The same tools professional equity desks rely on — made accessible for individual investors and advisors.
| Research Platforms Morningstar · Koyfin |
Returns-Based Analytics Portfolio Visualizer |
DIY Quant QuantConnect · Alpaca |
Institutional MSCI · Axioma · Venn |
QuantStark | |
|---|---|---|---|---|---|
| Factor Exposure Analysis | Sector/style only | Returns-based 4–6 academic factors | Build it yourself | ✓ Full | ✓ 130+ factors |
| Risk Decomposition | ✗ | ✗ | Build it yourself | ✓ Full | ✓ Built-in |
| Return Attribution | ✗ | Basic (fund-level) | Build it yourself | ✓ Full | ✓ Holdings-based |
| Portfolio Optimization | ✗ | ✓ MVO | ✓ | ✓ | ✓ Risk-aware |
| Backtesting | ✗ | ✓ | ✓ | ✓ | ✓ PIT-correct |
| Scenario / What-If | ✗ | Limited | Build it yourself | ✓ | ✓ Risk-model |
| Time to Value | Instant | Instant | Months of work | $100k+/yr | Accessible |
Here's a 25-stock portfolio analyzed by a typical tool vs. QuantStark.
Point-in-time history. Survivorship-bias-free. Monte Carlo simulations, retirement withdrawal modeling, tactical allocation backtests.
Plain-English explanations powered by the full factor model. Not a chatbot guess — structured attribution translated into language anyone can act on.
Mean-variance, minimum variance, risk parity, Black-Litterman. Constrained rebalancing that respects your convictions while reducing concentration.
Every analysis generates a client-ready explanation — the same conversation institutional PMs have with their risk committees, now available for your quarterly reviews.
"Here's why your portfolio underperformed this quarter — your value tilt cost you 3.2%, but your quality tilt saved you 1.8%. Here's what we recommend adjusting."
Upload or connect your portfolio from any brokerage. CSV, Excel, or API — that's all we need.
Every holding is mapped against a structural factor model and a full covariance matrix.
Interactive dashboards and plain-English AI explanations surface what matters — no quant background required.
Run optimizations, test scenarios, generate client reports. Execute yourself or share with your advisor.
~25 years
of US equity history powering the analysis
14,000+
securities covered (active + delisted)
130+
factors analyzed across your portfolio
What institutions build with million-dollar teams and vendor licenses — we've built lean, transparent, and accessible.
Managing 10–50+ individual stocks. The real questions aren't which stocks to buy — they're how much of each to hold, whether you're actually diversified, and why your portfolio dropped more than the market.
Serving clients who expect more than a pie chart. Factor exposures, risk attribution, optimized allocations — with branded reports that turn quarterly reviews into the conversations that build trust.
Running a $5M–$500M fund. Your investors ask about factor exposures. Axioma starts at $100k+/yr. QuantStark gives you the same methodology without the enterprise price tag.
You know what a Barra model does. You've outgrown 5-factor regression. You could build this yourself — but you'd rather start from a working platform than spend months on data pipelines.
Our factor library, risk model, optimizer, and attribution engine share a single coherent data layer. Every module agrees with every other module. AI can build individual pieces — consistency across a live, daily-updating system is the product.
Every calculation uses data exactly as it was available at that moment — no look-ahead bias, no survivorship bias, 14,000+ securities including delisted companies. This is what separates honest backtests from flattering ones.
Our data pipeline runs daily. Factors update. The risk model recalibrates. Your portfolio is monitored continuously — not analyzed once and forgotten.
Every factor and every model has been stress-tested by practitioners with deep experience in systematic equity research. Domain expertise catches what automation misses — the edge cases, the data anomalies, the silent errors that compound over time.