Professional
The full read on a US equity book.
A book for every client, the factor risk model, return attribution, report export and the research tools, for people who run other people's equity money and have to explain it. By invitation.
Factor analytics for US equity books. Say what you run and we will tell you honestly whether it fits.
01 What you get
Six things, each one live in the product today.
Computed from your own trades and the nightly data, not a roadmap item.
Books
One book per client or account holder, each holding as many portfolios as they have: brokerage syncs, uploaded files, typed holdings. Open a book and its accounts read as one; the roster above them shows every book's value, 1Y and year-to-date return against the S&P 500, and the model's predicted volatility, refreshed each night. The morning screen for a desk that runs more than one person's money.
Risk chapter
The fundamental factor model behind every number: six style factors, eleven industries and the market, estimated daily across the US universe. Predicted volatility and tracking error, the factor versus stock-specific split, which names drive the risk, and what a 2022-style rate hike, an oil spike or a growth/value flip would do to the book, next to the Covid and GFC drawdowns.
Value · Size · Momentum · Volatility · Leverage · Growth
Return attribution
Where the return actually came from over any window: the factor tilts, the industry bets, and the part that was stock selection. Against the benchmark, per period, from the trades you really made.
Report export
Every chapter of a book as one HTML or PDF document, built on demand from the same computed figures the dashboard shows, with the as-of date on it. For an IC pack, a client review, or a compliance file.
Compare and Optimizer
Compare lines up to five portfolios side by side on the same window and benchmark. The Optimizer proposes a tighter book against the risk model: minimum variance or minimum tracking error, with weight, sector, turnover and name-count limits you set, and shows the risk before and after.
Research tools
The Factor Monitor: daily factor returns, regression fit and exposures across the whole universe. The Backtest Engine: describe a strategy in plain language, single factor or a composite of up to five factor legs with their own direction and weight, and get coverage, information coefficient, quantile spreads and turnover on the same universe the risk model is estimated on. Plus full sigma and z-score displays across every per-name table.
02 Who it is for
Anyone holding a concentrated US-listed equity book.
The buyer is a portfolio shape, not a job title. The model covers US-listed stocks and the funds that hold them; where it cannot see, the app says so instead of guessing.
A good fit
- US equity SMA and model-portfolio managers
- Advisors running US-equity mandates for clients
- Long-only equity boutiques and an emerging manager's first fund
- A family office's public-equity sleeve
Not yet
- Bond, credit and multi-asset books: fixed income is not modelled
- Books that are mostly international or emerging-market funds: look-through coverage there is thin, and the coverage badge will say so
- Options-heavy or short books: options are carried at value, not modelled for risk
03 Request access
Tell us what you run.
A person reads every request and replies by email. You will hear back either way; a yes comes with the invite link in it.
- What does it cost?
- Priced in the conversation, by the number of books and seats, not on this page.
- How does access work?
- Send the form. A person reads it and replies by email; if it fits, the reply carries an invite link bound to your address. Open it, set a password (or keep signing in with Google), and the full product is on. No card, no self-serve upgrade.
- Is the model something we can put in front of a client or a committee?
- It is a Barra-style fundamental factor model: six style factors, eleven industries and a market factor, estimated by cross-sectional regression every trading day on Sharadar point-in-time data. The methodology page under the hood describes it, and every figure in the app carries its as-of date and a coverage badge saying how much of the book the model actually saw.
- Can several people on a team use it?
- Each person on the team gets their own invite and sign-in, and keeps their own books. Shared team workspaces, where two sign-ins see the same books, are not built yet, and we will say so rather than improvise.