The experiment in plain English
We took the 36 stocks tracked across this dashboard's portfolios — the quantum names (IONQ, RGTI, QBTS, QUBT, ARQQ, LAES) plus the DC-infrastructure and robotics holdings — pulled 6 months of daily closes (2026-02-09 → 2026-08-07, 124 trading days), and asked: which 3 stocks, held in equal weights, give the best expected return for the least risk?
A QUBO (Quadratic Unconstrained Binary Optimization) encodes a problem as a set of 0/1 yes-no switches with pairwise costs, which is the native input format of a quantum annealer. Here each stock gets one switch ("in the portfolio or not"), returns lower the energy, co-movement between pairs raises it, and a penalty term enforces "exactly 3 picks" — so the lowest-energy state is the best portfolio.
annualized vol 75.8%
annualized vol 35.9%
annualized vol 40.0%
Why this basket is interesting
The annealer didn't just grab the three hottest stocks. MRVL and MU had the highest raw returns (~+0.85–0.97%/day) but are violently volatile and move together with the rest of the AI-semi complex. Instead the optimizer paired one high-return engine (AMD) with two low-volatility stabilizers (DE, PTC) whose day-to-day moves barely correlate with it. PTC even has a slightly negative 6-month mean return — it earns its slot purely by cancelling out risk. That's mean-variance optimization working as intended: covariance matters as much as return.
Verification: because 36-choose-3 is only 7,140 combinations, we also checked every possible basket by brute force. The annealer's answer matched the exact global optimum.
Solver details
- Solver
- dwave-samplers SimulatedAnnealingSampler (Ocean SDK) — quantum-inspired, local
- Hardware run
- pending — D-Wave Leap account signup blocked in this environment; will re-run on LeapHybridCQMSampler
- Problem size
- 36 binary variables · 630 quadratic couplings · cardinality K=3 via penalty
- Objective
- max μTx/K − q·xTΣx/K², q = 5 (risk aversion)
- Anneal
- 4,000 reads × 5,000 sweeps, β 0.1 → 2×10⁶ · 24.9 s wall time
- Feasible reads
- 4,000 / 4,000 satisfied the exactly-3 constraint
- Brute force
- 7,140 combinations in 0.05 s — same answer
- Data
- yfinance daily closes, 2026-02-09 → 2026-08-07 · cost: $0.00
| Ticker | Sector | Mean Daily Ret | Ann. Vol | |
|---|---|---|---|---|
| MRVL | DC Infra | +0.968% | 96.7% | |
| MU | DC Infra | +0.849% | 96.2% | |
| AMD | DC Infra | +0.762% | 75.8% | PICKED |
| COHR | DC Infra | +0.533% | 93.9% | |
| AMAT | Robotics | +0.494% | 70.5% | |
| ARQQ | Quantum | +0.464% | 125.7% | |
| CGNX | Robotics | +0.430% | 69.3% | |
| IONQ | Quantum | +0.364% | 98.2% | |
| LRCX | DC Infra | +0.353% | 73.3% | |
| VRT | DC Infra | +0.352% | 75.3% | |
| GLW | DC Infra | +0.340% | 87.5% | |
| TER | Robotics | +0.315% | 87.2% | |
| ANET | DC Infra | +0.302% | 59.7% | |
| GEV | DC Infra | +0.228% | 53.8% | |
| AVGO | DC Infra | +0.224% | 47.7% | |
| ASML | DC Infra | +0.218% | 52.8% | |
| RGTI | Quantum | +0.213% | 101.9% | |
| QBTS | Quantum | +0.210% | 110.5% | |
| MPWR | DC Infra | +0.200% | 62.0% | |
| ETN | DC Infra | +0.186% | 44.5% | |
| APH | DC Infra | +0.174% | 46.2% | |
| NVDA | DC Infra | +0.163% | 38.6% | |
| QUBT | Quantum | +0.138% | 91.2% | |
| ABBNY | Robotics | +0.135% | 37.1% | |
| ROK | Robotics | +0.089% | 36.5% | |
| DE | Robotics | +0.077% | 35.9% | PICKED |
| TDY | Robotics | +0.055% | 26.3% | |
| EMR | Robotics | +0.023% | 36.1% | |
| FANUY | Robotics | +0.022% | 55.7% | |
| HON | Robotics | +0.009% | 29.9% | |
| SNPS | Robotics | −0.008% | 42.3% | |
| PTC | Robotics | −0.031% | 40.0% | PICKED |
| LMT | Robotics | −0.039% | 30.3% | |
| AVAV | Robotics | −0.177% | 82.6% | |
| ISRG | Robotics | −0.180% | 39.9% | |
| LAES | Quantum | −0.205% | 85.9% |
Why none of the quantum stocks made the cut
Slightly awkward for a quantum-computing demo: the optimizer looked at the quantum-sector tickers and passed. ARQQ has strong 6-month returns (+0.46%/day) but 126% annualized volatility — the risk penalty at q = 5 prices that out. The quantum names also correlate heavily with each other, so they can't hedge one another. Lower the risk aversion and they start appearing; that's the knob to play with in the next run.
Honest caveats (read before taking any of this seriously)
Toy scale. 36 assets choose-3 has 7,140 combinations — a laptop brute-forces it in 50 ms. Annealers only get interesting when the combinatorics explode (hundreds of assets, lot-size and turnover constraints), where exhaustive search dies. This demo proves the pipeline, not a quantum advantage.
Simulated, not quantum (yet). This run used classical simulated annealing from D-Wave's Ocean SDK — the same QUBO would submit unchanged to real Leap hardware once the account exists.
*Expected return is extrapolated history. "+67.8% annual" just annualizes an unusually hot 6-month window for AI-adjacent stocks. Past returns are not a forecast. Equal weights, no transaction costs, no shorting, single period.
Not investment advice. Research demo for the dashboard. Nobody should trade on this.
quantum-lab/results.json.