The top 5 problems with tactical asset allocation portfolios

There is a lot of interest in Tactical Asset Allocation (TAA) portfolios these days. The big TAA models are the various versions of the IVY portfolios (GTAA5, GTAA13, GTAA AGG3/6) and the Antonacci GEM/GBM portfolios. See here for a recent comparison. There are many others. The promise of higher than equity-like returns with low risk and drawdowns would be appealing to any investor. But often an investor’s actual real world experience with TAA portfolios can be a lot different than what the historical backtests or what investors’ expectations would suggest. In this post I’m going to list what I think are the biggest problems with TAA portfolios and what, if any, the alternatives or solutions are to those problems. This is going to turn into a series of posts. Here, I’ll mainly present an overview of the problems and possible solutions. In future posts I’ll dive into the nitty gritty of some of these problems, discuss some of the research in these areas, and present data on potential solutions. I’m still in the process of doing some of this research but I wanted to start the discussion before I have everything wrapped up. As usual, I’m sure I’ll get some great suggestions from my readers. Here is my list of the top 5 problems with TAA portfolios.

1. Poor replication of the asset classes. This one is pretty fundamental. And it is also an issue with many buy and hold portfolios as well but more so with TAA. If you look at the 13 asset classes in the GTAA 13 list of assets there are a couple that have no true or good real world implementations. The best examples are US large cap momentum and US small cap momentum. In the past couple of years there are a few ETFs that are attempting to track large cap momentum (MTUM, PDP). But we don’t know how well they will track the large cap momentum index and whether it is worth the extra fees. In small caps we need to use growth ETFs, like VBK, to try and get close to the momentum index but growth and momentum are not quite the same thing. These discrepancies in replication of the asset classes will lead to differences in returns mostly to the downside. This issue is not a huge one in my opinion. Most of the asset classes in the popular TAA models, e.g large cap value, are pretty well represented by the ETFs and the coverage will probably improve over time but it is a discrepancy that will lead to tracking error and needs to be accounted for.
2. Asset class coverage. Any TAA portfolio will leave out some asset classes. There is no point to including them all. But there are some pretty big holes in some of the models. This is even more true with some of the buy and hold portfolios. For example, the traditional 60/40 portfolio and the Permanent Portfolio leave out all international asset classes. That’s a huge problem. But even in the more modern TAA portfolios there are some big holes; international credit bonds, international real estate, international small cap stocks are just a few examples. This omission could lead to opportunity costs in terms of returns or risk adjusted performance. We should at least use a Global Market Portfolio as a benchmark. We can improve this by intelligently adding asset classes to the TAA models.
3. Slippage, fees, taxes. This one is a biggie. Any TAA system will have higher splippage, fees, and taxes than a buy and hold system. All these three will lead to lower than theoretical returns. Taxes are an issue for any portfolio in a taxable account but more of an issue for portfolios with higher turnover as TAA portfolios tend to be. Some of this can be mitigated with tax management strategies but it is an issue that lowers returns. Management fees are a direct subtraction from the published theoretical returns can could possibly destroy any advantage a particular strategy is trying to exploit. My favorite example here is the atrocious fees and implementation of commodity ETFs. Next, trading fees nowadays are not a huge impact to TAA systems with the rise if discount brokers and commission-free ETF lists. Slippage, however, is the big issue in this category. The difference between the theoretical price the model is buying at, usually the previous closing price, is the not the price the investor will buy at. The difference from the previous close plus bid/ask spreads can make a huge difference in returns when combined with the higher turnover of TAA systems. The good thing is that modern portfolio testers let you account for these factors in the TAA system but no matter, there will be significant differences between theoretical performance and real-world returns.
4. Moving average rules are timing the market. This issue is the single biggest discussion point for TAA portfolios. Most TAA portfolios use trend following with a moving average to lower risk and drawdowns. Many investors think this is just trying to time the market and will fail despite what the backtest results say. There is a lot of research that has been done in this area. The basic conclusion is the moving average rules work over the long term but they have significant periods where they don’t work at all and lead to lower returns than not using them. Also, the win rate for many moving average rules is barely above 50%. But the research shows there are some rules that are much more robust than others. Hint: the 200-day SMA is not the best rule. And that in some cases there is not a big impact to leaving out moving average rules all together. I’ll discuss this research in a coming post.
5. Markets have changed, the systems can be gamed. This is an issue with any portfolio or system that is different than the market portfolio made up of purely passive indexes. The argument here goes that TAA portfolios worked in the past but since markets have changed they are not working any more. Or that now that the systems are becoming more popular that they will stop working. There is some truth to these. And this has been happening forever. For example, Price to Book (P/B) used to be the most powerful value metric but has become much less effective over time. But there are some fundamentals that have stood the test of time: diversification, value,  and momentum are the key ones. As long as the TAA systems stay true to fundamentals then they stand a good chance of outperforming in the future. Also, there are ways to get around some of the more tactical issues. For example, a system can be implemented to take action during the middle of a month, rather than end of month to avoid some of market gaming concerns.

All together these problems will lead to lower than theoretical and backtested returns. The question then becomes whether the TAA portfolio in question has enough of a performance advantage to make it a viable investment choice versus the buy and hold methods.

That’s my list of top 5 problems with tactical asset allocation portfolios of any variety. What are your concerns, issues with tactical asset allocation portfolios?