included in the S&P 500 Index. Of the Top 10 (+/-) contributors, eight of the companies had a positive return over that timeframe and benefitted from the less concentrated Reverse strategy which applies more weight to the lower end of the large cap spectrum. However, two of the top ten, including Office Depot (the top differential company) present the interesting case of having significant negative total-period performance (-61% and -78% respectively) and yet providing significant positive contribution to Reverse. This is a function of the systematic “Buy low, Sell high” nature of Reverse weighting mentioned above. As the stock declined from around $12 at the beginning of the period to its low of $0.68, its position size within Reverse would have been increasing at every quarterly rebalance. Therefore, when the stock once again began appreciating in value, the Reverse Index was well positioned to take advantage of the ~620% rebound off the low – before it was eventually removed from the S&P 500 in December 2010.

The area in which the traditional S&P 500 Index excelled was through continued outsized performance from a relatively small number of very large companies. Eight of the bottom ten differential companies are Mega-Cap names which, solely by virtue of their size, receive large allocations in the S&P 500 and have had very strong performance over this timeframe. The other two companies on this list are energy companies that lost between 60-70% before leaving the S&P 500. The outsized contribution in the S&P 500 from these handful of very large, well-performing companies has lead some market observes to note that the S&P 500 is increasing looking like a momentum fund; A point that was well summarized by Ben Carlson in this 2016 articlein which he notes the momentum qualities of the S&P 500 and discusses the difficulties of maintaining a disciplined investing approach outside of the confines of a systematic Index.


Over the 10-year period examined, the S&P 500 has received great performance from some of its largest constituents. There is nothing particularly troubling about that on a portfolio level, given the overall concentration is still relatively low (Apple – the largest holding – is currently around 4%). However, as technology has advanced, so too has the pace and scale of disruption. Can the largest names of today (at their already mammoth size) continue their pace of outperformance going forward? And what happens to a “momentum” strategy when momentum turns? In the absence of knowing what the future holds, it may be beneficial to look at a strategy that systematically “Buys low and Sells high” within the curated and highly benchmarked universe of the S&P 500. Much as Ken Pomeroy’s research determined that 3-point percentage is random and therefore the best way to make more 3’s is to take more 3’s; Perhaps the best way to outperform the S&P 500 is to capture more contribution from 2/3’s (of the smaller, but still large cap) constituents instead of relying on the continued outperformance of a select few.

Posted by: Josh Blechman 06/05/18


The author, Josh Blechman is the Director of Capital Markets at Exponential ETFs, an SEC Registered Investment Advisor.

The Reverse Cap Weighted U.S. Large Cap Index (Reverse) is a rules-based reverse capitalization weighted index comprised of the 500 leading U.S.-listed companies as measured by their free-float market capitalization contained within the S&P 500 universe. The Index has an inception date of October 23, 2017, with a back tested time-series inception date of December 31, 1996.

The Reverse Cap Weighted U.S. Large Cap Index (the “Index”) is the property of Exponential ETFs, which has contracted with S&P Opco, LLC (a subsidiary of S&P Dow Jones Indices LLC) to calculate and maintain the Index. The Index is not sponsored by S&P Dow Jones Indices or its affiliates or its third-party licensors (collectively, “S&P Dow Jones Indices”). S&P Dow Jones Indices will not be liable for any errors or omissions in calculating the Index. “Calculated by S&P Dow Jones Indices” and the related stylized mark(s) are service marks of S&P Dow Jones Indices and have been licensed for use by Exponential ETFs. S&P® is a registered trademark of Standard & Poor’s Financial Services LLC (“SPFS”), and Dow Jones® is a registered trademark of Dow Jones Trademark Holdings LLC (“Dow Jones”).

Past performance of an index is not a guarantee of future results, which may vary.The value of investments may go down as well as up and potential investors may not get back the amount originally invested.Performance figures contained herein are contain both hypothetical and live returns; results, hypothetical or otherwise, are intended for illustrative purposes only. Index performance returns do not reflect any management fees, transaction costs, or expenses, which would reduce returns. Inclusion of a security within an index is not a recommendation by to buy, sell, or hold such security, nor is it considered to be investment advice. It is not possible to invest directly in an index.

The Index, strategy, and performance returns discussed are for informational purposes only and do not represent an offer to buy or sell a security and should not be construed as such.

One Comment

  1. Phil Bak June 19, 2018 at 8:26 am - Reply


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