Generating Tariff Exposures with ForecastOS Hivemind
When a U.S. hedge fund asked us to help with research to dampen volatility from shifting tariff rhetoric in the Trump era, the first road-block was obvious: no comprehensive dataset captured which of the most active ~3,000 U.S. equities were truly exposed to tariffs, let alone gave the knobs to dial those exposures up or down.
Fortunately, we already had the tool for the job: ForecastOS Hivemind.
What is ForecastOS Hivemind?
Hivemind is ForecastOS’ generative-AI engine for turning unstructured time series data into clean, point-in-time factors.
Under the hood, it ingests everything from SEC filings (or any text / financial information) to top podcasts (or any video / audio). It then indexes information by meaning, context, datetime, and associated company (where relevant).
Using Hivemind, you can define, customize, and score any concept throughout time, using any underlying dataset, whether it's tariff or AI exposures, CEO or research analyst optimism, etc.
Because factor recipes are just a few clicks or API calls away, quants can spin up bespoke signals in minutes instead of months!
Why Did We Build ForecastOS Hivemind?
Traditional factor libraries miss the idiosyncratic, fast-moving themes that drive returns and volatility today. Hivemind closes that gap by letting researchers easily generate, test, and deploy fresh, completely customizeable factors on demand, using both public and proprietary data.
Try ForecastOS Hivemind Out!
Whether you want to create tariff, AI / chip, or geopolitical-hot-spot exposures, just define:
- what you want scored,
- how you want it scored,
- your result schema (i.e. what format you want the factor data to be in), and
- which ForecastOS datasets you want to use,
and let ForecastOS Hivemind do the rest. For thematic exposures, sentiment, popularity, or any time series factor!
Demo and sandbox key available via trialaccess @ forecastos.com. Let's make the GPUs go brrr!