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Controlling antithetic variates

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  • Kawai, Reiichiro

Abstract

We establish and investigate a theoretical framework for controlling covariance matrices in the method of antithetic variates through control variates to further reduce estimator variance. Instead of preemptively and carefully designing an estimator vector with negatively correlated components, the proposed framework starts with a predefined estimator vector that incorporates specified control variates. The weights and control matrix are then analytically determined through matrix algebra. The joint optimality of the resulting estimator variance is ensured with respect to both the weights and the control matrix, with closed-form implementable formulas derived for the optimal parameter pair. Numerical results are provided for various typical examples to illustrate the effectiveness, potential, and challenges of the proposed framework.

Suggested Citation

  • Kawai, Reiichiro, 2026. "Controlling antithetic variates," European Journal of Operational Research, Elsevier, vol. 328(1), pages 162-173.
  • Handle: RePEc:eee:ejores:v:328:y:2026:i:1:p:162-173
    DOI: 10.1016/j.ejor.2025.08.027
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Philipson, Pete & Hickey, Graeme L. & Crowther, Michael J. & Kolamunnage-Dona, Ruwanthi, 2020. "Faster Monte Carlo estimation of joint models for time-to-event and multivariate longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 151(C).
    3. Bill Mitchell, 1973. "Variance Reduction by Antithetic Variates in GI / G /1 Queuing Simulations," Operations Research, INFORMS, vol. 21(4), pages 988-997, August.
    4. Reuven Y. Rubinstein & Ruth Marcus, 1985. "Efficiency of Multivariate Control Variates in Monte Carlo Simulation," Operations Research, INFORMS, vol. 33(3), pages 661-677, June.
    5. Chimyung Kwon & Jeffrey D. Tew, 1994. "Strategies for Combining Antithetic Variates and Control Variates in Designed Simulation Experiments," Management Science, INFORMS, vol. 40(8), pages 1021-1034, August.
    6. Athanassios N. Avramidis & James R. Wilson, 1996. "Integrated Variance Reduction Strategies for Simulation," Operations Research, INFORMS, vol. 44(2), pages 327-346, April.
    7. de O. Porta Nova, Acacio M. & Wilson, James R., 1993. "Selecting control variates to estimate multiresponse simulation metamodels," European Journal of Operational Research, Elsevier, vol. 71(1), pages 80-94, November.
    8. Noorani, Idin & Mehrdoust, Farshid & Nasroallah, Abdelaziz, 2021. "A generalized antithetic variates Monte-Carlo simulation method for pricing of Asian option in a Markov regime-switching model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 181(C), pages 1-15.
    9. Jangho Park & Rebecca Stockbridge & Güzin Bayraksan, 2021. "Variance reduction for sequential sampling in stochastic programming," Annals of Operations Research, Springer, vol. 300(1), pages 171-204, May.
    10. Nelson, Barry L., 1988. "Antithetic-variate splitting for steady-sate simulations," European Journal of Operational Research, Elsevier, vol. 36(3), pages 360-370, September.
    11. Athanassios N. Avramidis & James R. Wilson, 1998. "Correlation-Induction Techniques for Estimating Quantiles in Simulation Experiments," Operations Research, INFORMS, vol. 46(4), pages 574-591, August.
    12. Kawai Reiichiro, 2025. "Antithetic variates revisited again," Monte Carlo Methods and Applications, De Gruyter, vol. 31(4), pages 311-328.
    13. J. M. Burt & D. P. Gaver & M. Perlas, 1970. "Simple stochastic networks: Some problems and procedures," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 17(4), pages 439-459, December.
    14. Reuven Y. Rubinstein & Gennady Samorodnitsky & Moshe Shaked, 1985. "Antithetic Variates, Multivariate Dependence and Simulation of Stochastic Systems," Management Science, INFORMS, vol. 31(1), pages 66-77, January.
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