Limitations of Public API Data
This article explains the main limitations and caveats of using public Google Finance, Yahoo style or other free APIs as data sources for Model Reef drivers.
You will learn:
What to expect from public API data.
Typical gaps and issues.
How to design your models to be robust to these limitations.
These imports are powerful for drivers and scenario inputs, but they are not a replacement for audited financial statements or official accounting data.
No guarantee of completeness or continuity
Public API data often comes with constraints such as:
Missing data points for some dates or tickers.
Incomplete history, especially for less liquid or newer instruments.
Gaps around holidays, suspensions or corporate actions.
Model Reef will store whatever series is returned, but your modelling logic should not assume that every period has a value.
Where continuity matters, you may choose to:
Fill gaps using interpolation or forward fill in a preprocessing step.
Use aggregated or lower frequency series (weekly or monthly) rather than daily.
Potential differences vs official sources
Public API data may differ from:
Official exchange records.
Vendor grade data feeds.
Issuer reported metrics.
Differences can arise from:
Adjustments for splits and dividends.
Data vendor conventions.
Timezone or session cut off differences.
For high stakes work, always reconcile key series against authoritative sources before relying on them in decisions.
Limited fundamentals and classification detail
Google Finance and Yahoo style APIs are primarily oriented around:
Prices.
Volumes.
Basic reference data.
They generally do not provide full fundamental statement detail at a quality comparable to dedicated fundamentals feeds.
For full P&L, Balance Sheet and Cashflow driven work, you should prefer:
Fundamentals imports (for example stock ticker fundamentals).
PDF or Excel based financials.
Accounting system integrations (Xero, QuickBooks).
API sourced data is best used as driver or context, not as a core fundamentals input.
Rate limits and stability
Public APIs may have:
Rate limits per IP or per key.
Occasional downtime.
Changes in schema or endpoint behaviour over time.
In Model Reef this means:
Imports might fail temporarily if limits are exceeded.
You may occasionally need to retry or adjust your import strategy.
It is good practice to cache important series in the Data Library and not rely on live calls during critical modelling sessions.
Legal and licensing considerations
Different data sources and jurisdictions have different rules regarding:
Redistribution of data.
Commercial use.
Storage and retention.
When importing series from public APIs into Model Reef, you are responsible for ensuring that your usage complies with the relevant terms of service and any applicable laws or policies in your organisation.
Designing robust models
To account for public API limitations, aim to:
Use these series primarily as drivers and scaling factors.
Keep a copy of critical series in the Data Library so that your model is not dependent on live retrieval.
Document any important assumptions or transformations you apply to API data.
Combine public data with internal series and fundamentals rather than relying on it exclusively.
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