Monte Carlo–Based Financial Market Value-at-Risk Estimation on GPUs
Matthew F. Dixon, Thomas Bradley, Jike Chong and Kurt Keutzer
With the proliferation of algorithmic trading, derivative usage and highly leveraged hedge funds, there is increasing need to accelerate financial market Value-at-Risk (VaR) estimation to measure the severity of potential portfolio losses in real time. However, VaR estimation of portfolios uses the Monte Carlo method, which is a computationally intensive method. GPUs provide the scale of performance improvement to enable “on demand” deployment of financial market VaR estimates rather than as an overnight batch job.
This chapter allows quantitative financial application developers in the capital markets industry, ...
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