Axioma Portfolio Analytics and Risk Model Machine get upgrades

Source: Axioma

Axioma, a leading provider of innovative risk solutions for buy-side institutions, today announced the release of version 2016 R1 of its Axioma Portfolio Analytics and Risk Model Machine solutions.

 The enhancements provide increased flexibility and accommodate a wider variety of workflows.

“Axioma is committed to delivering innovative solutions that allow portfolio managers to focus on generating alpha,” said Mark Cushey, director of product management, Axioma. “The latest versions of Axioma Portfolio Analytics and Risk Model Machine exemplify how we help clients to remain competitive and work with them to streamline processes allowing for further efficiency across the board. This is incredibly important, as buy-side firms are under pressure to demonstrate innovation in an environment of commoditized performance and investor demand for transparency.”

The key highlights of the new version of Axioma Portfolio Analytics include:

  • Historical portfolio data uploads that are 2x-4x faster
  • Seamless integration of portfolio updates with stored analytics
  • Accommodation of more workflows, including sortable Excel reports and faster factor-based performance attribution calculations
  • A simplified implementation process
  • Improvements in web services

Noteworthy highlights of the new version of the Risk Model Machine include:

  • The ability to “stitch” together custom risk models, thus allowing clients to increase or reduce the number of style factors, industries or countries in the models over time
  • The flexibility to exclude industry factors from the custom risk model, limiting it to market, style and country, or just market and style

The newest version of Axioma Portfolio Analytics and the Risk Model Machine follows significant updates launched in Q1 to Axioma Risk, an enterprise-wide risk-management system.
Significant highlights include:

  • Pseudo Historical and Monte Carlo Risk Statistics – new methodology combines a linear pricing approach with a historical or Monte Carlo simulation. This approach gives users the best of two worlds: fast computation from linear exposures and rich risk simulations.
  • Integration of Axioma Commodity Model into Axioma Risk – The commodity model enables users to analyze commodity exposures and risk via cross-sectional factors. It complements the granular approach, which uses constant-maturity future curves.
  • Default Probability and Default Horizon Statistics – computes the probability of default at a user-specified horizon.
  • Custom Statistic – provides the flexibility to combine any existing statistics through mathematical operations.
  • Partitioned Stress Tests – enables filters to be applied to stress tests, allowing more targeted stress tests to be defined.
  • Generic Contract for Difference – expands on the existing Stock and Stock Index CFD pricing models by adding coverage for any type of instrument that Axioma Risk supports.
  • Equity Option Improvements in Axioma Risk – supports quanto options and dividend yield. Quanto options are American and European stock and stock index options whose currency is different from the currency of the underlying. Dividend yield is a fundamental pricing parameter that is now an integral part of stock and stock index option pricing.

Axioma Portfolio Analytics provides time-series risk analysis, stress testing and both traditional and factor-based performance attribution that is fully integrated with Axioma’s fundamental, statistical and macroeconomic risk models, as well custom risk models built with the Axioma Risk Model Machine.

Risk Model Machine allows clients to build their own proprietary risk models using Axioma’s IP and proven core models as the foundation. Clients then introduce and adjust risk factors and other parameters to tailor the models to their own specific investment process and approach.

Axioma Risk is an enterprise-wide risk management system that enables clients to obtain timely, consistent and comparable views of risk across the entire organization and across all asset classes.

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