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It enables quant teams, treasuries, and funds to backtest models, optimize portfolios, and analyze risk dynamically — reducing the gap between research and real-world trading.
A unified data layer aggregating tick-level market data, historical time series, and factor libraries from multiple venues. It supports model training, signal discovery, and alpha attribution, allowing researchers to explore relationships between liquidity, volatility, and execution performance.
A portfolio optimization and risk management suite designed for institutional treasuries. It enables real-time rebalancing, stress testing, and scenario analysis — integrating seamlessly with Algocor’s EMS to align portfolio targets with live execution constraints.
A high-fidelity simulation environment that replicates real-world trading conditions. The walk-forward backtesting framework prevents look-ahead bias and continuously adapts to market shifts — allowing quants to validate models using realistic fill logic and transaction costs.
An open, RESTful API that gives developers and desks direct access to analytics, backtesting, and execution endpoints. It serves as the integration backbone between Algocor’s data stack and clients’ internal systems, enabling automation, custom dashboards, and seamless model deployment.
