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 tha… Show more
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