A Different Kind of Edge
Systematic•Quantitative•Equities
Built for long-term advantage
↓Pereda Growth applies systematic research, machine learning and disciplined portfolio construction to identify relative opportunities across U.S. equities.
A broad universe of U.S. equities is evaluated using systematically engineered market, fundamental and quantitative information.
Machine-learning models systematically evaluate relative opportunities across the equity market.
Systematic signals are translated into structured long and short portfolios subject to defined exposure, diversification and implementation constraints.
Portfolio and execution controls govern exposures, exits, short-side risk, liquidity and implementation throughout the investment lifecycle.
We seek to generate returns primarily through security selection and relative performance rather than forecasts of broad market direction.
Research ideas must demonstrate robustness through rigorous out-of-sample testing before they are considered for production.
Portfolio construction, risk management and execution follow defined, repeatable rules designed to reduce reliance on discretionary decision-making.
Risk management is incorporated throughout portfolio construction and execution.
Portfolio-level constraints govern how risk is allocated across the strategy.
Dedicated controls recognize the asymmetric characteristics of short positions.
Implementation constraints are designed to balance signal capture with portfolio tradability.
Systematic execution and reconciliation processes govern the transition from model output to implemented positions.
