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Particle filtering-based maximum likelihood estimation for financial parameter estimation

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Title: Particle filtering-based maximum likelihood estimation for financial parameter estimation
Authors: Yang, J
Lin, B
Luk, W
Nahar, T
Item Type: Conference Paper
Abstract: © 2014 Technical University of Munich (TUM).This paper presents a novel method for estimating parameters of financial models with jump diffusions. It is a Particle Filter based Maximum Likelihood Estimation process, which uses particle streams to enable efficient evaluation of constraints and weights. We also provide a CPU-FPGA collaborative design for parameter estimation of Stochastic Volatility with Correlated and Contemporaneous Jumps model as a case study. The result is evaluated by comparing with a CPU and a cloud computing platform. We show 14 times speed up for the FPGA design compared with the CPU, and similar speedup but better convergence compared with an alternative parallelisation scheme using Techila Middleware on a multi-CPU environment.
Issue Date: 4-Sep-2014
URI: http://hdl.handle.net/10044/1/23845
DOI: https://dx.doi.org/10.1109/FPL.2014.6927411
ISBN: 9783000446450
Publisher: IEEE
Journal / Book Title: 24th International Conference on Field Programmable Logic and Applications, FPL 2014
Copyright Statement: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Conference Name: 24th International Conference on Field Programmable Logic and Applications, (FPL) 2014
Start Date: 2014-09-02
Conference Place: Munich, Germany
Appears in Collections:Faculty of Engineering
Computing



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