Why a volatility-regime model lost more often than it won on QBTS and still made money

QBTS was one of the most explosive movers anywhere over the window, and the question worth asking is how a volatility-gated rule copes with that kind of tape. The answer here is unusual: it lost on most trades and still finished well in the black. This is a backtest of one fixed rule set run through QBTS's saved history, not a forecast or a recommendation, and the live sample is far too small to grade.

A volatility gate, not a price level, governs this model. It measures how active QBTS has been, ranks that within the stock's spread of past readings, and lets a trade form only while the rank occupies a favored band, sitting out the calmer and the more frenzied regimes alike. Direction inside the band followed the setup, which here came to fifty-six longs and twenty-one shorts. The striking part is the record: only 38.96% of the 77 trades were winners, and yet a handful of outsized gains were enough to lift the flat-stake total to +532.42%.

How the model is built, end to end.

The reading the model lives by is QBTS's recent volatility, scaled against its own history. On a stock this volatile the favored band is a narrow target, and outside it, whether the tape is unusually calm or off the charts, the model stays flat. When volatility lands in the preferred slice the gate opens and a trade can form. Because the band is fixed to QBTS's own percentile range, a tradable regime is defined entirely by how this particular stock behaves, which on QBTS means the gate is open less often than the raw trade count might suggest.

A favorable regime is a permission slip, not an order. The model still waits on a direction read before committing, then opens with a stop and target set in advance. On a name as jumpy as QBTS that combination produces a lot of quick stop-outs and a handful of large winners. After entry the trade ends in one of a few places, and here the stop dominated: it closed more positions than the target, the settling reading, and the signal exits combined.

The illustration above runs the model across QBTS in a single line: the volatility reading, the percentile band it must occupy, and the long or short it yields. Nothing in the chain is elaborate; on a stock this violent the discipline is in accepting many small losses while waiting for the rare large winner. The model's lineage belongs in the frame as well. It began as one candidate in an automated search and earned deployment only by clearing backtest and walk-forward checks, the road from idea to live rules behind every number here.

At a glance

These figures come from a backtest of the model on QBTS, scored against fixed acceptance gates, not from a live track record.

Walk-forward verification

A trade walked through

The walked example is a long held about a day. With QBTS's volatility inside the favored band and the read pointing up, the model bought near 24 dollars and the target filled near 31 dollars for +30.11%. On a stock that moves this fast it is the model at its best, a regime-permitted entry that reached its target before the move could reverse.

What the full trade record shows

Across its 77 QBTS trades the model won 30 and lost 47. The exits were dominated by the stop: 43 were stopped out, 25 reached the profit target, 8 closed when volatility drifted out of the favored band, and 1 closed on a fresh signal.

A stop-dominated split like this is exactly what a win rate below two in five looks like under the hood: on a stock this explosive most positions are knocked out quickly, and the model leans on a thin set of targets that ran far to carry the whole book.

The single biggest trade was a long the settling reading carried to a +129.63% gain over roughly four weeks from a low base in late 2024, the single trade that did the heaviest lifting. Winners this size are rare, which is why losing most of the time still left the model well ahead.

The worst trade was a short stopped out for -19.49% over about a week in January 2025; that single loss is also the equity curve's deepest drawdown and the reason the drawdown gate is the one that bites.

No single trade carries the record except, on this name, very nearly one does, and with QBTS up close to tenfold over the window the book's lesson is how little of that move the model kept after waiting for its favored regime.

How does this compare to just holding QBTS

Over the same window the model was tested on, simply buying QBTS and holding would have returned vastly more. Putting the two together shows whether the rule earned its keep or merely rode an extraordinary tape. The honest answer is that it rode it, banking a small fraction, and the tiles below put numbers on just how wide that gap ran.

How well does the model reproduce its tape?

Walk-forward verification checks whether the saved rule path reproduces the expected signal behavior on held-out timestamps it was not built on. It is a consistency and replay-integrity test, not proof of live profit. A clean reproduction means the deployed rules behave like the studied ones; it says nothing about whether QBTS's volatility will keep visiting the favored band the way it did across the test window.

In live trading the model has been quiet so far, with too few signals to set beside the backtest. Until more live trades accumulate, the backtest is the only evidence there is, and it should be read as exactly that, a study of how the rules behaved on saved history.

When this approach fails

The model's failures are written into its design here: a win rate below two in five means losing is the normal trade. Most are small stop-outs taken when volatility sat in the favored band but the move went the other way, and on a stock this explosive those wrong-side moves can run hard before the stop trips, which is how the deepest trade lost 19.49% on a short stopped out in January 2025. The model leans on its rare large winners to overcome a steady drip of losers, and any stretch where those winners thin out would hurt.

Three things are worth watching if this ever trades at size. The first is the low win rate, because a book that loses most trades depends entirely on a few outsized winners arriving. The second is drawdown: the worst stretch was about 19.66%, deep enough to break the drawdown gate, and stop-outs can cluster on a stock this wild. The third is the gap between live and backtested behavior, the first hint the volatility band is no longer marking the same regimes it did in the study.

Risk and honest limits

On this run the model's automated checks logged a caution rather than a clean pass. It is one more reason to read everything here as backtest evidence about the rules, not a verdict on the stock.

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