Method
Our systematic framework: collect → formalize → validate → evaluate → deploy → refine. We build structured processes that amplify empirical insights while filtering out market noise.
1) Ingest
Systematically gather prediction insights from diverse digital sources. Maintain source attribution, temporal context, and background information.
2) Structure
Turn talk into predictions: instruments, direction, rules, timeframe (daily, non‑HFT), risk budget.
2.5) Coverage
Global equities and futures with multi‑region data ingest; breadth reduces narrative bias and improves robustness.
3) Backtest
Stability‑verified harness with leakage‑aware validation, walk‑forward analysis, and realistic slippage/fees.
4) Rank
Score sources by out‑of‑sample performance across risk‑adjusted return, drawdown, turnover, and stability.
5) Allocate
Gates determine resource routing. Only approaches that clear stability and risk thresholds earn deployment. Low volatility unlocks scaling; stability gates precede deployment.
6) Learn → Build
Generalize what works to train proprietary models (time‑series ML) and evolve algorithmic systems.
Gates and KPIs
- Infra velocity: ship ingestion + backtest scaffolding fast with minimum standards.
- Workflow robustness: agentic pipelines that are reproducible, inspectable, and low‑touch.
- Strategy throughput & quality: number cleared + out‑of‑sample performance (risk‑adjusted return, drawdown).