Corporate profit margins and income inequality

Really interesting paper from the Jerome Levy Forecasting Center.

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Duration of This Bull Market

Grant Williams has a fantastic presentation regarding overvaluation of the current market:

A World of Pure Imagination

A related presentation, but with a different focus, comes from Jim Rickards:

What I find interesting is that in these, and many other analyses, the bull market is defined as having started in 2009, making this one of the longest (and thus presumably most overwrought) bull markets in history.

That brings me to Josh Brown.

Back in 2016, he noted that a bull market starts once a new high is reached, not from the prior low, and also that a bull market is interrupted by a new bear market on a 20%+ drawdown.  From The Reformed Broker:

  • It’s become likely that we are in a secular bull market for stocks. We do not measure secular bull markets from the bear market low of the prior cycle. The 1982-2000 secular bull market is measured from the day in 1982 when stocks finally took out their 1966 high. It had been a 16 year secular bear market until closing above those highs, and stocks never looked back. We do not date that bull market from the lows of 1973-1974 that were the nadir of the prior bear. Nor should we use 2009 as our starting point for the current bull market. 2009 was merely the cycle low of the prior bear, not the starting point of the current bull.
  • The actual starting point of the current secular bull market is the spring of 2013, when we broke above the double-top record highs of 2000 and 2007. This means we’re only into the third year.
  • I also would like to asterisk the fall of 2011 because the S&P 500 dropped 21% briefly in the depths of that panic, which would restart the count anyway if you were using 2009. This is semantics but important if we’re serious about dating. A drop into 20%+ drawdown, even if it’s brief, means a bear market and the end of the previous bull, if we’re using the generally accepted 20% (which is also meaningless, but it is what it is).

 

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General Dubik at Jefferson Erie Global Summit IX

These are my notes from General Dubik’s talk on Friday, November 17, 2017.
Gen Dubik is highly credentialed, including member of CFR.  His slides are all titled “Institute for the study of war.

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Is Passive crowding out Active?

FTSE Russell recently reported that market share of passive ETFs and mutual funds has grown from 12% in January 1998 to 46% at the end of December 2016.  They carefully define “passive” as funds that are intended to replicate market capitalization weighted indexes by holding the underlying assets.  Specifically excluded from this definition are other than cap weighted indexes and funds that hold options instead of the underlying.  Goldman Sachs agrees with this trend if not the exact number, reporting a change from 17% passive to 38% between 2005 and 2016.
This trend has not gone unnoticed by the active management world.  Analysts at Bernstein warn that the rise of passive investing may be worse than Marxism.  Similarly, analysts at CLSA call it “investor socialism.”  There is fear that the blind investment into all companies on a cap weighted basis will overwhelm the impact of active managers, who invest based on their research and due diligence efforts.  Additionally, the momentum effect of passive investors might be expected to result in the largest and most often index-listed companies growing to even larger market capitalizations with higher valuations, and being added to even more indexes, regardless of their economic value.  However, available data has not borne this out.
Jim Rowley from Vanguard recently posted this chart on his blog (https://vanguardadvisorsblog.com/2017/08/08/no-more-no-less-challenging-for-active/).  It shows that the percentage of stocks with significant under and over performance has not changed.  Interestingly, a chart using this same data but starting in 1998 was used to show that dispersion has gone down in a different blog post:

No historical relationship between index fund asset percentage and dispersion

Source: Vanguard calculations using data provided by FactSet and Morningstar, Inc. Index fund asset percentage is the percentage of assets in U.S.-domiciled equity funds invested in index funds. Sector funds are included.

Note: Dispersion is defined as the percentage of stocks in the Russell 3000 Index that have either outperformed or underperformed the index by at least 10 percentage points.

Data from Zacks.com shows that the equities comprising the S&P 500 individually have betas ranging from -0.02 to 2.79.  Recognizing that this is a somewhat circular reference, only one stock has a negative beta, meaning that when the market moves up, on average they are ALL moving up.  This data implies that it may be difficult to implement a long-short strategy, because the equities that underperform in a rising market are still rising, even those that underperform the most.  Beta is defined here as a 5 year calculation based on monthly returns.  This is important, because it means that the betas are based entirely on bull market data.  So they are all moving up together, but not equally.  Active opportunities exist.

Another measure of active opportunity within the stock market is the CBOE implied correlation index.  If passive investing really overwhelms active, you would expect to see correlations rise.  This effect has not been seen in the data.  See detailed explanation from Henry Ma, https://www.etftrends.com/is-there-a-passive-investing-bubble/.

Another way to look at how passive holdings might impact market function or efficiency is to compare price volatility of individual stocks in comparison to the proportion of their shares that are held in passive funds.  If passive funds are holding and not trading shares, liquidity may suffer causing spreads to increase.  Savita Subramanian at BAML has found that as the passively held proportion increases, prices become stickier; equity price adjustments based on earnings surprises are not as quickly reflected in price.  In contrast, Pravit Chintawongvanich of Macro Risk Advisors looked at realized volatility versus percent passive ownership and did not find any effect.

Arbitrage price theory posits that if an arbitrage is available, market participants will make that trade until prices reach an equilibrium where the arbitrage is no longer available.  This suggests that if the market is becoming less efficient, active traders should have an advantage and active funds should show better results.  It is only one data point, but the most recent SPIVA report (https://us.spindices.com/search/?ContentType=SPIVA) shows that active fund performance has been improving over the first half of this year.

Although active managers continue to suffer outflows to passive funds, there is scant evidence to this point that passive investing has distorted the market to the point that active investors cannot impact prices.  Active investing is necessary and, in fact, makes passive investing possible by providing price discovery for passive equity buyers.

In a separate but related topic, The New Yorker reported last year on impacts passive investing may have on the economy, (https://www.newyorker.com/business/currency/is-passive-investment-actively-hurting-the-economy).

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Cars of the future

Maybe not flying yet like Jetsons or Back to the Future, but advances are in process and inevitable.

From Zacks Investment Management:

Self-Driving Cars Reach New Milestone – for those readers who are still reluctant to believe in the electric car and self-driving car revolutions, we understand (but it’s time to start believing). Where the U.S. government is generally snail-pace slow in legislating in lockstep with technological change, they have passed a bill that creates a national framework of regulations for the industry. The bill includes amendments covering cybersecurity issues and allows automakers to sell up to 80,000 self-driving vehicles annually, assuming that safety standards are met. On the automakers front, it’s been an active week as Ford detailed a strategy for future investment of research and resources into self-driving cars. General Motors followed suit by indicating that its ‘Cruise Automation’ business is making rapid progress on fully autonomous driving capabilities.

Lots of hate on Tesla and Elon Musk is a continuing theme, but Tesla just keeps on keepin’ on.  As soon as production of the Model 3 ramps up to plan, electric cars are a done deal and cannot be stopped.  I’m not sure why Zero Hedge has such an axe to grind (lots of MLP and energy positions, perhaps?), but they sure do.  Here’s a couple of the latest screeds:  http://www.zerohedge.com/news/2017-10-07/visualizing-many-failures-elon-musk

http://www.zerohedge.com/news/2017-10-06/teslas-big-secret-its-building-model-3s-hand

Meanwhile, the production line continues to go through development and troubleshooting:

The Model 3 body line slowed down to 1/10th speed

A post shared by Elon Musk (@elonmusk) on

And GM, Volvo, and Jaguar have also already announced they will be eliminating internal combustion engines completely.  https://www.wired.com/story/general-motors-electric-cars-plan-gm?mbid=social_twitter

 

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Neuroscience & Module Model

From Eric Barker:

Both neuroscience and psychology are starting to agree. Sometimes you don’t act like you because there is no singular “you.”

Here’s noted science author Robert Wright:

In this view, your mind is composed of lots of specialized modules—modules for sizing up situations and reacting to them—and it’s the interplay among these modules that shapes your behavior. And much of this interplay happens without conscious awareness on your part. The modular model of the mind, though still young and not fully fleshed out, holds a lot of promise. For starters, it makes sense in terms of evolution: the mind got built bit by bit, chunk by chunk, and as our species encountered new challenges, new chunks would have been added. As we’ll see, this model also helps make sense of some of life’s great internal conflicts, such as whether to cheat on your spouse, whether to take addictive drugs, and whether to eat another powdered-sugar doughnut.

Now modules aren’t physical structures in the brain, just like apps aren’t hardware in your phone. They’re software; the human nature algorithms that Mother Nature coded over thousands of generations of evolution.

Whichever module has the most emotional kick attached to it at any point wins the competition to be “you.”

Buddhism recognized this problem over 1000 years ago. And it also came up with a solution: mindfulness meditation.

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Fundamental Indexing

Consider the purpose of a market index.  We use an index to define the value of the market, overall.  When we use a market index as a benchmark for any specific holding or portfolio, we need to be able to rely on that index as a reasonable measurement for what “the market” is worth at any given moment, and over time.  If you are an efficient market hypothesis believer, market capitalization weighting is the only accurate way to measure the economic value of any specified market.

But what if you think that at least some of the time, prices for individual companies, sectors, and even the whole market can diverge from their true economic value?  This premise is the basis of factor investing, “smart beta,” and behavioral investing.  Several “fundamental” weighting schemes have been developed to try to measure economic value in ways other than equity price.

Dividend discount model is a simple and common method of determining the economic value of a stock.  Free cash flow models based on earnings are also widely recognized.  WisdomTree has offered both dividends and earnings weighted funds for over 10 years.  Jeff Weniger offers a thorough explanation of the advantages of earnings weighting at https://www.wisdomtree.com/blog/2017-05-15/the-wisdomtree-earnings-500-trexing-money-managements-accident-of-history and Jeremy Schwartz published a white paper in 2016 detailing dividend weighting,  https://www.wisdomtree.com/-/media/us-media-files/documents/resource-library/whitepaper/the-dividends-of-a-dividend-approach.pdf.  Pacer US Cash Cows 100 Index selects and weights the largest 100 companies by free cash flow.  The associated ETF, COWZ, just opened in December 2016.  They describe their approach here: https://youtu.be/kUyMqNq5IMo.  Please note that this is a new index as well, so it really doesn’t have a track record other than backtesting.

Oppenheimer weights by top line revenue, as explained by David Mazza, https://www.oppenheimerfunds.com/advisors/article/revenue-uncovers-value-in-a-rich-stock-market. The tech bubble is used as an example here.  You can see how at the height of the bubble, a minority of the stocks with increasing prices came to dominate the cap weighted index, but not so much the revenue weighted index.

Oppenheimer Revenue Weighting – graph from page 16 of Oppenheimer presentation – used with permission.

Rob Arnott (arguably the originator of fundamental weighting) and Research Affiliates (RAFI) have developed 3 unique indexes, which weight companies with varying combinations and definitions of sales, cash flow, dividends, and book value.   The FTSE RAFI US 1000 Index consists of the 1000 largest companies as calculated by their economic value, using a formula including total cash dividends, free cash flow, total sales, and book equity value.  Invesco, who sponsors the ETF for this index (PRF), shows the converse of the Oppenheimer example:  during the last crisis, the financial sector became under valued, and thus under weighted in the cap weighted index.

Invesco chart – used with permission.

Critics of the fundamental approach to indexing call it value investing by another name.  This is true by definition.  However, the difference between a value index and a fundamental index is that the fundamental index is not using the equity price in any form to determine inclusion or weight in the index.  A value index will always include some form of the price in its inclusion and/or weighting calculations, usually in a ratio (P/E, P/S, etc.).  The amount of value tilt changes over time for a fundamental index, while it is defined for a value index.  Issuers of fundamental indexes consider this a feature, not a bug.  The goal of the fundamental index is to represent the market constituents weighted by their economic value or economic impact, not to determine which equities or sectors are “incorrectly” priced.

What about performance?

As of 6/30/17 3 yr 5 yr 10 yr
YTD 1 yr 3 yr 5 yr 10 yr sd beta sd beta sd beta
S&P 500 TR Index 9.34 17.9 9.61 14.63 7.18 10.35 9.56 15.21
FTSE RAFI US 1000 Index 4.69 16.92 7.89 14.82 7.68 10.25 0.96 9.73 0.99 16.02 1.04
WisdomTree LargeCap Dividend Index 6.7 14.23 9.08 13.19 6.72 9.87 0.93 9.12 0.92 14.63 0.93
OFI Revenue Weighted Large Cap TR 7.41 16.49 8.7 15.55 7.29 10.38 0.98 9.9 1.01 16.51 1.07
WisdomTree US Earnings 500 Index 9.39 22.29 9.46 14.65 7.35 10.81 1.03 9.91 1.02 15.03 0.98
Pacer US 100 Cash Cows Index 6.74 23.15 9.02 16.98 10.32 13.46 1.2 12.41 1.2 19.83 1.21
Russell RAFI US Large Company Index 4.8 14.2 7.75 14.3 7.91 10.25 0.96 9.73 0.99 16.02 1.04
*Data from ETF providers and Morningstar

Please note that the outlier in this group, Pacer, reflects backtesting data prior to 2017.  The three year betas less then one suggest that the fundamental indexes are not performing as well as the S&P 500 over this portion of a bull market, and they are not.  A full market cycle would be the best way to evaluate performance.  The 10 year betas less than one might be what is expected – a dampening effect from removing the impact of excess pricing at market highs, and oversold equities at market lows. Another way to look at it would be that the market tends to overshoot at both extremes – the real economy is not moving as much.  But of the 6 indexes, only 2 reflect this theory.

What explains this?  The fundamental indexes are rebalanced quarterly or annually, while a cap weighted index self-rebalances on a continuous basis, other than adjustments for changes in listings and float. Rebalancing also adds trading costs as well as possible tax liabilities.  RAFI methodologies use 5 year averages of data, so they will be slower to respond to changes in issuer value than the cap weighted index.  The Oppenheimer and WisdomTree indexes are also capped by issuer and sector.  Similar to smart beta, it’s just more complicated to implement these strategies than cap weighted.

The ETFs based on fundamental indexes generally charge around .25% – .50%, while the cap weighted index ETF can be bought for .03%.  The 10 year returns net of fees are very similar to the cap weighted index.  Other cost considerations are size and trading cost of the ETFs, as well as tax implications. Obviously dividend weighted funds will have higher taxable income than cap weighted.

In summary, the theory of the fundamental index is quite compelling, but the current indexes somewhat less so. It seems likely that this reflects the difficulty in implementation rather than flaw in theory.

Disclosure:  I do not currently hold or plan to add any fundamental weight products for myself or clients.  Do have positions in cap weighted funds and ETFs.

 

 

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