Our research program covers multiple systematic and discretionary strategies across asset classes and market structures.
Mean-reversion and factor-based strategies exploiting statistical relationships across equity and derivative markets. Dimensionality reduction, cointegration analysis, and residual modeling drive our systematic stat-arb research pipeline.
Identifying mispricings in options and structured products through replicating portfolio construction. We model implied vs. realized dynamics to capture the spread between theoretical fair value and market price.
Monitoring and exploiting triangular and multi-leg inconsistencies across FX and crypto exchange rates. High-frequency data feeds and low-latency execution are critical to capturing these fleeting dislocations.
Macro-driven discretionary strategies focused on rates markets. We analyze yield curve dynamics, central bank policy, and term structure models to identify asymmetric risk-reward opportunities in fixed income.
Systematic approaches to pricing event outcomes in prediction markets. We develop probabilistic models for political, economic, and sporting events, identifying positive expected value opportunities where market prices diverge from calibrated probabilities.
An ongoing research sandbox exploring new sources of alpha. From alternative data to novel market microstructures, we continuously test and incubate ideas at the frontier of quantitative finance.
Our first series of research notes is in preparation covering arbitrage mechanics, market microstructure on prediction markets, and systematic strategy design.