A novel GPU implementation of eigenanalysis for risk management

Mustafa U. Torun, Ali Akansu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Portfolio risk is commonly defined as the standard deviation of its return. The empirical correlation matrix of asset returns in a portfolio has its intrinsic noise component. This noise is filtered for more robust performance. Eigendecomposition is a widely used method for noise filtering. Jacobi algorithm has been a popular eigensolver technique due to its stability. We present an efficient GPU implementation of parallel Jacobi eigensolver for noise filtering of empirical correlation matrix of asset returns for portfolio risk management. The computational efficiency of the proposed implementation is about 34% better than our most recent study for an investment portfolio of 1024 assets.

Original languageEnglish (US)
Title of host publication2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2012
Pages490-494
Number of pages5
DOIs
StatePublished - Nov 2 2012
Event2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2012 - Cesme, Turkey
Duration: Jun 17 2012Jun 20 2012

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

Other

Other2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2012
CountryTurkey
CityCesme
Period6/17/126/20/12

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Electrical and Electronic Engineering
  • Computer Science Applications

Keywords

  • CUDA
  • Eigen Decomposition
  • GPU
  • Jacobi Algorithm
  • Portfolio Risk

Cite this

Torun, M. U., & Akansu, A. (2012). A novel GPU implementation of eigenanalysis for risk management. In 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2012 (pp. 490-494). [6292956] (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC). https://doi.org/10.1109/SPAWC.2012.6292956