Arbiter is Facteus’s balanced, representative transaction dataset for investors who need fast signal they can actually forecast on. It helps fundamental and quant teams monitor company and category performance with investor-ready delivery and a methodology built to stand up.
Balanced, representative transaction data built for investors.
Designed for real-time predictions and earnings-related forecasting.
Best for teams that want fast, verified company and category signal without raw-row overhead.
On this page: what Arbiter is, what it solves, specs, proof, use cases, and FAQs.
Arbiter is built for earnings-related prediction and nowcasting.
Representativeness and stability matter when the model has to hold up quarter after quarter.
Some teams need a forecasting product, not a data-engineering project.
Arbiter helps investors move from company to sector without switching truth sources.
Arbiter is designed to support real-time predictions and earnings-related analysis with a representative transaction foundation.
See whether a move reflects idiosyncratic company behavior or broader consumer demand.
Get data shaped for active research and forecasting, with delivery that supports serious model use.
Arbiter benefits from Facteus’s broader validation approach against economic and public company benchmarks.
Arbiter gives investors fast access to representative transaction intelligence suited to forecasting and earnings prep.
| Specifications | Detail |
|---|---|
| Data type | Transaction data |
| Granularity | Aggregated investor-ready signal |
| Refresh cadence | Daily / one-day lag |
| Core use case | Forecasting and earnings-related analysis |
| Delivery | API, Snowflake, S3, approved workflows |
| Audience | Investors |
Investor forecasting data has to do more than move early. It has to keep working under scrutiny. That means it needs enough speed to create an edge, enough methodological consistency to support backtests, and enough representativeness to avoid turning panel noise into conviction.
Arbiter is built for that middle ground. It gives investors a balanced, representative transaction signal shaped for real-time prediction and earnings-related work. Rather than forcing teams to build everything from raw rows, it provides a cleaner path to actionable company and category monitoring.
Because Arbiter sits on Facteus’s broader verified data foundation, it benefits from a validation approach that looks outward, not inward. That means benchmarking against the economy and public results, not just internal panel logic. For investor teams, that is what helps a fast signal become a usable one.
Arbiter inherits the Facteus standard for investor trust.
185M+
cards
30+
diverse financial sources
2.0%
cards
1 day
lag delivery
Track momentum before reported results.
Support systematic and discretionary models.
Compare company performance against broader demand.
Validate whether a move is real or narrative-driven.
Arbiter is more pre-shaped for forecasting and investor analysis, while Ultra offers more raw, row-level flexibility.
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