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BOOK YOUR FREE STRATEGY SESSION NOW >>Combining systematic trading with some asset allocation strategies can undoubtedly help you achieve a higher degree of diversification.
In this video, we show you a rotational asset allocation model based on sector ETFs (that is, ETFs that track sector indexes) and evaluate its performance using as a benchmark the SPY, which is the S&P 500 ETF.
Watch the video to find out if this asset allocation model works!
Hey everyone! One of the coaches of Unger Academy, and I'd like to welcome you to this brand new video.
Today, we're going to be talking about sector ETFs and see if they could work well in an asset allocation model.
First things first, let's explain why we sometimes talk about asset allocation and investment models, even if our main focus is on systematic trading. The reason is pretty simple, and it's that these models can be very useful when you trade with a systematic approach - but actually with any approach - because they let you achieve further diversification. For example, you can combine systematic trading, which is a type of trading that works on a relatively short and medium term, with a different approach that involves investing in ETFs or stocks, so with an approach that is based on a different logic or, in any case, on different markets.
Moreover, in my opinion, asset allocation is not necessarily so distant from systematic trading. Because yes, it's true that in asset allocation, the execution is manual and not automated, so we send the orders manually, but in the end, the approach is quite the same. I use software to run tests and see what would have worked in the past, although I do it differently. Then I start to trade, or in any case, to make investment choices based on the results I get from my tests, which objectively tell me if a particular setup or idea would have worked at least in the past, and so if there's some possibility that it may work in the future as well.
So let's see the list of the ETFs we're going to consider. This is the etf.com website, and as you can see, I highlighted sector ETFs, so ETFs that track sector indexes, which are the ones we're going to be focusing on today.
Each of the ETFs I highlighted start with the letters 'XL' plus another letter and track a specific sector. For example, XLE tracks the energy sector; XLF tracks the financial sector; XLI tracks the industrial sector; XLK tracks the technological sector, and so on. Then I looked for some ETFs I'd be interested in analyzing. At this point, I put the chosen ETFs in the software we use - which we developed internally for this kind of analysis - and now I'm going to show you some tests and evaluate them together with you.
I applied a ranking to identify the best performing ETF within a certain list so that, period by period, the software can automatically choose the ETF that best meets the criteria and include it in the portfolio and then check the results.
So, to recap, in each period (and the period will vary), we are going to choose the best ETF based on a ranking and a composite momentum that, in this case, is built at 1, 3, 6, and 12 periods with different percentages of allocation.
So let's start with a weekly model. I ran the tests changing the portfolio composition every week, and I got this equity line. A glance is enough to tell you that using the EFT that best meets the criteria indicated doesn't look particularly profitable.
And let's take a look at the results. Remember that the test is quite long, as I tested the asset allocation model starting from 2000. So, as you can see, we have a maximum drawdown of 61.7%, which is very high. In 2008, the period of the subprime mortgage crisis, this model would have performed very badly since it would have recovered much later than the underlying benchmark, which is SPY, that is, the S&P500 ETF. Plus, buying and holding the SPY - so the S&P500 - would have produced much better results than this allocation model during the last period.
As for the annual returns, the profits of this model are much lower than those of the SPY.
So let's extend the time horizon a bit and go with one month instead of one week. Uhm, things get a bit more interesting here, but not always. If we take a closer look, we see that even if the strategy outperforms the benchmark in certain periods, the fact that then it realigns itself in this period (here) suggests that this is not a particularly solid strategy. Actually, there are too many periods when the market beats our allocation model.
In terms of returns, we see that the maximum drawdown is still very high: it touches a maximum peak of 41%, while the maximum drawdown of the benchmark is 55%.
As for the annual returns, they are more or less the same, and the difference between applying the strategy or buying and holding the benchmark, so the SPY, is very small. So, even in this case, I wouldn't particularly recommend adopting this allocation model.
Now let's move on to a longer time horizon and let's use two months as an interval for the rotation of the portfolio. In this case, too, we would have earned a little more than the benchmark, and perhaps it would have performed a little better in the last part, but all in all, in terms of drawdown, there's no significant improvement, since it's about 55% in both cases. So even in this case, I don't recommend adopting this asset allocation model.
Again, I don't particularly like the behavior of this allocation model in times of crisis, such as 2008, when it seems that the benchmark recovered much earlier. So, all in all, choosing to invest in the strongest sector ETF doesn't give us any real advantage even in times of crisis.
Let's take a look at the last test I did. I shifted the time horizon to quarterly, so every three months. Now things seem to be working a little better, but I'm not fully convinced by what I see. I mean, the results of the bi-monthly model aren't particularly attractive, while the quarterly model seems to be performing much better in terms of returns.
Interestingly, in this case, the strategy performs much better than the benchmark and suffers much less in times of crisis, as we can see here. However, this doesn't apply to all periods of crisis. I mean, look here, for example. Anyway, as I said, I'm not fully convinced because it does seem strange to me that the results are not very good with two months while with three months there seems to be a significant improvement. Actually, in terms of annual returns, the quarterly strategy clearly outperforms the benchmark, with a CAGR - the compound annual average return - of 17.4% compared to the 11.62% of the SPY. The difference is remarkable, and, in my opinion, it's not entirely justified by what we have seen so far.
So, guys, this video on rotational asset allocation models using sector ETFs is over. We have seen what these models and ETFs are and we have evaluated the results using different time horizons.
I leave it to you to delve a little deeper into this fascinating topic, especially for those like me who trade both systematically and in a more mechanical way with these kinds of approaches.
I'd also like to tell you that below, in the description of this video, you can find a link to a completely free webinar explaining how to build a well-diversified portfolio of automated trading strategies with the method of the 4-time world trading champion Andrea Unger.
And will see you in our next video dedicated to the world of trading and trading systems.
Goodbye to everyone!
We'll help you map out a plan to fix the problems in your trading and get you to the next level. Answer a few questions on our application and then choose a time that works for you.
BOOK YOUR FREE STRATEGY SESSION NOW >>Andrea Unger here and I help retail traders to improve their trading, scientifically. I went from being a cog in the machine in a multinational company to the only 4-Time World Trading Champion in a little more than 10 years.
I've been a professional trader since 2001 and in 2008 I became World Champion using just 4 automated trading systems.
In 2015 I founded Unger Academy, where I teach my method of developing effecting trading strategies: a scientific, replicable and universal method, based on numbers and statistics, not hunches, which led me and my students to become Champions again and again.
Now I'm here to help you learn how to develop your own strategies, autonomously. This channel will help you improve your trading, know the markets better, and apply the scientific method to financial markets.
Becoming a trader is harder than you think, but if you have passion, will, and sufficient capital, you'll learn how to code and develop effective strategies, manage risk, and diversify a portfolio of trading systems to greatly improve your chances of becoming successful.
