Coverage outgrows headcount
The watch list expands faster than the analyst team. Important disclosures get read late, unevenly or without the context of what the desk believed before.
Altys gives lean PMS teams one sourced research ledger across screening, company work, modelling, investment committee output and post-investment monitoring. The goal is not more documents. It is a process the whole desk can inspect and repeat.
A concentrated PMS book can have fewer positions than a broad fund and still require deeper attention per name. The research burden expands further when the same team screens the wider opportunity set.
The watch list expands faster than the analyst team. Important disclosures get read late, unevenly or without the context of what the desk believed before.
A spreadsheet contains one assumption, the investment memo another and the portfolio manager’s memory a third. Nobody can see the latest version of the full case.
Research and strategy tests can unknowingly use restated figures or information that was unavailable on the historical decision date.
Altys keeps the complete PMS research lifecycle on a source-linked, point-in-time foundation.
Express the investment rule in plain language, run it on calculated fields and preserve what would actually have passed on each historical date.
Map the business, segment drivers, management guidance, forensic risks and valuation evidence into a common company workspace.
Use spreadsheets or Python on the same sourced data, with assumptions and scenarios separated from reported facts.
Turn the work into an inspectable evidence pack that shows assumptions, counter-evidence, model sensitivities and portfolio impact.
Track whether business KPIs, guidance, cash conversion, ownership and valuation are moving with or against the original thesis.
A PMS research platform should connect idea generation with primary documents, company models, guidance history, forensic checks, investment-committee work, portfolio context and ongoing monitoring. A screen is only the first step.
Yes. Altys is designed for teams that need depth on each portfolio company while continuously watching a wider opportunity set. Monitoring can be configured around the specific drivers and risks of each thesis.
Altys stores financial information point-in-time, including when each value became available. Historical screens and backtests are evaluated against what could have been known on the decision date.
No. Altys prepares sourced data, context and repeatable workflows around the model. Analysts can continue using spreadsheets and Python for judgement-heavy modelling.
Bring a real company universe and a real monitoring problem. We will show how Altys can connect the data, research workflow and alerts around the way your team already invests.