Market risk analytics with no trade-offs
Monitor, explore, and explain real-time VaR and various sensitivities and stress scenarios. Centralize all risk inputs from multiple sources with zero trade-offs between portfolio transparency, investment agility, and client reporting.
Get a demo.png)
Why asset managers and hedge funds choose Opensee for market risk analytics
Key capabilities of Opensee for market risk analytics
VaR, tail risk, and custom investment scenario analysis
Historical, Monte Carlo, and parametric with marginal VaR, component VaR, and tail risk metrics. Run unlimited custom investment stress scenarios in parallel—testing macro shocks, sector crises, and tail events side-by-side with instant drill-down to fund, strategy, and position level. Support for long/short, multi-asset, and derivatives strategies.
VaR methodologies optimized for multi-strategy portfolios
Expected Shortfall (ES) and tail risk analytics
Scenario execution for macro, sector, and tail risk events
Historical backtesting and analysis and stress scenario validation
Empower PMs and risk teams with real-time portfolio analytics
Portfolio managers and risk teams can monitor intraday risk, slice exposures by sector, geography, factor, or position. Run real-time P&L attribution, simulate investment strategies, and generate investor reports on demand. Create custom analytics with Python for proprietary analytics and models without IT dependencies.
Drag-and-drop analytics interface for PMs and analysts
Natural language queries with Agensee AI
Python SDK for quants and advanced portfolio analytics
Excel, Tableau, and other BI connectors for investor reporting
Single source of truth across all funds and strategies
Consolidate fragmented portfolio risk data from all OMS/PMS, pricing vendors, and risk systems into one unified repository. Horizontally scalable architecture stores billions of positions with efficient compression and unlimited history. Full audit trail and version control for investor transparency and regulatory compliance (SEC, UCITS, AIFMD).
Eliminate data silos across all funds and strategies
Centralized market data, pricing, and portfolio positions
AI-driven anomaly detection and data quality KPIs
Zero downtime at enterprise scale
Custom Factor Models with full transparency and control
Build, test, and deploy custom or standard factor models at scale—Barra, proprietary multi-factor, style factors, or ESG factors. Analyze risk and performance attribution from fund level down to individual holdings. Combine factor exposures with VaR, ES, and stress testing for complete portfolio risk management with full explainability and auditability.
Custom factor model development with Python SDK
Risk & performance attribution by factor, sector, & position
Factor exposure analysis with historical backtesting
Real-time portfolio construction and "what-if" scenario modeling
Explore more Opensee solutions
P&L & Performance
Centralize your data universe to explain every P&L shift with surgical precision. Get transparent, deep-history insights needed for flawless investor reporting and smarter decision-making.
ESG Risk
Unify financial and extra-financial data, combine ESG, physical, and transition climate indicators across portfolios and funds, run forward-looking analyses, and support CSRD/ESRS, SFDR, and EU Taxonomy disclosures.
Market Data Store
Get your EOD and intraday market data into Opensee faster and leverage it for analytics and backtesting —saving time on development, maintenance, and support.
Collateral & Margin Management
Monitor SIMM exposure, optimize collateral allocation, and automate margin workflows in real time, with AI-driven insights and full regulatory audit trails.