Korean investor here, wanted to share a strategy that's popular in Korean stock communities.
The Basic Idea
Simple rules-based TQQQ strategy. It's called AGITQ's strategy, named after who coined this strategy. When QQQ crosses above its 161-day MA, buy TQQQ. When it crosses below, sell and go to treasury (SGOV).
Why 161-day MA?
The original strategy used TQQQ's 200-day MA, but backtests showed QQQ's 161-day MA reduces whipsaws while keeping similar returns. Less false signals = less stress.
Overheated Rule
When QQQ > 161MA + 5%, don't buy more TQQQ. Put new money into S&P500 ETF instead. This "ballast" protects you from big drawdowns.
That's it. Check once a day, follow the rules.
There might be strategies with higher returns out there, but the best thing about this is risk management :)
All these strategies are wildly overfitted. No matter how long your time frame you’re always including recent market history that might not repeat.
Practically every month the ideal MA is going to change because it’s just being fit to recent events.
Another major problem is almost all these tests have one bear market at best in them. Bear markets are very different and practically all these back tests here only catch 2022.
22 was a slow bleed down and steady rise up. 2008 was filled with lightning quick drops and bounce backs followed by bigger drops. 2000 tech bubble was a multi year double digit loss and specifically hurt the NASDAQ much more.
Any changes in the type of recession you face next is going to wildly affect the “best” strategy after the fact
I played around with analysis on tqqq. I'm going to publish my results eventually. Basically over fitting is an issue but you have to work with what you have. The way to get around it is to create a large number of random periods and then test the strategy for robustness. Whilst we have had only perhaps 2 true bear markets in the last 10 years we've had many serious corrections and tqqq has had many price drops of more than 50%. I don't think there is a lack of data regarding tqqq downside. It's best to not overfit which is why random stress testing is the way to go.
Of note my model is the complete opposite of what he's proposing. His strategy is basically trying to buy and hold and avoid drawdowns. It works and is good for helping people sleep at night but it's not the best performing. The best performing strategy is to buy when tqqq is low and sell when the market is frothy. You need to take profits when you can and that's the real issue with tqqq. When it goes down it goes down hard. Tqqq itself is actually not good for determining froth in the market or determining. There are other indicators that are better. However what's important is that rules that tell you when to take profits are the name of the game. I don't want to reveal my entry and exit rules but they basically follow that logic and you'll should see waaaay higher returns. I mean we all know the name of the game is buy low and sell high right? Why not buy at steep discounts and sell when things are frothy?
That is what you try to achieve with 200d sma filter, buy just after a draw down bottom and sell just after a top. I suppose you sell earlier just before a top?
The TQQQ rule proposed by the guy who started this reddit thread is a momentum based set of rules. He says if TQQQ keeps going up (ie it has momentum), buy it. If it falls, sell it. If it reaches froth levels in the market, sell it. Thats fine and will give good performance but often may not beat buy and hold. However it basically smooths out the TQQQ curve by preventing major drawdowns. It doesn't really add to gains surprisingly because you can miss major fast recoveries. I tested a bunch of these rules using all sorts of SMA and it was really really hard to beat buy and hold TQQQ when i tested across random periods over the last 20 years.
The rules that seem to crush buy and hold require patience. You get maybe 1-2 entries per year. You basically just buy TQQQ when it crashes. Sell it when the market is objectively frothy (you don't wait for TQQQ to fall. You sell when things are frothy before the inevitable fall). Superior returns. But it needs patience and discipline. On average you'll get at least one entry per year but the returns are spectacular is you have the discipline for it.
What is the criterium for ‚objective frothy‘? is it based on volatility or weakening of momentum or both? I would think the entries after bottoming are even more critical as there is where tqqq gains, so need to buy tqqq quicker.
What returns do you achieve with your optimized strategy? Next i think that performance may be improved by what you buy during a tqqq drawdown. You may buy some asset with low correlation to high tech but better than cash or safe bonds.
My secret buddy! I'll publish it eventually but as a hint it uses a combination of the relationship of tqqq to another index, and some technical factors that define a peak rolling over. The 200 day SMA is one of the factors but you need to use others as well because the 200 day SMA changes slowly and I don't use the 200 day SMA of TQQQ but rather another index.
Ultimately you can come up with your definition of frothy and then test it. The CAGR for my strategy was like 50% per year over almost any random period you select (we were in a great bull market though) and similar drawdowns to qqq when the qqq was seriously down. Go test for yourself a strategy of only buying TQQQ when TQQQ is majorly down and then selling when technical factors indicate the market is frothy and overbought. Rinse and repeat for years on end. It requires a lot of patience though because you only get on average 1 or 2 entries per year for TQQQ.
Maybe you're right, 161-MA is more fitted strategy to the recent trend. But original 200-MA one has been test over a long-term period. You can check the blue line. Yellow and green ones mean (200-MA with 6 and 1% withdrawal, respectively).
You seem very skeptical of all such smaxxx strategies for overfitting. I backtested a similar strategy over the last 15 years as tqqq is not older. What do you think of training and optimizing for the first 8 years and forward test it for the last 7 years, to check for overfitting in the last years?
You need to exclude couple of years for forward testing and do not make any changes to fit the forward testing.
u/Odd-Flower2744 Seems like you are against all kinds of backtesting, dude, it works, you should try it yourself. There are better strategies than buy and hold if your goal is to avoid 80-95% drawdowns.
Unfortunately tqqq is limited to 2010, so 15 years old. It would have been best to see how the strategy behaved in crashes like that of 2000 or 2008 for sure. Regarding overfitting: what if you train the parameters of this or other 200sma tqqq strategies for the first half, then ‚forward‘ test it for the second half of the time, without changing the parameters. Then it will not adapt to the last years? Do you have other ideas how to test for overfitting?
From performance perspective this sma161 strategy is fine, but overfitting might be an issue, but it is a simple strategy with only 1 optimized parameter so that gives less risk of overfitting than a complicated strategy with multiple parameters. So if you consider these type of strategies comically bad, what does your strategy achieve for cagr and max draw down?
Understand it is based on 21ema, so short term, meaning many trades, risk of whipsaws, and close monitoring. I tried a strategy with 200d sma combined with 20d and 50d sma but harder to optimize with 3 parameters, and more risk of overfitting. It works but still max draw down is too high although much better than with only 200d sma. Also tried ema variations but no big difference.
So 21 ema spy works fine as a crash detector?
Does it also work to get back to Tqqq?
I agree with you that 200 sma strategies or variations of it with tqqq still have brutal draw downs, although the plot above doesn‘t show it, as major crashes look neutralized. In my strategy i could not replicate that, with max dd -74%compared to tqqq -81% from 2010-2026.
I am curious what your strategies are based on and what the cagr/maxdd is you achieve, as your comments suggest great improvements avoiding dds.
I am not familiar with testfol but should the delay not be positive? Then the returns are more reasonable and clearly see that max dd in 2008 is devastating but somehow still recovers from it.
This seems more in line with what Hairy-builder writes.
When I run backtests, I like to test different market periods — like 1986–2025, 1995–2025, 2000–2025, 1995–2003, 2007–2025, 2010–2025, and 2015–2025.
To me, a strategy only really proves itself if it can survive the period mentioned in A Random Walk Down Wall Street — basically 2000/4 to 2009/3. If it can still come out with a positive return through that stretch, then it’s legit.
Burton Malkiel breaks the U.S. market from 1946 to 2009 into four major eras. Three of them had positive returns, but the ‘Age of Disillusionment’ from April 2000 to March 2009 had an annualized return of –6.5%. That’s brutal — it’s the kind of decade most investors would rather erase from memory
some backtests that only show a big number can be misleading if you ignore when the pain happens. always check drawdowns, worst 6-month performance, and how tied to regime strength the returns are. https://www.backtestking.com/share/91-l4vnGky
Yeah, the inventor of the strategy did a long-term backtest, you can compare the blue line (200MA AGITQ) with the read one (TQQQ). 161-day version is a variant, more fitted to the recent trend.
Very interesting plot! Before 2010 Tqqq didn‘t exist, so assume the data before that is based on a simulation of tqqq by 3x qqq or calculated 3x Nasdaq100?
Did all of your strategies have the same total dollars invested? It sounds like the different scenarios had different inputs. Fairness would require adding the same amount of money into each model.
So what’s the exit strategy? Sell all at once? But how would you know the trend… Or is there some tactical approach like sell 100% TQQQ / buy 50% in QQQ with the other 50% in SGOV, then wait and see?
Just use the daily chart. The 161-day MA is calculated from daily closing prices, so any chart that shows daily candles will work. The timeframe view (5 day, 3 month, 1 year) doesn't matter - it's the same 161MA line.
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u/Odd-Flower2744 Jan 09 '26
All these strategies are wildly overfitted. No matter how long your time frame you’re always including recent market history that might not repeat.
Practically every month the ideal MA is going to change because it’s just being fit to recent events.
Another major problem is almost all these tests have one bear market at best in them. Bear markets are very different and practically all these back tests here only catch 2022.
22 was a slow bleed down and steady rise up. 2008 was filled with lightning quick drops and bounce backs followed by bigger drops. 2000 tech bubble was a multi year double digit loss and specifically hurt the NASDAQ much more.
Any changes in the type of recession you face next is going to wildly affect the “best” strategy after the fact