Hivemind Factors Explain Incremental Out-of-Sample Variance
Using the top 6 Hivemind macro factors and our 292 new Hivemind subindustries, we measure incremental out-of-sample explained variance.
Discover emergent themes. Quantify consensus interest. Generate factors for anything from point-in-time data. For institutional investors.
Using the top 6 Hivemind macro factors and our 292 new Hivemind subindustries, we measure incremental out-of-sample explained variance.
Now, more than ever, the stock market is driven by emergent themes. Let's explore how Hivemind both surfaces and creates exposures for point-in-time emergent trends.
If you ran a large book through 2025’s volatility, you probably spent more time on the phone than in the market. “Are you down? We’re off 3%.” Most of those calls were really a fishing expedition for: "what exposure did I miss?" and "does everyone have it, or just me?" The uncomfortable truth is that, outside of a handful of slow-moving style boxes, few managers can answer that question with conviction.
Create a S&P 500 macro investment strategy in 100 lines of code. Can overlay on any US equities strategy. 2.5% annualized excess return, 1.0x information ratio, 3.4x one-way turnover.
Callum, our summer intern, codes live to demonstrate how easy it is to use InvestOS and ForecastOS to build a simple QVM investment strategy. He walks through the process of creating composite scores for quality, value, and momentum, calculating active weights, portfolio optimization and backtesting, and more.
In a ~13 minute video, we build and backtest an ML-powered market and factor neutral quantitative investment strategy using ForecastOS and InvestOS.
With our software, tools, and expertise, this exercise could be repeated to tailor any institutional investment strategy to any unique client mandate or market demand.
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.
ForecastOS Hivemind
Company Exposures
Generate custom exposures in minutes
Use our reasoning engine to create point-in-time company exposures. Better understand how your holdings are exposed (direction and magnitude) to anything, hypothetical or actual, like GenAI, inflation, tariffs, war, etc.
Trends: Daily
Identify emerging trends
Our AI systematically identifies, classifies, and ranks market relevant trends daily.
Trends: Persistent
Analyze trends over time
Explore aggregated daily trends, grouped by similarity, across time. Fad or foundation?
Synthetic Data Pipeline Builder
Create bespoke risk and alpha factors
Generate custom risk and alpha factors from structured and unstructured point-in-time data using GenAI. Create that management team or product moat factor you always wanted! No engineering or infrastructure mess required. Completely customizeable steps, inputs, and outputs.
After several years of investment banking and software engineering, I spent the last 6 years - first in the Alpha Generation Lab at CPPIB and now at ForecastOS - creating data and AI-driven tools to capture systematic alpha. ForecastOS Hivemind is my best yet!
Better backtesting in 10 lines of open-source code.
For extensible portfolio engineering / optimization, backtesting, risk models, and reporting software. Enterprise support available by request.
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Access 1000s of point-in-time (PIT) factors with ForecastOS FeatureHub.
Pull pre-engineered feature / factor data anywhere in 1 line of code; no data engineering pipeline required.
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See all the pieces of your investment strategy!
Visualize, manage, understand, and analyze your systematic investment research processes in a friendly UI with enterprise-grade access management.
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Book a call / demo to explore the ForecastOS Investor Toolkit.