Data and Indicators
Sapiat’s data products cover all asset classes, including equities, fixed income, credit and alternatives. Sapiat leverages advances in Machine Learning to combine market data with other information including alternative data sources to produce new risk signals, regime indicators, and factor-like baskets.
Clients can subscribe to Risk Model Data in three main ways including direct file feeds, APIs, and Sapiat analytic tools via third-party platforms.
Sapiat Statistical Risk models are used to forecast portfolio risk at multiple horizons across all asset classes. The Sapiat Statistical Risk models implement
• Robust estimation processes that reduces pitfalls of both cross-sectional and time series approaches
• State-of-the-art integration of GARCH processes to forecast volatility clustering
• Regime Conditioning
• Comprehensive Tail Risk methodology
Sapiat constructs thousands of factors designed to pinpoint sources of systematic risk for portfolios of financial instruments. Sapiat factors can be used by institutional investors and fund managers to analyse fund exposures, manage asset allocation, construct portfolios and understand the investment chracteristics.
The broad range of factors can be broadly classified in 4 groups:
Regime shifts have been a cause of unexpected variability in investment performance. The ability to better understand the nature of regimes and to detect changes more dynamically is of fundamental importance to investors. Application of new non-linear machine learning techniques on market and alternative data allow for better extraction of regimes that affect particular portfolios. Sapiat helps to customize and implement regime detention using our library of methodologies and data sources.
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