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 optimization engines — Q72 Confidence Alpha, Markowitz, Risk Parity, and Black-Litterman — and validates every allocation out of sample against real historical data. An optional quantum-assisted refinement pass runs on real quantum hardware.

Question 2

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

Accepted Answer

Q72 optimizes on CDaR (Conditional Drawdown at Risk), Confidence, and Correlation instead of the Sharpe ratio. Classical mean-variance optimizers like Bloomberg PORT and BlackRock Aladdin treat all return forecasts with equal confidence, which amplifies estimation noise and produces unstable allocations. Q72 Confidence Alpha assigns a proprietary confidence score to each asset's forecast and re-weights the optimization objective accordingly, producing allocations that are more robust under uncertainty. Q72 also validates every result out of sample rather than reporting in-sample Sharpe ratios.

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 runs four engines simultaneously: Q72 Confidence Alpha (confidence-weighted optimization), Markowitz mean-variance, Risk Parity, and Black-Litterman. An optional fifth engine — a quantum-assisted refinement — uses a two-stage QAOA process on real quantum hardware. All engines receive the same input data and the same Confidence Alpha pre-weighting.

Question 5

Is Q72's quantum optimization validated out of sample?

Accepted Answer

Yes. The four classical engines are validated with a genuine walk-forward backtest: at each historical rebalancing date, the entire selection and weighting logic is re-run blind, using only data available up to that point. The quantum-assisted result is only used when it demonstrably improves on the classical solution without increasing volatility — otherwise the classical allocation stands. Every run shows both results side by side.

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.