Since 2005, GoGo Capital has managed capital for global institutions with a single guiding idea: rigorous research, executed through robust systems, measured by risk-adjusted outcomes. In 2025, we expanded our toolkit to incorporate event-macro strategies expressed via liquid prediction markets, enabling direct exposure to event probabilities where policy and macro catalysts drive returns.
We pursue repeatable advantage. Research hypotheses are pre-registered; backtests include realistic constraints; and deployment follows explicit approval thresholds. Post-trade reviews are routine, objective, and documented.
Technology minimizes operational risk: unified data pipelines, feature stores, simulation frameworks, and an OMS/EMS stack with auditability and granular entitlements. Risk is a first-class constraint at every stage of the lifecycle.
Clients receive look-through exposure, factor decompositions, tail-risk metrics, and policy/event briefings when relevant. Reporting focuses on drawdowns, dispersion, and calibration—not anecdotes.
Cross-functional pods, standardized risk language, and a culture that favors checklists over intuition.
We apply scenario analysis, regime detection, and liquidity-aware sizing to reduce left-tail exposure. Hedging is dynamic and model-governed; exceptions require committee review.
Portfolio construction emphasizes correlation structure and capacity constraints. Concentration and exposure-at-risk limits are enforced in pre-trade checks and monitored continuously.
Idea generation combines bottom-up fundamental work and top-down macro analysis with alternative data. Versioned research artifacts, transparent assumptions, and independent replication create institutional memory and reduce model risk.
We maintain benchmarking against naive baselines to ensure signal quality remains above implementation costs.