This is my quarterly missive intended primarily for my fellow financial professionals wherein I share items I have run across or thought about this quarter which I think might be beneficial to you. This month’s email may seem longer than normal; that’s because there are lots of graphs.

Between now and the end of the year I have seminars for CPAs (through Surgent) in Charlotte, Duluth (GA), Memphis, Chattanooga, Macon, and Raleigh. I would love to see you at one of those sessions.

Also, if you are looking for a speaker at your professional conference or event, please feel free to contact me for more information. I shared this last time, but thought I would just once more, I spoke at the FPA of North Alabama a while back and they made a short video clip.

First, I’m sure you are all familiar with Bill Sharpe’s famous paper, The Arithmetic of Active Management (if you haven’t read it, it really is a “must read”). Pedersen just came out with a paper that explores a few areas where Sharpe’s simple argument doesn’t hold, Sharpening the Arithmetic of Active Management. Very interesting nuances that I hadn’t previously considered.

Second, I saw an article about how calm markets have been recently and I wanted to see it graphically so I whipped up a spreadsheet. This data is through the end of September:

Notes and points of possible interest:

• I did the volumes on a log-scale (right) because of how they have grown over time.
• 21-day is to make it roughly monthly data (252-ish trading days in normal years, depending on how weekends fall. Also leap years, and market closures around 9/11/01 and the paperwork crisis of 1968 (market closed on Wednesdays) make that a little imprecise, but close enough).
• The last data point (September 2017) is at the 5th percentile of all the past volatility. So clearly on the low side, but certainly not unprecedented.
• The extreme volatility points (>3%) are located at:
• October ‘87 crash
• Last four months of 2008
• March ‘09
• August ‘11
• To convert from daily volatility to annualized equivalent you would (in theory) multiply by the square root of the number of periods. So 3% times the square root of 252 would be about 48%! Momentum and mean reversion throw that off though. Annualizing daily returns gives higher than actual annual volatility because of mean reversion in daily returns, and annualizing monthly returns gives lower volatility because of momentum.

Third, we removed REITs from client portfolios a while back and now a paper is out, Are REITs a Distinct Asset Class?, that supports our logic.

Fourth, for asset protection trusts, Nevada is winning:

• How Nevada Became America’s Safest State for Wealth Protection
• Klabacka v. Nelson: Nevada Supreme Court Makes Historically Significant DAPT Ruling
• State Rankings Chart

The last link above is to new charts on the best DAPT and Dynasty trust states. Nevada and South Dakota are the winners on both (ranked 1-2 and 2-1), and Tennessee is number three on both lists.

Fifth, suppose we have the following results:

Investment B has a beta of 2 but no alpha. There is just leverage. It is easier to see graphically:

Now suppose the returns looked like this:

This time there is no beta (leverage), but an alpha of 6%. It is easier to see graphically:

You can see that beta is just another way of talking about the slope of the line on an x-y scatter chart. Alpha is just another way of talking about the y-intercept.

We can also compare two investments to see if the difference in the returns is just the slope (leverage or beta) or is one is really a better investment (alpha or y-intercept). I modified my Russell spreadsheet to add a chart that shows the differences. Feel free to play with it, but here are some items I thought were of interest. Click the graphs for larger versions.

Small beats large right? Let’s see the scatter chart:

Notice I put the equation for the best fit line on the top right corner, but it’s kind of small. It says Y=1.1052X-0.0005 and the R^2 is 0.7388. That means the beta is 1.1052 for US Small vs. US Large but the alpha is (very slightly) negative. The R^2 is the correlation squared, so if we take the square root of 0.7388 we can see the correlation between the two is 85.95%.

What about value vs. growth?

Y=0.7195X+.0035 with an R^2 of 0.7225. So, value only moves about 72% (on average, this isn’t standard deviation, this is slope, standard deviation would be the dots spread out more vertically, but the slope line’s steepness and position could be unchanged) as much as growth, but on average is 0.35% higher (monthly, since this is all monthly data).

What about in small cap where I think the value effect is bigger?

Y=0.667X+0.0051 with an R^2 of 0.7758. So it is better – on alpha, not on beta. We could leverage value up by half (1.5*0.667) and we would have a slope (beta) of 1.0 and have an alpha of about 75 bps a month (1.5*51)! The standard deviation before the levering was 17.37% (small value) vs. 22.60% (small growth). After levering, the small value would be 26.06% so we might want to lever less to make the standard deviations the same rather than the slope of the line 1. If we did so, then the leverage would be 1.30 (rather than 1.50) and the equation would be y=0.8801x+0.0066. Even though the volatility is the same, the CAGR would have been 16.86% for small value vs. 9.64% for small growth – alpha of 722 bps annually!

(All of the above unrealistically assumes the risk-free rate is zero, and we could borrow or lend at that rate, but I didn’t want to complicate it even more by incorporating that piece too.)

Finally, I thought I would do the graph and equation for EM vs. Foreign (MSCI Emerging Markets Index and MSCI All Country World ex USA Index).

EM is on the y-axis and foreign on the x-axis:

The equation of the best-fit line is y=1.023x+0.0047 with an R^2 of 58.05% (i.e. correlation of 76%).

So, the beta is above 1 and there is a positive alpha (47bps/month). Notice the pretty big down months in EM though. The two points at the bottom are October ’08 (-22.01, -27.35) and August ’98 (-14.10, -28.91).

Too many people focus on the raw numbers and don’t deconstruct them into the beta or slope of the line (it’s easy to lever or de-lever something) vs. the alpha or level of the line (it’s easy to lower it with high costs, but very hard to raise it).

Sixth, I was thinking about maximum retirement plan contributions and I whipped up a few charts. For an owner younger than 50 in dollar terms:

In percentage terms:

(It’s not 100% at the beginning because the x-axis is Net Business Income rather than Adjusted Net Business Income which has the ½ of SE tax removed. The various plan calculations use Adjusted Net Business Income.)

Here it is for an owner over 50 in dollars:

And in percentages:

Seventh, I took three of my favorite valuation measures (Shiller PE Ratio, Average Equities, & Tobin’s Q) where I have quarterly data going back to the early 1950’s. I regressed the subsequent 10-year average return of the S&P 500 on them. In that regression, Tobin’s Q was not statistically significant. Possibly because of multicollinearity problems with the other variables (they are all pretty correlated). Dropping it, the best-fit line is given by the formula:

0.319282668 + -0.557755455 * (Average Equities) + -0.001400086 * (CAPE)

The adjusted R^2 is 0.869052254, which means I can explain about 87% of the subsequent 10-year returns with those metrics. Based on the most recent values, the 10-year expected return (average annual) is 4.57%. Nominal. Since the 10-year treasury is at 2.36%, the quity risk premium is estimated to be about 2.2% over the next 10 years. That’s pretty skinny.

[I also tried a 5-year regression and all the variables were significant. The best-fit line was given by the formula 0.380288396 + -0.879251158 * (Average Equities) + -0.007287618 * (CAPE) + 0.236929186 * (Tobin’s Q). The adjusted R^2 was 0.599125144 so not nearly as good a fit though. Predicts a 5.34% average annual return.]

Here’s the problem though. Suppose a client has $1,000,000 portfolio and you put it all in bonds because of how low the ERP is. At the end of a decade (no cash flows) at 2.36% it’s just $1,262,708 [$1,000,000*1.0236^10]. In a 60/40 mix it would be $1,436,155 [$1,000,000*(1+0.0457*0.6+0.0236*0.4)^10]. Of course, 60/40 is riskier, but $173,000 extra isn’t nothing.

Eighth, I saw pass rates on the most recent CFA exams here and it prompted me to do some calculations and comparisons. Since the pass rates on each level of the CFA were 43%, 47%, and 54% respectively, if we assume no one dropped out of the program after passing a level (the best-case assumption), then of those starting the CFA the overall success rate is roughly 10.9% (0.43*0.47*0.54). For comparison, the most recent CFP pass rate was 64.4%. IMCA only reports first-time and retake pass rates for the CIMA, not the overall pass rates, but I estimate the overall rate is 57.6% (0.57+(1-0.57)*0.42)*(0.57+(1-0.57)*0.46).

So, end-to-end, the CFP & CIMA exams have 60-percent-ish pass rates while the CFA exams are 10-percent-ish.

Ninth, how many fund managers actually beat index funds? Hint, it’s way worse than you thought.

Tenth, I have been explaining the optimal order for spending down a portfolio in retirement for a long time but realized my advice could be more granular.

The default order is:

1. Taxable (preserves tax deferral in the other accounts)
2. IRA (no RMDs on the Roth, so this reduces future RMDs by taking the funds now)
3. Roth

In other words, the taxable account should be exhausted before drawing down the IRA which in turn should be exhausted before drawing upon the Roth. There are exceptions to the default order however:

1. To the extent the assets in the taxable account have a low basis and/or the owner’s life expectancy is short, it may be prudent to leave the assets untouched for a step-up in basis rather than sell them to live on.

2. After the taxable account is exhausted, if the tax bracket is abnormally high it may make sense to spend Roth funds ahead of IRA funds (or find some other way to get to next year and a more normal tax bracket such as tapping a HELOC temporarily).

Contrary to popular belief, if the tax bracket is abnormally low (or there is “room” in a moderate bracket) it is not optimal to withdraw extra funds.  Rather, (partial) Roth conversions to use those low brackets are a superior strategy.  (See this post for more on the analysis of Roth vs. IRA in general.)

The reason the Roth is last in the list is simply because, under current tax law, there are no RMDs on Roth IRAs (there are on Roth 401(k) accounts).  If all retirement accounts had RMDs (or no RMDs) they would all be equivalent (see this post for caveats though).

The real goal is to preserve tax deferral as long as possible (without triggering higher tax rates), so with that in mind, we can add a little complexity to the simple order above. This is a more complete ordering for a married couple who may also have inherited IRAs:

1. Taxable
2. IRA or Roth inherited by older spouse
3. IRA or Roth inherited by younger spouse
4. Older Spouse’s IRA
5. Younger Spouse’s IRA
6. Roth

This order assumes the spouses have similar ages.  It is possible that given a large enough age disparity options 3 & 4 could swap places temporarily.

There is a related asset location strategy too. You decide between what is in taxable accounts vs. tax-advantaged accounts (these are generally retirement plans, though Coverdells, 529s, HSAs, etc. are also tax-advantaged) by putting the most efficient assets in the taxable accounts and everything else in the retirement accounts (details can be found here). Within the retirement accounts though, you then sort by expected return. You want the highest return items in the buckets with the longest deferral (i.e. lowest RMDs).

So, to recap, it’s a two-pass sort. First, assets with the highest tax efficiency in taxable accounts, and the lowest tax-efficiency in retirement accounts. Second, within the retirement accounts, the highest expected return assets should go into Roth-type accounts and lowest expected return assets into traditional retirement accounts.

Eleventh, this paper has great new data on very long-term returns on various asset classes in many countries – including investments in housing.

Here are the very highest level geometric real returns (see the paper for more granular info) for the period 1870-2015, but be sure to read my notes below:

• Bills (very short-term gov’t debt), 0.82%
• Bonds (approximately 10-year gov’t debt), 2.01%
• Stocks, 4.73%
• Housing, 7.46%

A few things I want to point out in case you just skim and don’t read the whole paper:

• The return on housing includes rental income not just price appreciation. But it is an unlevered (no mortgage) return.
• There are no taxes considered on any of the asset classes. In the case of the housing, that means no real estate taxes are included in the figure. In most places those taxes are about 1% so I would consider the returns overstated by about that much.
• Transaction costs aren’t considered on any of the investments either, and there is some survivorship bias (wartime devastation of some European housing). Depending on how frequently the investment is turned over those costs can be significant too (less so today on stocks, but historically it was much higher). I would subtract about another 1% from the housing and stock returns to account for that.
• We still haven’t accounted for any capital gains taxes or ordinary income taxes. Given the exclusion from gain on sale of a home (section 121 today and in the old days the ability to roll the gain into the next purchase as long as it was more expensive, and a one-time exclusion on downsizing), and the ability of many clients to use retirement accounts to purchase the other investments, you can ignore those taxes. In the case of a primary residence you are not taxed on the yield either (the yield is the rent you aren’t paying – the economists call this imputed rent).
• The returns on housing (again unlevered, total return) and stocks (what the paper calls risky assets) then are roughly the same.
• Stocks of course are much more liquid than housing. Also, as the ratio of housing to land has changed over time (much bigger houses on much smaller lots) I would expect the appreciation (but not rental income) to be smaller now (the structure depreciates in real dollars).
• The standard deviation of housing as shown in the paper is misleading. That is the standard deviation of returns to an index of all housing returns in each country. Since most housing risk is idiosyncratic (local market or specific to the property) that is way too low for any actual owner. On a primary residence alone (or just a few in a local area) the risk would be similar to stocks. Again, unlevered. If you have a mortgage it is like buying stocks on margin – but it doesn’t feel as risky.

Adjusting for the items I mentioned, I believe the compound real returns are approximately:

• Stocks ~3.5%
• Housing ~4.0%
• Bonds ~2.0%
• Bills ~1.0%

(Inflation was just under 4.0% in this data, so you could add that back to get nominal estimates)

Very different than what people think because we generally only see U.S. 1926 to present figures and think that is normal.

Twelfth, ESG investing (avoiding investments with “bad” Environmental, Social, or Governance aspects) is becoming more popular but has been around a long time. The approach was previously known as SRI (Socially Responsible Investing) or colloquially as avoiding “sin stocks”.

A quick note on terminology first. If I talk about a “good” or “bad” investment, it isn’t clear whether I mean in the moral sense or in the risk-adjusted-return sense, so I am going to use good/bad to refer to the expected risk-adjusted returns and virtuous/evil to refer to moral qualities. I’m also going to avoid scare quotes even though in many (perhaps most) cases reasonable people could disagree about the virtuousness or evilness of an investment. Of course, when I say “evil investor” I merely mean one that invests in companies that fail the ESG screen – not that they are literally evil people. Now on with the show …

There are a few issues with ESG investing, some of which are not obvious:

1. There is no universally, or even widely, accepted definition of an evil company. One person’s “arms dealer” is another person’s “defense contractor.” So, it isn’t clear which investments should be avoided. Google’s motto is “don’t be evil” yet they are frequently considered evil by at least some people.
2. ESG investments are screened, not weighted. In other words, if it is evil it gets zero investment. If it is “not-evil” (which is different from virtuous) it gets full investment. So, rationally, companies should be a little evil – little enough not to be screened out, but as much as is consistent with high returns otherwise.
3. Evil investors will get higher returns. As virtuous investors avoid evil investments the price declines, which is simply another way of saying the expected return rises.
4. There is a temptation to think that by investing in virtuous companies returns will be higher – virtuous investors can have their cake and eat it too. It is easy to imagine that evil companies will have higher costs or lower sales (or both) because of their practices. But if that is true, they are not just evil, they are stupid. An evil businessman might not particularly care about the environment or women’s rights, but he is unlikely to actually reduce earnings to try to harm either! Thus, the argument that virtuous stocks are good investments, can ignore the ESG part. Unless, somehow you believe the market is not pricing the expected returns of evil investments correctly. My guess is that management errs more frequently the other direction – a CEO would actually give up some shareholder return to be seen as virtuous and this is actually an agency cost problem, not a benefit.

Thirteenth, I highly recommend this paper from some folks at AQR about some of the issues in structuring even passive investments. Many considerations that you might not have thought about.

Fourteenth, this article is aimed at estate planning attorneys, but it is a great collection of questions – many of which should be asked in financial planning engagements.

Fifteenth, we got an email from a good client recently with the subject line, “Nervous About Capital Markets.” The relevant portion of the email he sent was:

David and Anitha,

I can be your poster child for your next article on a client who is concerned about the capital markets … I don’t understand why the capital markets continue to go up when no legislation on growth, tax relief, and infrastructure have occurred (the very reason the markets took off). At some point, investors will bail.

I don’t like to market time. I know our portfolio with you is diversified. What words of wisdom (“ride it out, what is your time horizon, what if you lose half?, etc.”) can you give someone who thinks the markets will deeply recede with the next North Korean shot or Presidential response/impropriety?

I thought you might like to see a portion of my response:

I may write a longer response later, I had a few thoughts kicking around that I was considering on the drive in this morning (prior to your email). I’m also currently re-reading some older research about the equity risk premium and thinking about that. In the meantime, I always pay attention to Robert Shiller’s opinions, and he recently had a very good analysis here.

Short version, which comports with what I see and what I had been thinking (it’s nice to be validated by Shiller, but maybe I’m falling prey to confirmation bias), is that markets look very high on the numbers, but there isn’t any euphoria – in fact the opposite. We’re not having to talk people out of loading up on stocks, we’re having to talk them out of going to cash. In that sense, you are the “poster child” – but one that actually supports staying invested! It’s odd, but frequently you should be worried about your allocation when you’re not worried. (This is true in both directions – in 1999 people were very comfortable if they were loaded up on internet stocks, in 2006 they were very comfortable buying real estate, and in early 2009 they were very comfortable in cash. The uncomfortable position is generally the most profitable. Going back even further, in 1980 people were scared to death of both bonds and stocks – remember this? – but loved their gold and money market accounts at double-digit rates.)

Of course anything can happen, and I don’t have any particular foreknowledge of what will happen. Today asset prices seem high, but psychology isn’t crazy. That implies to me that prices may actually be right. If our future is Japan’s recent past (since the early 1990’s), values are probably just about right.

Finally, my recurring reminders:

J.P. Morgan’s updated Guide to the Markets for this quarter is out and filled with great data as usual.

Jonathan Clements, Morgan Housel, and Larry Swedroe, all continue to publish valuable wisdom. Just a reminder to go to those links and read whatever catches your fancy since last quarter.

That’s it for this quarter. I hope some of the above was beneficial.

Addendum:

If you are receiving this email directly from me, you are on my list of Financial Professionals who have requested I share things that may be of interest.  If you no longer wish to be on this list or have an associate who would like to be on the list, simply let me know.

We have clients nationwide; if you ever have an opportunity to send a potential client our way that would be greatly appreciated.  We also have been hired by some of our fellow advisors as consultants to help where we can with their businesses.  If you are interested in learning more about that arrangement, please let us know.

We also offer a monthly email newsletter, Financial Foundations, which is intended more for private clients and other non-financial-professionals who are interested.  If you would like to be on that list as well, you may edit your preferences here.

Finally, if you have a colleague who would like to subscribe to this list, they may do so from that link as well.

Regards,
David

Disclaimer: The information set forth herein has been obtained or derived from sources believed by author to be reliable. However, the author does not make any representation or warranty, express or implied, as to the information’s accuracy or completeness, nor does the author recommend that the attached information serve as the basis of any investment decision. This document has been provided to you solely for information purposes and does not constitute an offer or solicitation of an offer, or any advice or recommendation, to purchase any securities or other financial instruments, and may not be construed as such.