Question 1

What is Q72?

Accepted Answer

Q72 is a portfolio optimization platform for independent wealth managers, family offices, and institutional investors. It runs the same asset universe and constraints through four portfolio construction methodologies — Q72 Confidence Alpha, Markowitz, Risk Parity, and Black-Litterman. The twelve classical portfolio outcomes are evaluated with walk-forward out-of-sample validation. An optional quantum-assisted refinement applies only to Q72 Confidence Alpha and is reported separately.

Question 2

How is Q72 different from Sharpe-based tools like Bloomberg PORT or BlackRock Aladdin?

Accepted Answer

Q72 Confidence Alpha combines confidence-weighted forecasts, CDaR risk control, and correlation-aware selection. Markowitz, Risk Parity, and Black-Litterman remain independent reference methodologies under the same mandate and constraints. Q72 evaluates the twelve classical portfolio outcomes with walk-forward out-of-sample validation instead of relying only on in-sample metrics.

Question 3

Who is Q72 for?

Accepted Answer

Q72 is designed for independent wealth managers, family offices, RIAs (Registered Investment Advisers), and institutional investors who need validated, side-by-side comparison of multiple optimization methodologies rather than a single black-box recommendation. It is a B2B SaaS platform — not available to retail or consumer investors.

Question 4

What optimization methods does Q72 use?

Accepted Answer

Q72 compares four portfolio construction methodologies under the same mandate and constraints: Q72 Confidence Alpha, Markowitz mean-variance, Risk Parity, and Black-Litterman. The three reference methodologies retain their own independent logic and do not receive Q72 Confidence Alpha pre-weighting. Quantum is not a fifth methodology; it is an optional two-stage refinement of Q72 Confidence Alpha on real quantum hardware.

Question 5

How is Q72's quantum refinement evaluated?

Accepted Answer

The twelve classical portfolio outcomes are evaluated with genuine walk-forward out-of-sample validation. The optional quantum refinement is assessed separately: a quantum candidate is retained only when it improves the same Q72 objective without increasing volatility, otherwise Q72 Classic remains. Any historical quantum performance figure is labelled as a replay of the final live weights, not as a walk-forward out-of-sample track record.

Question 6

Does Q72 store client data?

Accepted Answer

No. Q72 processes ticker symbols, capital amounts, and allocation weights only. No client names, identities, account numbers, or personal data are ever entered, transmitted, or stored. Optimization results are encrypted in transit and at rest and are scoped exclusively to the user's account.

Research. Methodology.
Use Cases.

Markowitz vs. Risk Parity vs. Black-Litterman vs. Q72 Confidence Alpha: What Changes When the Mandate Stays the Same?

Why Portfolio Construction Still Relies on One Method

The Quantum Advantage in Portfolio Optimization: What It Actually Means

Q72 Confidence Alpha: Why Forecast Quality Changes Everything

Out-of-Sample Validation: The Standard Q72 Refuses to Drop

Handling Large Asset Universes with Spectral Clustering

Black-Litterman Without the Headache

Research. Methodology.Use Cases.