Summary: R code for Portfolio Performance Measurement and Benchmarking from Christoperson, Carino, and Ferson(2009)

Description: PerformanceAnalytics is an R package that provides a collection of econometric functions for performance and risk analysis. It applies current research on return-based analysis of strategy or fund returns for risk, autocorrelation and illiquidity, persistence, style analysis and drift, clustering, quantile regression, and other topics.

As a key repository of important performance and risk benchmarking and attribution functions, it is important to keep up with the latest publications in the field. Christopherson(2009) is such a publication. David Cariño is a Research Fellow at Russell Investments, one of the co-authors of this text and would co-mentor this project.

The majority of the measures described in Portfolio Performance Measurement and Benchmarking already exist in Performanceanalytics, but several newer or lesser used functions do not. A non exhaustive list includes: * holding period returns * linked returns * cash flow and unit value returns * money weighted returns * Modigliani measure * Appraisal Ratio * Fixed Income Risk Measures for duration, convexity, prepayment, and issuer-specific risks * market timing metrics * portfolio attribution * linking attribution * benchmark and index construction

Additionally, there are multiple chapters on factor analysis that may be mostly covered by functions already in the package FactorAnalytics: overlap and required functionality will need to be cross-referenced, with necessary additional functionality created as part of this project.

References:

Test: The successful applicant will demonstrate proficiency with R, and specifically with xts and PerformanceAnalytics or PortfolioAnalytics. This could be via identifying a patch or extension, providing a new demo script for the one of the packages that would show understanding of the functionality provided, or by doing a detailed proposal with pseudocode for one or more potential enhancements to the toolchain. The ideal candidate would also demonstrate prior interest or experience in finance.

Mentor:

David Cariño is Research Fellow at Russell Investments

Doug Martin is the head of the University of Washington Computational Finance program, and would co-mentor this project.

Peter Carl is one of the primary authors of these related packages, and would mentor the GSOC participant.

Brian Peterson is one of the primary authors of these packages, has previously mentored GSoC projects, and would be backup mentor for this project. 2012-03-23

 
developers/projects/gsoc2012/performancebenchmarking.txt · Last modified: 2012/03/23 by braverock
 
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