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A volatility decomposition control variate technique for Monte Carlo simulations of Heath Jarrow Morton models
Institution:1. School of Finance and Economics, University of Technology, Sydney, PO Box 123, Broadway NSW, Australia;2. Lacima Group and University of Technology, Sydney, PO Box 123, Broadway NSW, Australia;3. Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita'' degli Studi di Foggia, via IV Novembre 1, Foggia 71100, Italy;1. Al Jalila Children''s Specialty Hospital, Dubai, United Arab Emirates;2. Medical School, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai, United Arab Emirates;3. Medicare Orthopaedics and Spine Hospital, Dubai, United Arab Emirates;1. Department of Bridge Engineering, Southwest Jiaotong University, Chengdu, China;2. Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China;1. Energy Institute, School of Electrical and Electronic Engineering, University College Dublin, Ireland;2. Economic and Social Research Institute, Dublin, Ireland;3. Department of Economics, Trinity College Dublin, Ireland;1. Center for Infrastructure, Transportation, and the Environment, and the VREF’s Center of Excellence for Sustainable Urban Freight Systems, Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA;2. Department of Geography and Planning University at Albany, Albany, NY, USA
Abstract:The aim of this work is to develop a simulation approach to the yield curve evolution in the Heath, Jarrow and Morton Econometrica 60 (1) (1992) 77] framework. The stochastic quantities considered as affecting the forward rate volatility function are the spot rate and the forward rate. A decomposition of the volatility function into a Hull and White Rev. Financial Stud. 3 (1990) 573] volatility and a remainder allows us to develop an efficient Control Variate Method that makes use of the closed form solution of the Hull and White call option. This technique considerably speeds up the simulation algorithm to approximate call option values with Monte Carlo simulation.
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