By Michael Stokes | 4 October 2010
Inspired by the excellent work of Mebane Faber I've been tinkering obsessively with my own TAA model and I've come to the conclusion that TAA really is that good (as one component of a broader portfolio— more on this later). This post is a primer for those unfamiliar with tactical asset allocation. In a follow up (see post below) I'll take a more technical look.
What is TAA? From Wikipedia:
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First, the focus is on asset classes (not individual stocks, funds, etc.) Second, though the definition doesn't strictly call for it, TAA tends to trade less frequently and ignores more day-to-day market noise. And third, TAA relies more on diversification to provide for risk management (as opposed to entry/exit points).
When I talk about TAA I'm using Faber's published model as a jumping off point ("standing on the shoulders of giants" and all that jazz), so the focus is on trend-following/momentum. My end goal is a strategy that trades infrequently (once per month or less), selecting from a diversified basket of asset classes those that are exhibiting the strongest trend/momentum, and allocating the portfolio between them in a "smart" way (i.e. in a way that maximizes expected return versus volatility). My basket includes: U.S. Stocks, China Stocks, Japan Stocks, Gold, Oil, Commodities, Real Estate, and U.S. 10-Year Treasuries.
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Active strategies (including our own) are based on market inefficiencies and anomalies that are by their nature fleeting. Folks who trade the way we trade are in a perpetual quest to stay ahead of the curve because the doors of short-term opportunity are forever opening and closing. Contrast that with tried-and-true trend-following, which works as well today as it did 100 years ago. The lowly 50/200-day moving average crossover, that's been around since the dawn of ticker tape, was more effective over the last decade than at any point since at least 1930 (read more).
It's that kind of reliability that makes sleeping at night easier on us active traders. Why not just trade trend-following/momentum? Because the successful among us will, at the end of the day, soundly outperform the best TAA strategy. The point isn't to replace what we do now, but to provide a stable foundation for a portion of our portfolio that's reliably rooted in the long-term.
What's Next?
1. I'll post a follow up this week taking a more technical look at Faber's TAA model versus our own.
2. I've allocated a portion of my own portfolio to trading our TAA model (I eat my own cooking). I'll be sharing our picks monthly and tracking performance here on the blog (a value-added service of being the best readers in the blogosphere).
Happy Trading,
ms
P.S. to learn more about Faber's TAA model pick up his book The Ivy Portfolio.
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TAA Backtest And Expectations
By Michael Stokes | 6 October 2010
Unfamiliar with Tactical Asset Allocation (TAA)? Click for a primer. I want to put this discussion about TAA into perspective. Just how much juice can we really expect from this TAA thingamajig?
Note that when I talk about TAA, I'm using Mebane Faber's model as a jumping off point, so I'm trading a diversified basket of asset classes infrequently (once per month or less) with a focus on trend-following and momentum (read above post). In this post I'll show a backtest of my take on a TAA model, and in a follow up post I'll take a more technical look at what I considered when building the model.
The graph above shows backtested results of the TAA model (red) versus the S&P 500 (grey) since 1971. The model does not employ leverage. See end of post for assumptions about return on cash and trade frictions.
The real benefit of this flavor of TAA is NOT on generating [maximal] returns, [rather,] it's on managing losses. To illustrate, below I've included a chart showing drawdowns for the model (red) vs the S&P 500 (grey) since 1971. I like this very much….
And Lastly, Numbers For The Number-Lovers
Key Points…
1. IGNORE RETURNS. The fact that the model outperformed the market (or any other asset class) is meaningless. Returns are an illusion; they're just a function of risk. Much more important are returns relative to volatility/drawdown and the smoothness of the equity curve over different market regimes. On both, the model shines.
2. These results are made even better by the fact that this model is very much not curve-fitted. My rules are similar to Faber's: select asset classes that are in an uptrend and showing positive momentum. These are tried-and-true rules that have worked since the dawn of ticker tape.
3. There are limitations to this flavor of TAA because of how infrequently it trades and how broad the asset classes are that it's holding. I don't claim that my take on TAA is the best one, but I do think we're pretty close to the ceiling of what one could reasonably expect from this type of approach. Without more active trading there's only so much blood to squeeze from this turnip.
4. There are two other variations on the model I'm also tinkering with: (a) trading with leverage, and (b) holding positions for at least a year to take advantage of reduced long-term CG rates in taxable accounts.
In a follow up post I'll take a more technical look at what I considered when building the model. As always, more to follow.
Happy Trading,
ms
Test assumptions: (a) when an appropriate ETF existed, I ran this test using actual ETF data. For periods prior, I used index or futures data but did not adjust for an ETF expense ratio, which would add some drag to the results presented here, (b) results do not account for transaction costs or slippage, but given how infrequently the model trades, an investor with a reasonably sized portfolio should be able to closely reproduce these results, (c) taxes have been ignored, and (d) I've assumed a return on cash of HALF the nearest 13-week Treasury.
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