What is an investment model API?
An investment model API lets software retrieve model information in a structured format. Instead of copying allocations, performance, or publication details from a web page, an authorized application can request the relevant data and process it consistently.
A model API can provide information about target portfolios and research records. It does not necessarily connect to an investor's brokerage account, place orders, hold assets, or determine whether a model is appropriate for a particular person.
Retrieve model holdings and weights
Structured targets can support internal portfolio review, reporting, reconciliation, or implementation workflows without manual transcription.
Read model and benchmark records
Performance endpoints can provide dated series and comparison data for dashboards, analysis, and repeatable reporting.
Confirm what was available and when
Publication metadata helps applications distinguish the current model state from prior records and verify the timing of a release.
Use validation facts programmatically
Research data can expose documented model facts and validation results without requiring another system to interpret charts or page copy.
- Investment professionals building internal research dashboards.
- Analysts comparing model and benchmark records.
- Developers integrating portfolio data into authorized applications.
- Organizations creating recurring review and reporting workflows.
- Which data is public and which requires subscriber authorization?
- How are models, dates, weights, and record types identified?
- How often does the underlying publication change?
- What rate limits, security controls, and usage terms apply?
The API documentation describes available endpoints, authentication, response schemas, rate limits, and examples. Professional, Business, and Enterprise plans include authenticated API access. The public site separately exposes performance, method, evidence, and audit context that can be reviewed without an API key.
Review the model method, research evidence, forward-tracked records, and research standards before deciding how model data should be used.