FAA: A Lookback in Time…

In the spirit of wrapping up the FAA model investigation, I thought I would extend the backtest further back to 1926. Data used are all monthly total return series from proprietary databases and they are the best estimates that I have to work with. Looking back so far offers a LOT of insights. One will be able to stress test how the specific strategy performed in different environments.

I employed 7 different asset classes: commodities, emerging market equities, US equities, US 10 year bonds, US 30 year bonds, short term treasuries and European equities. For benchmarking purposes, I constructed a simply momentum portfolio that holds the top 3 assets, an equal weight portfolio, and a traditional sixty-forty portfolio. Lookbacks for momentum are 4 months, in line with what Keller and Putten used.

FAA-Long-SS FAA-Long-Performance

One very interesting aspect I found from this extended backtest is to see how the strategies performed during the Great Depression. While equal weight and sixty forty suffered large draw downs, FAA and relative momentum did comparatively well.  Below is a deeper analysis into the Great Depression. As you can see, momentum strategies in general provided a great buffer against drawdown.

Depression

 

GD-PERF

The main reason for this is that during the drawdown period, the FAA strategy were all loaded with bonds:

GD-Holdings-FAA

 

 

When I am researching trading systems, I really like to break down its components apart and analyse it as much as possible. It is only by understanding how they fit together will you be able to judge its future viability. When it will work and when it won’t work. And since these days TAA strategies have become so pervasive, it begs to questions whether we are taking appropriate precautions to its future performance.

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4 comments

  1. Very interesting analysis!

    But I am very intrigued about what data sources you used.
    I don’t think there is data on emerging markets or REITs or commodities index dating back to 1926! Even for common indices like Dow Jones there is no daily data, only weekly. FAA volatility was based on daily measurements.

    So, I am very curious how did you manage to test back to 1926 with this data shortage.

  2. Hi Stefan,

    One of the perks of being an undergrad student is that I can get access to free data sources, usually institutional grade. ;)

    The data series are individually extended back; kind of like working backwards given how the current day indices are created. I don’t have access to housing prices though but I am confident that the available series is a good gauge for past performance.

    Thanks for reading,
    Mike

  3. Hi Mike,

    I changed your symbol list to: tickers = spl(‘SPY,EFA,EWJ,EEM,IYR,RWX,IEF,TLT,DBC,GLD,QQQ’).

    For the calculation of FAA I use:
    models$faa<-faa.bt(data,top,lookback, weight.mom=c(1,0.5,0.5),cash = "IEF")

    When I do this, I get this error after calling the line above:
    Error in .xts(e, .index(e1), .indexCLASS = indexClass(e1), .indexFORMAT = indexFormat(e1), :
    index length must match number of observations

    What could be the reason for this error?

    Thomas

  4. This is an extraordinary analysis! Getting data back to 1926 for these asset classes is really amazing. I’ve seen plenty of back tests on momentum strategies but never anything that had access to this type of historical data. Wow!

    Thank you for posting these results.

    -Gerald

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