By Andreas Clenow
Dynamic Asset Allocation Part One
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Why Allocation Models are Better than you Think
Simple tactical asset allocation models outperform not only the stock markets, but the vast majority of investors. That’s a bold statement to make, but I’ll go step further. Even though the regular TAA approach performs really well, we can significantly improve it with fairly simple methods. And I’ll prove it.Â
In this series of five articles, I will explain all the details. First, I’ll show the regular TAA approach, explain how it works, and how it outperforms the markets. I’ll then go into the potential problems with these classic tactical models, before showing how to improve them. You will get all the details of how I apply momentum overlay to greatly improve performance, and I will give you suggestions for research areas to push the concept to even greater length.Â
So, let’s kick it off with the basics. Here’s the basic idea. Most people pick stocks or time the market, and mostly end up spending a lot of time and effort only to underperform the market. What if you could achieve a better performance without all of that time and effort, with a very simple portfolio diversification?
Let’s take the most famous example and give it a closer look. The aptly named All Weather Portfolio was proposed by Ray Dalio as a sort of fire-and-forget solution to long term asset management. You would buy six different assets and fixed weights and reset these weights just once a month. The reason for the reset, or rebalance, is that the difference in performance would soon move the actual weights too far from the target weights. That’s why we need to reset them.
Dalio’s portfolio was based on stocks, medium term treasuries, long term bonds, gold and commodities. His All Weather Portfolio holds 30% stocks, 15% medium term treasuries, 40% long term bonds, 7.5% gold and 7.5% commodities. This portfolio clearly has much more fixed income than stocks, and the reason for that is simply that stocks are much more volatile.
I know that this sounds like a very boring way to manage your money. But boring can be very efficient. Let’s have a look at the performance of this simple model over time. It’s easy to model and backtest this allocation, and we can use ETFs for each of the five positions.Â
If you looked at these backtest details compared to the S&P 500 and concluded that the All Weather Portfolio failed to beat the market, take another look. Sure, the index returned 8.4% over this period while the allocation model only did six percent and change. But return without risk context is simply irrelevant. If all you want is to aim for the highest possible return, you also need to accept the highest possible risk. The logical conclusion of that is to spend all your money on lottery tickets. You’re very likely to lose all your money, but at least you have a tiny chance of winning big.
In finance we always aim for the best possible risk adjusted return. And from that perspective, the All Weather Portfolio knocks it out of the park. We have a much lower volatility, a significantly higher Sharpe ratio and less than half of the drawdown.Â
Comparing the index to the AWP model is no contest. The allocation model wins easily. But that doesn’t mean that it doesn’t have issues, or that it can’t be improved.Â
In the next article, I will bring up these issues, explain what problems we can see with the classic AWP model and how we could approach addressing them. After that, I will teach you a very practical approach to improving not only the All Weather Portfolio, but also most other allocation or trading approaches.
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Originally posted 16th September 2024
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