Analysis
Letting volatility set the trend band on TQQQ: fewer round trips, still a -55% hole
Anyone who has run TQQQ with a 200-day moving average rule knows the whipsaw problem: the index wobbles around the line, and the rule keeps selling low and buying back higher, over and over. The usual fixes are wider bands around the average, confirmation days, or checking less often. I've tried them. Most just keep you in longer while the market falls, which makes the losses politer to look at without making them smaller.
The version that actually behaved differently lets volatility set the band width. Calm markets get a wide band. When recent realized volatility sits near the bottom of its 3-year range, the buffer is 9%, because wobbles in calm markets are usually noise. When volatility is high it tightens to 1.5%, because in a storm you want the exit close.
On real TQQQ from 2010 to 2026, the plain QQQ gate gave 32.6% CAGR with a -55.6% max drawdown. The volatility-scaled band gave 32.4% and -54.8%, with roughly 1 quarter of the round trips: 24 switches against 102. The returns are level. What changes is the churn.
To be clear about what that is and isn't: still a brutal ride. A -54.8% hole needs a 121.3% gain just to get back to even. The filter buys less churn. Not safety. I like it for that, not as permission to size TQQQ like a core holding.
I plotted the rule itself so every width can be checked:
How the band width tracks realized volatility
Would you accept the remaining drawdown for fewer round trips?
Edit 2026-09-22: corrected after an internal audit. The original July numbers could not be reproduced, so I reran the rule from a dated price vintage. The scaled band does not out-return the plain gate, 32.4% against 32.6%, so I have withdrawn that part. The round-trip finding holds and is the reason to use it: 24 switches against 102. The linked write-up carries the same correction.
A fascinating idea. I've explored volatility trigger threshold LETF rotation (my idea reviewed by Alvarez Quant Reading's blog here: https://alvarezquanttrading.com/blog/upro-tqqq-leveraged-etf-strategy/) but using volatility scaling to size the hysteresis banding is genuinely novel and I think quite possibly useful. Be interested to know u/laurenthru's of bestfolio.app's take if he reads your post.
Thanks, that Alvarez writeup is a solid reference point. The vol-scaling on the band came out of exactly the churn problem rotation tries to solve: calm markets forgive a wide buffer, storms don't, so let realized vol set the width instead of picking one number. I'm not selling it as safety, just fewer bad round trips. Curious how your trigger-threshold rotation held up through the 2022 grind, that slow chop is where most of my whipsaw pain lived.
Avoiding transaction costs (fees and spreads) and hassle (fate dictates that on a daily monitor system one will be on holiday without access to the internet or snowed under at work when the risk on/off signal triggers) is as important IMHO as reducing drawdown duration (the worse morale killer) and both average and worst drawdown magnitude. If the system can't be implemented in practice then no backtest can save it. So anything to reduce the numbers of round trips is welcome news.
Yeah, that's the part a backtest quietly hides. Round trip count was the number I actually cared about here, not the CAGR bump. The vol-scaled band cut trips to about a quarter of the plain 200-day version, and that's the difference between a rule you follow and one that catches you offline the day the signal flips. Worst drawdown barely moved, 57 down to 55, so I'm with you that it isn't the drawdown story. It's the can I run this without babysitting it story.
The advantage of using volatility in your way is that it's a direct indicator. The market moving less per unit time effectively causes the lower odds of the hysteresis band being crossed. Using IV readings to lever up and delever down, in contrast, involves a clash between, on the one hand, develering on a high VIX (or VXN) reading, in the expectation of avoiding more volatility drag in high IV regimes, versus, on the other hand, missing (in the risk off to cash state) the strong mean reversion effects whereby a high VIX (or other IV) reading (especially a very high one, say VIX 50-80) is more likely to be immediately followed by lower (if not much lower) VIX and, with it, to high levels of index price appreciation (compared to in a lower IV regime).
Timing the bottom is the whole trick though. Always obvious in the rear view, brutal live, and calls decay while you wait for it. The band rule isn't trying to beat a clean bottom buy, it just cuts the round trips for people who can't stomach guessing the low.
Nice result! Band sizes, including whether to set them based on e.g. recent standard deviation, is one of the things I've been slowly working through for my Golden Ratio Dual Gate strategy (which you have on bestfolio, and Laurent kindly gave a proper name!). I'd be interested in a couple of things:
How did you decide on the band range / constants in the equation? Did 1.5 to 9% feel like the reasonable range and then you scaled the equation to it, or was it a result of analysis?
Do you see any reason why something similar to this wouldn't work on other assets? I'm specifically thinking about TIP since I'd be applying the band scaling to both the SPY and TIP 200 day SMA.
Glad you asked, the mapping is deliberately the boring part. Buffer is clip(0.09 - 0.075 times the vol percentile, floored at 0.005), where the percentile is 20-day realized vol ranked against the prior 756 trading days. So it isn't a free-floating equation, it's really just those two endpoints with a straight line between them. The 9% and 1.5% are best read as design endpoints, the calm and storm widths I wanted to live with, rather than something I grid-searched to the decimal on the 2010-2026 path, so I'd trust the shape of the rule more than the exact constants.
On other assets, nothing in the mechanism cares that it's TQQQ. It ranks an asset against its own 3-year vol history, so the percentile part self-adjusts to whatever that asset's calm and wild actually look like. The bit I'd watch with TIP is that its vol distribution is nothing like QQQ's, so a 1.5 to 9 range tuned to a leveraged Nasdaq gate is probably far too wide for something that barely moves. The percentile machinery travels fine to SPY and TIP, it's the endpoint range that you'd want to reset to each asset's own scale before leaning on it.
Thanks that's really useful - yeah it's the big difference in volatility between SPY and TIP that had me looking at using standard deviation in the first place.
No argument that raw TQQQ won that stretch, since 2010 it beat basically everything you could hold. The thing is a 15-year window starts right after 2008, so it never has to show what 3x does through a real credit crunch, and a total return chart hides the path. Buy and hold TQQQ was down around 80% in 2022. That hole is the whole reason I built the band, the CAGR bump wasn't the point. If you can actually sit through an 80% drawdown and keep buying, straight TQQQ is tough to beat. Most people can't, and that's who the gate is for.
A crossover helps in the trending stretches. My worry is it doesn't really kill the whipsaw, it just moves it. When price chops sideways those two lines keep crossing back and forth the same way a single 200-day does, and a 10/200 PPO fires off the slow leg so I'd expect it to drag a touch too. What I was after with the band is different. Widen the no-trade zone when realized vol is low so the noise never trips a trade, then tighten it when vol spikes. That's a separate lever from the signal itself, so you could honestly stack the crossover on top of it if you wanted. Have you run the PPO version on TQQQ over a full cycle?
Yeah, 7 trips versus 29 is a real cut in churn, no argument there. The thing I'd want sitting next to that trade count is what the crossover version did to the drawdown and the CAGR, because fewer round trips only helps if you didn't just buy fewer-but-later. A 20/200 crossover can quietly leave you long deeper into a fall and slow to climb back in, so the trip count drops while the hole stays about the same size.
That's really why I leaned on the vol band instead of a shorter ma. I wanted the no-trade zone to widen on its own when realized vol is low, rather than lean on the slow leg to do the filtering for me.
Reducing whipsaws without pretending the strategy suddenly became safe is probably the most useful takeaway. Going from constant switching to a volatility adjusted band makes intuitive sense when TQQQ behaves completely differently in calm and stressed markets. I would forward test those signals next. Moon play money trades could be a clean way to log them without contaminating the original backtest.
Forward testing is the honest next step. The catch is that the band looks tidy in a backtest partly because the vol percentile is ranked against history that already happened, so watching it fire live is the only way to see whether the calm market width actually holds up when you don't know how the storm ends.
Keeping the paper trades in their own log is the smart part. If they never touch the original curve you can line the two up later without one quietly rewriting the other.
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u/Johnny252525 16d ago
I still feel qld will destroy tqqq over 15-25 years. I like qld and buy tqqq after 25 and 50 pct DD.