A closer look at investing.

Methodology / Insight

Why Portfolio Construction Still Relies on One Method

Portfolio teams often refine a single optimization method with constraints until it becomes a trusted internal engine. But constraints can improve an output without proving that the underlying methodology is the strongest choice. A fairer test is to apply the same mandate and limits across several methods—and compare what actually holds up.

Research / Quantum

The Quantum Advantage in Portfolio Optimization: What It Actually Means

The phrase 'quantum advantage' has become a marketing staple. At Q72, we hold it to a stricter standard — and explain what that means for the portfolios you manage.

Deep Dive / Engine

Q72 Confidence Alpha: Why Forecast Quality Changes Everything

Classical mean-variance treats all return forecasts equally. That's the fundamental flaw. Here's how confidence-weighted optimization changes the risk architecture — and why it matters before any quantum circuit runs.

Methodology / Validation

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

In-sample Sharpe ratios look good in every backtest. We explain why Q72 only shows out-of-sample validation, how it is implemented, and what it means for the reliability of the recommendations you act on.

Research / Technical

Handling Large Asset Universes with Spectral Clustering

Quantum optimization has real hardware constraints. How Q72 uses spectral clustering to run quantum-assisted optimization on large portfolios without sacrificing the quality of the result.

Methodology / Models

Black-Litterman Without the Headache

The Black-Litterman model is theoretically elegant and practically cumbersome. How Q72 implements it as a production-ready engine — and why it produces meaningfully different results from standard Markowitz even when you don't specify any views.