Leapday offers an event‑centric analytics platform that isolates and quantifies the price and volatility impact of corporate announcements. Using research‑driven models that incorporate behavioral bias adjustments, it delivers forward‑looking, trade‑ready signals via a real‑time API, enabling quantitative traders and asset managers to capture consistent alpha around event windows.
Funding
Funding not disclosed
Founders
Product
Problem
Financial markets generate a constant stream of data, making it difficult for investors to isolate the impact of specific corporate events from overall market noise. Traditional earnings forecasts often focus on beat/miss outcomes, which do not directly translate into actionable trading signals.
Solution
Leapday provides an event‑centric analytics platform that extracts and quantifies the price and volatility effects of corporate events. By applying research‑driven models that account for documented behavioral biases, the system generates forward‑looking signals that target the actual market reaction rather than simple expectation metrics. The platform delivers these forecasts in a format that can be directly integrated into trading strategies, enabling users to capture consistent alpha around event windows. Continuous validation against historical outcomes ensures the signals maintain performance across market regimes.
Target Audience
Primary customers are quantitative traders, hedge funds, and asset‑management firms that require precise, event‑driven market forecasts to inform short‑term trading strategies.
Features
- Event‑focused signal engine that isolates price and volatility moves tied to specific corporate announcements
- Behavioral bias models that adjust forecasts for systematic market over‑ or under‑reactions
- Optimized forecasts calibrated for actionable trade execution rather than binary beat/miss predictions
- Real‑time API delivering event‑level alpha signals for integration with algorithmic trading systems
- Ongoing performance verification to maintain “verified alpha” across diverse market conditions