Overview
Investors need to estimate the projected return and risk for their portfolios across a variety of scenarios. Risk engines are important in helping to understand how assets move together. Forward-looking simulations are essential to understand the stochastic impact of new information on your portfolio.
However, traditional numerical analysis such as factor models and Monte Carlo simulations are often limited by their linear approaches and strong assumptions — even though experience tells us that asset returns are non-stationary, noisy, and not IID.
SAPIAT addresses these limitations by greatly expanding the forecast data sets used, by implementing a new approach to model the multitude of forecast information for each scenario, and by employing high performance computing to run the actual calculations.
SAPIAT Scenario™ provides a robust and truly forward looking simulation framework that enables both Asset Owner and Asset Manager clients to explore the impact on their portfolio from upcoming events like changes in the macro-economic environment, geopolitical events, secular vs non secular changes and climate change.
Each SAPIAT product is available via APIs, managed services, or in the SAPIAT platform with pre-configured SAPIAT Dashboard™ for several user types: pension trustee, CEO & executive committee, CIO & investment committee, risk & performance analysts, and marketing teams.
Key Features
- Widest scenario coverage: from popular research houses, highly ranked economists, public sources and user input
- Consistent methodology: for simulation-based scenarios for path-dependent multi-horizon forecasting of full distribution across all asset classes
- Flexible ingestion: forecasts information from structured and unstructured data, including proprietary NLP engines
- Relevant scenarios: from market regimes to geopolitical scenarios and climate change
- High Tech: leverages parallelized High Performance Computing (HPC)
- Full coverage: all instruments from public to private markets, full granularity
- Powerful explanation: understand causal relationships through SAPIAT’s extensive risk factors library
- Allocation tools: from manual revisions to fully automated optimization
- Transparent & Reliable: robust methodology provides reliability. No black-box, intuitive explanation for all stakeholders.