Foreshadowing: Tactical Asset Allocation


I’m going to be starting a new monthly feature here on the blog tracking the real-time performance of a monthly tactical asset allocation model (similar in spirit to Mebane Faber’s excellent work).

I’m not ready to share details just yet (I’m still tinkering), but I wanted to get my “trades” in for the upcoming month before it’s too late. At the close on 09/30, the new October model allocation will be:

Long 45% IEF (U.S. 10-Year Treasuries)

Long 30% VNQ (Real Estate)

Long 25% GLD (Gold)

This is very much a work-in-progress (and I hope I don’t regret jumping the gun like this) but I didn’t want to wait another whole month to get the ball rolling.

I’ll be using the model to trade a bit of my own capital, but unlike our proprietary strategies, it will not be independently-audited. This one is just for giggles.

More to follow.

Happy Trading,

. . . . .

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13 Responses to “Foreshadowing: Tactical Asset Allocation”

  1. 1 Damian

    Ah I was wondering if you were going to get back on this – so this is buy at the close? and the % are of total equity allocated to the system?

    • 2 MarketSci

      Yes and yes, buy at the close on the last day of the month and % are % of total equity allocated to system. Similar to Mebane’s in many ways with some additional bells and whistles.

      [note: this is different that the tactical allocation we’ve talked about in the past that is on my perpetual to do list]


  2. 3 CarlosR


    I’m a fan of Meb’s, and last month I actually started using the system he describes in his paper (for just a portion of my longer-term funds). In retrospect, I don’t think I could have picked a worse month to start, as I’m looking at some sizable whipsaws, and I’ve only just started. :(

    Nonetheless, I think his basic system is a good one, although what he does with his managed accounts is somewhat different from the strategy described in his paper.

    But I’m always looking for a better mousetrap, so I’ll be following your work in this area with interest. It’s definitely an area that can benefit from some more analysis.


  3. 4 Lars Bech

    Hi Michael

    Very interesting indeed for the investors like myself who doesn’t have several hours every day following the market etc.

    May I encourage you to reveal how your Tactical Asset Allocation works in detail ?

    I am a fan of Mebane Fabers work, but having read it I wanted to add something to prevent some of the whipsaws and minimize the drawdown. Then I found the blog of Guy Lerner – – who has introduced a feature that leads to better results.

    Thanks for a great blog.

    • 5 MarketSci

      Hello Lars – I’ll be sharing the spirit of all the rules but not specific parameters values because this is still a work in progress and it’s going to be a while I think before I’m totally happy with it. Be on the look out for a post sometime this month.

      And thanks for the link – will take a look see.


  4. 6 MarketSci

    Just to make it unofficially official, I’ll also be running a leveraged variation of the portfolio (more on this later). The official position for October is:

    Long 70% IEF
    Long 45% VNQ
    Long 40% GLD

    Total Allocation: 155%


    • 7 KamalD

      All three selections are much more sensitive to interest rates then equities (which are currently artificially low due to central bank actions in US, Europe and Japan), just thought I would point that out as a tale risk that may get magnified.

  5. 8 steve

    surprised no EEM in the mix (or other EM ETF)

    • 9 MarketSci

      RE to Steve: I’m still finalizing what asset classes to cover. I know I’m stating the obvious here, but the problem with almost all equity related indices is that regardless of how disimilar they might appear (S&P 500 vs EM for instance) they tend to still be highly correlated.

      At the moment I’m working with S&P 500, gold, 10Y UST, real-estate, China, and commodities. Subject to change as I go deeper down this rabbit hole.


  6. 10 MarketSci

    Diary Note: the model has evolved quite a bit since this post. If I could go back a day in time, the allocation would have looked like…

    Long 50% IEF (95% for leveraged variation)
    Long 20% VNQ (30% for leveraged)
    Long 30% GLD (60% for leveraged)

    This comment is just for posterity’s sake…I won’t be using these revised numbers (because my trades for October are already in).


  7. I’m guessing that yours picks are technical/market-timing based from how your other strategies are run. They happen to confirm my other long-time fundamental biases (increased money supply, supporting long gold, with drastically reduced money velocity causing deflation, supporting long T-bonds). W/o knowing anything about your methodologies, might I recommend taking a look at long TLT (or short TBT to get extra alpha from the decay) to replace long IEF? The 10 yr-30 yr spread is quite steep considering how low the rates are across the curve, so it would appear that the 30 year would have a better risk/reward profile on the long side.

    I also just entered a swing long trade on GKK and RAS based the fact that they have broken out of a long consolidation base on sector strength (ETFs like VNQ and RWO were a factor, in addition to breakouts in breathren such as GBE having already occurred), so it appears I’m agreeing w/ you on that sector, as well, although I believe GKK and RAS in particular pose the best risk/rewards.

  8. You nailed it on this market down day w/ your sector picks!

  9. 13 KamalD

    Hi Micheal
    I am glad you are publicly trying Faber’s system. Just to understand better, Faber has three different theses that he suggests combining and I think you are attempting to that, so I am very curious how it plays out, would you be willing to put out some of the back testing you might have done? With that said:

    1. Faber’s original system is simple SMA using equal weights among major assets classes. He says most variations of SMA (6 mo, 10 mo, 12 mo, 200 d) produce similar favorable improvements, and I agree, I did independent audit of this using total return data for a number of asset classes. This system only works as long or cash. He does not recommend shorting. Do you also plan to avoid shorts on sell signals?

    2. He also discusses the benefit of leverage to magnify the beta of the chosen portfolio. There is no quantitative data offered on how much leverage is ideal, have you played with or pondered about various levels of leverage and did you find any particular gems as to when the leverage stops adding value and creates unacceptable risks of a series of whipsaw losses wiping out the portfolio beyond recovery?

    3. He also discusses as a separate paper the rotation based selection of top 1, 2, or 3 asset classes in a 5 asset class portfolio. Again the analysis provided is simplistic i.e. the classes are always invested equally. No position sizing based on the standard deviation (risk) among the classes, if they were selected on strength he assumes equal allocation to the number of top assets. Also the question of how many periods in the past to use as indicative of strength is left open to interpretation. What are your thoughts (analysis) about the position sizing among the asset classes and how many data points (he uses monthly returns of 3 months, six months etc) to use.

    4. There is some discussion in his work about tax management – we can leave that for another time – but there is room for improvement if one carefully manages the short term trades by shorting similar but not equal tickers until the timing is long term.

    It would be great if you can comment on the above generically or specifically to what your current plan is with the test portfolio.

    Like Carlos R, I recently started using the simple (item 1 above) system of 10 month SMA, on my optimized asset allocation (for the buy and hold), i.e. I am subjecting all assets in the portfolio to the hold or cash rule based on 10 month SMA action. August signal (was interestingly most items on sell) and September all items were on buy) the whipsaw was painful, which is fine, due to all-in, method I chose.

    I know that there are a lot of points here, but as a long term system, they are worth exploring. Best wishes on your new experiment. Also here is a plug for Meb Faber – he is starting an ETF (GTAA) proprietary trading program based on all or many of the above but with more asset classes and more frequent weekly look – see and his writeup about it at we wish him much success at this new program.

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