Archive for 2018

Current Best Choice for Loan Allocation

Tuesday, October 23rd, 2018

We have been asked recently why we are using an ultra-short-term, investment-grade, floating rate debt fund instead of some other higher yielding debt fund in the Loan allocation.

The short answer is that ultra-short-term, investment-grade, floating rate debt is currently most attractive considering inflation, taxes, rising Fed Funds rates, and degree of correlation with stock market price changes and stock market event risk.

That more attractive status will continue until the Federal Reserve has substantially completed its interest rate normalization program sometime in 2019.

The blue line in this chart is the actual Federal Funds rate; and the red line is the Federal Reserve forecast of where they expect the Federal Funds rate to go. You can see that the forecast is for about 3.4%. The current 10-year Treasury rate is about 3.2% which will surely rise as short-term rates rise.

(click images to enlarge)

Looking across the various types of debt available in mutual funds and ETFs, it is clear to us that ultra-short-term, investment-grade, floating-rate debt (“UST-IG-FR”) is the best current choice.

Senior floating-rate bank loans will probably have higher return after inflation, after taxes, after Fed rate increases than UST-IG-FR debt, but with significantly higher credit risk, and significant stock market “event risk”. Due to low loan quality, bank loan debt has significant correlation with stock market price moves, and limited liquidity in a crisis. T-Bills will have essentially no credit risk or stock market event risk but lower return than UST-IG-FR debt after inflation, taxes and Fed rate increases.

At this late stage in the stock market cycle, using debt with a high correlation to the stock market is not good risk management.

We expect to redeploy our Loan allocation to longer duration debt sometime in later 2019, based on the published schedule of rate increases from the Federal Reserve.

This is how the prices of T-Bills, UST-IG-FR debt and senior banks loans did over the past 12-months as the Fed Funds rate rose 1.02% over those 12-months.

The following charts plot the price change of funds representing key debt categories over the past 12-months, during which the Federal Reserve raised the Fed Funds Rate (the base rate for USA debt) by 1% in 0.25% increments at a steady pace.

We make the simplistic assumption that the funds will experience a repeat of price changes over the next 12 months that they experienced over the last 12 months. That is because the Federal Reserve rates over the next 12 months are expected to rise by the same amounts, at the same pace, over the next 12 months as they did over the lasts 12 months.

TREASURY DEBT

CORPORATE DEBT

MUNICIPAL DEBT

REGIONAL AGGREGATE INVESTMENT GRADE DEBT

 

The next table  illustrates our view on key debt types and shows UST-IG-FR debt as one of three categories with expected positive return after inflation, after taxes, after a 1% Fed Funds rate increase over the next 12 months. The other two are 1-3-month Treasury Bills and senior, floating rate bank debt.

UST-IG-FR debt has a lower net yield than Senior Bank Loans, but much lower credit risk and much lower stock market event risk. UST-IG-FR has some minor credit risk being rated “A” and minimal stock market event risk.

If essentially zero credit risk and essentially zero stock market event risk is the goal, then T-Bills are the way to go. However, we think Ultra-Short-Term, Investment-Grade, Floating Rate Debt is where we want to be at this time and until the Fed substantially completes rate normalization in 2019.

For the “Duration Price Effect”, we make the assumption that the price behavior over the last 12 months during a 1% Fed Funds rate increase will be duplicated over the next 12 months during which the Fed’s behavior is expected to be the same as the last 12 months. The Fed raised its base rate 1% over 12 months and plans to do the same over the next 12 months.

The Maximum Drawdown is a measure of the largest drop from a peak to a trough during the indicated period.

You can see that an estimate of the total return after inflation, after taxes and after duration price effect is 0.04% for T-Bills, 0.35% for UST-IG-FR debt and 0.81% for senior floating rate bank debt (note this sort of bank debt has major potential liquidity problems during a crisis).

Medical Equipment ETF (XHE) Added To Tactical Sleeves

Wednesday, September 26th, 2018
  • ETFs with solid momentum are currently focused on tech, health care and small-cap.
  • Only 18 of 2051 ETFs passed our momentum screening filter rules.
  • We further subjectively evaluated quantitative and qualitative data for the 18 and selected medical equipment ETF XHE as an addition to our tactical sleeve.

For those clients who complement their core strategic positions with a tactical momentum rotation sleeve as part of their Personal Investment Policy, we have added the medical equipment ETF (XHE) to those tax deferred accounts where we have discretion; and we recommend that addition for those accounts for which we provide advice.

That advice is to clients only. For readers here, this article is for information purposes only, and is not personal investment advice.

The filter we use to select ETFs for tactical momentum rotation requires at minimum these things:

  • Upward sloping 1-year regression trend line
  • 200-day average higher than 1 month ago and price above 200-day average
  • Price return 10% or more in excess of both T-Bills total return and S&P 500 total return over 12 months ending 1 month ago
  • Maximum drawdown over last 3 months not more than 10%
  • 3-month average Dollar trading volume per minute at least $15,000
  • Total Dollar trading volume over 3 months greater than the 3-mo total volume ending 3 months ago.

From the current 18 survivors of that filter out of 2051 ETFs, we subjectively evaluated other quantitative and qualitative factors, to select XHE for addition to tactical momentum rotation sleeves.

To remain in the portfolio a tactical position must continue to satisfy the minimum conditions on a weekly review basis, except that the total return, if greater than that of T-Bills, need only exceed that of the S&P 500 by 2%; and trading volume growth is not required. A position might be replaced with a more attractive tactical selection if the total amount allocated to the tactical sleeve is fully invested.

The following presents some, but not all, of the information we used in addition to our rules-based filter to make our selection.

The next two charts effectively demonstrate the recent historical momentum and superior performance that suggests the likelihood (but not certainty) of short-term inertial continuation of momentum for XHE.

(click images to enlarge)

1-Year

This shows the 1-year total return of S&P 500 (SPY in blue), S&P 500 Health Care Sector (XLV in orange), and S&P Total Market Medical Equipment (XHE in red).

3-Years

This shows the relative total return performance of SPY, XLV and XHE over the past 3 years.

The next two charts add another healthcare ETF (PSCH) currently in our tactical sleeve, and also as a useful comparison, the iShares momentum factor ETF (MTUM).

1-Year


3-Years


Currently, of the 18 momentum ETFs identified by our filter, they are all small-cap, technology, health care, except for one retail ETF.

The relative returns of the five identified ETFs can also be viewed in tabular form to isolate specific trailing periods from 1 month to 3 years, as shown here:

Additionally, you can see the volatility (standard deviation) and Sharpe Ratio [(total return in excess of T-Bill return)/standard deviation)].

XHE is generally higher return than SPY and XLV, but is also more volatile. However, its Sharpe Ratio (return you get for the volatility of the ride) is competitive with the S&P 500.

This next table presents some comparative valuation and fundamental data.

XHE has higher valuation ratios, lower yield, lower ROE and ROA than the S&P 500 and its health care sector, which are risk factors. It has somewhat lower debt.

The following table shows a “growthier” XHE, compared to the S&P 500 and its health care sector. Its 1-year PEG (P/E divided by 1-year forward earnings growth expectations) is competitive with the S&P 500 and better than the S&P 500 healthcare sector.

State Street Global advisors forecasts a 14.6% 3-5 year earnings growth path for the health care sector versus a 13.4% path for the S&P 500.

Looking inside of XHE’s 74 holdings, and comparing them to the holdings of factor funds operated by Vanguard, we see that 33 of them accounting for 48% of XHE assets by weight are included in the portfolio of VFMO (Vanguard’s momentum ETF based on the Russell 3000).

We also see that 9 XHE holdings (16% of its assets by weight) are included in VFMF (Vanguard’s multi-factor fund, also based on the Russell 3000). The multi-factor fund holds stocks that present a balance of attributes between value, quality and momentum, after excluding the most volatile stocks.

Including those not seen, 3 of the XHE holdings are in the Vanguard value factor fund (VFVA) and 21 are in the Vanguard quality factor fund (VFQY).

We do not commit to publish an article when this position is closed. We may do so, but make no promise to do so; and even if we did it may not be timely.

If you take a tactical position in any security mentioned here, do not rely on a subsequent article to notify you of a change in our position on the security. We, of course, keep our clients advised of any changes or actions on a timely basis.

Risk Asset Allocation Based On Momentum Relative To T-Bills

Friday, September 7th, 2018
  • It’s more about winning by not losing in Bear markets than winning in Bull markets.
  • The approach tends to generate higher returns and lower maximum drawdowns than Buy-and-Hold when a Bear is in the study period.
  • The approach tends to underperform Buy-and-Hold in study periods that do not include Bear markets.
  • The approach with a single risk asset versus T-Bills tends to be more tax efficient in regular accounts than selecting the highest momentum of several risk assets or T-Bills due to longer in-market periods with more long-term taxable gains.
  • The approach is better suited to tax-deferred accounts than regular taxable accounts.
Questions continue to come in about systematic approaches to tactical allocation portfolio changes – methods not based on biases, media frenzy, forecasts, chart patterns, valuation or fundamentals.

Probably the simplest approach, and one that is about as objective and non-judgmental as systems can be, is to hold those risk assets that are doing best, unless none of them are doing better than T-Bills; in which case hold T-Bills until the risk assets start doing better than T-Bills.

The most reliable aspect and driver of returns of the approach is minimizing major drawdowns, as shown by the flat lines in the blue timing portfolio when the red benchmark portfolio experienced major drawdowns.

Secondarily, the approach may increase total return. However, each trade triggers a tax event, so only those cases where the average holding time between trades is over 1 year avoid ordinary income taxes on the trades; and those that have the longest position hold times benefit most by compound growth.

The approach can be used in an outright decision to hold risk assets or risk-free T-Bills (or other “cash”), or it can be used for guidance in a strategic allocation portfolio to make overweight and underweight decisions.

The approach is not tax efficient for regular taxable accounts, but in some cases the outperformance may be worth the tax cost. Trading systems such as this are best used in tax-deferred accounts.

Relative and absolute momentum can be done at an extremely simple level, such as rotating between one specific risk asset and T-Bills (e.g. the S&P 500 and T-Bills).

That method could be used in layers, with more than one pair of two assets (e.g. S&P 500 and T-Bills as one pair, and emerging markets stocks and T-Bills as another).

It is also possible with the method to choose one or more risk assets within a larger group of risk assets or T-Bills (e.g. the two strongest momentum risk assets out of five or T-Bills).

Working with simple pairs of one risk asset versus T-Bills is more likely to create longer position hold times, and therefore be more tax efficient for regular taxable accounts than alternating between risk assets or T-Bills. Alternating between risk assets creates more frequent trades and would be more suitable for in tax deferred accounts.

The method helps avoid the severity of Bear markets, but it also needs Bears to generate enough of a performance difference to make the effort and potential tax cost worthwhile.

The approach does not work with all assets. Testing is required to see if it worked in the past.

Here are some actual 09/03/18 relative return and absolute momentum indicated holdings:

It is possible to operate this approach by visual inspection of charts, but for more precision and to avoid seeing what you may want to see, using quantitative data is preferable.

You would need to find the performance evaluation period (e.g. the number of days, weeks, months quarters, years) that produces the best combination of high return and low maximum drawdown, based on long-term history, and the best frequency of decision making (e.g. daily, weekly, monthly quarterly or longer). The “best fit” evaluation period and decision frequency will probably drift over time, so it needs to be regularly evaluated for adjustment.

The information that follows gets a bit into the weeds of the approach.

The securities we used for the test were selected in part because they had adequate history to capture a sufficiently long study period:

  • VFINX: S&P 500
  • VGTSX: total international stocks
  • VEIEX: emerging markets stocks
  • VGSIX: US real estate
  • VFINX: intermediate-term Treasuries
  • Treasury Bills

ETF alternatives may be more tax efficient for current use, but did not have sufficient history for long-period analysis.  These ETFs are classes that invest in and share the same underlying portfolio as the mutual funds used in the study (except for BIL):

  • VOO: S&P 500
  • VXUS: total international stocks
  • VWO: emerging markets stocks
  • VNQ: US real estate
  • VGIT: intermediate-term Treasuries
  • BIL: Treasury Bills

If the investor wishes to use options (for example, covered Calls) on the S&P 500 position, then SPY would be needed because it has the options and liquidity that would be suitable.

There are other ETFs from other sponsors that could just as well be used instead of the Vanguard ETFs in a forward practice.

First, Portfolio Visualizer is among the sites that provide good tools for experimenting with the approach, and it is free. There are subscription sites that have a number of pre-built models that can be followed as well.

The data that follows is entirely from Portfolio Visualizer.

The tables above and below illustrate how the evaluation period and frequency might be regularly reviewed for possible adjustment, and provide evidence of the efficacy of the approaches from 1997 to 2018 YTD, as well as return, maximum drawdown and several other important metrics for the results for method and their benchmarks.

The illustrative cases are for the S&P 500 as a single risk asset versus T-Bills (above); and the best 2 of 5 risk assets versus T-Bills (below).

The charts and tables that follow are for S&P 500 versus T-Bills, and for selecting the best 2 of 5 assets (S&P 500, DM stocks, EM stocks, US REITs, and Intermediate-term Treasuries) versus T-Bills.

In each case, the backtest period was about 42 years (1997-2018 YTD).

In the best 2 of 5, the result could be 2 risk assets, 1 risk asset and T-Bills, or all T-Bills.

Single Risk Asset vs T-Bills

The timing model produced a 19.67% return over the period 1997-August 2018 versus 8.42% for the equal weight portfolio, which in this case is 100% S&P 500. Note that these results are based on investable assets, not indexes.

While results such as this could have been available to you if you did this on your own, they would not have been effective for a “hedge” fund type investment with their 2% management fees and 20% of gains above a preferred return, because the return difference of 2.22% would have been wiped out by their fees.

The volatility (standard deviation) of the method was lower than buy-and-hold. The best year was better, and the worst year was dramatically better (negative 7.67% versus negative 37.02%). The superior maximum drawdown was critical (down 16.31% versus down 50.97% for buy-and-hold).

The average trade lasted 29.9 months, which tended to create capital gains as opposed to ordinary income when trades were executed.

The Sharpe Ratio (return in excess of T-Bill return, divided by the standard deviation of return – how “bumpy” the ride was) was better for the method (0.79 versus 0.48), as was the Sortino Ratio (like the Sharpe Ratio but only divided by the size of downside volatility) at 1.29 versus 0.70.

Last, as a small form of diversification, the correlation to total US stocks was only 0.74 versus 0.99 for buy-and- hold

The complete trade history from 1997 is in this table:

However, not all backtests are inspiring. The specific time period you test and whether or not a Bear intervened are critical to how attractive the method appears.

It can be years of effort with little if any outperformance to show (and taxes in regular accounts) if a Bear is not in the period.

It takes a Bear to make relative momentum versus T-Bills look good.

Best 2 of 5 Risk Assets vs T-Bills

As with the single risk asset (S&P 500) versus T-Bills, the best 2 of 5 risk assets was superior (excluding any tax considerations) to the equal weight, buy-and-hold approach.

Compound return was better by 4.73%. Standard deviation was almost the same. The best year was better by 16.73%. The worst year was better by 13.68%. The maximum drawdown was better (less severe) by 26.15%. The Sharpe Ratio was higher by 0.37. The Sortino Ratio was better by 0.79. The correlation to total US stocks was lower by 0.30, and the Beta to total US stocks was lower by 0.22. All good.

There were many trades for an average trade holding time of 2.37 months. That created a lot of ordinary income for someone doing this in a regular taxable account. The trades over the past year are in this table.

Selecting the best 2 of 5 risk assets might be expected to be more effective during periods without a Bear market, but the evidence in our test suggests that is not the case. Looking at the period 2010 through August 2018 (a period without a Bear), we were able to find an evaluation period that produced a 2+% higher return (before any tax costs), but it produced a 1+% more severe maximum drawdown — it did not provide the downside protection the method is intended to provide.

The most useful evaluation period we found for the best 2 of 5 model was 12 months. It produced a 9.56% return versus 7.49% for the equal weighted benchmark, but experienced a 16.69% maximum drawdown versus 15.50% for the benchmark.

The following charts show the results for evaluation periods of 1, 11 and 12 months.

1 Month Evaluation Period (2010 –Aug. 2018)


11 Months Evaluation Period (2010 – Aug. 2018)


12 Months Evaluation Period (2010 – Aug 2018)


Because we consider maximum drawdown protection key to the utility of relative momentum versus T-Bills, our conclusion is that the method needs a Bear market to be attractive.

Relative momentum allocation between a risk asset and T-Bills can produce meaningfully higher return and substantially less severe maximum drawdowns, but the fact is that the avoidance of large drawdowns (Bear markets) is the most important contributor to the potential of the method to outperform.

If there is no Bear market during the time the method is used, the potential for outperformance is limited.

Tax costs are a problem in taxable accounts (more when selecting among multiple risk assets, because position holding time is shorter with more ordinary income tax cost).

No universal evaluation period is effective for all risk assets, and the evaluation periods that work best drift over time, making continuous curve fitting part of the challenge and work load.

Not all assets have good potential with the method (basically only those that have occasional major drawdowns appear to work well).

Because of the role of Bear markets in creating advantage for the method, it is important when reviewing reports about the method to distinguish between long-term studies incorporating one or more Bears, and short-term studies of Bull markets.

Winning by not losing is the most important benefit of the method. The benefit derived is greatest when the loss experienced by buy-and-hold is greatest.

As must always be said, past performance is no guarantee of future performance.

I hope that for those of you who have been asking about the popular idea of risk reduction with relative momentum versus T-Bills, that this is helpful.

 

 

Relative Momentum Portfolio Rotation to Minimize Bear Market Risk

Friday, August 24th, 2018
  • Relative momentum rotation between strategic assets and cash
  • Relative momentum rotation between a choice of strategic assets and cash
  • Potential problems when using relative momentum approach

One approach to a simple rules-based, mechanical system to manage opportunity and potentially minimize maximum drawdown in Bear markets is to use relative momentum between each strategic asset and a risk-free asset (T-Bills) as an alternative — all-in or all-out of each strategic asset based on its return versus the return of T-Bills.Bear market.

The shorter the evaluation period, the smaller the maximum drawdown exposure — but the greater the trade frequency which is not tax efficient in a regular taxable account, and the more frequent the whipsaw (sort of a head-fake by the market requiring reversal of the position with positive loss or opportunity cost).

The longer the evaluation period, the larger the maximum drawdown exposure — but the lower the trade frequency, which is more tax efficient in regular taxable account, and the less frequent and potentially less costly the whipsaw.

Ways to attempt the avoid the worst of each evaluation period length while attempting to capture some of the best of the each evaluation period may be to use an average of shorter and longer periods, or to step into and out of strategic positions in phases by using more than one evaluation period length.

Relative Performance Rotation With the Swensen Portfolio:

Let’s look at an example, using the Swensen Reference Portolio as a base case with 2018-08-23 data.

Swensen is the CIO of the Yale Endowment, who proposed his “Reference Portfolio” as something from which to depart for a personally suitable portfolio in his book, “Unconventional Successs: a Fundamental Approach to Personal Investment”. He did not recommend momentum rotation in that book.

The Swensen portfolio is 70% OWN, 30% LOAN and 0% RESERVE.

This table shows the Swensen portolio as the default allocation, and to the right of that are four alternative allocations based on whether the strategic risk asset has outperformed risk-free cash over a 3, 6, or 12 months rating period, or the average of those periods. Where the risk asset did not outperform, cash is held in lieu of the asset.

(click images to enlarge)

Pink shaded cells indicate that the strategic risk asset is not held and instead the money for that slot is held in Reserve in risk-free T-Bills.

The tables on the left show the total return of each asset over each evaluation period and the excess return. The excess return is the total return minus the return of the risk-free asset (T-Bills) for the same period.

For equities (OWN), the relative momentum method suggests not owning the emerging markets fund at this time, and only owning the non-US developed markets fund if using the 12-month evaluation period.  Total US stocks and US REITs have positive excess return for all periods and would be held at the full strategic allocation level.

For debt (LOAN), the relative momentum method suggests intermediate-term Treasuries should not be owned if using the 12-month evaluation period.  Short-term TIPS are OK for all the periods.

You can operate portfolios, with any chosen set of risk assets using relative momentum as illustrated here. Such portfolios can be rebalanced at intervals ranging from monthly, quarterly, semi-annually to annually.

The longer rating periods may lag too much, and the shorter periods may be prone to whipsaw losses or opportunity cost. The method is intended to capture the bulk of major up trends and to avoid the bulk of major down trends.

This is not a panacea approach, and may or may not improve returns, but probably can limit maximum drawdowns associated with Bear markets without relying on the variable quality of judgement (assuming as is typically the case that market tops are a process of rolling over; not a steep, sudden drop).

Staged In-and-Out Approach:

Let’s say, you were using a staged in-and-out approach to each strategic asset based on three steps governed by the 3-month, 6-month and 12-month relative returns.

  • VTI would be 30% (all-in)
  • VEA would be 10% (1/3 out)
  • VWO would be 0% (all-out)
  • VNQ would be 15% (all-in)
  • VGIT would be 10% (1/3 out)
  • VTIP would be 15% (all-in)
  • CASH would be 20% (residual not in strategic assets).

Critical Note:

This simple relative momentum investing does not include consideration of the fundamental condition, fundamental prospects for or valuation of the assets used and being rotated. That is a key weakness and risk factor associated with this approach unless the assets are pre-selected based on fundamentals and/or valuation.  Presumably, the strategic assets and their allocation weights would have been chosen for a good long-term fundamental, non-technical reasons.  This method is meant merely to modulate exposure to each strategic asset based on performance relative to a risk-free asset (T-Bills).

Building More Complexity:

The approach can become progressively more complex and granular. For example, a portfolio may have a tactical sleeve that involves less diversified assets, that may be higher opportunity/risk or that are expected to exhibit particularly favorable momentum over shorter periods of time.

Such a sleeve might be for the top momentum sector funds, or top country funds, or top ETFs of any type, or top momentum individual stocks, or the top security from a custom list.

In the example below, we created a tactical sleeve that would invest in the top 2 momentum sectors among the 10 Vanguard US large-cap/mid-cap sector funds, and also invest in the top momentum stock among the 5 FAANG stocks [Facebook (FB), Amazon (AMZN), Apple (AAPL), Netflix (NLFX), Google (GOOG)].

In addition, just to make it yet more complex, the default strategic assets are considered for substitution with a related alternative.  In this case we use these alternatives:

  • default S&P 500 (SPY), alternatives S&P 500 pure growth (RPG) and S&P 500 pure value RPV)
  • default total US stocks (VTI), alternatives S&P 100 (OEF) and Russell 2000 (IWM)
  • default total international stocks (VXUS), alternatives DM markets (VEA) and EM markets (VWO)
  • default US REITs (VNQ), alternative  international real estate (VNQI)
  • default US high dividend (VYM), alternative international high yield (VYMI)
  • default short-term Treasuries (VGSH), alternatives short-term investment-grade corporate bonds (VCSH), ultra-short-term, investment-grade, floating-rate debt (FLOT)
  • default intermediate-term Treasuries (VGIT), alternative intermediate-term corporate investment-grade corporate bonds (VCIT)
  • default long-term Treasuries (VGLT), alternative long-term investment-grade corporate bonds (VCLT)
  • default short-term TIPS (VTIP), alternative long-term TIPS (TIP).

Note: This is not a recommendation for a portfolio, merely an illustration of how complexity can be increased.

It is probably obvious that as the number of portfolio slots increases, and the number of securities considered for each slot increases, the decision process moves from one of paper and pencil to one requiring a database return download source and some coding in an Excel spreadsheet – unless you want to drive yourself a little bit crazy.

 

Life Stage Asset Allocation Reference Timeline

Monday, August 13th, 2018
  • Consensus Life Stage appropriate asset allocation
  • Historical Life Stage asset allocation returns
  • Forecasted Life Stage asset allocation returns

During this long Bull market, some portfolios have been more aggressive than might be expected over the long-term. Now, we are approaching or may be in the 9th inning or the 11th hour, and are exposed to some extraordinary event risks. It may be appropriate to review what the consensus Life Stage allocation is according to major money management institutions.

By Life Stage, we mean, not age, but how many years before you convert from adding assets to your portfolio to withdrawing assets – the Withdrawal Stage of Life.

While people can enter the Withdrawal Stage at any age, the standard reference model is at age 65 with an estimated 30 years to live (for the portfolio to last). Based on that assumption, institutions have designed what they believe are the most sensible and prudent allocations leading up to and following the commencement of the Withdrawal Stage.

This is the model simplified to 4 asset categories that is near the average of the recommendations of 12 leading institutions (excluding the cash level, which tends to be around 2%-4% in later stages):

You may wonder how those allocation levels have performed historically.

This table shows recommended allocations at 5-year intervals before and after entering the Withdrawal Stage, and how they performed over various cumulative periods through July 2018, and over individual calendar years through 2017, plus forecasts by Vanguard and BlackRock.

The data is for indexes, except for international Dollar hedged government bonds which is based on the Vanguard fund with that objective from 2014-2017, and the VALIC foreign government bonds fund (Dollar hedged opportunistically) from 2008-2013.

 

Even though the stock market may continue on longer than expected, we think those near or in the Withdrawal Stage should give careful consideration to these “rule of thumb” allocation levels; judge strategic aggressiveness relative to them; and if more aggressive, shift tactically toward them.

We’d like to be more safe than sorry over the next couple of years. As we have discussed before, we are using ultra-short-term, investment grade, floating rate US bonds in lieu of other bonds during this Fed rate hiking cycle; probably until early 2019 (maybe longer for the international bonds portion).

[directly related securities:  VTI, VXUS, BND, BNDX, FLOT, FLRN]

Big Changes With New Communications Services Sector

Wednesday, August 8th, 2018
  • New Communications Services sector 49% Facebook, Alphabet and Netflix.
  • Consumer Discretionary and Information Technology provide key stocks to new sector.
  • Communications Services has lower PEG ratio than Consumer Discretionary and Information Technology which provided most of it constituents.

Next month the Global Industrial Classification System (GICS) will launch a new sector: Communications Services. That sector will include the stocks formerly of the Telecom Sector (notably Verizon and AT&T), but also numerous stocks pulled out of the Information Technology and Consumer Discretionary sectors.

These changes modify the relative appeal of the Info Tech and Consumer Discretionary sectors.

This table shows how the top stocks in the new sector (represented by XLC, a new ETF with a head start on the new sector) come from sister sectors Info Tech (XLK) and Consumer Discretionary (XLY).
(click images to enlarge)

Those are some big names leaving both XLK and XLY, going into XLC. Lots of movement among the so-called FAANG stocks (Facebook, Amazon, Apple, Netflix and Google [now Alphabet]). Facebook, Alphabet, and Netflix will compose 49% of the new sector. Apple remains in Info Tech (XLK) and Amazon remains in Consumer Discretionary (XLY).

We will have to rely on simulated histories going forward to compare each of these three sectors to their historical attributes. One such study provided by the sponsor of these ETFs shows Info Tech and Consumer Discretionary becoming more expensive relative to their simulated 15-year histories; and Communications Services less expensive than its history than the other two.

The PEG ratios (P/E over 3-5 yr forecasted earnings growth) is most attractive for Communication Services at 1.1, versus 2.0 for new Info Tech and 1.5 for new Consumer Discretionary.

This is the full list of members of the new sector along with their weights.

Very recently Communications Services underperformed the other two simulations, because it holds FaceBook, which took a steep dive in late July from which it has not yet recovered.

A backtested plot by Bloomberg of the returns of the new and two recomposed sectors shows each of the three simulations outperformed the S&P 500 since the market bottom in 2009 through April 30, 2018.

This ETF has one of the fastest adoption rates. Even though the sector is not yet official, XLC has raised $368 million in just 2 months of existence. Expense ratio 13 basis points.