Joined Nov 11, 2007
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Thinking About a 4 Factor ETF Rotational System

Thinking about what kind of ETF rotational system I would like to trade prompted me to ruminate a while upon which factors ( constituent or element that brings about certain effects or results) should be included. I want to keep things simple, which for me means not using more than four factors.

For an ETF system, we need to be able to assign some measure to the ETF in order to compare its performance relative to all of the other ETFs in the universe. I will call this factor 1.

Factor 1: This particular factor is often a measure of strength or weakness, perhaps Rate-of-Change, as we explored in the Fidelity Select system. The factor could be a moving average, or combination of moving averages, or the slope of a linear regression line.

For this next system, we will use RSI for factor 1.

Factor 2: Our next factor concerns how long the ETF will be held before it is rotated. Perhaps not rotating until after a specific amount of trading days have passed is an unnecessary waste of a factor. In that case, we could scan the ETF universe nightly to update the ranks for factor 1, and then rotate the next day into the ETFs that have moved into the top ranking.

As I believe that time exits have the tendency to be curve-fit, I want to make sure that we have a factor 2 that is robust, or else we will discard it and simply update the ETF rankings once a day.

Factor 3: The more I learn about trading and the markets, the more I realize the important role of volatility in affecting returns. For this reason, factor 3 will incorporate some measure of volatility. Will we use volatility to penalize the ranking mechanism, as we did in the Fidelity Select System, or will we seek to trade higher volatility ETFs? This will remain to be seen.

Factor 4: When I think about building a system that I could trade confidently for years at a time, factor 4 necessarily becomes some sort of drawdown protection. Factor 4 might only need to be something as simple as a moving average filter. Perhaps the moving average filter is replaced with inverse ETFs, and we instead diversify among a number of ETFs.

Other considerations, which I classify as filters rather than factors, concern how we decide which of the ETFs to exclude from our universe. Perhaps we only want ETFs that are liquid or perhaps we just want to include the S&P500 sectors. I have often wondered if these things that I consider filters are actually factors. This issue would make for an interesting discussion. Anyway, for now, I will not consider how we filter the universe to be a factor.

Next we will look at the basic ETF rotational system. I will outline the initial factors to be tested and will likely discuss my rationale for using them.

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  1. bzb

    Great to see you’re exploring the possibilities of ETF rotational systems. There certainly are multiple approaches and performance metrics to be investigated. While I agree with much of your post I would take exception to the statement:
    “As I believe that time exits have the tendency to be curve-fit, ……”
    After spending hundreds of hours testing the various non-correlated systems in the BZB Dirty Dozen systems for the Qs, all of which used a fixed bar exit, if only as an alternate, I found that 80% of the 16 systems optimized at an 8 bar exit, with the highest correlation on the short side. My current endeavor, Project Z, which approaches the markets from an enirely different direction has produced the same number 8, which leads me to believe that there are, in fact, identifiable cycles (in this case for the Qs) that can provide a tradeable edge. That’s just my observation.

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    • Woodshedder

      BZB, love it. I’m thrilled to hear about your use of time stops. I was hoping that someone would eventually challenge that assertion about time exits (I’ve written it many times) but no one has, until now. I will jog over to your blog and take a look..
      Thanks again!

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  2. Thomas Musselman

    Per Larry Connors, ETFs don’t need to be as oversold as stocks to work; also Country ETFs are best in terms of RSI2 effect.

    When I last looked last June, the 100 largest non-leveraged,non-inverse etfs listed by assets on yahoo were:


    There were 6 primary ETF families : iShares, SPDRS, Rydex, Vanguard, ProShares, and PowerShares.

    iShares – The world’s largest ETF family has 100’s of choices .The most popular:

    the MSCI Emerging Markets, EEM the Russell 2000, IWM

    Dow US Real Estate, IYR , and the Japan Fund, EWJ

    Their latest include the S&P Target Date ETFs TZD, TZE, TZG, TZI, TZL, TZO, TZV ticker symbols. These include target dates 2010 through 2040 and a retirement income fund ticker symbol TGR.

    SPDRs Sector ETFs – S&P Depository Receipts offers 9 distinct ETFs based on 9 sectors of the S&P 500.

    Consumer Discretionary, XLY Consumer Staples, XLP

    Energy Select, XLF Health Care Select, XLV

    Industrial Select, XLI Materials Select, XLB

    Technology Select, XLK, and Utilities Select, XLU

    the ETF SPDR, SPY holds all 500 stocks in the S&P 500. It is the most active ETF.

    Rydex – over 100 ETFs and mutual funds. ; and the first leveraged ETF to retail investors.

    ETFs are broken into sub categories such as

    Equal Weight which includes S&P Financial ETF, RYF Pure Style: example S&P Pure Value, RPV

    Mega Cap : example Russell Top 50, XLG , and Leveraged & Inverse: example 2X S&P 500, RSU

    Currencies: example the Australian Dollar Trust, FXA and Euro Trust, FXE

    Vanguard – a share class of 20 of their domestic and international stock index funds and 4 of their bond funds. Examples include

    European VGK Growth VUG , and Dividend Appreciation, VIG

    Bonds: short medium term total intermed bond market long US Treas Market-weighted bond index


    ProShares – The world’s largest provider of short and leveraged ETFs offers 76 different types

    inverse ETFs :examples Short Dow 30, DOG and Short QQQ, PSQ

    Leveraged ETFs 2x iexample would be the Ultra QQQ, QLD


    QQQQ, DOW, S&P,midcap400,smallcap600, Russell2000, Russell1000Val, Russell1000Gro,RussellMidcapVal,RussellMidcapGro,Russell2000Val,Russell2000Gro


    basic mat,consumer goods, consumer svcs, fin’l, healthcare, industrials, oil/gas, real estate, semicon, tech, telecom, utils

    2x: UCD, UCO, UGL,, AGQ,

    commodity, oil, gold, silver,

    short EFZ SEF, DDG, PSQ, DOG , SH, MYY, SBB , RWM,

    EAFE (europe/asia/far east) , financials, oil& gas, QQQ, DOW, S&P500, Midcap400, Smallcap600, Russell2000


    commodity, oil, gold, silver , EAFE, Japan, China, basic materials, consumer goods, comsumer services, financials, healthcare, industrials,

    2x short EUO, YCS, PST, TBT, DUG, SRS , SSG, REW, TLL, SDP

    euro, yen 7-10 yr Treasuries, 20yr+Treasuries, oil/gas , real estate, semicond, tech, telecom, utils


    Russell1000Val, Russell1000Gro, Rus. MidcapVal, RusMidcapGro, Rus2000Val, Rus2000Gro, QQQ, DOW , S&P 500, Midcap400, Smallcap600, Russell2000

    PowerShares – based on, what Invesco calls an intellidex or intelligent index rather than a static index, as the other ETF families. These intellidexes are dynamic, quantitative, rule based stock groups. Examples
    Active Alpha Multi Cap, PQZ

    Active Mega Cap, PMA

    Active US Real Estate, PSR

    Dynamic Market PWC proprietary cap appreciation rank, each sector

    Dynamic OTC PWO proprietary rank, including each sector, of OTC

    Dynamic MagniQuant PIQ top 10% of largest 2000 US companies by proprietary rank for cap appreciation

    FTSE Rafi US 1500 Small-Mid PRFZ small-midcap by fundamental ratio ranks

    FTSE Rafi US 1000 PRF large US companies by fundamental ranks

    They also offer commodity ETFs such as

    DB Gold Fund, DBL and double gold long DGP and double gold short DZZ and 1x short DGZ which are ETNS (Deutsche Bank index)

    silver DBS

    precious metals DBP

    base metals DBB

    DB Oil Fund, DBO and OLO long and SZO short or 2x DZO long and DTO short ETNS (Deutsche Bank crude oil futures index)

    6 commodities DBC gold, oil, heating oil, aluminum, wheat, corn

    emerging markets ADRE cap weighted depository receipts (drs)

    foreign developed mkt: drs ADRD

    europe: drs ADRU

    agriculture DBA also AGF long and ADZ short, or 2x DAG long and AGA short ETNS (Deutsche Bank index)

    global agriculture PAGG

    commodity DPU long and DDP short, or 2x DYY long and DEE short ETNS (longs are optimized Deutsche Bank commodity index; shorts regular index)

    global coal PKOH

    energy DBE oil, heating oil, gasoline, natural gas

    global steel PSTL

    industrial metals BDG long and BOS short or 2x BDD long and BOM short (Deutsche Bank liquid commodity index: alum, copper,zinc futures)


    US dollar bull UUP

    US dollar bear UDN

    high G-10 interest rate currencies DBV US, Can, NZ, Aus dollars; euro, UK pound, Jap yen, norwegian and swedish krona: a bet on the high interest rate countries among them

    and specialized ETFs like

    S&P Buy/Write, PBP index on calls of S&P

    Value Line Industry Rotation, PYH VL industry and company rank

    Value Line Select PIV VL timeliness, safety, and tech ranks

    Nasdaq smallest cap 10% PQSC


    companies expected to join NASDAQ 100 PNXQ


    e.g. PTE is telecomm, PBS media, PIC insurance, PMR retail, PJP pharma, PTJ healthcare

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  3. Thomas Musselman

    those liquid etfs were:


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    • Woodshedder

      Thomas, thanks! I built a portfolio of ETFs, but I built it about a year ago, and it probably needs updating. As the testing begins, I will detail the ETFs in the portfolio that I will be using to test.

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  4. Plasmahidef

    Hi Wood,

    How about filtering out ETFs that have less than 5 years of history – thereby leaving ETFs with enough historical data points for various factors to be not skewed by 2008 drop and 2009 rebound.


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  5. Caligula

    Any thoughts on taking the PPT monthly hybrid change industry data and creating a rotation system with it?

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    • Woodshedder

      Cali, I’ve thought about it lots. Problem is, it would be very difficult for me to test without learning Jeremy’s database and programming, and that would take a tremendous amount of time.

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  6. Thomas Musselman

    Today’s WSJ has an article by Eleanor Laise (p. R1) warning that a massive # of ETFs have massive spreads; please consider when coming up with a system. The 10 largest dollar volume ETFs make up 60% of all volume. More than 300 of 800 trading on NYSE Arca in December had spreads > $.05/share; 6 of them >$.50. Also the article warns of large divergences compared to underlying assets held, especially in bond ETFs.

    Article suggests looking up iNAV calculated every 15 seconds on yahoo or google (warning that won’t work for international ETFs whose underlying markets are closed).

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    • Woodshedder

      Thomas, thanks for that information.

      I’ve been working with your “liquid” ETF list and have been adding and subtracting some.

      I’m beginning to think that the best way to handle it is to have as few ETFs as possible, keeping only the most liquid, and trying to get all sectors represented, as well as some inverse ETFs.

      I’m pretty much sure I’m not going to use any of the bond/credit ETFs.

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  7. geckoman

    Woodrow, it’s been a while since I last caught up with you. I am trying to work on a new rotational system and recalled some of your work on the Fidelity Rotational system. Have you done anymore work on the 4 factor rotational system? Interested in starting this project back up?

    I have some ideas for penalizing for volatility and ranking using RSI. I need to build a system that ranks about 20 ETF’s and buys the top 4 ranked ETF’s. I want to do this for diversification. Not sure if I am watering down by doing so. I would need to hold for 30 days. Anyway, in working on this project I instantly thought of the work you have done in the past.

    Shoot me an email geckoman72 at gmail .com

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