DocumentCode :
1697756
Title :
FPGA based eigenfiltering for real-time portfolio risk analysis
Author :
Torun, Mustafa U. ; Yilmaz, Ozgur ; Akansu, Ali N.
Author_Institution :
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
fYear :
2013
Firstpage :
8727
Lastpage :
8731
Abstract :
The empirical correlation matrix of asset returns in an investment portfolio has its built-in noise due to market microstructure. This noise is usually eigenfiltered for robust risk analysis and management. Jacobi algorithm (JA) has been a popular eigensolver method due to its stability and efficient implementations. We present a fast FPGA implementation of parallel JA for noise filtering of empirical correlation matrix. Proposed FPGA implementation is compared with CPU and GPU implementations. It is shown that FPGA implementation of eigenfiltering operator in real-time significantly outperforms the others. We expect to see such emerging high performance DSP technologies to be widely used by the financial sector for real-time risk management and other tasks in the coming years.
Keywords :
eigenvalues and eigenfunctions; field programmable gate arrays; graphics processing units; investment; matrix algebra; parallel algorithms; risk analysis; CPU implementations; FPGA based eigenfiltering; GPU implementations; Jacobi algorithm; asset returns; eigensolver method; empirical correlation matrix; field-programmable gate array; graphics processing unit; high performance DSP technologies; investment portfolio; market microstructure; noise filtering; parallel JA; real-time portfolio risk analysis; real-time risk management; Correlation; Field programmable gate arrays; Graphics processing units; Jacobian matrices; Portfolios; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6639370
Filename :
6639370
Link To Document :
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