- CONTROL VARIATES FOR VARIANCE REDUCTION IN INDIRECT INFERENCE: INTEREST RATE MODELS IN CONTINUOUS TIME

Gabriele Fiorentini, Francesca Di Iorio and Giorgio Calzolari

Working Papers. Serie AD from Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie)

Abstract: Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for estimating stochastic differential equations. They adjust for the bias (inconsistency) caused by discretization of the underlying stochastic process, which is in continuous time. The price to be paid is an increased variance of the estimated parameters. The variance suffers from an additional component, which depends on the stochastic simulation involved in the estimation procedure. To reduce this undesirable effect, one could properly increase the number of simulations (or the length of each simulation) and thus the computational cost. Alternatively, this paper shows how variance reduction can be achieved, at virtually no additional computational cost, by use of control variates. The Ornstein-Uhlenbeck process, used by Vasicek to model the short term interest rate in continuous time, and the square-root process, used by Cox, Ingersoll and Ross, are explicitly considered and experimented with. Monte Carlo experiments show a global efficiency gain of almost 50% over the simple indirect estimator.

Keywords: Efficient Monte Carlo; Variance reduction technique; control variates (search for similar items in EconPapers)
Pages: 19 pages
Date: 1998-01
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Citations: View citations in EconPapers (10)

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Related works:
Journal Article: Control variates for variance reduction in indirect inference: Interest rate models in continuous time (1998)
Working Paper: Control variates for variance reduction in indirect inference: interest rate models in continuous time (1996)
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Persistent link: https://EconPapers.repec.org/RePEc:ivi:wpasad:1998-09

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