QBTS AI stock prediction, Monte Carlo, and QML research
D-Wave Quantum gives public investors exposure to quantum annealing and optimization use cases. The stock is usually treated as a speculative quantum theme trade.
Ticker
QBTS
Market
NYSE
Theme
quantum annealing, optimization, and commercial quantum systems
Today's Public Snapshot
QBTS AI signal and IV regime
Latest backend snapshot: 2026-06-16. Data is rendered only when a public backend snapshot exists.
AI signal
Bearish
Next-session model label
Up probability
34%
55%+ Bullish, 45% or lower Bearish
IV regime
BULLISH_SKEW
Options volatility context
IV view
Call demand elevated
Opportunity score 72.5
How to read the QBTS AI percentage
The percentage is the estimated probability that QBTS closes higher in the next trading session. It is not a long-term price target and it is not a recommendation to buy or sell.
Why IV regime appears before prediction
Options volatility helps separate directional momentum from market-implied risk. Reading IV first makes the AI signal easier to interpret in context.
AI Prediction Snapshot
QBTS stock prediction result
QBTS prediction work should be read as a volatile basket signal, not a standalone answer. The live model can produce an ensemble up-probability, while this public snapshot keeps the SEO page useful and crawlable.
Public result
Speculative quantum volatility watch
Next trading session · 2026-06-12
Ensemble up probability
Live model
Run live AI Prediction
RF up probability
Live model
Shown after live run
LR up probability
Live model
Shown after live run
Daily volatility
Live model
Shown after live run
Sentiment score
Live model
Shown after live run
How to read this signal
- Use Batch Prediction to compare QBTS with IONQ, RGTI, QUBT, and DWAV.
- Check whether the next-session signal is supported by QML equity-curve persistence.
- Use Monte Carlo before sizing because small-cap quantum names can gap quickly.
Historical Accuracy
QBTS historical prediction win rate
Win rate is calculated only from records where the next trading-day close has been verified.
Win rate
18.2%
insufficient_data
Monthly
18.2%
2026-06 2/11
Verified
11
Minimum 10
Correct
2
Next-session direction
High conf.
18.2%
11 verified records
Updated
2026-06-16
candidate model
QBTS historical prediction records
| Date | Signal | Probability | Bucket | Last close | Actual next close | Change | Result |
|---|---|---|---|---|---|---|---|
| 2026-06-16 | Bearish | 34% | high confidence | $24.58 | - | - | Pending |
| 2026-06-15 | Bullish | 64% | high confidence | $25.95 | $23.98 | -7.59% | Miss |
| 2026-06-12 | Bullish | 67% | high confidence | $24.16 | $26.30 | 8.86% | Correct |
| 2026-06-11 | Bullish | 65% | high confidence | $23.41 | $23.35 | -0.26% | Miss |
| 2026-06-10 | Bullish | 64% | high confidence | $24.07 | $23.82 | -1.06% | Miss |
| 2026-06-09 | Bearish | 36% | high confidence | $24.42 | $23.25 | -4.79% | Correct |
| 2026-06-08 | Bullish | 58% | high confidence | $25.83 | $23.52 | -8.94% | Miss |
| 2026-06-05 | Bearish | 39% | high confidence | $23.85 | $25.83 | 8.30% | Miss |
| 2026-06-04 | Bullish | 58% | high confidence | $27.64 | $23.84 | -13.75% | Miss |
| 2026-06-03 | Bearish | 36% | high confidence | $27.55 | $27.64 | 0.33% | Miss |
| 2026-06-02 | Bullish | 59% | high confidence | $29.91 | $27.52 | -7.99% | Miss |
| 2026-06-01 | Bearish | 41% | high confidence | $29.18 | $29.91 | 2.50% | Miss |
Why Track It
D-Wave Quantum research context
Track QBTS when you need a high-volatility comparison point against IONQ, QSI, and broader AI infrastructure trades.
Research Angles
- Liquidity and volatility can dominate short-term price behavior.
- Theme rotation inside quantum stocks can separate QBTS from larger AI names.
- Batch Prediction helps compare QBTS against the rest of a quantum watchlist.
Workflow
How to research QBTS
Start with the module that matches the question, then compare the signal against risk and benchmark context.
Step 1
Start with Batch Prediction for relative ranking inside a quantum basket.
Step 2
Check QML equity curves for persistence versus IONQ and QSI.
Step 3
Use Monte Carlo to stress-test the next 10-day price range.
FAQ
QBTS stock prediction FAQ
What does the QBTS AI percentage mean?
It is the model's estimated next-session up probability. A 60% reading means the model currently estimates a 60% chance of an up close for the next session, not a 60% expected return.
How is QBTS historical win rate calculated?
Win rate only counts verified prediction rows where the next trading-day close is available. Pending rows are excluded until they can be scored.
Why does IV regime matter for QBTS?
IV regime shows options-market pressure, skew, and volatility context. It helps explain whether the market is pricing unusual risk around the ticker.
Is this QBTS page investment advice?
No. This page is research and education only. It should be used with your own risk controls and independent analysis.
Related Research
Compare QBTS with nearby tickers
IONQ
IonQ
Track IONQ when you want to compare momentum, drawdown pressure, and model probability for a high-beta quantum computing name.
QSI
Quantum-Si
Track QSI when you want a smaller-cap innovation signal that is less directly tied to mega-cap technology beta.
QS
QuantumScape
Track QS when you want to measure whether battery-tech momentum is improving or fading against EV and growth-stock benchmarks.