Simulated likelihood estimation of diffusions with an application to exchange rate dynamics in incomplete markets |
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| Affiliation: | 1. Department of Cellular & Integrative Physiology, Indiana University School of Medicine, Indianapolis, IN 46202-5120, United States;2. RTI International, Global Health Technologies, Research Triangle Park, NC 27709, United States;1. Pediatric and Adult Congenital Heart Disease Center, IRCCS Policlinico San Donato University Hospital, San Donato Milanese (MI), Italy;2. Exercise Pathophysiology Laboratory, Cardiac Rehabilitation Division, Salvatore Maugeri Foundation, IRCCS, Scientific Institute of Veruno, Veruno (NO), Italy;3. Bioengineering Service, Salvatore Maugeri Foundation, IRCCS, Scientific Institute of Veruno, Veruno (NO), Italy |
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| Abstract: | We present an econometric method for estimating the parameters of a diffusion model from discretely sampled data. The estimator is transparent, adaptive, and inherits the asymptotic properties of the generally unattainable maximum likelihood estimator. We use this method to estimate a new continuous-time model of the joint dynamics of interest rates in two countries and the exchange rate between the two currencies. The model allows financial markets to be incomplete and specifies the degree of incompleteness as a stochastic process. Our empirical results offer several new insights into the dynamics of exchange rates. |
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