Among all the ETFs in circulation, Spy and QQQ are certainly among the most followed by investors and traders. Both replicate very important American share indexes and are used both for passive investment strategies and as a basis for building trading systems.
To see them seem almost interscambious, but in reality they hide interesting differences that is worth analyzing. In this article we go to see what really distinguishes them, how they behave in Mean Reverting and Trend Following approaches, and which of the two can be more suitable for trading.
Do you want help to improve your trading approach? Click here >>>
What are ETF spy and qqq
Spy and QQQ are two ETFs which, as anticipated previously, reply American share indices, but with very different structures.
Spy follows the S&P 500, which includes the 500 companies with the most capitalization of the United States. It is a large and very diversified index, which practically represents the entire American stock market. Inside we find a good distribution between various sectors: technology, health, finance, energy, consumer goods, and so on. Despite this, today the S&P 500 is also strongly influenced by the big tech, which alone represent an important slice of it.
QQQ, on the other hand, replies the Nasdaq 100, an index consisting of the 100 major non -financial companies listed on the Nasdaq market. Here the concentration is decidedly more evident as technology dominates and the first 10 titles represent a large part of the index. We are talking about names such as Apple, Microsoft, Nvidia, Amazon, Meta … Companies that have pulled the entire market in recent years.
In essence, Spy is more balanced, while QQQ is much more exposed to the technological sector and the dynamics related to the “growth”, that is, to those companies that focus everything on future growth.
Despite these differences, as shown in Figure 1, the two Etfs move very similarly. This happens because many of the companies present in QQQ are also among the main of the’s & P 500, and this leads to a very high correlation between the two tools, especially in the short and medium term movements.
Figure 1. High correlation between spy (in red) and qqq (in blue).
Spy vs qqq with trading mean reverting strategies
To compare the behavior of Spy and QQQ in a Mean Reverting context, we applied a very simple strategy on both tools, with the aim of highlighting the “character” of each.
With Mean Reverting we mean an approach that aims to exploit the rebounds after excessive movements: it starts from the assumption that, after a sudden drop, the price has a tendency to return towards more “normal” values.
The analysis was done on daily data from 2010 to today, and the basic idea is to take advantage of the rebounds after small bearish excesses, remaining in line with the long -term trend, which on both ETFs is clearly bullish.
It is therefore only a long long strategy, built not to be operational in itself, but to evaluate which of the two tools is better for this type of logic.
Specifically, every time the price breaks the minimum of the previous session, a long position is opened for a fixed value of $ 10,000. The location is then closed to the breakdown of the maximum day before.
The logic is simple: you enter after a downward acceleration and you just go out the price shows a recovery signal, as shown in Figure 2.
Figure 2. Example of trade carried out by a Mean Reverting type strategy.
Results of the approach Mean Reverting on Spy
As the 3 and 4 figures show, the MEAN REVERTING approach applied on Spy did not produce particularly exciting results. Despite a percentage of winning operations greater than 69%, the Averrage Trade stops just over 6 dollars, an absolutely insufficient value to cover even the operating costs of a real strategy. The Equity Line in Figure 3 shows a growing trend in the long run, but marked by deep and frequent drawdown.
Figure 3
Figure 4
Results of the approach Mean Reverting on QQQ
Turning to QQQ, analyzing the figures 5 and 6, the picture does not change much. The Equity Line shows a similar trend, with a slight positive inclination but with fluctuating performances. Here too the Averal Trade is too low, equal to only 5.87 dollars.
In summary, the results do not prove to be promising continuously.
Figure 5
Figure 6
Spy vs qqq with trading trend following strategies
After having tested a Mean Reverting type idea, we now try to apply a trend following approach on both tools.
By trend follow you mean a logic in which you try to follow the direction of the price: if the market rises, you buy; If it goes down, you go out or sell. The goal is not to anticipate an inversion, but enter the trend already underway, in the hope that it will continue.
Also in this case we have chosen a very simple logic, mostly useful to analyze the nature of the instrument. The analysis was always conducted on daily data from 2010 to today, using a Long strategy only, in line with the positive basic trend of Spy and QQQ.
The rule is this: Long enters the rupture of the maximum of the previous session, focusing on a continuation of the ongoing movement. The location is closed to break the minimum of the day before. Some examples are shown in figure 7.
The goal, once again, is not to build a strategy ready for use, but to understand if Spy or QQQ behave better when the price takes direction.
Figure 7. Example of trade made by a strategy with a trend following approach.
Results of the Trend Following approach on Spy
Turning to the results, we immediately notice an important difference compared to the Mean Reverting strategy. As seen in Figure 8, the trend following approach applied to SPY returns a decidedly more orderly and growing Equity Line over time, with a much more “clean” structure than that seen in the previous test. The logic therefore seems to work better, even if the Averrage Trade remains low, around 12 dollars, as shown in Figure 9. It is a slightly better value than the previous test, but still too low to be considered translated in reality, once costs and slippers are included.
Figure 8. Equity Line of the Trend Following approach on Spy.
Figure 9
Results of the Trend Following approach to QQQ
The real jump can be seen on QQQ, as shown in Figure 10. Here the curve is even more regular, and above all the Averal Trade almost doubles compared to Spy, reaching $ 22.40 (Figure 11).
It is an important difference, which shows how QQQ manages to exploit the directional movements much better, probably thanks to its greater volatility and the most “explosive” nature of the technological basket.
Figure 10. Equity Line of the Trend Following approach to QQQ.
Figure 11
Spy or qqq: which one to choose to trade? Considerations and operational advice
Spy and QQQ move in a very similar way, and the results of the tests we have seen also confirm it. The correlation between the two tools is high, both in prices and in behaviors, especially when simple logics such as those tested are applied.
Mean reverting in recent periods seems to make more and more effort. Also in this case, both equity line show weakness and a Averrage Trade too low in order to be considered tradable. The trend following, on the other hand, gives better results, in particular on QQQ, which thanks to its greater volatility manages to better exploit the accelerations of the market.
An interesting idea, given the high correlation between Spy and QQQ, could be to develop a strategy on one of the two tools and validate it on the other. If the logic is really robust, it should adapt to both without too many adjustments. It is an excellent test to understand if the strategy is really working or it is only the result of an excess of optimization.
Finally, to deal with the problem of the verge trade bass, an option to consider is the use of future (such as the ES for the S&P 500 or the NQ for the Nasdaq). These tools allow you to work with a greater value, also making strategies with modest amendments more sustainable from an operational point of view and consequently more suitable for trading, unlike the ETFs that are better lent to the “Buy and Hold”.
Do you want help to improve your trading approach? Click here >>>
Until next time,
Andrea Unger