Archive for September, 2018

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.