Rotational
Rotational combines component rotation and asset class rotation to hold a small basket of ETFs or ETNs, selecting the handful with the most momentum from a representative sampling of classes and components.
Throughout this article, when I refer to momentum, I am referring to an exponentially smoothed measure based solely on price movement.
I may or may not make notes about the macro implications of trends in these categories. If I do, they will appear below each category’s list of members. Noting the existence of a theme behind the trend does not necessarily mean I agree with the theme. It is important to remember that these themes are unimportant to the execution of the plan. The plan is strictly mechanical in nature, and these notes are merely postulations about the possible reasons behind the price movements.
Bonds
Every member of this category that has a valid smoothed momentum measurement has positive momentum. As a group, every member of this category has increased in momentum over the last four weeks. The biggest momentum gainer is also the current momentum leader.
Treasuries 20+ Yrs (TLT), +2.9
Emerging Mkt Debt (ESD), +2.6
Treasuries _7-10 Yrs (IEF), +1.9
Low-Grade Corporate (HYG), +1.5
Mortgage Backed Securities (MBB), +1.3
Treasuries _1-3 Yrs (SHY), +1.1
High-Grade Corporate (LQD), +0.8
International Treasury (BWX), too new for measurement
A continued move into long bonds in the U.S. might imply a “flight to safety” combined with a bet on continued Fed moves to more accommodative interest rates.
Commodities
The rich get richer and the poor get poorer, as every commodity that had positive momentum four weeks ago gained in momentum, and every commodity that had negative momentum continued to lose momentum. Again, the biggest momentum gainer is also the current momentum leader.
Oil (USO), +14.4
Gold (GLD), +8.7
Silver (SLV), +5.8
Agriculturals (DBA), +5.5
Natural Gas (UNG), -1.8
Base Metals (DBB), -1.8
The move in base metals could be a bubble popping or speculation on worldwide economic weakness, while the continued increases in oil and gold are either bets on geopolitical risk or a continued rise in U.S. or global CPI measurements. To some degree, the agriculture prices are rising in response to oil’s rise, based on the growing of grains for biofuel usage.
Countries
Non-Japanese Asian and emerging markets continue to dominate the top of this list. In the last four weeks, South Korea has lost some momentum, while Canada, Russia, and Australia have gained momentum. The high-flyer is still China, and it is the only country in the top five from four weeks ago to have lost momentum.
China (FXI), +22.2
India (INP), +17.8
Brazil (EWZ), +17.4
Hong Kong (EWH), +12.7
Australia (EWA), +9.3
South Africa (EZA), +8.9
Russia (RSX), +8.8
Canada (EWC), +8.6
South Korea (EWY), +8.5
Spain (EWP), +7.4
Singapore (EWS), +6.6
Germany (EWG), +6.3
Malaysia (EWM), +6.1
Taiwan (EWT), +5.2
Netherlands (EWN), +4.1
United Kingdom (EWU), +3.1
France (EWQ), +3.0
Switzerland (EWL), +2.2
Mexico (EWW), +1.6
Italy (EWI), +1.5
Austria (EWO), +1.3
United States (SPY), +1.1
Sweden (EWD), +0.5
Belgium (EWK), -0.2
Japan (EWJ), -1.1
The chatter is that China’s economy is overheating, as measured by CPI and GDP, and their central bank may be taking steps to tighten credit in response, hence the loss of momentum in the stock market. South Korea is tied to export, particularly to the U.S., as is Mexico, and these markets have also lost momentum based on a “U.S. recession bet” being made by many market movers. Note also the low amount of momentum in the U.S. relative to foreign markets.
Currencies
Every tradable currency ETF that I track has gained relative to the U.S. dollar in the past four weeks. While the G10 Currency Harvest, an ETF that approximates a carry trade strategy over the G10 nations, has gained momentum, it hasn’t gained much in the last four weeks cumulatively, as it gave most of those gains back in the last two weeks.
Canadian Dollar (FXC), +6.2
Australian Dollar (FXA), +4.6
Swedish Krona (FXS), +3.5
Euros (FXE), +3.4
Swiss Franc (FXF), +2.7
Japanese Yen (FXY), +2.4
British Pound (FXB), +1.8
G10 Currency Harvest (DBV), +1.4
Mexican Peso (FXM), +0.7
The biggest gainers are the commodity-based currencies. Mexico’s currency is hampered by the ongoing “U.S. recession bet,” as they are a large U.S. trading partner. The carry trade ETF is impacted by the amount of volatility in the currency markets over the last few months, as the leverage needed to make the carry appealing is too painful when volatility is high.
Industries
Materials, energy, and technology continue to dominate the top of the momentum rankings, with a little bit of jostling for position going on. The industries with the most negative momentum continue to be homebuilding, financials, and consumer cyclicals, with a smattering of technology groups thrown in for good measure. While some of my industrial ETFs are international in scope, most are focused on U.S. markets. The U.S. market has lost momentum in the last four weeks, and so have most of the industry ETFs I track.
Materials, Steel (SLX), +13.7
Materials, Gold Miners (GDX), +10.7
Energy, Clean (PBW), +8.9
Telecom, Wireless (WMH), +7.6
Energy, Oil Services (OIH), +6.4
Energy, Oil Equipment and Services (IEZ), +6.2
Materials, Natural Resources (IGE), +6.1
Energy, Exploration and Production (PXE), +5.8
Industrials, Environmental Services (EVX), +5.4
Industrials, Aerospace and Defence (PPA), +5.3
Materials, Metals and Mining (XME), +5.1
Technology, Electronics (PHW), +4.4
Technology, Software (SWH), +4.0
Health Care, Biotech (IBB), +3.4
Health Care, Equipment (IHI), +3.2
Utilities, Water (PHO), +3.1
Technology, Internet (HHH), +3.0
Technology, Networking (IGN), +3.0
Utilities, General (XLU), +3.0
Cons. Staples, Goods (IYK), +1.8
Health Care, Providers (IHF), +1.1
Cons. Staples, Food and Beverages (PBJ), +0.9
Financials, Capital Markets (KCE), +0.7
Health Care, Pharma (PPH), +0.7
Cons. Cyclicals, Building and Construction (PKB), +0.3
Industrials, Agriculture (MOO), too new for measurement
Financials, Brokers (IAI), -1.1
Cons. Cyclicals, Leisure and Entertainment (PEJ), -1.6
Technology, Semiconductors (SMH), -1.8
Financials, Insurance (KIE), -1.9
Cons. Cyclicals, Services (IYC), -1.9
Telecom, General (IYZ), -1.9
Industrials, Transports (IYT), -2.2
Cons. Cyclicals, Retail (RTH), -2.6
Financials, Regional Banks (RKH), -3.5
Financials, Banking (KBE), -5.6
Cons. Cyclicals, Homebuilders (XHB), -16.3
The macro theme moving these markets is the “U.S. recession bet,” especially as most players seem to think it will be driven either by a slowdown in housing or by the “sub-prime financial crisis.”
REITs
Real estate is deserving of a separate asset class, and the way for me to capture that is through ETFs that track Real Estate Investment Trusts. All of these are currently experiencing negative momentum, or are too new to be ranked, therefore, I will not establish any position in them. Note also that some of the newer ones do not have appreciable liquidity, defined in the proper sense of ease in trading i.e. volume.
International (RWX), -1.1
United States (IYR), -3.3
Industrial/Office (FIO), too new for measurement
Mortgage (REM), too new for measurement
Residential (REZ), too new for measurement
Best of the Rest
Five of the six asset types had an eligible candidate, accounting for 50% of prospective portfolio weight. From all categories, the five highest-momentum candidates not already chosen are:
India (INP), +17.8
Brazil (EWZ), +17.4
Hong Kong (EWH), +12.7
Materials, Gold Miners (GDX), +10.7
Australia (EWA), +9.3
Model Allocation
10% in each of the following, listed in alphabetical order.
Australia (EWA)
Brazil (EWZ)
Canadian Dollar (FXC)
China (FXI)
Hong Kong (EWH)
India (INP)
Materials, Gold Miners (GDX)
Materials, Steel (SLX)
Oil (USO)
Treasuries 20+ Yrs (TLT)
Tracking
Consider this site’s initial post on the model to be a “buy” on Monday’s open, at market, for the above allocations.
November 19th, 2007 at 1:25 pm
As I understand this system, am I corect in that it will look at data elements like the 21, 55, 100 and 200 day EMA’s? Indicators like DMI and momentum oscillators such as RSI and MACD are also most likely considered too, right? I’ve been watching one of my stocks, SPH, in the same manner as it also seems to track closely with these indicators.
I can see why ETF’s representing materials, international markets and currencies are identified by this system as they definitey been looking as very attractive in all the commentaries that I have been reading. I like the name of Rotational as the forces of a rotating system are directly proportional to its momentum.
November 19th, 2007 at 6:53 pm
I’m keeping the methodologies relatively simple. This one uses only 3 different length EMAs to determine smoothed momentum, and has some degree of forced asset allocation, provided the class has at least one bullish component or member. The weakness of this system will be when the macro picture is in flux; the strength will be during the majority of the time that the macro picture is trending in one asset class or another.
November 24th, 2007 at 9:16 am
what are the factors that go into your ranking for momentum strength? is it merely based on price increase over a period of time?
November 24th, 2007 at 10:05 am
It’s the difference between two exponential moving averages (one short and one long) of price only, converted to a percentage basis and then smoothed with another EMA. Read more here: PPO Signal line.
My testing didn’t include dividends, but a dividend-adjusted metric would be very close in most cases, and usually dividend yield isn’t enough to make a difference. If I ever have any situations where momentum is roughly equal but dividend yields do make a difference, I’ll point it out. That’s most likely to happen in the currency or bond asset classes.
January 5th, 2008 at 8:48 am
Hi Bill,
I just started watching your rotational suggestions. It’s an interesting technique. I’m curious, are you a hold to the numbers and follow your schedule kind of guy or will you react to extreme market conditions, say like the just posted jobs numbers, and move up a scheduled reassessment? One of the things I have noticed within the short time I’ve been aware of sector rotational systems is that because of the weighting they can go down fast and hard once the sector goes bad and we all know how easy it is to get into a hole but hard to climb out.
Also, do you know any of the history of the rotational concept? Who was the originator and why do you expect it to work better than previous systems?
Thanks and I really appreciate your website, you’ve done a lot of work and thinking.
January 5th, 2008 at 9:50 am
Rotational is a system I’m tracking and trading, not a suggestion or recommendation for anybody.
In terms of tracking the systems and their performance with the hypothetical portfolios, I will be completely mechanical. In my personal trading, I reserve the opportunity to deviate from the system, but I don’t intend to do that often, because I believe the discretion is better put at the design and testing phases of system development, and not at the execution phase. If I do anything in my personal portfolio, I intend to announce it on the site the night before execution, if at all possible. The interesting thing will be seeing if my occasional deviations add, or subtract, value from the system. For example, INP presented two opportunities to me, one to add value (by trimming when it traded at surplus to NAV) and one to subtract value (by panicking and selling under $90). I passed on both and stuck to the system.
There are various ways to reduce volatility in systems like Rotational, especially downside volatility. I considered stop losses, increasing the numerical diversification, a “faster” momentum measure, and forcing an asset class diversification regardless of trend strength. In the end, I decided to go with the latter three. The bounces in oil, gold, the Euro, and the long bond ETFs helped defray last week’s fall quite a bit. Also, the hardest falls could by had by the leading momentum players – but having more entries means that I’m more likely to have something moving up the ladder at the same time something else is moving down. Of course, in the long run these techniques to defray volatility will degrade CAGR, it’s a question of making a tradeoff that I can live with.
As mentioned in comment 2, above, the real danger in this system is a cessation of trending for an extended period. The whipsawing will hurt more than having one trend end while another starts (and gets picked up by the system).
One of the systems I’m tracking is partially based on buying extremes of fear, and another system I’ve tested (but discarded as too short-term and active for my tastes) buys these kinds of dips. As scary as it seems, there’s more money made buying panic than selling into it.
There’s nothing new under the sun, and the ideas are pretty old. Trading relative strength systems go back at least to O’Shaughnessy, and he also researched adding a valuation overlay. There are some other papers suggesting that the spread of relative strength in an asset class has implications for performance of them long or with a short extension. Similarly, there are lots of academic papers on asset class allocation, including domestic and foreign stocks, bonds, and commodities in the mix. Mebane Faber has some work on trend-following models in asset allocation, and I think he researched relative strength but instead went with long/cash in each bucket based on trend and applies leverage to juice return if desired.
I think I’m the only one writing about mixing relative strength and asset allocations with a small component of forced asset allocation, but I could be wrong. The odds are that somebody else is doing it and not writing about it. My momentum measure is also “faster” i.e. shorter than what’s found in the literature, because the limitations of most testing databases are total return series at month-end, and you can get some different results using daily bars to generate momentum measures.
From what I’ve seen, I like the results of the various combinations I’ve seen used by others. I think that the number of positions, some (but not a completely) forced cross-asset allocation, and a slightly quicker momentum measure will produce improved results.
I’m glad you appreciate the website! Good to have you as a member, and great questions!