{"id":4412,"date":"2011-06-20T10:41:54","date_gmt":"2011-06-20T10:41:54","guid":{"rendered":"http:\/\/hgpu.org\/?p=4412"},"modified":"2011-06-20T10:41:54","modified_gmt":"2011-06-20T10:41:54","slug":"reconfigurable-control-variate-monte-carlo-designs-for-pricing-exotic-options","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4412","title":{"rendered":"Reconfigurable Control Variate Monte-Carlo Designs for Pricing Exotic Options"},"content":{"rendered":"<p>Exotic options are financial derivatives which have complex features including path-dependency. These complex features make them difficult to price, as only computationally intensive Monte-Carlo methods can provide accurate prices. This paper proposes an FPGA-accelerated control variate Monte-Carlo (CVMC) framework for pricing exotic options. An optimised implementation of arithmetic Asian option pricing under this framework in a Virtex-5 xc5vlx330t FPGA at 200 MHz is 24 times faster than a multi-threaded software implementation on a Xeon E5420 at 2.5 GHz; it is also 2.4 times faster than the Tesla C1060 GPU at 1.3 GHz.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Exotic options are financial derivatives which have complex features including path-dependency. These complex features make them difficult to price, as only computationally intensive Monte-Carlo methods can provide accurate prices. This paper proposes an FPGA-accelerated control variate Monte-Carlo (CVMC) framework for pricing exotic options. An optimised implementation of arithmetic Asian option pricing under this framework in [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[89,576,3],"tags":[14,1804,377,72,20,199],"class_list":["post-4412","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-finance","category-paper","tag-cuda","tag-finance","tag-fpga","tag-monte-carlo-simulation","tag-nvidia","tag-tesla-c1060"],"views":2454,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4412","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4412"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4412\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4412"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4412"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4412"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}