Every layer of your portfolio, measured.
Three questions about your investments that are surprisingly hard to answer: are they working, what do I actually own, and what should I change. Connect your accounts, view them as one portfolio, and QuantStark rebuilds your history from your actual trades, looks inside your funds, and answers the three in that order.
No sign-up for the demo. Built for US stocks and US equity funds.
Advisors and managers: Request Pro access →
Illustrative figures, not real portfolio data.
The five chapters
One pass through your portfolio, question by question
Past, present, next. Each chapter answers one question and shows its evidence.
Figures on this page are illustrative.
It reads your portfolio, then tells you what matters
The moment your holdings load, QuantStark ranks what deserves attention: the position that carried you, what lagged, concentration that is easy to miss, and tilts you may not have intended.
- Every finding explained from your own numbers.
- Good news is reported too. A healthy portfolio earns a green card rather than silence.
Are your investments working, and is the risk worth it?
A true return rebuilt from your actual trades, benchmarked against a simple index fund over the identical window, then taken apart so you can see where it came from.
- Money you deposited was never profit. Time-weighted and money-weighted, over any window you choose.
- Per-position profit in dollars, from your actual fills, including what you have already sold.
- Factor-based return attribution. Your gain split into the market, the systematic factor tilts your holdings carry, and the stock picking that was genuinely yours. If the outperformance was one growth tilt in disguise, it says so.Pro
What do you actually own, once the funds are opened?
We read the funds' own holdings filings across every account at once, so your real top names are what you own rather than what the labels say.
- 25 names on the statement can hide one company held six ways.
- Your whole book described as one company: how expensive it is, how profitable, how much debt it carries, each against the index.
- Systematic factor exposures, measured rather than inferred. Your book's tilt to value, size, momentum, volatility, leverage and growth, each sized against the index. A software company and a biotech can sit in different sectors and still carry the same systematic exposure, which is what makes them fall together.
Eight names that look spread out share one momentum and growth tilt.
What happens in a bad market?
A volatility number is hard to feel, so we replay real past markets on exactly what you hold today.
- Crashes and turns replayed on your book, including early 2020 when markets fell about a third in a month.
- Predicted volatility, beta and tracking error. A model estimate, called an estimate wherever it appears.
- Factor risk versus specific risk. How much of your risk comes from the broad market and shared factor exposure, and how much is specific to the companies you chose.
| Scenario | You | Index |
|---|---|---|
| Covid crash | −33.0% | −32.7% |
| 2008 crisis | −38.4% | −44.5% |
| 2022 rate rises | −17.7% | −26.1% |
| Q4 2018 selloff | −18.8% | −21.5% |
Most of the risk comes from shared factor exposure, not the individual companies.
So what do I change, and does it help?
The fix arrives already drafted: which names to trim, sized by how much risk each one is adding rather than selling the largest first, and three ways to redeploy.
- Test it before the money moves. Add, trim or drop and watch concentration and risk respond live.
- Or solve it: least risk, least tracking error, or the smallest change that fixes the one problem.Pro
- Where should the next $1,000 go? Top up what you hold, or fill a gap with a new name, screened by trait, sector and size.
- Keep the draft and track it beside the real one, so a year later you know whether you were right.
- Research beyond your own book. Screen the full universe by factor, sector and size, or compare two ETFs side by side on holdings, exposures and overlap. Both work with no portfolio loaded.
Under the hood
Computed from company filings, not just inferred from price history
Most portfolio tools infer a style label from how a ticker's price has moved, which stops working exactly when prices stop behaving. We build each exposure from what the company reported and from how its stock has traded.
18 factors (6 style, 11 industry, 1 market)·re-estimated every trading day·point-in-time data, no survivorship bias, no look-ahead
The AI explains the numbers. The engine computes them.
The AI is never allowed to do the arithmetic itself. Positions we cannot reconcile against your account are labelled approximate, everything downstream inherits the hedge, and each chapter shows how much of your portfolio the model covered.
How the model works →Stays current
Connect once. It keeps watching.
Link one account or several and your positions and trades refresh every night. When a new structural problem appears (a sector crossing the concentration line, one trait taking over your risk, cash sitting idle long enough to cost you something), you get one email. Quiet when nothing changes.
…and 20+ more, connected securely via SnapTrade.
No broker link? Upload a holdings file (CSV or Excel) or enter your positions by hand.
All trademarks are the property of their respective owners; their use does not imply affiliation or endorsement.
Security
See what's driving your portfolio.
One connection. Every answer, from what you own to what to change.
Try the DashboardThe dashboard is free. The Professional version adds the full risk model, return attribution, report export and the research tools, by invitation. Request access →