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Control variates for variance reduction in indirect inference: interest rate models in continuous time

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  • Calzolari, Giorgio
  • Di Iorio, Francesca
  • Fiorentini, Gabriele

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. There is, in fact, an additional component of the variance, which depends on the stochastic simulation involved in the estimation procedure. To reduce this udesirable effect one should enlarge the number of simulations (or the length of each simulation) and thus the computation cost. Alternatively, this paper shows how variance reduction can be achieved, at virtually no additional computation cost, by use of control variates. The Ornstein-Uhlenbeck equation, used by Vasicek to model the short term interest rate in continuous time, and the so called square root equation, used by Cox, Ingersoll and Ross, are explicitly considered and experimented with. Monte Carlo experiments show that, for some parameters of interest, a global efficiency gain about 35%-45% over the simplest indirect estimator is obtained at about the same computation cost.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 23160.

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Date of creation: Nov 1996
Date of revision: Nov 1996
Handle: RePEc:pra:mprapa:23160

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Keywords: Monte Carlo; variance reduction techniques; control variates; indirect inference; discretization; short-term interest rate; stochastic equation;

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References

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  1. BROZE, Laurence & SCAILLET, Olivier & ZAKOIAN , Jean-Michel, 1993. "Testing for Continuous-Time Models of the Short-Term Interest Rate," CORE Discussion Papers 1993031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976 Elsevier.
  3. Hendry, David F. & Harrison, Robin W., 1974. "Monte Carlo methodology and the small sample behaviour of ordinary and two-stage least squares," Journal of Econometrics, Elsevier, vol. 2(2), pages 151-174, July.
  4. BROZE, Laurence & SCAILLET, Olivier & ZAKOIAN, Jean-Michel, . "Quasi-indirect inference for diffusion processes," CORE Discussion Papers RP -1327, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. Gallant, A. Ronald & Tauchen, George, 1997. "Estimation Of Continuous-Time Models For Stock Returns And Interest Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 1(01), pages 135-168, January.
  6. Chan, K C, et al, 1992. " An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-27, July.
  7. Brennan, Michael J. & Schwartz, Eduardo S., 1979. "A continuous time approach to the pricing of bonds," Journal of Banking & Finance, Elsevier, vol. 3(2), pages 133-155, July.
  8. Vasicek, Oldrich, 1977. "An equilibrium characterization of the term structure," Journal of Financial Economics, Elsevier, vol. 5(2), pages 177-188, November.
  9. Cox, John C & Ingersoll, Jonathan E, Jr & Ross, Stephen A, 1985. "A Theory of the Term Structure of Interest Rates," Econometrica, Econometric Society, vol. 53(2), pages 385-407, March.
  10. Calzolari, Giorgio & Sterbenz, Frederic P, 1986. "Control Variates to Estimate the Reduced Form Variances in Econometric Models," Econometrica, Econometric Society, vol. 54(6), pages 1483-90, November.
  11. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  12. Calzolari, Giorgio, 1979. "Antithetic variates to estimate the simulation bias in non-linear models," Economics Letters, Elsevier, vol. 4(4), pages 323-328.
  13. Bianchi, Carlo & Cleur, Eugene M, 1996. "Indirect Estimation of Stochastic Differential Equation Models: Some Computational Experiments," Computational Economics, Society for Computational Economics, vol. 9(3), pages 257-74, August.
  14. Michael J. Brennan and Eduardo S. Schwartz., 1979. "A Continuous-Time Approach to the Pricing of Bonds," Research Program in Finance Working Papers 85, University of California at Berkeley.
  15. Bianchi, C. & Cesari, R. & Panattoni, L., 1994. "Alternative Estimators of the Cox, ingersoll and Ross Model of the Term Structure of Interest Rates: A Monte Carlo Comparison," Papers 236, Banca Italia - Servizio di Studi.
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Citations

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Cited by:
  1. Raknerud, Arvid & Skare, Øivind, 2012. "Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein–Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3260-3275.
  2. Giorgio Calzolari & F. Di Iorio & G. Fiorentini, 1999. "Indirect Estimation of Just-Identified Models with Control Variates," Econometrics Working Papers Archive quaderno46, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  3. Di Iorio, Francesca & Calzolari, Giorgio, 2006. "Discontinuities in indirect estimation: An application to EAR models," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2124-2136, April.
  4. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," SFB 373 Discussion Papers 1998,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  5. Enrique Sentana & Giorgio Calzolari & Gabriele Fiorentini, 2004. "Indirect Estimation Of Conditionally Heteroskedastic Factor Models," Working Papers wp2004_0409, CEMFI.
  6. Giorgio Calzolari & Francesca Di Iorio & Gabriele Fiorentini, 2001. "Indirect inference and variance reduction using control variates," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 39-53.
  7. Giorgio Calzolari & F. Mealli & C. Rampichini, 2001. "Alternative Simulation-Based Estimators of Logit Models with Random Effects," Econometrics Working Papers Archive quaderno48, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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