CognityFoF version 2.7 allows analysts and portfolio managers to quickly construct, analyze and compare multiple portfolio scenarios. A new portfolio statistics module computes and reports over 75 risk and performance measures, and benchmark comparisons. Modeling enhancements include new multi-factor data back-fill methods and a new multivariate skewed and fat-tailed distribution model for use in estimating risk and optimizing portfolios. Version 2.7 also includes extensive usability enhancements and new charting, reporting and Excel output features.
"Our focus continues to be on providing an integrated analytics platform that serves all roles and levels of the fund-of-hedge-funds organization," said Doug Martin, CEO of FinAnalytica. "This latest version offers analysts and portfolio managers new flexibility in ranking, analyzing and comparing fund allocation scenarios while giving risk mangers, CIOs and Investment Committees an aggregate analytical view of their firm wide positions and risk exposures."
CognityFoF provides a full range of tools to support manager selection, asset allocation, risk reporting and portfolio optimization based on more modern quantitative finance methods including downside expected tail loss (ETL) risk measures, downside risk adjusted performance measures, robust statistics for diagnosing unusual manager performance, and Bayes methods for combining analyst and portfolio manager views with historical returns in the portfolio optimization process.
CognityFoF is a client server platform with browser based access that is offered either as an in-house installation or as an ASP. This latest release supports 64-bit editions of Microsoft Windows and has programmable API access through a new Web Services interface. Martin added, "In addition to enhanced usability and expanded modeling capabilities, Version 2.7 allows hedge funds and third party software firms to integrate CognityFoF analytics into their existing platforms through the new web services API."